# Patent

## Title
Method, system, and computer program product for physician efficiency measurement and patient health risk stratification utilizing variable windows for episode creation

## Abstract

A method for measuring physician efficiency and patient health risk stratification is disclosed. Episodes of care are formed from medical claims data and an output process is performed. Physicians are assigned to report groups, and eligible physicians and episode assignments are determined. Condition-specific episode statistics and weighted episode statistics are calculated, from which physician efficiency scores are determined.

## Background
CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a Continuation of co-pending U.S. patent application Ser. No. 13/621,234, filed Sep. 15, 2012, which is a Continuation of U.S. patent application Ser. No. 13/012,219, filed Jan. 24, 2011, and issued as U.S. Pat. No. 8,340,981 on Dec. 25, 2012, which is a Continuation-in-part (CIP) of abandoned U.S. patent application Ser. No. 12/769,090, filed Apr. 28, 2010, which is a Continuation of U.S. patent application Ser. No. 10/794,216, filed Mar. 5, 2004, and issued as U.S. Pat. No. 7,739,126 on Jun. 15, 2010, which claims the benefit of U.S. Provisional Patent Application Ser. No. 60/549,601, filed Mar. 2, 2004, all of which are hereby incorporated by reference in their entirety as if set forth herein.


BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates broadly to management of medical information. More specifically, the present invention relates to management of medical information to perform and report measurements of physician efficiency.
2. The Prior Art
Recent evidence has suggested that about 10-20% of physicians, across specialty types, practice inefficiently. Efficient means using the appropriate amount of medical resources to treat a medical condition and achieve a desired health outcome. Thus, efficiency is a function of unit price, volume of service, intensity of service, and quality of service. This group of inefficient physicians is responsible for driving 10% to 20% of the unnecessary, excess medical expenditures incurred by employers and other healthcare purchasers, equating to billions of dollars nationally.
To improve market efficiency, it is useful to apply a system that accurately measures individual physician efficiency. Recent evidence has demonstrated that leading physician efficiency measurement systems have only about 15-30% agreement across measurement systems. This means that when one system ranks a physician as inefficient, only about 15-30% of the other systems ranked the same physician as inefficient. The remaining 70% (or more) of systems ranked the same physician as efficient.
These findings show that existing systems have significant error in attempting to accurately identify inefficient physicians. The error needs to be eliminated, or significantly reduced, if healthcare purchasers are to accurately identify inefficient physicians and take action (e.g., attempt to change physician behavior, provide incentives for employees to use more efficient physicians). Every physician falsely measured as efficient (or inefficient) leads to continued inefficiency in the healthcare marketplace.
There are ten common physician (or physician group) efficiency measurement errors present in most existing physician efficiency measurement systems, which are in order of importance: (1) examine all episodes of care for a physician; (2) use a physician's actual episode composition; (3) no severity-of-illness measure by medical condition; (4) no identification of different episode treatment stages; (5) no age category assignment by medical condition; (6) no tracking mechanism for related complication episodes; (7) improper episode outlier criteria; (8) under-report charges attributed to partial episodes; (8) over-report charges attributed to episode endpoints; and (10) no minimum number of episodes of care. These errors are discussed next.
Many physician efficiency methodologies continue to examine “services per 1,000 members” or “all episodes of care” tracked to a physician. These approaches probably add the most to efficiency measurement error. The methodologies attempt to adjust services per 1,000 members and to adjust all episodes of care by age and gender—and then compare one physician's utilization pattern to a peer group average. However, age and gender explain less than 5% of the variance in a patient's medical expenditures. This means that over 95% of the variance is unexplained, and may be attributed to differences in patient health status.
Some methodologies adjust services per 1,000 members and adjust all episodes of care based on specific International Clinical Modification of Diseases ninth edition (ICD.9) code algorithms that measure expected resource intensity. The idea is that a patient's diagnosis codes will provide more predictive power than age and gender alone. The most predictive of the published and marketed models explain only 20% to 30% of the variance in a patient's medical expenditures. This means that 70% or more of the variance continues to be unexplained, and may be attributed to differences in patient health status.
Physicians often criticize the services per 1,000 members and the all episodes of care methodologies that use a predictive case-mix adjustment factor. Physicians state that the methodologies do not appropriately adjust for differences in patient health status—rightly stating that their patients may be “sicker.”
If all claim line items (CLIs) or episodes of care tracked to a physician are used in the efficiency analysis, then up to 70% of the observed utilization difference between physicians may be attributed to patient health status differences. Therefore, patient health status differences are measured rather than individual physician efficiency differences. This weakness in current case-mix adjustment tools means that not all CLIs or patient episodes of care treated by a physician can be examined. Instead, an isolated set of more prevalent medical conditions by severity-of-illness level needs to be examined across physicians of a similar specialty type.
The second measurement error, which occurs in most if not all current efficiency measurement systems, occurs when the physician's actual episode composition is used. The reason is as follows. The differences in physicians' patient case-mix composition results in differences in variability (i.e., the standard deviation) around a physician's average episode treatment charges. This variability is not due to the efficiency or inefficiency of a physician, but instead results because longer and more resource-intensive medical conditions generally require more services and, therefore, have more potential variability around average (or mean) episode treatment charges.
For example, easier-to-treat upper respiratory infection (URI) episodes may have the following mean and standard deviation (with outlier episodes removed): $185±$65. Here, the standard deviation around the mean is not large—and is 0.35 the size of the mean (i.e., 65/185=0.35). However, easier-to-treat pediatric asthma episodes may have the following mean and standard deviation (with outlier episodes removed): $1,650±$850. Here, the standard deviation around the mean is larger than for URI episodes—and is 0.52 the size of the mean (i.e., 850/1,650=0.52).
The variation difference between the two conditions is 49% greater for asthma than URIs_[(0.52−0.35)/0.35]. This variation difference occurs for two reasons: (1) more resource-intensive conditions require more services to treat; and (2) there generally are a small number of episodes available to examine in a given physician efficiency study as compared to the universe of episodes that could actually be studied—and a smaller number of episodes results in a higher chance for variability around the mean. This variation is not the result of physician treatment pattern differences.
If the statistically based variability around the mean is not corrected, then substantial error may enter into the physician efficiency measurement equation. Consequently, the final physician efficiency score differences may be attributed to the statistical condition-specific variability around the mean episode charge (due to the case-mix of episodes treated).
The above example showed that the variation difference may be 50% or more (around a condition-specific mean episode value). Logically, then, if all episodes treated by physicians are examined and efficiency scores are calculated, there has to be some statistical bias present.
A significant statistical bias may be present. Using a more traditional episode-based efficiency measurement methodology, lower-episode-volume physicians treating patients with a higher case-mix index score are more likely to receive an inefficient ranking as compared to lower-episode-volume physicians treating patients with a lower case-mix index score. This finding results because a physician with higher case-mix patients treats episodes having more variability (i.e., a greater standard deviation) around average episode treatment charges. With a low volume of episodes (most often the norm, and not the exception), this physician needs only a few higher-cost episodes then the peer group average to make his/her treatment pattern appear significantly higher than the peer group comparator.
However, a physician with lower case-mix patients treats episodes having less variability around average episode treatment charges. With a low volume of episodes, this physician's treatment pattern will not be as influenced by one or two higher-cost episodes as compared to the peer group average. Consequently, his/her treatment pattern does not appear (as often) significantly higher than the peer group comparator.
Thus, by examining all medical condition episodes, a substantial component of any observed physician efficiency difference may be attributed to statistical condition-specific variability around the mean episode charge—and not to physician treatment patterns efficiency. This effect may be present even when we examine the easier-to-treat episodes (SOI-1 level episodes) for the medical conditions.
The third error takes place in those efficiency measurement systems that do not employ an appropriate episode severity-of-illness measure. Severity-of-illness may be defined as the probability of loss of function due to a specific medical condition. Most, if not all, current claims-based episode groupers and methods do not have an appropriate severity-of-illness index by medical condition. Consequently, significant clinical heterogeneity remains in many episodes for a given medical condition. The end result may be physician efficiency differences that are attributed to inaccurate episode severity-of-illness adjustment, and not to physician treatment patterns variation.
Moreover, some claims-based episode groupers stratify formulated episodes for a medical condition by the presence or absence of a specific surgery or service (e.g., knee derangement with and without surgery; ischemic heart disease with and without heart catheterization). The reason for performing this stratification is to reduce episode heterogeneity for a medical condition. In effect, the stratification serves as a sort of severity-of-illness adjustment.
However, stratification based on the presence of surgery or a high-cost service results in at least two physician efficiency measurement errors: (1) performing surgery versus not performing surgery is the treatment patterns variation we need to examine in determining physician efficiency, and this variation is not captured in more traditional methodologies; and (2) the episodes of care are unnecessarily separated into smaller groups whereby physicians may not have enough episodes to examine in any one smaller group. Consequently, the stratified episodes of care need to be recombined for accurate physician efficiency measurement.
The fourth physician efficiency measurement error occurs in claims-based episode groupers do not have a method for identifying different episode treatment stages including initial, active, and follow-up treatment stages. Identifying different treatment stages is important in medical conditions, such as breast cancer, prostate cancer, colorectal cancer, acute myocardial infarction, and lymphoma. For example, breast cancer should be stratified into initial, active, and follow-up treatment stages.
An initial breast cancer episode is one where the patient has a surgery for the cancer (e.g., lumpectomy, modified radial mastectomy). An active breast cancer episode is one where no surgery is present, but chemotherapy or radiation treatment is observed within the episode. Here, the patient underwent surgery in a previous study period, so no surgical event is found in the patient's current ongoing breast cancer episode. Instead, during the study period, the claims data shows that the patient is being treated with chemotherapy and/or radiation. The presence of these treatments defines an active breast cancer episode. The utilization pattern and charges are different for an active breast cancer patient as compared to an initial breast cancer patient. A follow-up breast cancer episode is one where no surgery, chemotherapy, or radiation treatment is present in the patient's episode of care. After initial and active treatments, physicians will continue to code for breast cancer over the future years of patient follow-up care.
In a given study period, physicians do not treat an equal distribution of each episode type (initial, active, and follow-up). Moreover, the episode types have different average charges. About 20% of episodes may be classified as initial breast cancer episodes. Overall care for initial breast cancer episodes ranges between $15,000 and $25,000 per episode. About 15% of episodes may be classified as active breast cancer episodes. Overall care for active breast cancer episodes ranges between $12,000 and $18,000 per episode. About 65% of episodes may be classified as follow-up breast cancer episodes. Overall care for follow-up breast cancer episodes ranges between $350 and $600 per episode.
Consequently, the blending of the three treatment stage episodes results in average treatment charges of about $5,500 to $6,500 per episode. In fact, this is the average breast cancer charge that would be observed for most claims-based episode groupers.
The blending of initial, active, and follow-up episodes may lead to substantial physician efficiency measurement error. For example, assume during a study period that Oncologist A treats mostly active breast cancer patients, while some other oncologists have a good mixture of active and follow-up patients. Then, Oncologist A's treatment pattern for breast cancer will appear inefficient (as compared to his peer group of oncologists) because active episodes are about 30 times more expensive to treat than follow-up episodes. In fact, Oncologist A's treatment pattern difference is attributed to a different treatment stage episode case-mix.
Therefore, treatment stage episode types need to be correctly identified and separately examined. Otherwise, the final physician efficiency score differences may be attributed to nothing more than the initial, active, and follow-up episode case-mix.
The fifth error happens in those physician efficiency measurement systems that do not examine condition-specific episodes by age category. Studies have illustrated that broad-based age bands are important to separately examine—even after episodes have been assigned a severity-of-illness index. The reason is that physicians tend to treat children and adults differently for most conditions. For example, children are less likely than adults to receive a chest x-ray and potent antibiotics for many medical conditions. If episodes are not examined by broad-based age category, the end result may be physician efficiency differences that are attributed to patient age differences—and not to treatment patterns variation.
The sixth error occurs in those physician efficiency measurement systems that do not link and include the charges and utilization from a patient's complication episodes to his underlying medical condition. Complications are those episodes that are clinically related to the underlying medical condition. Consequently, many condition-specific episodes have under-reported charges. In fact, actual outputs from some claims-based episode groupers may show under-reported charges for patients with diabetes and other chronic conditions (e.g., asthma, congestive heart failure).
For example, the reason for the under-reported episode charges is that physicians code up to 70% of an average diabetic's charges under related complications to the diabetes (e.g., eye, neuropathies, circulatory, renal) and not diabetes care. Therefore, without considering and including related complication episodes with the actual diabetes episode, physician efficiency differences may be attributed to incomplete episode charges and utilization—and not to treatment pattern variations.
Furthermore, for patients with specific medical conditions, any model that attempts to stratify patients by health risk may produce unstable or erroneous results. The reason is that a patient is missing key claims information needed to accurately classify a patient into an appropriate severity-of-illness and other classes. For example, without tracking related complications to a diabetic patient, many diabetic patients will appear to have no complications when in fact they have eye or circulatory complications.
The seventh physician efficiency measurement error happens when the condition-specific outlier episode analysis is not performed in an appropriate manner. Many current methodologies perform the high-end outlier analysis by eliminating a percent of condition-specific episodes at the peer group (or aggregate episode) level. That is, the methodologies eliminate the high-end outliers before assigning episodes to physicians.
However, this method results in physician efficiency measurement error because a higher proportion of episodes assigned to the most inefficient physicians will be eliminated (as compared to the proportion of episodes eliminated for efficient physicians). Consequently, the inefficient physicians' condition-specific treatment patterns now more closely resemble the treatment patterns of the efficient physicians.
An example demonstrates this error. Assume Physician A has seven episodes of acute bronchitis with the following per episode charges: $235, $245, $325 $400, $525, $550, and $600. Also, the outlier cut-off threshold for high-end outlier episodes is set at $399 at the peer group level. Physician A now has only three episodes remaining at $235, $245, $325. The mean charge is $268 per episode. Assume Physician B also has 7 episodes of acute bronchitis with the following per episode charges: $210, $225, $235, $255, $285, $320, and $390. The peer-group level outlier threshold remains at $399. Therefore, Physician B has all seven episodes remaining, and the mean charge is $274.
The end result shows no statistical difference between Physicians A and B. The mean episode charge of Physician A is slightly lower than Physician B (i.e., $268 versus $274 per episode). However, using an outlier rule where we eliminate 5% of episodes (or at least 1 high-end outlier) are eliminated at the physician level, the results are significantly different. Physician A now has six remaining episodes (i.e., here we eliminate only 1 high-end outlier), and the mean charge of the six non-outlier episodes is now $380 per episode. For Physician B, the mean charge for the six non-outlier episodes is now $255 per episode. Physician A is statistically higher in average (or mean) episode charges than Physician B by $125 per episode.
The eighth error occurs in those systems that under-report charges attributed to partial (or incomplete) episodes of care. Some methodologies do not separate partial from complete episodes of care when measuring physician efficiency. Partial episodes result because a patient enrolled in a health plan during the study period or disenrolled during the study period. However, including partial episodes leads to inaccurate efficiency measurement because of under-reported episode charges—especially when some physicians have more partial episodes than other physicians.
A reason partial episodes often slip through the cracks and into an efficiency analysis is because the methodologies do not use a membership eligibility file to ensure the member is present for the entire study period. Instead, the methods assume that a condition-specific episode of care is complete if the episode exceeds some minimum duration time period. For example, if a patient's episode of diabetes is 40 days or more in duration, then the episode is marked as complete—and not partial. If a patient's diabetes episode is 39 days or less, then the episode is marked as partial.
Applying an indiscriminate time period duration to condition-specific episodes produces a high percentage of episodes marked as complete, which are actually partial (or incomplete) episodes. That is, many health plan's have membership turnover rates of 20% or higher. Consequently, a diabetes episode of 40 days duration—marked as complete—has at least a 20% chance of being a partial episode of care because of membership turnover. The end result may be physician efficiency differences that are attributed to the inclusion of partial episodes—and not to treatment patterns variation.
The ninth error happens in physician efficiency measurement systems that over-report charges attributed to episode endpoints. Some methodologies do not appropriately end a patient's episode of care before measuring a physician's efficiency. For example, chronic conditions may continue indefinitely and, therefore, patient episodes of care may be of various durations (e.g., 60 days or 600 days)—depending on the amount of available patient claims data. The end result may be physician efficiency differences that are attributed to excessively long or variable chronic condition episode durations—and not to treatment patterns variation.
The tenth error takes place in those systems that impose few requirements for having a minimum number of episodes in a certain number of medical conditions. Many methodologies do not require a minimum number of condition-specific episodes when comparing a physician's efficiency to a peer group. Instead, only a small handful (e.g., less than 10 episodes) are enough. However, there may be significant episode of care heterogeneity in one or two condition-specific episodes—even after applying a sophisticated severity-of-illness index. Consequently, examining an episode here-and-there for a physician may introduce significant error into a physician's efficiency measurement. The end result may be physician efficiency differences that are attributed to the heterogeneity in the low number of episodes examined—and not to treatment patterns variation.
Various systems have been patented in the episode of care field. Such systems are shown, for example, in U.S. Pat. Nos. 5,557,514, 5,835,897 and 5,970,463. However, none of these systems adequately overcome the aforementioned problems with respect to appropriately building and analyzing episodes of care. As importantly, existing systems fail to discuss an episode-of-care-based system for measuring individual or physician group efficiency measurement.
BRIEF SUMMARY OF THE INVENTION
In one aspect, the present invention provides a method of determining physician efficiency. The method comprises: obtaining medical claims data; performing patient analysis using the obtained medical claims data to form episodes of care; performing output process based on performed patient analysis, the output process comprising at least one act selected from the group consisting of: eliminating partial episodes of care and episodes of care marked with comorbidities; assigning episodes to physicians; grouping claim line items in episodes to service categories; and applying a maximum duration rule to episodes of care; assigning at least one physician to a report group; determining eligible physicians and episode assignments by performing at least one act selected from the group consisting of: eliminating physicians from the report group, the eliminated physicians having specialties that are not assigned to a grouping of medical conditions that account for some episodes treated by a physician having a specialty type; eliminating physicians that are not in a report group of interest; and eliminating episode assignments not meeting a selected criterion; calculating condition-specific episode statistics; calculating weighted episode statistics across medical conditions; and determining efficiency scores for physicians from the calculated condition-specific episode statistics and the weighted episode statistics calculated across medical conditions.
In an embodiment, the act of calculating condition-specific episode statistics comprises calculating condition-specific episode statistics for physicians in the report group. In an embodiment, the act of calculating condition-specific episode statistics comprises calculating condition-specific episode statistics for peer groups. In an embodiment, the act of calculating weighted episode statistics comprises calculating peer group weighted episode statistics across medical conditions. In an embodiment, the act of calculating weighted episode statistics comprises calculating physician weighted episode statistics across medical conditions.
In another aspect, the present invention provides a computer program product tangibly embodied in computer instructions which, when executed by a computer, determine physician efficiency. The computer instructions, when executed, perform the acts of: obtaining medical claims data; performing patient analysis using the obtained medical claims data to form episodes of care; performing output process based on performed patient analysis, the output process comprising at least one act selected from the group consisting of: eliminating partial episodes of care and episodes of care marked with comorbidities; assigning episodes to physicians; grouping claim line items in episodes to service categories; and applying a maximum duration rule to episodes of care; assigning at least one physician to a report group; determining eligible physicians and episode assignments by performing at least one act selected from the group consisting of: eliminating physicians from the report group, the eliminated physicians having specialties that are not assigned to a grouping of medical conditions that account for some episodes treated by a physician having a specialty type; eliminating physicians that are not in a report group of interest; and eliminating episode assignments not meeting a selected criterion; calculating condition-specific episode statistics; calculating weighted episode statistics across medical conditions; and determining efficiency scores for physicians from the calculated condition-specific episode statistics and the weighted episode statistics calculated across medical conditions.
In an embodiment, the act of calculating condition-specific episode statistics comprises calculating condition-specific episode statistics for physicians in the report group. In an embodiment, the act of calculating condition-specific episode statistics comprises calculating condition-specific episode statistics for peer groups. In an embodiment, the act of calculating weighted episode statistics comprises calculating peer group weighted episode statistics across medical conditions. In an embodiment, the act of calculating weighted episode statistics comprises calculating physician weighted episode statistics across medical conditions.
In yet another aspect, the present invention provides a system for determining physician efficiency. The system comprises means for obtaining medical claims data; means for performing patient analysis using the obtained medical claims data to form episodes of care; means for performing output process based on performed patient analysis, the output process comprising at least one act selected from the group consisting of: eliminating partial episodes of care and episodes of care marked with comorbidities; assigning episodes to physicians; grouping claim line items in episodes to service categories; and applying a maximum duration rule to episodes of care; means for assigning at least one physician to a report group; means for determining eligible physicians and episode assignments by performing at least one act selected from the group consisting of: eliminating physicians from the report group, the eliminated physicians having specialties that are not assigned to a grouping of medical conditions that account for some episodes treated by a physician having a specialty type; eliminating physicians that are not in a report group of interest; and eliminating episode assignments not meeting a selected criterion; means for calculating condition-specific episode statistics; means for calculating weighted episode statistics across medical conditions; and means for determining efficiency scores for physicians from the calculated condition-specific episode statistics and the weighted episode statistics calculated across medical conditions.
In an embodiment, the means for calculating condition-specific episode statistics comprises means for calculating condition-specific episode statistics for physicians in the report group. In an embodiment, the means for calculating condition-specific episode statistics comprises means for calculating condition-specific episode statistics for peer groups. In an embodiment, the means for calculating weighted episode statistics comprises means for calculating peer group weighted episode statistics across medical conditions. In an embodiment, the means for calculating weighted episode statistics comprises means for calculating physician weighted episode statistics across medical conditions.
In yet another aspect, the present invention provides a method of performing patient health risk stratification, the method comprising: obtaining medical claims data; performing patient analysis using the obtained medical claims data to form episodes of care; and performing output process based on performed patient analysis, the output process comprising at least one act selected from the group consisting of: eliminating partial episodes of care and episodes of care marked with comorbidities; assigning episodes to physicians; grouping claim line items in episodes to service categories; and applying a maximum duration rule to episodes of care.
In yet another aspect, the present invention provides a computer program product tangibly embodied in computer instructions which, when executed by a computer, performs patient health risk stratification. The computer instructions, when executed, perform the acts of: obtaining medical claims data; performing patient analysis using the obtained medical claims data to form episodes of care; and performing output process based on performed patient analysis, the output process comprising at least one act selected from the group consisting of: eliminating partial episodes of care and episodes of care marked with comorbidities; assigning episodes to physicians; grouping claim line items in episodes to service categories; and applying a maximum duration rule to episodes of care.
In yet another aspect, the present invention provides a system for performing patient health risk stratification. The system comprises: means for obtaining medical claims data; means for performing patient analysis using the obtained medical claims data to form episodes of care; and means for performing output process based on performed patient analysis, the output process comprising at least one act selected from the group consisting of: eliminating partial episodes of care and episodes of care marked with comorbidities; assigning episodes to physicians; grouping claim line items in episodes to service categories; and applying a maximum duration rule to episodes of care.
Additional features and advantages of the present invention will be realized by one skilled in the art upon reading the following detailed description, when considered in conjunction with the accompanying drawings.



BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a drawing that illustrates, in flow diagram form, functional aspects of the present invention.
FIG. 2 is a flowchart that illustrates, in flow diagram form, a sequence of acts executed in accordance with embodiments of the present invention.
FIG. 3 is a drawing that illustrates a dynamic window period utilized in defining the duration of an acute episode of care in accordance with embodiments of the present invention.
FIG. 4 is a drawing that illustrates a static window period utilized in defining the duration of an acute episode of care in accordance with embodiments of the present invention.
FIG. 5 is a drawing that illustrates a variable window period utilized in defining the duration of an acute episode of care in accordance with embodiments of the present invention.
FIG. 6 illustrates, in flow diagram form, a sequence of acts executed to perform a vertical merge rule function in accordance with embodiments of the present invention.
FIG. 7 illustrates, in flow diagram form, a sequence of acts executed to perform a horizontal merge rule function in accordance with embodiments of the present invention.
FIG. 8 illustrates, in tabular form, a Practitioner Efficiency Measurement Report 1, detailing average charges per episode of care.
FIG. 9 illustrates, in tabular form, a Practitioner Efficiency Measurement Report 2, detailing average utilization per episode of care



DETAILED DESCRIPTION
Step A: Utilize Claims Data File
Medical claims data is utilized in an embodiment of the present invention, and generally consists of a family, member, claim, and claim line item (CLI) structure. A claim generally consists of one or more CLIs. The claims data consists of medical events that are incurred by the patient visiting a healthcare professional or a facility in the ambulatory, outpatient, inpatient, home, and other environments where medical services may be delivered.
Step B: Extract Core Claims Data Fields
In order to form longitudinal episodes of care, assign them to physicians, and analyze individual physician efficiency, medical claims data must be mapped to the system requirements of the present invention. The process maps medical claims by performing field mapping and field value mapping. In field mapping, fields in the source data are identified that correspond to each of the required fields. In field value mapping, for each field where applicable, the user determines the field value that corresponds to each possible value that may occur in the source data.
Five types of data are mapped: client-defined codes, value fields, dates, system-specific codes, and standard codes. The present invention uses client-defined codes for physicians and members. Value fields include dollar amount, counts, and similar numeric data according to specified value formats. Calendar dates are mapped according to the specified standard format. System-specific codes include provider type, place of service, physician specialty, type of service, and similar codes. Standard codes include CPT codes, ICD.9 procedural codes, and similar codes.
A record refers to a CLI. The mapped claims file consists of one output record for each record in the source data, except those that are duplicates resulting from adjudication process. The field byte size is noted in Table 1 below. Each record is terminated by a one byte end-of-line character.
The present invention uses the fields in the following table. Mandatory fields must be filled for all records in the order listed for correct functionality of the present invention. Non-mandatory fields are optional.







TABLE 1







CLI Mapping Code Fields















Mandatory


Field



or Non-


Number
Type
Name & Description
Format
mandatory














1
1
Primary subscriber identifier. The subscriber number
15 char
M




used to identify a family unit.




2
1
Member identifier. The unique identifier of a person
15 char
M




within a family. The field value should uniquely identify






an individual when combined with the primary subscriber






identifier (field #1).




3
3
Claim start date. Date of first service on a claim.
8 date
NM





yyyymmdd



4
3
Claim end date. Date of last service on a claim.
8 date
NM





yyyymmdd



5
—
Not applicable to commercial market.
15 char
—


6
5
Subscriber's mailing address. The zip code of the
15 char
NM




subscriber's address.




7
4
Gender code. The gender for this CLI.
1 char, enum
NM


8
4
Race code. The race identifier for this CLI.
1 char, map
NM


9
3
Member's date of birth. The date of birth for the member
8 date
M




on this CLI. The entry in this field is used to calculate the
yyyymmdd





member's age.




10
4
Member status code. The entry in this field is used to
2 char
M




identify members who will be analyzed. Once a study
Field must =





population is identified, each member should be
10 for





assigned a value of 10 in this field. Otherwise, the 
member to





member will not be processed.
be processed



11
1
Referring provider identifier. Defines the provider that
15 char
NM




referred a member to another provider that generated the






specific claim of interest.




12
5
Procedure code year. The year that a specific CPT-4,
1 char
NM




HCPCS, UB-92, or ICD.9 procedure code was used on a






claim.




13
—
Not applicable to commercial market.
3 char
—


14
—
Not applicable to commercial market.
20 char
—


15
1
Performing provider identifier. This field refers to the
15 char
M




provider that billed for the specific CLI.




16
4
Provider type code. The type of billing entity that
1 char, map
M




delivered the service for this CLI.




17
4
Physician specialty code. The specialty under which the
2 char, map
M




physician or other health care professional delivered the






service for this CLI when delivered for payment.




18
—
Not applicable to commercial market.
1 char
—


19
—
Not applicable to commercial market.
1 char
—


20
2
Line item service count. The number of services
4 char
M




performed on a specific CLI.




21
—
Not applicable to commercial market.
1 char
—


22
4
Place of service code. The place where the unique
2 char, map
M




service of this line item was rendered to the patient.




23
3
Claim line item (CLI) start date. This field refers to the
8 date
M




date of the first service on a CLI
yyyymmdd



24
3
CLI end date. Date of last service on a CLI.
8 date
M





yyyymmdd



25
5
Procedure code. The specific CPT-4, HCPCS, ICD.9
5 char
M




procedure, UB-92, and other procedure codes used to






identify a specific service.




26
5
Initial procedure code modifier. Used to add an initial
2 char
NM




modifier to a procedure code.




27
5
Second procedure code modifier. This field is used to
2 char
NM




add a second modifier to a procedure code.




28
4
BETOS Code. Every CLI processed by the system
3 char
M




expect those submitted on UB-92 forms must have a






BETOS code.




29
5
National drug code. The national drug code (NDC) that
11 char
NM




identifies a specific prescription drug by product name,






formulation, and quantity.




30
—
Not applicable to commercial market.
7 char
—


31
2
Allowed charge amount. The allowed charge amount,
10 char
M




often referred to the covered charge amount. Allowed






charges typically equal submitted charges minus






ineligible charges and discounts. They include (are the






sum of) paid, copay/deductible/coinsurance, and COB.




32
—
Not applicable to commercial market.
2 char
—


33
—
Not applicable to commercial market.
1 char
—


34
5
CLI diagnosis code. The primary ICD.9 diagnosis code
5 char
M




on a CLI.




35
4
Detailed grouping code. A detailed grouping code is a
15 char
NM




client-specified identifier that is the base data element






aggregated together to form a report group. For example,






zip codes or tax identification numbers could be detailed






grouping codes.




36
5
Secondary CLI diagnosis code. The secondary ICD.9
5 char
NM




diagnosis code on a CLI.




37
5
Tertiary CLI diagnosis code. The tertiary ICD.9 diagnosis
5 char
NM




code on a CLI.









Provider type codes (Field 16) identify the type of billing entity that delivered a service to a patient. The defined provider types are: none, physician, facility, pharmacy, independent service provider, and other. For none, no provider type is identified. Physicians are professionals delivering medical care services, not just physicians. This provider type includes physicians, chiropractors, acupuncturists, podiatrists, nurse practitioners, physical therapists, and other professionals delivering medical care services. Facility includes hospital inpatient, hospital outpatient, long term nursing homes, intermediate nursing homes, skilled nursing homes, rehabilitation facilities, end-stage renal disease facilities, and similar facilities. Pharmacy includes walk-in or mail-order pharmacies. This provider type is used by the present invention to identify the use of a prescription drug. Independent service providers include providers that are not associated with a facility or a physician's office, such as independent laboratories and imaging centers. Typically, an independent service provider delivers services that, depending on physician office capabilities, could be provided in a physician's office directly. Other is healthcare services such as durable medical equipment providers, medical supply providers, ambulance, home meal delivery, and other similar providers. Table 2 shows the provider type codes.







TABLE 2







Provider Type Codes










Provider Type
Code







None
0



Physician
1



(This value is not applicable to
2



commercial populations.)




Facility
3



Pharmacy
4



Independent service provider
5



Other
6










Table 3 shows physician specialty codes (Field 17).








TABLE 3







Physician Specialty Codes










Specialty
Code














None (Use this code when physician 
0



is not the provider type)




Allergist
1



Allied Practitioner
2



Anesthesiology
3



Anesthesiology Assistant
4



Cardiology
5



Cardiothoracic surgery
6



Chiropractor
7



Dermatology
8



Emergency Medicine
9



Endocrinology
10



Family/General Practice
11



Gastroenterology
12



General Internist
13



General surgery
14



Genetic
15



Infectious Disease
16



Neonatal Care
17



Nephrology
18



Neurology
19



Neurosurgery
20



Obstetrician/Gynecologist
21



Oncology/Hematology
22



Ophthalmology
23



Optometry
24



Oral-maxillofacial Surgeon
25



Orthopedist
26



Otolaryngology (ENT)
27



Pain management
28



Pathology
29



Pediatrics
30



Plastic surgery
31



Podiatry
32



Psychiatry
33



Psychologist
34



Psychology Professional (e.g., social worker)
35



Pulmonology
36



Radiology
37



Rheumatology
38



Sports and physical medicine
39



Urology
40



Vascular surgeon
41



Critical care
42



Other
99










The place of service code identifies where a unique service was provided to a patient (e.g., office, outpatient facility of a hospital, inpatient facility of a hospital). Table 4 shows the place of service codes (Field 22)







TABLE 4







Place of Service Codes









Place of Service
Code
Description












None
0
No place of service code or unknown place




of service.


Office
1
Service delivered in a physician's office.


Home
2
Service delivered in a patient's home 




environment.


Emergency room
3
Service delivered in the emergency room 




department of a hospital.


Urgent care facility
4
Service delivered in an urgent care facility.


Inpatient hospital
5
Inpatient service delivered in a hospital.


Outpatient hospital
6
Outpatient service delivered in a hospital.


Ambulance
7
Service delivered in a land, air or water 




ambulance.


Ambulatory surgical 
8
Service delivered in a walk-in surgical 


center

center.


Birthing center
9
Service delivered in a birthing center.


Military treatment 
10
Service delivered in a military treatment 


facility

facility.


Inpatient psychiatric 
11
Service delivered on an inpatient basis at a 


facility

psychiatric facility for mental health or 




chemical dependency.


Public health clinic
12
Service delivered in a state or local public 




health clinic or a rural health clinic.


Independent 
13
Service delivered at an independent 


laboratory

laboratory.


Alternative care 
14
Service delivered in an alternate care facility 


facility

such as a skilled nursing facility, nursing 




facility, custodial care facility, hospice, 




adult living care facility (ACLF), 




psychiatric facility partial hospitalization, 




community mental health center, 




intermediate care facility/mentally 




retarded, residential substance abuse 




treatment facility, psychiatric residential 




treatment center, comprehensive inpatient 




rehabilitation facility comprehensive 




outpatient rehabilitation facility, end 




stage renal disease treatment facility, or 




similar facilities.


Other ambulatory 
15
Service delivered in a walk-in 


facility

environment such as a school, homeless 




shelter, health center, immunizations 




center, or similar facility.


Mobile unit
16
Service delivered in a unit that brings 




specific services to communities.


Other
17
Other places of service not included in 




the types listed in this table.


Pharmacy
18
Indicates that the prescription drug was 




dispensed by a walk-in or mail-order 




pharmacy. This includes hospital-run 




pharmacies that may dispense 




prescription drugs on an outpatient basis.









Type of Service (BETOS) Codes (Field 28)

In an embodiment, the present invention uses BETOS (Berenson-Eggers type of service) Codes as the type of service code (Field 28). The BETOS Code system is a procedure code system that organizes procedures and services into groupings that have been generally accepted as clinically meaningful. The BETOS Code system categories allow objective assignment of procedures and services. A BETOS Code must be assigned for each service on a CLI (e.g., CPT-4, HCPCS), except those submitted on UB-92 forms. Any homegrown codes or other special service codes that do not have BETOS Code must be mapped to a specific BETOS Codes.
In an embodiment, the present invention groups all health services with a BETOS Code into one of 11 service categories. Moreover, an embodiment of the present invention also groups all health services with a BETOS Code into one of 21 sub-service categories. Services without a BETOS Code will be assigned to our other medical services category. In an embodiment, alternative CLI health services grouping system may be applied other than BETOS codes.
The services provided during an episode of care are separated into the following 11 service categories and 21 sub-service categories presented below.
Category 0 is the overall results in the output files. The overall results are normally presented in the 0 row or the 0 section of the output file. This category captures the overall information for a physician. In an embodiment, the present invention calculates overall charges, but does not calculate overall utilization. As a result, the overall utilization entry 0 row is used to present the average duration (in days).
The professional visits (prof visits) service category presents charges and utilization for professional visits incurred in the physician's office, clinic or outpatient department of a hospital. For utilization, the numerator unit is visits. The sub-service category also is professional visits. This sub-service category presents charges and utilization for professional visits incurred in the physician's office, clinic, or outpatient department of a hospital.
The diagnostic tests (diag tests) service category presents charges and utilization for diagnostic tests incurred in the physician's office, clinic, outpatient department of a hospital, or surgicenter. Diagnostic tests represent imaging tests (X-rays, CAT scans, MRIs, etc.), functional tests (EKGs, echocardiograms, etc.), and invasive tests. There are three sub-service categories for diagnostic testing. The first sub-service category is imaging tests. This sub-service category presents charges and utilization for imaging tests, which include x-rays, CAT scans, MRI, and other related imaging tests. For utilization the numerator unit is services or tests. The second sub-service category is invasive testing. This sub-service category presents charges and utilization for angiography, cardiac catheterization, myocardial imaging, myelography, and other related invasive testing. For utilization, the numerator unit is services or tests. The third sub-service category is functional testing. This sub-service category presents charges and utilization for electrocardiograms, cardiovascular stress tests, echography, and other related functional testing. For utilization, the numerator unit is services or tests.
The laboratory and pathology (lab/path) service category presents charges and utilization for laboratory and pathology services incurred in the physician's office, clinic, outpatient department of a hospital, or surgicenter. For utilization, the numerator unit is services. There are two sub-service categories. The first sub-service category is laboratory (lab). This sub-service category presents charges and utilization for laboratory services incurred in the physician's office, clinic, outpatient department of a hospital, or surgicenter. For utilization, the numerator unit is services. The second sub-service category is pathology (path). This sub-service category presents charges and utilization for pathology services incurred in the physician's office, clinic, outpatient department of a hospital, or surgicenter. For utilization, the numerator unit is services.
The medical and surgical procedures (med/surg) service category presents charges and utilization for medical and surgical procedures incurred in the physician office, clinic, outpatient department of a hospital, and surgicenter. For utilization, the numerator unit is services or procedures. There are two sub-service categories. The first sub-service category is medical (med). This sub-service category presents charges and utilization for ophthalmological services (including eye exams), electro-oculography, otolaryngologic exam, evaluation of speech/voice, cardiac rehabilitation, muscle testing, neurobehavioral exams, and related medical procedures. For utilization, the numerator unit is services or procedures. The second sub-service category is surgical (surg). This sub-service category presents charges and utilization for surgical procedures incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. For utilization, the numerator unit is services or procedures.
The prescription drugs (Rx) service category presents charges and utilization for outpatient and ambulatory prescription drugs. For utilization, the numerator unit is prescription drug fills. The sub-service category also is prescription drugs. This sub-service category presents charges and utilization for outpatient and ambulatory prescription drugs.
The professional inpatient services (prof inpt) service category presents charges and utilization for all inpatient professional services. For utilization, the numerator unit is services. The sub-service category also is inpatient professional.
The facility outpatient visits (outpt facility) service category presents charges and utilization for services incurred in an outpatient department of a hospital or surgicenter. For utilization, the numerator unit is visits. There are two sub-service categories. The first sub-service category is emergency room facility. This sub-service category presents charges and utilization for emergency room facility services. For utilization, the numerator unit is visits. The second sub-service category is other outpatient facility. This sub-service category presents charges and utilization for other outpatient facility services, including medical/surgical, rehabilitation, and other services incurred in an outpatient department of a hospital or surgicenter. For utilization, the numerator unit is visits.
The facility inpatient days (hosp inpt days) service category presents charges and utilization for inpatient days for all hospital inpatient facility services. For utilization, the numerator unit is hospital inpatient days. The sub-service category also is inpatient facility days.
The facility inpatient admissions (hosp inpt admits) service category presents utilization for admissions for all hospital inpatient facility services. For utilization, the numerator unit is admissions. Charges are not presented for this service category. For charges, this service category is entered as “0,” because the episode charge component is assigned to the Facility Inpatient Days service category. The sub-service category also is inpatient facility admissions.
The alternative sites (altern sites) service category presents charges and utilization for skilled nursing facility and half-way home services. For utilization, the numerator unit is services. The sub-service category also is alternative sites.
The other medical services (other med) service category presents charges and utilization for other professional medical services incurred in the physician's office, clinic, outpatient department of a hospital, and dialysis center. Other medical services include physical therapy, chiropractic services (other than professional visits), chemotherapy and radiation, dental, durable medical equipment, and ambulance services. For utilization, the numerator unit is services. There are six sub-service categories. The first sub-service category is physical therapy. This sub-service category presents charges and utilization for manual therapy, electric simulation and other modalities, orthotics training, prosthetic training, and related physical therapy services. For utilization, the numerator unit is services.
The second sub-service category is dialysis. This sub-service category presents charges and utilization for end-stage renal disease (ESRD), hemodialysis, hemoperfusion, and related dialysis services. For utilization, the numerator unit is services. The third sub-service category is chemo/radiology. This sub-service category presents charges and utilization for chemotherapy administration, provision of chemotherapy agents, radiation dosimetry, brachytherapy isodose plans, radiation treatment delivery, and other related chemo/radiation services. For utilization, the numerator unit is services. The fourth sub-service category is anesthesia. This sub-service category presents charges and utilization for anesthesia. For utilization, the numerator unit is services. The fifth sub-service category is durable medical equipment (DME). This sub-service category presents charges and utilization for crutches, walkers, commode chairs, pressure pads, beds, portable oxygen, breast pumps, infusion supplies, wheelchairs, and related DME services. For utilization, the numerator unit is services. The sixth sub-service category is other medical care. This sub-service category presents charges and utilization for other medical care not easily classified elsewhere (e.g., ambulance, influenza immunization, dental not classified elsewhere). For utilization, the numerator unit is services.
Step 1. Build Flattened CLI Structure Input File
The traditional structure of CLI input files is hierarchical. In a hierarchical structure, there is a family (or subscriber) unit, and the individual members within the family are associated with the family unit. Then, the claim submissions for a member are associated to the member. This claim record generally contains information such as provider ID, provider specialty type, name of provider, and place of service. Finally, the CLIs within a claim are associated with the particular claim. The CLIs generally contain the detailed record information of each individual service rendered by the healthcare provider (e.g., CPT-4 code, ICD.9 (diagnosis) codes, number of services provided, service start and end dates).
Therefore, in a hierarchical structure, there are at least four different record types: family, member, claim, and CLI.
An advantage of the hierarchical structure is that it gives the user one data file, which generally is easy to manage. Furthermore, this structure is intuitive, as the structure is generally how claims processors at health plans think about organizing the submitted claims data.
The disadvantage of the hierarchical structure is that reading the records from the claim input file into the software takes significantly more CPU requirements as compared to the flattened CLI structure employed in embodiments of the present invention. Therefore, the hierarchical structure requires significantly higher software system processing time.
For the flattened CLI structure, there is only one record type produced for each CLI. Moreover, all records in the file are the exact same type and format. Therefore, each record forms a block that consists of a given number of the exact same bytes.
The flattened CLI structure contains all record field information that is present in the hierarchical CLI structure. Therefore, CLI records from members in the same family need to contain repeating family, member, and some unique claim information. On the surface, one may think that the repetition of family, member, and claim field variables on each CLI record will form a larger data file as compared to the hierarchical CLI structure.
However, this is not the case because the hierarchical CLI structure requires a ‘marker’ after each record to signify the start of another record. For example, in an embodiment, a marker is needed to signify that the family record information has ended and the member information begins; a marker is needed to signify that the member information has ended and the claim information begins; and a marker is needed to signify that the claim information has ended and the first CLI information for the claim begins.
Another issue with the hierarchical CLI structure is that the number of subordinate blocks of data is variable and, therefore, separate markers must be used to encode this information. For example, a family may have from one to N number of family members. Likewise, a single member may have from one to N number of claims, and a claim may have from one to N number of CLIs. In each of these cases, some type of encoding marker must be used to include this information into the data file. Additional CPU time is used in the software to read and handle these additional markers.
The volume of required markers within the hierarchical CLI structure makes the data file size similar to that of the flattened CLI structure.
The advantage of the flattened CLI structure is that the data file is easily read into a medical claims-based software, requiring significantly less CPU requirements as compared to a hierarchical CLI structure. The reason for less CPU intensive record reading is that computers like to read fixed length records of the same type and format (i.e., blocks of data). The overall read step processing time, then, is significantly reduced.
Step 2: Read in Run.INI File
The operation of the system of the present invention is influenced by parameters. Parameters are named controls found within the system of the present invention run initialization file (or RUN.INI File). Controls influence the results generated by the system of the present invention. Table 6 presents the parameters in the RUN.INI file.







TABLE 6







Parameters in the RUN.INI File









Parameter Name
Notes
Values










Module Control Programs









RUN_PATAN
Controls whether the PATAN module is
0 = No



executed during the current run.
1 = Yes




Initial System setting = 1


RUN_PROVSPEC
Controls where the PROVSPEC module is
0 = No



executed during the current run.
1 = Yes




Initial System setting = 1


RUN_PROVAN
Controls whether the PROVAN module is
0 = No



executed during the current run.
1 = Yes




Initial System setting = 1







General Directory Parameters









DIR_BIN
Defines the location of program files.
Directory path


DIR_SYSTABLE
Defines the location of system methodology
Directory path



tables (see the “Control Tables” section of




this manual).



DIR_DATA
Defines the root directory for all data files,
Directory path



both input and output.



DIR_RUNTABLE
Defines the location of both data-specific
Directory path



tables and pre-specified tables (see the




“Control Tables” section of this manual).



FILE_PROVIDER
Defines the location of the physician
File Name



specialty file (see the “Data-Specific Tables”




section of this manual).



FILE_GROUPCODEMAP
Defines the detail grouping code to the
File Name



aggregate grouping code.








Module Runtime Parameters


Grouper function









SWITCH AGGREGATESTART
Defines the start number for the Aggregate
0 = Do not eliminate any



Grouping Codes to be processed. For more
Aggregate Grouping



information on Aggregate Grouping Codes
Codes from the beginning



see the chapter, “Report Group Structures”.
of the list



NOTE: Leave the value of this switch at 0




unless you want to limit the groups to be
N (any whole number) =



processed.
Specifies the first




Aggregate Grouping Code




to be processed. All codes




that are smaller than this




value will not be




processed




Initial System setting = 0


SWITCH_AGGREGATEEND
Defines the end number of the Aggregate
0 = Do not eliminate any



Grouping Codes to be processed. For more
Aggregate Grouping



information on Aggregate Grouping Codes
Codes from the end of the



see the chapter, “Report Group Structures.”
list




N (any whole number) =




Specifies the last




Aggregate Grouping Code




to be processed. All codes




that are larger than this




value will not be




processed.




Initial System setting = 0


FILE_SPECAGE
Identifies the file containing the age control
File Name with respect to



table for each specialty.
DIR_RUNTABLE




Initial System setting =




specage.tab


FILE_MBCONDITIONS
Identifies the file that relates medical
File Names with respect to



conditions to classifications in accordance
DIR_RUNTABLE



with the present inventions.
Initial System setting =




mbconditions.tab







PATAN









SWITCH_DROPPARTIAL
Controls whether partial episodes are
0 = Include



included in analysis.
1 = Exclude




Initial System setting = 1


SWITCH_DROPCOMORB
Controls whether comorbid episodes are
0 = Include



included in analysis.
1 = Exclude




Initial System setting = 1


SWITCH_ASSIGNTHRESHOLD
Defines a percent whereby when a physician
Any whole number



has this percent or more of total professional
representing a percent



charges associated with an episode, that
Initial System setting = 20



episode is assigned to the physician. The




professional charges considered for this




threshold may occur in an office visit, clinic,




hospital outpatient, hospital inpatient, or




other professional setting (e.g., nursing




home, halfway home, home visit professional




charges). All facility charges and prescription




drug charges are excluded.








PROVSPEC


NONE


PROVAN









SWITCH_LOWOUTPERCENT
Defines what percentage of a physician's
0 = 0.0%



least expensive episodes will be removed
1 = 1.0%



from analysis. PROVAN removes episodes
2 = 2.5%



from each medical condition in the
3 = 5.0%



physician's marketbasket separately.
4 = 10.0%



PROVAN starts with the least expensive
Initial System setting = 2



episode and continues removing episodes in




order of expense until the specified




percentage of episodes is reached.



SWITCH_LOWOUTDOLLAR
Sets a threshold for episode charges. All
A whole number



episodes below the value of this switch will
representing a dollar value.



be dropped from analysis.
Initial System setting = 20


SWITCH HIGHOUTPERCENT
Defines what percentage of a physician's
0 = 0.0%



most expensive episodes will be removed
1 = 1.0%



from analysis. PROVAN removes episodes
2 = 2.5%



from each medical condition in the
3 = 5.0%



physician's marketbasket. PROVAN starts
4 = 10.0%



with the most expensive episode and
Initial System setting = 3



continues removing episodes in order of




expense until the specified percentage of




episodes is reached.



SWITCH_HIGHOUTDIFF
The parameter SWITCH_HIGHOUTDIFF
A whole number that



determines whether a signal episode should
represents a percent.



be removed as a high-outlier. This high-end
NOTE: Should always 



outlier parameter is applied when one high-
be ≧100. If ≦100,



end outlier cannot be removed under the
then an episode will



SWITCH_HIGHOUTPERCENT parameter.
ALWAYS be removed.



The value of this parameter is a whole
Initial System setting = 250



number representing a percent. If the




charges for the most expensive episode are




at least the defined percent greater than the




charges for the next most expensive




episode, the most expensive episode is




removed as a high outlier. A maximum of




one episode for each medical condition in




each physician's marketbasket may be




removed using this rule.



SWITCH_MINEPCOUNT
Sets the requirement for the number of
Any whole number 



episodes a physician must treat to be
Initial System setting = 2



included in the analysis. This parameter




implement part of the N × 3 rule, which




specifies that a physician must treat N




episodes in three medical conditions to be




included. For example, if the N value is equal




to four, the rule would require four episodes




in each of three conditions, and the rule




would become, in effect a “4 × 3” rule.




In the N × 3 rule:




N = The number of episodes of a




specific medical condition a physician




must treat during the study period.




This number can be changed by the




user.




3 = the minimum number of medical




conditions in which the physician must treat




episodes. The medical conditions must be in




the physician's marketbasket . This number




cannot be changed.



SWITCH CONFLEVEL
Sets the p value for statistical confidence.
1 = 0.75




(p < 0.25)




2 = 0.90




(p < 0.10)




Initial System setting = 1







PATAN Date Parameters









STUDYSTARTDATE
Defines the start date of the study period.
A date in the format




yyyymmdd


STUDYENDDATE
Defines the end date of the study period.
A date in the format




yyyymmdd


STUDYMIDDATE
Sets the midpoint date of the study period. A
A date in the format



chronic episode of care must start on or
yyyymmdd



before this date.



STUDYQ4DATE
Defines the date that is the end of the third
A date in the format



quarter of the study period (the last day
yyyymmdd



before the fourth quarter starts). An acute




episode of care from a medical condition with




a window period 120 days must start on or




before this date.








Slider Parameters









STUDYSLIDER1_START
Sets the start date of the slider period for
A date in the format



Slider 1.
yyyymmdd


STUDYSLIDER1_END
Sets the end date of the slider period for
A date in the format



Slider 1.
yyyymmdd


STUDYSLIDER2_START
Sets the start date of the slider period for
A date in the format



Slider 2.
yyyymmdd


STUDYSLIDER2_END
Sets the end date of the slider period for
A date in the format



Slider 2.
yyyymmdd


DIR_PATSORT
Identifies the subdirectory that receives the
Directory name



PATSORT output. This subdirectory is within
Initial System setting = 



the DIR DATA directory path.
patsort


DIR_PATAN
Identifies the subdirectory that receives the
Directory name



PATAN output. This subdirectory is within
Initial System setting = 



the DIR_DATA directory path.
patan


DIR_PROVSORT1
Identifies the subdirectory that receives the
Directory name



PROVSORT1 output. This subdirectory is
Initial System setting = 



within the DIR_DATA directory path.
provsort1


DIR_PROVSPEC
Identifies the subdirectory that receives the
Directory names



PROVSPEC output. This subdirectory is
Initial System setting = 



within the DIR_DATA directory path.
provspec


DIR_PROVSORT2
Identifies the subdirectory that receives the
Directory name



PROVSORT2 output. This subdirectory is
Initial System setting = 



within the DIR_DATA directory path.
provsort2


DIR_PROVAN
Identifies the subdirectory that receives the
Directory name



PROVAN output. This subdirectory is within
Initial System setting = 



the DIR_DATA directory path.
provan







Data file Parameters - within DIR_DATA









COREFILE
Defines the subdirectory and filename that
Directory name/File name



contains the input claims file. The
Initial System setting =



subdirectory is within the DIR_DATA
extract/corefields



directory path.



CORESORTED
Defines the subdirectory and filename that
Directory name/File name



contains the sorted claims file. The
Initial System setting =



subdirectory is within the DIR_DATA
patsort/sampledata. sort



directory path.



ASNFILE
Defines the subdirectory and filename that
Directory name/File name



contains the output file from PATAN. The
Initial System setting =



subdirectory is within the DIR_DATA
patan/assign.tab



directory path.



ASNSORTED
Defines the subdirectory and filename that
Directory name/File name



contains the sorted output file from PATAN.
Initial System setting =



The subdirectory is within the DIR_DATA
provsort1/assign.tab.sort



directory path.



ASNSPECFILE
Defines the subdirectory and filename that
Directory name/File name



contains the output file from PROVSPEC.
Initial System setting =



The subdirectory is within the DIR_DATA
provspec/assignspec.tab



directory path.



ASNSPECSORTED
Defines the subdirectory and filename that
Directory name/File name



contains the sorted output file from
Initial System setting =



PROVSPEC. The subdirectory is within the
provsort2/assignspec.tab.sort



DIR_DATA directory path.



SCOREFILE
Defines the subdirectory and filename that
Directory name/File name



contains one of the two final output files. The
Initial System setting =



subdirectory is within the DIR_DATA
provan/score.tab



directory path.



DETAILFILE
Defines the subdirectory and filename that
Directory name/File name



contains one of the two final output files. The
Initial System setting =



subdirectory is within the DIR_DATA
provan/detail.tab



directory path.









Step 3: Read in CLIs from Flattened CLI Structure

The CLIs in the Flattened CLI Structure are now read into the patient sort (PATSORT). PATSORT sorts CLIs by the primary sort key of member (or patient) and the secondary sort key of date of service on each CLI. During PATSORT, all CLIs with zero dollars in charges ($0) are removed from further analysis.
Step 4: Apply Sliders
An embodiment of the present invention uses sliders to establish that a member was present during an ongoing condition-specific episode of care. The purpose of sliders is to establish the presence of members during ongoing condition-specific episodes of care without using an eligibility file. Often, membership eligibility files are not readily accessible to the user.
An embodiment of the present invention employs two sliders, each of which can be set with a start date and an end date. These dates can be set by the user. The period that includes the start and end dates and the time in between is the slider period. The use of sliders allows the user to establish that a member was present at least for some period of time near the beginning and near the end of the study period. If so, then the user concludes that the member was present during the ongoing condition-specific episode of care.
An embodiment of the present invention checks to see that the member was represented by a CLI that began and ended during each slider period. If not, then the member and all CLIs related to that member are removed from the analysis.
The two sliders are referred to herein as Slider 1 and Slider 2. Slider period settings for a calendar year study period are as follows: Slider 1 is set for the time period of January 1 through June 30. (If not using a calendar year, then use the first six months of the study period.) Slider 2 is set for the time period of July 1 through December 31. (If not using a calendar year, then use the second six months of the study period.) With these settings, a member must have a claim in both the first and second halves of the year to be included in the analysis.
Table 7 illustrates examples of suggested slider settings for a study period that starts on January 1 and ends on December 31.







TABLE 7







Recommended Slider Settings









Example 




#
Slider Settings
Notes





1
Slider period 1: January
With these settings, a member must 



1 through June 30
have one final adjudicated claim in 



Slider period 2: July 1
each slider period to be included in 



through December 31
the analysis. These settings increase 




the likelihood that a member included 




in the analysis was in fact present 




during an ongoing episode of care.


2
Slider period 1: March 1
A member who has one final 



through December 31
adjudicated claim during slider period 



Slider period 2: March 1
1 is assumed to be present during the 



through December 31
entire year. Slider 2 is ignored because 




its slider period is identical to Slider 




1's period. This setting keeps many 




members in the analysis.









Step 5: Perform PATAN Analysis to Form Episodes of Care

The Patient Analysis (PATAN) forms episodes of care using a Grouper function explained herein. The Grouper function is based on the International Classification of Diseases, 9th revision (ICD.9) and the Current Procedural Terminology, 4th edition (CPT-4). The Grouper function groups together over 14,000 unique ICD.9 diagnosis codes into 526 meaningful medical conditions. Each ICD.9 code is assigned to a single medical condition.
The resulting 526 medical conditions are formed based on clinical homogeneity with respect to generating a similar clinical response from physicians treating a patient. Table M shows selected ICD.9 codes mapped to several medical conditions.







TABLE M







Selected Diagnosis (ICD.9) Codes Mapped to Medical Conditions










Medical





Condition
Medical Condition
ICD.9



Number
Long Description
Codes
Brief Description













5.2
Conjunctivitis
077.0
Conjunctivitis, inclusion




077.8
Conjunctivitis, viral




372.0
Conjunctivitis, acute




372.01
Conjunctivitis, serous




372.1
Conjunctivitis, chronic




372.14
Conjunctivitis chronic allergic




372.22
Contact blepharonconjunctivitist


6.5
Otitis media
381
Eustachian tube disorder




381.02
Acute mucoid otitis media




381.06
Acute allergic sanguinous otitis 





media




381.20
Chronic mucoid otitis media




382
Suppurative otitis media




382.00
Acute suppurative otitis media




382.4
Suppurative otitis media




382.01
Acute suppurative, with drum 





rupture




382.1
Chronic tubotympanic 





suppurative


7.2
Sinusitis
461.0
Acute maxillary sinusitis




461.2
Acute ethomoidal sinusitis




461.3
Acute sphenoidal sinusitis




473
Chronic sinusitis




473.2
Chronic ethmoidal sinusitis




473.3
Chronic sphenoidal sinusitis


9.11
Asthma
493.0
Extrinsic asthma




493.02
Extrinsic asthma, acute 





exacerbation




493.1
Intrinsic asthma




493.01
Extrinsic asthma, status 





asthmaticus




493.2
Chronic obstructive asthma




493.21
Chronic obstructive, status 





asthmaticus


10.2
Hypertension
401.1
Benign essential hypertension




405.1
Secondary benign hypertension




402
Hypertensive heart disease




402.0
Hypertensive heart disease, 





malignant




403.00
Hypertension renal, malignant




403.1
Hypertension renal, benign 





disease




405.0
Secondary malignant 





hypertension




402.11
Hypertensive heart, malignant, 





heart failure




404.01
Hypertensive heart/renal, 





malignant health failure




404.11
Hypertensive heart/renal, benign, 





heart failure









The 526 medical conditions are placed into one of 37 Principle Medical Condition Groups (PMC Groups). The PMC Groups generally represent organ, body, or medical condition types (e.g., PMC Group 5-Eye Conditions; PMC Group 9-Respiratory Conditions; PMC Group 24-Mental Disorders). Table 8 presents the list of PMC Groups.







TABLE 8







Principle Medical Condition (PMC) Groups









Principle




Medical




Condition
PMC Group
PMC Group


Groups
Long Description
Abbreviated Description












1
Preventive Care
Preventive Care


2
Infectious and Parasitic 
Infectious & Parasitic Dz



Diseases



3
Human Immunodeficiency 
HIV Infections



Infections



4
Nervous System Conditions
Nervous System Conditions


5
Eye Conditions
Eye Conditions


6
Ear Conditions
Ear Conditions


7
Nose Conditions
Nose Conditions


8
Mouth Conditions
Mount Conditions


9
Respiratory Conditions
Respiratory Conditions


10
Heart and Pulmonary 
Heart and Pulmonary Cond



Conditions



11
Cerebrovascular and Artery 
Cerebrovasc & Artery Cond



Conditions



12
Vein and Lymphatic 
Vein & Lymphatic Cond



Conditions



13
Digestive System Conditions
Digestive System Cond


14
Hernias
Hernias


15
Hepatobiliary System and 
Hepatobiliary Sys & Pancreas



Pancreas



16
Thyroid Disorders
Thyroid Disorders


17
Diabetes Mellitus
Diabetes Mellitus


18
Other Endocrine Disorders
Other Endocrine Disorders


19
Metabolic Disorders
Metabolic Disorders


20
Immunity and Blood Disorders
Immunity & Blood Disorders


21
Lymphatic and Hematopoietic 
Lymph & Hematopoietic Tiss



Tissue



22
Urinary Tract and Kidney 
Urinary Tract & Kidney Cond



Conditions



23
Female Reproductive 
Female Reproductive Cond



Conditions



24
Male Reproductive Conditions
Male Reproductive Cond


25
Infertility Treatment
Infertility Treatment


26
Maternity-Related Conditions
Maternity-Related Cond


27
Neonatal Conditions
Neonatal Conditions


28
Congenital Anomalies
Congenital Anomalies


29
Skin and Subcutaneous Tissue 
Skin & Subcutaneous Tissue



Conditions



30
Breast Conditions
Breast Conditions


31
Musculoskeletal Conditions
Musculoskeletal Conditions


32
Upper Limb Conditions
Upper Limb Conditions


33
Lower Limb Conditions
Lower Limb Conditions


34
Mental Disorders
Mental Disorders


35
Burns
Burns


36
Other Medical Conditions
Other Medical Conditions


37
Replaced Diagnosis Codes
Replaced Diagnosis Codes









Within each PMC Group, medical conditions are listed in ascending order of expected resource intensity level and physiologic progression of the condition or disease (from least resource intensive and physiologic progression to the most resource intensive and physiologic progression). Table 9 shows an example for PMC Group 6, Ear Conditions.







TABLE 9







PMC Group 6-Ear Conditions








Medical



Condition
Medical Condition


Number
Long Description











6
Ear Conditions


6.1
Otitis externa


6.2
Wax in ear


6.3
Open wound of ear


6.4
Other disorders of ear


6.5
Otitis media


6.6
Disorders of tympanic membrane


6.7
Disorders of middle ear


6.8
Vertiginous syndromes


6.9
Mastoiditis


6.10
Hearing loss


6.11
Malignant neoplasm of middle ear









The 526 medical conditions in the Grouper function account for 100% of all medical conditions and expenditures as identified by ICD.9 medical condition diagnostic codes. Each condition receives a Medical Condition Number (e.g., Medical Condition 4.1-neuritis upper and lower limbs; Medical Condition 5.16-glaucoma; Medical Condition 7.2-sinusitis; Medical Condition 9.11-asthma; Medical Condition 10.13-ischemic heart disease). Table 10 presents the list of medical conditions in the Grouper function.







TABLE 10







List of Medical Conditions in Grouper Function













Number


Medical


of


Condition
Medical Condition
Medical Condition
Severity


Number
Long Description
Abbrev Description
Classes













1
Preventive Care
Preventive Care
—


1.1
General medical exam
General medical exam
1


1.2
Gynecological exam
Gynecological exam
1


1.3
Screenings for medical conditions
Screening of med conditions
1


1.4
Vaccinations
Vaccinations
1


1.5
Prophylactic therapy
Prophylactic therapy
1


1.6
History of medical conditions
Hx of medical conditions
1


1.7
Postpartum exam
Postpartum exam
1


1.8
Surgical aftercare
Surgical aftercare
1


2
Infectious and Parasitic Diseases
Infectious & Parasitic Dz
—


2.1
Intestinal infections
Intestinal infections
1


2.2
Other bacteria disease
Other bacteria diseases
3


2.3
Drug-resistant microorganism
Drug-resistant microorganism
1


2.4
Septicemia
Septicemia
2


2.5
Tuberculosis
Tuberculosis
3


2.6
Other viral diseases
Other viral diseases
3


2.7
Chickenpox
Chickenpox
3


2.8
Herpes simplex
Herpes simplex
3


2.9
Viral warts
Viral warts
1


2.10
Infectious mononucleosis
Infectious mononucleosis
1


2.11
Cytomegalic inclusion disease
Cytomegalic inclusion dz
1


2.12
Non-arthropod-borne viral diseases
Non-arth-borne viral dz
3


2.13
Arthropod-borne diseases
Arthropod-borne dz
3


2.14
Venereal diseases
Venereal diseases
3


2.15
Other mycoses
Other mycoses
1


2.16
Cryptococcosis
Cryptococcosis
1


2.17
Candidiasis
Candidiasis
3


2.18
Coccidioidomycosis
Coccidioidomycosis
3


2.19
Histoplasmosis
Histoplasmosis
3


2.20
Blastomycotic infection
Blastomycotic infection
2


2.21
Helm inthiases
Helm inthiases
3


2.22
Scabies
Scabies
1


2.23
Toxoplasmosis
Toxoplasmosis
3


2.24
Pneumocystosis
Pneumocystosis
1


2.25
Other infectious diseases
Other infectious diseases
3


3
Human Immunodeficiency Infections
HIV Infections
—


3.1
HIV infection with no complications
HIV n/no complications
1


3.2
HIV infection with infectious complication
HIV with infectious comp
3


3.3
HIV infection with CNS involvement
HIV with CNS involvement
3


3.4
HIV infection with malignancy
HIV with malignancy
3


3.5
HIV infection with multiple complications
HIV with multiple comp
3


4
Nervous System Conditions
Nervous System Conditions
—


4.1
Neuritis upper and lower limbs
Neuritis upper, lower limbs
2


4.2
Peripheral neuropathy
Peripheral neuropathy
3


4.3
Headaches
Headaches
2


4.4
Disorders of cranial nerves
Disorders of cranial nerves
2


4.5
Carpal tunnel syndrome
Carpal tunnel syndrome
1


4.6
Benign neoplasm of non-CNS nerves
Benign neop non-CNS nerves
1


4.7
Nerve root and plexus disorder
Nerve root and plexus dsdr
3


4.8
Tremor disorders
Tremor disorders
2


4.9
Injury to peripheral nerves and nerve roots
lnj peripheral nerv & nerv roots
3


4.10
Neurofibromatosis
Neurofibromatosis
1


4.11
Inflammatory diseases of CNS
Inflammatory dz of CNS
1


4.12
Paralytic syndromes
Paralytic syndromes
3


4.13
Myoneural disorders
Myoneural disordes
2


4.14
Benign neoplasm of CNS
Benign neoplasm of CNS
1


4.15
Injury of spinal cord
Injury of spinal cord
3


4.16
Congenital anomalies of nervous system
Cong anomalies nerv sys
3


4.17
Parkinson's disease
Parkinson's disease
1


4.18
Seizure disorders
Seizure disorders
3


4.19
Multiple sclerosis
Multiple sclerosis
1


4.20
Other CNS diseases
Other CNS diseases
3


4.21
Muscular dystrophies
Muscular dystrophies
2


4.22
Malignant neoplasm of non-CNS
nerves Malig neop non-CNS nerves
1


4.23
Malignant neoplasm of spinal cord
Malig neop spinal cord
1


4.24
Malignant neoplasm of brain, initial care
Malig neop brain, initial
1


4.25
Malignant neoplasm of brain, active care
Malig neop brain, active
1


4.26
Malignant neoplasm of brain, inactive care
Malig neop brian, inactive
1


5
Eye Conditions
Eye Conditions
—


5.1
Refractive errors
Refractive errors
1


5.2
Conjunctivits
Conjunctivitis
2


5.3
Other disorders of conjunctiva
Other dsdr of conjunctiva
2


5.4
Infections of the eyelids
Infections of the eyelids
2


5.5
Disorders of eyelids
Disorders of eyelids
2


5.6
Disorders of lacrimal system
Dsdr of lacrimal system
2


5.7
Keratitis
Keratitis
3


5.8
Other disorders of cornea
Other disorders of cornea
3


5.9
Disorders of iris and ciliary body
Dsdr iris and ciliary body
3


5.10
Strabismus
Strabismus
3


5.11
External eye injury
External eye injury
2


5.12
Disorders of globe
Disorders of globe
3


5.13
Internal eye injury
Internal eye injury
2


5.14
Disorders of vitreous body
Disorders of vitreous body
2


5.15
Other eye disorders
Other eye disorders
3


5.16
Glaucoma
Glaucoma
3


5.17
Cataract
Cataract
3


5.18
Other retinal disorders
Other retinal disorders
3


5.19
Macular degeneration
Macular degeneration
2


5.20
Retinal detachments and defects
Retinal detach & defects
3


5.21
Blindness and visual disturbances
Blindness & visual disturb
3


5.22
Malignant neoplasm of eye
Malignant neoplasm of eye
1


6
Ear conditions
Ear Conditions
—


6.1
Otitis externa
Otitis externa
3


6.2
Wax in ear
Wax in ear
1


6.3
Open wound of ear
Open wound of ear
3


6.4
Other disorders of ear
Other disorders of ear
3


6.5
Otitis media
Otitis media
3


6.6
Disorders of tympanic membrane
Dsdr of tympanic membrane
3


6.7
Disorders of middle ear
Disorders of middle ear
3


6.8
Vertiginous syndromes
Vertiginous syndromes
3


6.9
Mastoiditis
Mastoiditis
3


6.10
Hearing loss
Hearing loss
3


6.11
Malignant neoplasm of middle ear
Malig neop of middle ear
1


7
Nose Conditions
Nose conditions
—


7.1
Rhinitis
Rhinitis
2


7.2
Sinusitis
Sinusitis
2


7.3
Other nasal disorders
Other nasal disorders
3


7.4
Deviated nasal septum
Deviated nasal septum
1


7.5
Nasal bone fracture
Nasal bone fracture
2


7.6
Malignant neoplasm of nasal cavities
Malig neop of nasal cavities
3


8
Mouth Conditions
Mouth Conditions
—


8.1
Cleft palate and lip
Cleft palate and lip
3


8.2
Congenital anomalies of oral cavity
Cong anomalies oral cavity
2


8.3
Congenital anomalies of face, jaw, skull
Cong anom face, jaw, skull
2


8.4
Disorders of teeth
Disorders of teeth
3


8.5
Open wound of face and mount
Open wound face & mouth
3


8.6
Anomalies of jaw size
Anomalies of jaw size
1


8.7
Other dentofacial anomalies
Other dentofacial anom
1


8.8
Gingival and periodontal diseases
Gingival & periodontal dz
2


8.9
Other disease of supporting structure
Other dz supporting struct
1


8.10
Temporomandibular joint disorder
TMJ disorder
1


8.11
Other dentofacial disorders
Other dentofacial disorders
3


8.12
Diseases of jaws
Diseases of jaws
2


8.13
Disease of salivary glands
Diseases of salivary glands
3


8.14
Diseases of oral soft tissue
Diseases of oral soft tissue
3


8.15
Benign neoplasm of oral cavity
Benign neop of oral cavity
2


8.16
Jaw fracture
Jaw fracture
3


8.17
Malignant neoplasm of oral cavity
Malig neop oral cavity
3


9
Respiratory Conditions
Respiratory Conditions
—


9.1
Upper respiratory infections
Upper respiratory infections
3


9.2
Diseases of upper respiratory tract
Dz upper respiratory tract
3


9.3
Lower respiratory diseases
Lower respiratory disease
3


9.4
Acute bronchitis
Acute bronchitis
2


9.5
Hypertrophy of tonsils and adenoids
Hypertrophy tonsils & aden
2


9.6
Congenital anomaly of respiratory system
Cong anon respire system
3


9.7
Pneumonia
Pneumonia
3


9.8
Disorders of lower respiratory tract
Dsdr of lower respir tract
1


9.9
Pleurisy
Pleurisy
2


9.10
Chronic bronchitis
Chronic bronchitis
2


9.11
Asthma
Asthma
3


9.12
Benign neoplasm of bronchus and lung
Benign neop bronchus & lung
3


9.13
Emphysema
Emphysema
2


9.14
Chronic obstructive pulmonary disease
COPD
1


9.15
Spontaneous pneumothorax
Spon pneumothorax
1


9.16
Lung transplant
Lung transplant
1


9.17
Malignant neoplasm of pharynx and larynx
Malig neop pharyn & laryn
2


9.18
Malignant neoplasm of pleura
Malig neop of pleura
2


9.19
Malignant neoplasm of bronchus and lung,
Malig neop bron/lung, active
2



active




9.20
Malignant neoplasm of bronchus and lung,
Malig neop bron/ling, inactive
2



inactive




10
Heart and Pulmonary Conditions
Heart and Pulmonary Cond
—


10.1
Abnormal heart beat
Abnormal heart beat
2


10.2
Hypertension
Hypertension
3


10.3
Congenital anomaly of circulatory system
Cong anom circulatory sys
3


10.4
Ventricular arrhythmias
Ventricular arrhythmias
3


10.5
Supraventricular arrhythmias
Supraventricular arrhythmias
3


10.6
Atrial septal defect
Atrial septal defect
2


10.7
Ventricular septal defect
Ventricular septal defect
2


10.8
Angina pectoris
Angina pectoris
1


10.9
Rheumatic fever
Rheumatic fever
2


10.10
Conduction disorders
Conduction disorders
3


10.11
Other heart disease
Other heart disease
3


10.12
Rheumatic heart disease
Rheumatic heart disease
2


10.13
Ischemic heart disease
Ischemic heart disease
3


10.14
Heart value disorders
Heart value disorders
3


10.15
Pulmonary heart disease
Pulmonary heart disease
3


10.16
Congestive heart failure
Congestive heart failure
2


10.17
Cardiomyopathy
Cardiomyopathy
2


10.18
Other aneurysm
Other aneurysm
3


10.19
Aortic aneurysm, initial
Aortic aneurysm, initial
2


10.20
Aortic aneurysm, follow-up
Aortic aneurysm, follow-up
2


10.21
Acute myocardial infarction, active
Acute myocardial infrct, active
2


10.22
Acute myocardial infarction, follow-up
Acute myocardial infct, fup
2


10.23
Heart transplant
Heart transplant
1


10.24
Malignant neoplasm of mediastinum
Malig neop of mediastinum
2


10.25
Malignant neoplasm of heart
Malig neoplasm of heart
1


11
Cerebrovascular and Artery Conditions
Cerebrovasc & Artery Cond
—


11.1
Pigmented nevus
Pigmented nevus
1


11.2
Superficial injury of head and neck
Superficial injury head & neck
2


11.3
Contusion of head and neck
Contusion of head and neck
1


11.4
Concussion
Concussion
3


11.5
Cerebral laceration
Cerebral laceration
3


11.6
Diseases of capillaries
Diseases of capillaries
1


11.7
Disorders of arteries
Disorders of arteries
3


11.8
Generalized arteriosclerosis
Generalized arteriosclerosis
3


11.9
Fracture of skull
Fracture of skull
3


11.10
Transient cerebral ischemia
Transient cerebral ischemia
3


11.11
Injury to blood vessels of head and neck
Inj to bl vessels head & neck
1


11.12
Occlusion of cerebral arteries
Occlusion of cerebral arteries
3


11.13
Cerebrovascular hemorrhage following injury
Cerebro hemorrhage, injury
3


11.14
Cerebrovascular hemorrhage
Cerebrovascular hemorrhage
2


12
Vein and Lymphatic Conditions
Vein & Lymphatic Cond
—


12.1
Anal fissure and fistula
Anal fissure and fistula
2


12.2
Hemorrhoids
Hemorrhoids
3


12.3
Other peripheral vascular diseases
Other peripheral vascular dz
3


12.4
Varicose veins of other sites
Varicose veins of other sites
3


12.5
Varicose veins of lower extremities
Varicose veins lower extreme
3


12.6
Thrombophlebitis
Thrombophlebitis
3


13
Digestive System Conditions
Digestive System Cond
—


13.1
Helicobacter pylori infection
Helicobacter pylori infection
1


13.2
Congenital anomaly of digestive system
Cong anom digestive system
1


13.3
Infectious diarrhea and gastroenteritis
Infect diarrhea/gastroenteritis
2


13.4
Other disorders of esophagus
Other disorders of esophagus
3


13.5
Gastritis and duodenitis
Gastritis and duodenitis
3


13.6
Gastroesophageal reflux
Gastroesophageal relux
1


13.7
Functional digestive disease
Functional digestive disease
2


13.8
Disorders of stomach and duodenum
Dsdr stomach & duodenum
3


13.9
Irritable colon
Irritable colon
1


13.10
Peptic ulcer
Peptic ulcer
3


13.11
Diverticula of intestine
Diverticula of intestine
3


13.12
Other diseases of intestine
Other diseases of intestine
3


13.13
Noninfectious gastroenteritis and colitis
Noninfect gastroent & colitis
3


13.14
Appendicitis
Appendicitis
3


13.15
Benign neoplasm of stomach
Benign neoplasm of stomach
2


13.16
Benign neoplasm of small intestine
Benign neoplasm small
2




intestine



13.17
Benign neoplasm of colon and rectum
Benign neop colon/rectum
2


13.18
Intestinal obstruction
Intestinal obstruction
2


13.19
Vascular insufficiency of intestine
Vascular insufficiency intest
2


13.20
Crohn's disease
Crohn's disease
3


13.21
Gastrointestinal hemorrhage
Gastrointestinal hemorrhage
2


13.22
Intestine and pancreas transplant
Intest/pancreas transplant
1


13.23
Malignant neoplasm of anus and rectum, initial 
Malig neop anus/rectum, initial
1


13.24
Malignant neoplasm of anus and rectum,
Malig neop anus/rectum, active
1



active




13.25
Malignant neoplasm of anus and rectum, fup
Malig neop anus/rectum, fup
1


13.26
Malignant neoplasm of esophagus
Malig neop of esophagus
3


13.27
Malignant neoplasm of stomach
Malign neoplasm of stomach
1


13.28
Malignant neoplasm of small intestine
Malig neop of small intestines
2


13.29
Malignant neoplasm of peritoneum
malign neop of peritoneum
1


13.30
Malignant neoplasm of colon, initial
Malig neop of colon, initial
2


13.31
Malignant neoplasm of colon, active
Malig neop of colon, active
2


13.32
Malignant neoplasm of colon, follow up
Malig neop of colon, fup
2


14
Hernias
Hernias
—


14.1
Other hernia site
Other hernia site
3


14.2
Diaphragmatic hernia
Diaphragmatic hernia
3


14.3
External abdominal hernias
External abdominal hernias
3


15
Hepatobiliary System and Pancreas
Hepatobiliary Sys & Pancreas
—


15.1
Congenital anomaly of hepatobiliary system
Cong anom hepatobiliary sys
1


15.2
Other disorders of biliary tract
Other disorders of biliary tract
3


15.3
Cholecystitis
Cholecystitis
2


15.4
Cholelithiasis
Cholelithiasis
3


15.5
Benign neoplasm of liver and biliary passages
Benign neop liver/biliary pass
1


15.6
Other disorders of liver
Other disorders of liver
3


15.7
Hepatitis
Hepatitis
3


15.8
Benign neoplasm of pancreas
Benign neoplasm of pancreas
1


15.9
Diseases of pancreas
Diseases of pancreas
2


15.10
Chronic liver disease
Chronic liver disease
3


15.11
Liver transplant
Liver transplant
1


15.12
Malignant neoplasm of gallbladder
Malign neop of gallbladder
2


15.13
Malignant neoplasm of liver
Malignant neoplasm of liver
2


15.14
Malignant neoplasm of pancreas
Malig neop of pancreas
2


16
Thyroid Disorders
Thyroid Disorders
—


16.1
Other disorders of thyroid
Other disorders of thyroid
3


16.2
Goiter
Goiter
1


16.3
Hypothyroidism
Hypothyroidism
1


16.4
Hyperthyroidism
Hyperthyroidism
3


16.5
Malignant neoplasm of thyroid
Malignant neoplasm of thyroid
1


17
Diabetes Mellitus
Diabetes Mellitus
—


17.1
Diabetes mellitus with no complications
Diabetes w/no complications
1


17.2
Diabetes mellitus with ophthalmic
Diabetes with ophthalmic
3



manifestation




17.3
Diabetes mellitus with neurologic manifestation
Diabetes with neurologic
3


17.4
Diabetes mellitus with circulatory manifestation
Diabetes with circulatory
3


17.5
Diabetes mellitus with renal manifestation
Diabetes with renal
3


17.6
Diabetes mellitus with multiple complications
Diabetes with multiple comp
3


18
Other Endocrine Disorders
Other Endocrine Disorders
—


18.1
Other endocrine disorders
Other Endocrine Disorders
3


18.2
Disorders of adrenal gland
Disorders of adrenal gland
2


18.3
Disorders of pituitary gland
Disorders of pituitary gland
3


18.4
Benign neoplasm of pituitary gland
Benign neop of pituitary gland
1


18.5
Malignant neoplasm of other endocrine glands
Malig neop other endo glands
2


18.6
Malignant neoplasm of thymus gland
Malig neop of thymus gland
1


18.7
Malignant neoplasm of pituitary gland
Malig neop of pituitary gland
1


18.8
Malignant neoplasm of adrenal gland
Malig neop of adrenal gland
1


19
Metabolic Disorders
Metabolic Disorders
—


19.1
III-defined metabolic symptoms
III-defined metabolic symptoms
1


19.2
Disorders of fluids and electrolytes
Dsdr of fluids and electrolytes
3


19.3
Nutritional deficiencies
Nutritional deficiencies
1


19.4
Disorders of lipid metabolism
Disorders of lipid metabolism
2


19.5
Gout
Gout
3


19.6
Other disorders of metabolism
Other disorders of metabolism
3


19.7
Cystic fibrosis
Cystic fibrosis
2


20
Immunity and Blood Disorders
Immunity & Blood disorders
—


20.1
Congenital anomaly of spleen
Congenital anomaly of spleen
1


20.2
Disease of blood forming organs
Dz of blood forming organs
1


20.3
Disease of white blood cells
Diseases of white blood cells
1


20.4
Anemia disorders
Anemia disorders
2


20.5
Aplastic anemias
Aplastic anemias
1


20.6
Thrombocytopenia
Thrombocytopenia
1


20.7
Other disorders of blood
Other disorders of blood
1


20.8
Disorders of immune mechanism
Dsdr of immune mechanism
3


20.9
Malignant neoplasm of spleen
Malignant neoplasm of spleen
1


21
Lymphatic and Hematopoietic Tissue
Lymph & Hematopoietic Tiss
—


21.1
Lymphadenitis
Lymphadenitis
1


21.2
Hemangioma
Hemangioma
2


21.3
Other malignant neoplasms of lymphoid tissue
Other malig neop lymph tissue
3


21.4
Burkitt's tumor
Burkitt's tumor
2


21.5
Lymphoma, active
Lymphoma, active
2


21.6
Lymphoma, inactive
Lymphoma, inactive
2


21.7
Hodgkin's disease, active
Hodgkin's disease, active
2


21.8
Hodgkin's disease, inactive
Hodgkin's disease, inactive
2


21.9
Sarcomas
Sarcomas
2


21.10
Leukemia, active
Leukemia, active
2


21.11
Leukemia, inactive
Leukemia, inactive
2


21.12
Multiple myeloma
Multiple myeloma
2


22
Urinary Tract and Kidney Conditions
Urinary Tract & Kidney Cond
—


22.1
Other disorders of urethra
Other disorders of urethra
2


22.2
Congenital anomalies of bladder and urethra
Cong anom bladder and urethra
2


22.3
Urinary tract infections
Urinary tract infections
2


22.4
Urethritis
Urethritis
2


22.5
Urethral stricture
Urethral stricture
2


22.6
Other disorders of bladder
Other disorders of bladder
3


22.7
Kidney infection
Kidney infection
3


22.8
Hydronephrosis
Hydronephrosis
1


22.9
Congenital anomalies of kidney and ureter
Cong anom kidney and ureter
3


22.10
Disorders of kidney and ureter
Disorders of kidney and ureter
3


22.11
Calculus of kidney and ureter
Calculus of kidney and ureter
2


22.12
Glomerulonephritis
Glomerulonephritis
3


22.13
Bladder transplant
Bladder transplant
1


22.14
Renal dialysis
Renal dialysis
1


22.15
Renal failure
Renal failure
2


22.16
Kidney transplant, initial
Kidney transplant, initial
1


22.17
Kidney transplant, follow-up
Kidney transplant, follow-up
1


22.18
Malignant neoplasm of bladder and urethra
Malig neop bladder and urethra
1


22.19
Malignant neoplasm of kidney and ureter
Malig neop kidney and ureter
1


23
Female Reproductive Conditions
Female Reproduction Cond
—


23.1
Disorders of cervix and vagina
Disorders of cervix and vagina
3


23.2
Cervicitis and vaginitis
Cervicitis and vaginitis
2


23.3
Uterovaginal prolapse
Uterovaginal prolapse
3


23.4
Other disorders of uterus
Other disorders of uterus
3


23.5
Other disorders of female genital organs
Other dsdr female genital org
3


23.6
Ovarian dysfunction
Ovarian dysfunction
3


23.7
Menstrual disorders
Menstrual disorders
2


23.8
Menopausal symptoms
Menstrual disorders
1


23.9
Benign neoplasm of uterus
Benign neoplasm of uterus
2


23.10
Endometriosis
Endometriosis
2


23.11
Ovarian cyst
Ovarian cyst
1


23.12
Carcinoma in situ of cervix
Carcinoma in situ of cervix
1


23.13
Malignant neoplasm of placenta
Malig neop of placenta
1


23.14
Malignant neoplasm of cervix and vagina
Malig neop of cervix & vagina
2


23.15
Malignant neoplasm of ovary and fallopian
Malig neop ovary & fallop tube
1



tube




23.16
Malignant neoplasm of uterus
Malignant neoplasm of uterus
1


24
Male Reproductive Conditions
Male Reproductive Cond
—


24.1
Hydrocele
Hydrocele
2


24.2
Orchitis and epididymitis
Orchitis and epididymitis
2


24.3
Disorders of male genital organs
Dsdr of male genital organs
3


24.4
Disorders of penis
Disorders of penis
2


24.5
Other disorders of prostate
Other disorders of prostate
3


24.6
Prostatic hypertrophy and prostatitis
Prostatic hyertro & prostatitis
2


24.7
Malignant neoplasm of other male genital
Malig neop other male gen org
3



organs




24.8
Malignant neoplasm of testis
Malignant neoplasm of testis
1


24.9
Malignant neoplasm of prostate, active
Malig neop of prostate, active
1


24.10
Malignant neoplasm of prostate, inactive
Malig neop of prostate, inactive
1


25
Infertility Treatment
Infertility Treatment
—


25.1
Contraceptive management
Contraceptive management
1


25.2
Infertility female
Infertility female
2


25.3
Procreative management
Procreative management
1


25.4
Infertility male
Infertility male
1


26
Maternity-Related Conditions
Maternity-Related Cond
—


26.1
Abnormal product of conception
Abnorm product of conception
1


26.2
Ectopic pregnancy
Ectopic pregnancy
2


26.3
Spontaneous and induced abortions
Spont and induced abortions
1


26.4
Single newborn, normal pregnancy
Single newborn, normal
1


26.5
Single newborn, complicated pregnancy
Single newborn, complicated
3


26.6
Multiple newborns, normal pregnancy
Multiple newborns, normal
1


26.7
Multiple newborns, complicated pregnancy
Multiple newborns, complic
3


26.8
Other obstetrical care
Other obstetrical care
1


26.9
Completely normal delivery
Completely normal delivery
1


26.10
Multiple gestation
Multiple gestation
1


26.11
Complications before birth
Complications before birth
3


26.12
Complications of delivery
Complications of delivery
3


27
Neonatal Conditions
Neonatal Conditions
—


27.1
Other minor neonatal conditions
Minor neonatal conditions
3


27.2
Perinatal jaundice
Perinatal jaundice
3


27.3
Other major neonatal conditions
Major neonatal conditions
3


27.4
Respiratory distress syndrome
Respiratory distress syndrome
1


27.5
Disorders due to short gestation
Disorders to short gestation
3


28
Congenital Anomalies
Congenital Anomalies
—


28.1
Congenital anomalies of sense organs
Cong anom of sense organs
3


28.2
Congenital endocrine and metabolic anomaly
Cong endo/metabolic anom
1


28.3
Congenital reproductive system anomaly
Cong reproductive sys anom
1


28.4
Other chromosomal anomaly
Other chromosomal anomaly
1


28.5
Down's syndrome
Down's syndrome
1


29
Skin and Subcutaneous Tissue Conditions
Skin & Subcutaneous Tissue
—


29.1
III-defined integument symptoms
III-defined integument sym
1


29.2
Congenital anomalies of skin
Congenital anomalies of skin
1


29.3
Congenital integument anomaly
Cong integument anom
1


29.4
Other infections of skin and subcutaneous
Other inf skin/subcutan tissue
2



tissue




29.5
Other disorders of skin and subcutaneous
Other dsdr skin/subcutan tiss
3



tissue




29.6
Skin keratoses
Skin keratoses
2


29.7
Impetigo
Impetigo
1


29.8
Urticaria
Urticaria
1


29.9
Dermatitis and eczema
Dermatitis and eczema
2


29.10
Cellulites and abscess, finger and toe
Cellul & abscess, finger/toe
2


29.11
Cellulites and abscess, leg and buttock
Cellul & abscess, leg/buttock
1


29.12
Cellulites and abscess, other site
Cellul & abscess, other site
1


29.13
Rosacea
Rosacea
1


29.14
Dermatophytoses
Dermatophytoses
2


29.15
Sebaceous cyst
Sebaceous cyst
1


29.16
Pilonidal cyst
Pilonidal cyst
2


29.17
Acne
Acne
1


29.18
Lipoma
Lipoma
2


29.19
Benign neoplasm of skin
Benign neoplasm of skin
1


29.20
Diseases of nail, excluding infections
Dz of nail, excluding infections
1


29.21
Diseases of hair and hair follicles
Dz of hair and hair follicles
2


29.22
Erythematous condition
Erythematous condition
2


29.23
Psoriasis and pityriasis
Psoriasis and pityriasis
2


29.24
Carcinoma in situ of skin
Carcinoma in situ of skin
1


29.25
Chronic skin ulcer
Chronic skin ulcer
2


29.26
Other malignancy of skin
Other malignancy of skin
2


29.27
Kaposi's sarcoma
Kaposi's sarcoma
3


29.28
Malignant melanoma of skin, initial
Malig melanoma of skin, initial
2


29.29
Malignant melanoma of skin, active
Malig melanoma of skin, active
2


29.30
Malignant melanoma of skin, follow up
Malig melanoma of skin, fup
2


30
Breast Conditions
Breast Conditions
—


30.1
Inflammatory disease of breast
Inflammatory disease of breast
2


30.2
Cystic breast disease
Cystic breast disease
2


30.3
Benign neoplasm of breast
Benign neoplasm of breast
1


30.4
Carcinoma in situ of breast, initial
Carc in situ of breast, initial
1


30.5
Carcinoma in situ of breast, active
Carc in situ of breast, active
1


30.6
Carcinoma in situ of breast, follow-up
Carc in situ of breast, fup
1


30.7
Malignant neoplasm of breast skin
Malig neop of breast skin
1


30.8
Malignant neoplasms of breast, initial
Malig neop of breast, initial
2


30.9
Malignant neoplasm of breast, active
Malig neop of breast, active
2


30.10
Malignant neoplasm of breast, follow-up
Malig neop of breast, fup
2


31
Musculoskeletal Conditions
Musculoskeletal Conditions
—


31.1
Congenital musculoskeletal anomaly
Cong musculoskel anomaly
1


31.2
Congenital anomalies of spine
Congenital anomalies of spine
3


31.3
Other arthropathy disorders
Other arthropathy disorders
3


31.4
Bursitis
Bursitis
3


31.5
Other disorders of bone and cartilage
Other dsdr bone & cartilage
3


31.6
Nonallopathic lesions
Nonallopathic lesions
2


31.7
Bone transplant
Bone transplant
1


31.8
Cervical spine pain
Cervical spine pain
3


31.9
Low back pain
Low back pain
3


31.10
Other acquired deformity
Other acquired deformity
2


31.11
Other curvature of spine
Other curvature of spine
2


31.12
Scoliosis
Scoliosis
1


31.13
Minor injury of trunk
Minor injury of trunk
1


31.14
Osteoporosis
Osteoporosis
1


31.15
Benign neoplasm of skull and trunk bones
Benign neop skull/trunk bones
1


31.16
Other osteochondropathies
Other osteochondropathies
1


31.17
Osteomyelitis
Osteomyelitis
3


31.18
Diffuse connective tissue disorders
Diffuse connective tiss dsdr
1


31.19
Rheumatoid arthritis
Rheumatoid arthritis
3


31.20
Dislocation of vertebra
Dislocation of vertebra
3


31.21
Fracture of vertebra
Fracture of vertebra
3


31.22
Major injury of trunk
Major injury of trunk
1


31.23
Traumatic pneumothorax
Traumatic pneumothorax
3


31.24
Crushing injury of trunk
Crushing injury of trunk
2


31.25
Malignant neoplasm of skull and trunk bones
Malig neop skull/trunk bones
1


32
Upper Limb Conditions
Upper Limb Conditions
—


32.1
Contusion of upper limb
Contusion of upper limb
2


32.2
Sprain/strain of wrist and finger
Sprain/strain of wrist & finger
2


32.3
Sprain/strain of upper arm
Sprain/strain of upper arm
2


32.4
Sprain/strain of lower arm
Sprain/strain of lower arm
2


32.5
Open wound of hand and fingers
Open wound hand & fingers
3


32.6
Open wound of arm
Open wound of arm
3


32.7
Dislocation of finger and wrist
Dislocation of finger and wrist
3


32.8
Dislocation of upper arm
Dislocation of upper arm
3


32.9
Congenital deformities of upper limb
Cong deformities upper limb
3


32.10
Benign neoplasm of upper limb
Benign neop of upper limb
1


32.11
Fracture of hand bones
Fracture of hand bones
3


32.12
Amputation of finger
Amputation of finger
2


32.13
Fracture of radius and ulna
Fracture of radius and ulna
3


32.14
Fracture of humerus
Fracture of humerus
3


32.15
Fracture of clavicle and scapula
Fracture of clavicle/scapula
3


32.16
Amputation of hand and arm
Amputation of hand and arm
3


32.17
Crushing injury of upper limb
Crushing injury of upper limb
3


32.18
Malignant neoplasm of upper limb
Malig neop of upper limb
1


33
Lower Limb Conditions
Lower Limb Conditions
—


33.1
Contusion of lower limb
Contusion of lower limb
2


33.2
Sprain/strain of foot and ankle
Sprain/strain of foot and ankle
2


33.3
Sprain/strain of leg
Sprain/strain of leg
3


33.4
Sprain/strain of hip and thigh
Sprain/strain of hip and thigh
1


33.5
Open wound of foot and toes
Open wound of foot and toes
3


33.6
Open wound of leg
Open wound of leg
3


33.7
Open wound of hip and thigh
Open wound of hip and thigh
3


33.8
Dislocation of foot and ankle
Dislocation of foot and ankle
3


33.9
Dislocation of knee
dislocation of knee
2


33.10
Dislocation of hip
Dislocation of hip
3


33.11
Congenital deformities of lower limb
Cong deformities lower limb
3


33.12
Joint replacement
Joint replacement
1


33.13
Benign neoplasm of lower limb
Benign neop of lower limb
1


33.14
Hammer toe
Hammer toe
3


33.15
Degenerative joint disease
Degenerative joint disease
2


33.16
Fracture of foot bones
Fracture of foot bones
3


33.17
Fracture of ankle
Fracture of ankle
3


33.18
Fracture of patella
Fracture of patella
2


33.19
Fracture of tibia and fibula
Fracture of tibia and fibula
3


33.20
Amputation of toes
Amputation of toes
2


33.21
Other joint derangement
Other joint derangement
3


33.22
Derangement of knee
Derangement of knee
3


33.23
Fracture of femur
Fracture of femur
3


33.24
Amputation of foot and leg
Amputation of foot and leg
3


33.25
Crushing injury of lower limb
Crushing injury of lower limb
3


33.26
Malignant neoplasm of lower limb
Malig neoplasm of lower limb
1


34
Mental Disorders
Mental Disorders
—


34.1
Other nonpsychotic disorders
Other nonpsychotic disorders
3


34.2
Psychogenic conditions
Psychogenic conditions
3


34.3
Sleep walking
Sleep walking
1


34.4
Hypersomnia
Hypersomnia
1


34.5
Insomnia
Insomnia
2


34.6
Other neurotic disorders
Other neurotic disorders
1


34.7
Maltreatment syndrome
Maltreatment syndrome
1


34.8
Sexual deviations
Sexual deviations
1


34.9
Tics and repetitive movements
Tics and repetitive movements
3


34.10
Hysteria
Hysteria
3


34.11
Delays in metal development
Delays in mental development
2


34.12
Phobic disorders
Phobic disorders
2


34.13
Anxiety disorders
Anxiety discords
2


34.14
Personality and disturbance disorder
Personality & disturb dsdr
3


34.15
Other nonorganic psychoses
Other nonorganic psychoses
1


34.16
Other eating disorders
Other eating disorders
1


34.17
Nonpsychotic depression
Nonpsychotic depression
2


34.18
Obsessive-compulsive disorders
Obsessive-compulsive dsdr
1


34.19
Paranoid states
Paranoid states
2


34.20
Sleep apnea
Sleep apnea
1


34.21
Major depression
Major depression
3


34.22
Mental retardation
Mental retardation
2


34.23
Manic depression
Manic depression
3


34.24
Bipolar depression
Bipolar depression
3


34.25
Bulimia
Bulimia
1


34.26
Anorexia nervosa
Anorexia nervosa
1


34.27
Autism
Autism
1


34.28
Narcolepsy
Narcolepsy
1


34.29
Alcohol dependence
Alcohol dependence
3


34.30
Drug dependence
Drug dependence
3


34.31
Organic dementias
Organic dementias
3


34.32
Schizophrenia
Schizophrenia
3


34.33
Alzheimer's disease
Alzheimer's disease
1


35
Burns
Burns
—


35.1
Burn of upper limb
Burn of upper limb
3


35.2
Burn of lower limb
Burn of lower limb
3


35.3
Burns of head and neck
Burns of head and neck
3


35.4
Burn of trunk
Burn of trunk
3


35.5
Burn of multiple sites
Burn of multiple sites
3


36
Other Medical Conditions
Other Medical Conditions
—


36.1
Complication of surgery
Complication of surgery
1


36.2
Complication of genitourinary procedure
Complic genitourin procedure
1


36.3
Complication of orthopedic procedure
Complic orthopedic procedure
1


36.4
Complication of gastrointestinal procedure
Complic gastrointestinal proc
1


36.5
Complication of respiratory procedure
Complic respiratory procedure
1


36.6
Complications of trauma
Complications of trauma
1


36.7
Complication of nervous system procedure
Complic nervous sys proc
1


36.8
Complication of vascular procedure
Complic vascular procedure
1


36.9
Complication of transplant
Complication of transplant
1


36.10
Effects of external causes
Effects of external causes
1


36.11
Poisoning by medicines
Poisoning by medicines
1


36.12
Toxic effects of substances
Toxic effects of substances
1


36.13
Personal assaults
Personal assaults
1


36.14
Motor vehicle accident
Motor vehicle accident
1


36.15
General presenting symptoms
General presenting symptoms
1


36.16
Non-specific exanthem
Non-specific exanthem
1


36.17
Abdominal pain
Abdominal pain
1


36.18
Dyspnea
Dyspnea
2


36.19
Chest pain
Chest pain
1


36.20
Non-newborn jaundice
Non-newborn jaundice
1


36.21
Non-newborn cyanosis
Non-newborn cyanosis
1


36.22
Shock
Shock
1


36.23
Spleenomegaly
Spleenomegaly
1


36.24
Hepatomegaly
Hepatomegaly
1


36.25
Coma and stupor
Coma stupor
1


36.26
Gangrene
Gangrene
1


37
Replaced Diagnosis Codes
Replaced Diagnosis Codes
—


37.1
Replaced non-specific diagnosis codes
Replaced non-specific dx code
1









An embodiment of the present invention forms longitudinal episodes of care for a patient using medical claims data. A longitudinal episode of care is defined as all services linked together that are used to treat a patient's medical condition within a specified period of time, including all ambulatory, outpatient, inpatient, and prescription drug experience. This linkage allows examination of a physician's (or a physician group's) global patterns of treatment for a patient with a specific condition, such as diabetes and arthritis. The longitudinal episode of care may also be used in patient disease management, patient health promotion and wellness, and many other healthcare programs.
Acute Episodes of Care
An acute episode of care has a finite duration and is defined by a specified time period, or window period. An embodiment of the present invention has three types of window periods for acute episodes of care.
Dynamic Window Period:
The specified time period, or window period, is based on the maximum number of days between contact with a provider for which follow-up care is still reasonable. Each of the medical conditions has its unique dynamic window period. If the date of service for a patient's episode is separated by a longer period than the dynamic window period, the latest date of service considered the start date for a new condition-specific episode of care.
For example, as shown in FIG. 3, the dynamic window period for Medical Condition 9.1-upper respiratory infections is 60 days. Assume that a patient had three services in January and two services in August of the same calendar year. Because the services in the series were separated by more than 60 days, these would be two episodes of care. Table 11A gives the dynamic window periods for medical conditions in PMC Group 9-Respiratory Conditions.







TABLE 11A







Medical Condition Dynamic Window Periods 


for PMC Group 9-Respiratory Conditions









Medical




Condition
Medical Condition
Window


Number
Long Description
Periods












6
Ear conditions
—


6.1
Otitis externa
90


6.2
Wax in ear
60


6.3
Open wound of ear
90


6.4
Other disorders of ear
90


6.5
Otitis media
90


6.6
Disorders of tympanic
120



membrane



6.7
Disorders of middle ear
120


6.8
Vertiginous syndromes
180


6.9
Mastoiditis
180


6.10
Hearing loss
365


6.11
Malignant neoplasm of
365



middle ear









Static Window Period:

The specified time period, or window period, is based on the maximum number of days after contact with a provider for which follow-up care is still reasonable. Each of the medical conditions has its unique static window period. From the initial date of service for a patient's episode, the static window period defines the fixed number of days to count from the initial date of service to define all services to include in the episode of care. Then, if another medical condition-specific service is observed for the same patient after the fixed number of window period days, this service is considered the start date for a new second condition-specific episode of care. For the second episode of care, the static window period defined fixed number of days is again applied.
For example, as shown in FIG. 4, the static window period for Medical Condition 9.1 upper respiratory infections is 40 days. Assume that a patient had three services in January, the first on January fifth (5th), and two services in August in the same calendar year, the initial service on August tenth (10th). The three services in January were within the static 40 day window period from the initial service on January fifth (5th); this is because 40 days to count out from January fifth (5th) is about February fourteenth (14th). Therefore, these three services are in the first episode of care. Then, the second episode of care begins on August tenth (10th), and 40 days are counted out from August tenth (10th). Therefore, the two services in August are in the second episode of care. Table 11B gives the static widow periods for medical conditions in PMC Group 9-Respiratory Conditions.







TABLE 11B







Medical Condition Static Window Periods for 


PMC Group 9-Respiratory Conditions









Medical

Static


Condition
Medical Condition
Window


Number
Long Description
Periods












6
Ear conditions
—


6.1
Otitis externa
60


6.2
Wax in ear
40


6.3
Open wound of ear
60


6.4
Other disorders of ear
60


6.5
Otitis media
60


6.6
Disorders of tympanic
80



membrane



6.7
Disorders of middle ear
80


6.8
Vertiginous syndromes
120


6.9
Mastoiditis
120


6.10
Hearing loss
—


6.11
Malignant neoplasm of
—



middle ear









Variable Window Period:

The specified time period, or window period, is based on the maximum number of days after contact with a provider for which follow-up care is still reasonable. Each of the medical conditions has its unique variable window period. From the initial date of service for a patient's episode, the window period defines the fixed number of days to count from the initial date of service to define all services to include in the episode of care. Then, if another medical condition-specific service is observed for the same patient after the fixed number of window period days, this service is considered the start date for a new second condition-specific episode of care. The fixed number of window period days is extended by a set number of days for each reoccurrence of a medical condition-specific episode of care.
For example, as shown in FIG. 5, the window period for the initial episode of Medical Condition 9.1 upper respiratory infections is 40 days. Assume that a patient had three services in January, the first on January fifth (5th), and two services in August in the same calendar year, the initial service on August tenth (10th). The three services in January were within the 40 day window period from the initial service on January fifth (5th); this is because 40 days to count out from January fifth (5th) is about February fourteenth (14th). Therefore, these three services are in the first episode of care. Then, the second episode of care begins on August tenth (10th), and the window period is extended by 8 days and therefore, 48 days are counted out from August tenth (10th). Therefore, the two services in August are in the second episode of care.
Chronic Episodes of Care
A chronic episode of care by definition is ongoing and once started will go on indefinitely. Therefore, chronic episodes of care have no window period associated with them and the user may define a desired fixed duration for Chronic Episodes of Care. For example, Medical condition 10.2 Hypertension or Medical Condition 9.11 Asthma have no window period and once an episode of Hypertension or Asthma starts, it will continue on indefinitely. In an embodiment, to calculate physician efficiency, chronic episodes may have a finite duration and end after 180 days or 365 days.
Step 100: Form Inpatient Encounters and Assign Diagnosis
The Grouper function first checks professional service CLIs for inpatient facility place of service to identify potential inpatient encounters. A professional service includes the Types of Service of visits, lab/path services, medical and surgical procedures, and diagnostic tests. All facility charges and prescription drugs are excluded from professional services. The professional services occur in a Place of Service of hospital inpatient.
The identification of a professional service that starts a potential inpatient encounter is called a trigger event.
The rule associates with the potential inpatient encounter all services that occurred on the dates following the trigger event. Services continue to be counted until an end date is reached. The end date is identified when there is a two-day gap in professional charges. At this point the potential encounter ends. For example, if one CLI ends on a Monday and the next CLI begins on Wednesday, then the two CLIs could be part of a single inpatient encounter because only one day (Tuesday) separates them. If the second CLI begins on Thursday, then it would be part of a separate inpatient encounter because two days (Tuesday and Wednesday) separate it from the first CLI.
The rule then looks at all professional service charges associated with the potential inpatient encounter to determine whether they total $350 or more. If the professional service charges total $350 or more, the rule concludes that we have identified an eligible inpatient encounter. Experience shows that charges should almost always be over this minimum threshold level. The minimum threshold level is subject to change over time.
For inpatient encounters with professional service charges of $350 or more, the rule assigns a diagnosis code to all CLIs associated with the encounter. To assign the appropriate diagnosis code, all professional service CLIs associated with the encounter are identified. The rule then temporarily assigns these professional service CLIs to one of 526 medical conditions. Using these temporary assignments, the rule adds up all charges by medical condition. The medical condition with the highest charge amount is then assigned as the medical condition for the entire encounter, and all CLIs associated with the encounter receive diagnosis codes appropriate for that medical condition.
The rule uses professional charges to identify the start and end dates of a hospital inpatient encounter. Facility services (i.e., room and board service and ancillary services) are assigned to the ongoing encounter using these start and end dates.
Step 120: Drop Inpatient Encounters without Minimal Professional Charges
If the overall professional service charges associated with the potential encounter do not reach $350, then an eligible inpatient encounter has not been identified. For example, consider a cardiac stress test that includes physician charges of $250 marked with inpatient facility as the place of service and a facility-related component of $300. Broken down in this way, we can see that the medical charges (non-facility and drug charges) do not meet the $350 threshold, and the potential encounter would not be regarded as an eligible inpatient encounter. When the potential encounter does not meet the $350 threshold, all CLIs associated with the potential inpatient encounter are released and will be examined as described in the next step.
Step 130: Form Outpatient Encounters and Assign Diagnosis
To identify outpatient facility encounters, the Grouper function examines all professional service CLIs except those already assigned to an inpatient facility encounter. The rule looks for professional service CLIs that have a Place of Service of inpatient hospital, emergency room, urgent care, outpatient facility, surgicenter, or birthing center as the place of service. At this point in the process, the professional service CLIs with a Place of Service of inpatient hospital did not meet the minimum hospital inpatient encounter criteria. These CLIs are now examined for a possible outpatient facility encounter.
The identification of a professional service that starts a potential outpatient encounter is called a trigger event. CLIs with Provider Type services that include only laboratory and durable medical equipment do not trigger a potential outpatient encounter.
Once a potential outpatient encounter has been identified, the rule inspects all CLIs that occurred on the date of the potential encounter to determine whether total charges equal or exceed $100. If so, then the rule concludes that an eligible outpatient encounter has been identified. Experience shows that charges should almost always be over this minimum threshold level. The minimum threshold level is subject to change over time.
For outpatient encounters with total charges of $100 or more, the rule assigns a diagnosis code to all CLIs associated with the encounter. To assign the appropriate diagnosis code, all professional service CLIs associated with the encounter are identified. The rule then temporarily assigns these professional service CLIs to one of 526 medical conditions. Using these temporary assignments, the rule adds up all charges by medical condition. The medical condition with the highest charge amount is then assigned as the medical condition for the entire encounter, and all CLIs associated with the encounter receive diagnosis codes appropriate for that medical condition.
Step 140: Drop Outpatient Encounters without Minimal Total Charges
If the total charges are less than $100, the rule concludes that that we have not identified an actual outpatient encounter. For example, many labs are performed in outpatient hospital facilities. This analysis helps ensure that lab-only events are not included as outpatient encounter.
CLIs associated with potential outpatient encounters that do not meet the $100 threshold may still be associated with medical condition episodes. They are released and through subsequent analysis may be assigned to the following service categories: Professional Visits, Diagnostic Tests, Laboratory and Pathology, Medical and Surgical Procedures, Prescription Drugs, Alternative Sites, or Other Medical Services.
Facility CLIs not associated with actual inpatient or outpatient encounters are assigned to other medical care service categories based primarily on the procedure code that may be present on the CLI. For example, if the procedure code indicates chemotherapy, it would be assigned to the service category Other Medical Services as part of the sub-service category Chemo/Radiology. If no explanatory procedure code is present, the facility CLI will be categorized under the service category Other Medical Services as part of the sub-service category Other Medical Care.
Step 150: Ill-Defined Diagnosis Code Rule
A patient's medical service will appear in an episode of care if the claim line item (CLI) has a valid and “defined” assigned ICD.9 code. For example, defined codes include ICD.9 codes such as 250.0 (diabetes without mention of complication), 244.3 (iatrogenic hypothyroidism), and 370.20 (superficial keratitis).
However, up to 40% of all CLIs may have “ill-defined” assigned ICD.9 codes. Ill-defined means that either the ICD.9 codes are either missing or nonspecific ICD.9 codes. Nonspecific codes include ICD.9 codes such as 780.9 (other general symptoms), 796.4 (other abnormal clinical findings), and 799 (other ill-defined causes of morbidity). Non-specific codes are treated as if the ICD.9 code on the CLI is missing. The CLI remains, but the ill-defined value on the CLI is ignored. Ill-defined ICD.9 coding falls into medical condition 37.1.
To prevent under-reporting of utilization within an episode of care, a defined ICD.9 code is assigned to CLIs with ill-defined ICD.9 codes. Consequently, the Ill-Defined Diagnosis Code Rule assigns a diagnosis code to each CLI with an ill-defined code as follows.
The Grouper function first looks for an appropriate diagnosis during the two days before and after the non-specific diagnosis code date. For example, assume a CLI has a non-specific diagnosis code on March 17. The rule looks backwards two days until March 15 for a valid and accurate diagnosis code. If no defined diagnosis code is found, then the rule looks two days forward until March 19 for a valid accurate diagnosis code. If no appropriate diagnosis is found, the rule then examines the five days before and after. If no appropriate diagnosis is found, the rule then examines the nine days before. In an embodiment, nine days forward in time can be examined and day period durations and number can be changed.
Moreover, the expected resource intensity level of each of 526 medical conditions is considered. If there are two separate CLIs on a given day that have a defined ICD.9 code, the rule assigns the diagnosis code of the more resource-intensive medical condition to the CLI with an ill-defined code. For example, if there is a diagnosis code for diabetes on February 15 and also a diagnosis code for upper respiratory tract infection on February 15, then diabetes will be assigned because it is more resource intensive. So, if there are two CLIs on the same day with different ICD.9 codes in the primary position field, then the most resource intensive diagnosis code is assigned during the two day look-back assignment process, during the two day look-forward assignment process, and so forth.
Table N shows the resource intensity rank order assigned to different medical conditions. The lower the resource intensity rank number for a medical condition, the higher the expected need for medical care services as compared to medical conditions with higher resource intensity rank numbers.







TABLE N







Resource Intensity Rank Order for Medical Conditions









Medical

Resource


Condition
Medical Condition
Intensity


Number
Long Description
Rank












6
Ear Conditions
—


6.1
Otitis externa
464


6.2
Wax in ear
459


6.3
Open wound of ear
457


6.4
Other disorders of ear
455


6.5
Otitis media
454


6.6
Disorders of tympanic membrane
450


6.7
Disorders of middle ear
449


6.8
Vertiginous syndromes
440


6.9
Mastoiditis
436


6.10
Hearing loss
192


6.11
Malignant neoplasm of middle ear
 84


22
Urinary Tract and Kidney Conditions
—


22.1
Other disorders of urethra
428


22.2
Congenital anomalies of bladder and
413



urethra



22.3
Urinary tract infections
412


22.4
Urethritis
411


22.5
Urethral stricture
410


22.6
Other disorders of bladder
397


22.7
Kidney infection
396


22.8
Hydronephrosis
335


22.9
Congenital anomalies of kidney and ureter
334


22.10
Disorders of kidney and ureter
140


22.11
Calculus of kidney and ureter
132


22.12
Glomerulonephritis
130


22.13
Bladder transplant
 57


22.14
Renal dialysis
 49


22.15
Renal failure
 50


22.16
Kidney transplant, initial
 46


22.17
Kidney transplant, follow-up
Not applicable


22.18
Malignant neoplasm of bladder and urethra
 25


22.19
Malignant neoplasm of kidney and ureter
 20









If a CLI has not been assigned to a valid ICD.9 code at this point, then the CLI will not be assigned to an episode of care at this point in time.
Prescription drug CLIs generally do not have an ICD.9 diagnosis code assigned. An embodiment of the present invention assigns a defined ICD.9 diagnosis code to each prescription drug CLI by applying the same Ill-Defined Diagnosis Code Rule as for any other service category that has an ill-defined ICD.9 code.
Step 160: Trigger Episode of Care Building
A Grouper function treats the start and end points for chronic and acute episodes differently. For chronic conditions (e.g., diabetes, asthma, ischemic heart disease), an episode of care begins when a CLI is initially found during the study period that has a defined ICD.9 code that has been assigned to that medical condition. Then, chronic conditions may continue on indefinitely as recognized by the window period of 365 days (refer to Table 11 for chronic disease window periods of 365 days).
However, for the purposes of physician efficiency analysis, chronic conditions are considered to be 180-day duration. Therefore, a chronic condition ends 180 days after identifying the first CLI with a diagnosis (defined ICD.9 code) for the specific chronic condition. The rule determines that the patient is present for 180 days during the study period after the first CLI with a diagnosis for the specific chronic condition. Moreover, in the physician efficiency analysis, all chronic conditions included in the analysis must start before the last day of the first half of the study period and must have a 180-day duration. The embodiment recognizes that this maximum allowable duration may be varied.
For acute conditions (e.g., upper respiratory infections, otitis media, conjunctivitis), an episode of care begins when a CLI is initially found during the study period that has a defined ICD.9 code that has been assigned to that medical condition.
For acute conditions, the patient's episode duration directly relates to the process of care. The process of care is identified using window periods for each medical condition. A medical condition's window period is based on the maximum number of days between contact with a provider for which follow-up care is still reasonable. Each medical condition has its own unique window period as presented for select medical conditions in Table 11. If the date of service for a patient's episode is separated from the previous date of service by a period longer than the window period for that condition, the latest date of service is considered the start date for a new condition-specific episode of care.
For example, upper respiratory infections generally last up to 30 days. The window period is made about 1.5-to-2.5 times as long as the expected average longer duration episodes for a medical condition to ensure episode completion. Therefore, the window period for upper respiratory infections is about 60 days. Acute condition episodes are considered complete (or end) if an amount of time (equal to the window period) elapses in which no ICD.9 codes for that condition are present.
Continuing our upper respiratory infection example, assume that a patient had three treatments for upper respiratory infection in January and two in the following August. The window period for upper respiratory infections is 60 days. Because the two groups of treatments were separated by more than 60 days, they would be considered two separate episodes of care. In the physician efficiency analysis, the maximum allowable duration for any acute condition is 180 days. The embodiment recognizes that this maximum allowable duration may be varied.
Step 170: Apply Rank Order Rule
After the triggering episode of care building rule, the rank order rule assigns claims that continue to have ill-defined diagnosis codes (e.g., missing or non-specific ICD.9 codes) to the highest resource-intensity ranked ongoing episode for a patient. Table N presents the resource intensity rank order for select medical conditions.
After the rank order rule, generally more than 98% of CLIs receive a defined ICD.9 code, and are assigned to one of the patient's ongoing condition-specific episodes of care. However, the percent ranges generally from 85% to 99% of CLIs that receive a defined ICD.9 code, depending on the accuracy of original ICD.9 coding in the particular medical claims data file of being examined.
Step 180: Apply CLI Day Rule
The Grouper function next examines the more resource-intensive medical condition episodes to ensure an appropriate number of CLIs are present within the episode of care. This is to ensure that no episodes are built because of a single CLI ICD.9 miscoding by a physician.
Most episodes, after being built, are eligible using the requirement that only one CLI is present with a condition-specific ICD.9 diagnosis code. For example, Table 12 shows that only one CLI with an ICD.9 code is required for conditions such as neuritis, headaches, conjunctivitis, otitis media, sinusitis, and upper respiratory infections.
However, some episodes, after being built, are eligible using the requirement that a CLI with a condition-specific ICD.9 code must be present on two different days. These are episodes of medical conditions that can be expected to last more than one day. For instance, the one CLI on two different days rule is required for conditions such as myoneural disorder, multiple sclerosis, pneumothorax, pneumocystosis, fracture of skull, intestinal obstruction, hepatitis, fracture of vertebra, and deep burns.
Other episodes, after being built, are eligible using the requirement that a CLI with a condition-specific ICD.9 code must be present on three different days. These episodes are more chronic by nature and require more resource intensive treatment. For example, the one CLI on three different days rule used for conditions such as injury of the spinal column, malignant neoplasm of nasal cavities, malignant neoplasm of lung, cerebrovascular hemorrhage, malignant neoplasm of pancreas, and renal failure.
If the built episode does not meet the required eligibility criteria, then the CLIs in the episode are released and through subsequent analysis, may be assigned to another of the patient's ongoing episodes of care. The diagnosis coding on the released CLIs is treated the same way as if the ICD.9 code were “μl-defined.”







TABLE 12







Claim Line Item (CLI) Day Rule Table









Medical

CLI


Condition
Medical Condition
Day


Number
Long Description
Rule












6
Ear Conditions
—


6.1
Otitis externa
1


6.2
Wax in ear
1


6.3
Open wound of ear
1


6.4
Other disorders of ear
1


6.5
Otitis media
1


6.6
Disorders of tympanic membrane
1


6.7
Disorders of middle ear
1


6.8
Vertiginous syndromes
1


6.9
Mastoiditis
1


6.10
Hearing loss
1


6.11
Malignant neoplasm of middle ear
3


16
Thyroid Disorders
—


16.1
Other disorders of thyroid
1


16.2
Goiter
1


16.3
Hypothyroidism
1


16.4
Hyperthyroidism
2


16.5
Malignant neoplasm of thyroid
3


22
Urinary Tract and Kidney Conditions
—


22.5
Urethral stricture
1


22.6
Other disorders of bladder
1


22.7
Kidney infection
1


22.8
Hydronephrosis
1


22.9
Congenital anomalies of kidney and ureter
1


22.10
Disorders of kidney and ureter
1


22.11
Calculus of kidney and ureter
1


22.12
Glomerulonephritis
1


22.13
Bladder transplant
3


22.14
Renal dialysis
3


22.15
Renal failure
3


22.16
Kidney transplant, initial
3


22.17
Kidney transplant, follow-up
3


22.18
Malignant neoplasm of bladder and urethra
3


22.19
Malignant neoplasm of kidney and ureter
3









Step 190: Apply Rank Order Rule

After the CLI day rule, the rank order rule is reapplied in an attempt to assign CLIs, which were released during the CLI day rule, a defined diagnosis code as defined under Step 170. The ill-defined CLIs are assigned to the highest resource-intensity ranked ongoing episode for a patient that has passed the CLI day rule.
Step 200: Severity-of-Illness Assignment Rule
Each patient's condition-specific episode is labeled with a severity-of-illness marker to reduce the heterogeneity of episodes within a medical condition. Severity-of-illness is defined as the probability of loss of function due to the physiologic progression or impact of the medical condition. Under this definition, the Grouper function uses only ICD.9 diagnosis codes to assign a patient's episode with a severity-of-illness marker. The Grouper function does not define severity-of-illness by resource utilization within the patient's condition-specific episode (such as whether a surgery or a resource-intensive diagnostic test was present in the patient's episode of care).
There are up to three (3) severity-of-illness (SOI) classes for each of the 526 medical conditions, with SOI-1 being the least severe (routine, noncomplicated) and SOI-3 being the most severe. However, the embodiment recognizes that there may be a differing number of SOI classes. Some medical conditions have only one or two severity-of-illness levels. Refer to the fourth column in Table 10, List of Medical Conditions in the Grouper function.
The severity-of-illness assignment rule operates to increase the SOI class on a patient's medical condition episode on the basis of two main criteria: (1) the ICD.9 codes that are present on the CLIs in each episode with respect to SOI class; and (2) the number of CLIs with ICD.9 codes in the more severe SOI classes.
With respect to the first criterion, Table 13 shows the selected diagnosis (ICD.9) codes listed in Table M stratified by SOI class. The ICD.9 codes within each SOI class are stratified based on the probability of loss of function due to the physiologic progression of the medical condition. A patient's episode may receive a more severe SOI ranking only if CLIs within the episode have ICD.9 coding present in the more severe SOI classes. For each medical condition episode of care, the severity-of-illness assignment rule accesses this table and determines whether the appropriate ICD.9 coding is present for a potential increase in SOI ranking.







TABLE 13







Selected Diagnosis (ICD.9) Codes by Medical Condition and


Severity-of-Illness Level












Medical

Number of





Condition
Medical Condition
Severity
SO1-1
SO1-2
SO1-3


Number
Long Description
Classes
Class
Class
Class















5.2
Conjunctivitis
2
077.0
372.1
—





077.8
372.14






372.0
372.22






372.01




6.5
Otitis media
3
381
381.20
382.01





381.02
382
382.1





381.06
382.00







382.4



7.2
Sinusitis
2
461.0
473
—





461.2
473.2






461.3
473.3



9.11
Asthma
3
493.0
493.01
493.21





493.02
493.2






493.1




10.2
Hypertension
3
401.1
402
402.11





405.1
402.0
404.01






403.00
404.11






403.1







405.0









With respect to the second criterion, Table 14 shows the minimum number of CLIs with required ICD.9 codes in the more severe SOI classes. For each medical condition episode of care, the severity-of-illness assignment rule accesses this table and determines the number of CLIs with required ICD.9 codes. If the number of CLIs with required ICD.9 codes is not achieved, then the patient's condition-specific episode will remain in the less severe SOI class (e.g., SOI-1 class). For example, a patient's sinusitis episode will receive an SOI-2 rank only if the episode contains 6 or more CLIs (refer to Table 14) with the ICD.9 codes listed in the sinusitis SOI-2 column of Table 13. Otherwise, the sinusitis episode will receive an SOI-1 rank.







TABLE 14







Number of CLIs with Required ICD.9 Codes in the More Severe SOI Classes












Medical

Number of





Condition
Medical Condition
Severity
SOI-1
SOI-2
SOI-3


Number
Long Description
Classes
Class
Class
Class















5.2
Conjunctivitis
2
1
6
—


6.5
Otitis media
3
1
6
10


7.2
Sinusitis
2
1
6
—


9.11
Asthma
3
1
6
10


10.2
Hypertension
3
1
6
10









Step 210: Vertical Episode Merge Rule

Often the physiology of some medical conditions results in the manifestation of different symptoms. Depending on a patient's presenting symptoms, a physician may code a patient's diagnosis under different, but somewhat correlated medical conditions. Considering physician coding alone can result in episodes that are fragmented and don't give a full picture of care received for a medical condition. The Grouper function addresses this situation using a technique called the vertical episode merge rule.
For example, a physician may assign a patient to one of several cardiovascular disease-related medical conditions: ischemic heart disease, congestive heart failure, cardiac arrhythmia, hypertension, and other cardiovascular conditions. Likewise, presenting symptoms could result in a physician assigning a patient to one of several respiratory-related medical conditions: emphysema, chronic bronchitis, chronic obstructive pulmonary disease, asthma, and lower respiratory infections.
However, there usually is one underlying physiologic condition for a patient having several related medical conditions. To address this issue, physician panels were formulated to determine which of a patient's condition-specific episodes should be combined and when. The panels developed algorithms for combining related condition-specific episodes and assigning a patient to an overall medical condition episode based on the underlying most resource-intensive physiologic condition. Within each PMC Group, the panels listed medical conditions in ascending order of expected resource intensity level and physiologic progression of the condition or disease (from least resource intensive and physiologic progression to the most resource intensive and physiologic progression (refer to Table 10).
The vertical episode merge rule accesses Table 10 and merges a patient's condition-specific episodes in the same PMC Group. The episodes merge down the PMC Group medical condition list, always merging the patient's lesser resource intensity episodes into the most resource intensive medical condition episode. For example, assume a patient has episodes of ischemic heart disease, hypertension, and angina pectoris. Table 10 shows that ischemic heart disease is the more resource-intensive medical condition in PMC Group 10. Consequently, hypertension and angina pectoris are folded into the patient's ischemic heart disease episode. This indicates that remaining hypertension and angina pectoris episodes are derived from patients without ischemic heart disease.
Failure to consider a patient's underlying medical condition will distort the accuracy of a physician's efficiency measurement. For example, in the above patient, episodes would be generated for ischemic heart disease, hypertension, and angina pectoris even though the patient's angina and hypertension can be attributed to the underlying condition of ischemic heart disease. Consequently, utilization experience within the patient's ischemic heart disease episode would be understated. If the vertical episode merge rule did not exist for combining related condition-specific episodes, then a patient's medical condition utilization would be understated and a physician's practice pattern efficiency measure would be inaccurate.
The vertical episode merge rule considers how much time separates episodes in the same PMC Group. For Episode #2 to be considered for merge to a previously occurring Episode #1, a CLI from Episode #2 must either overlap Episode #1's duration time period or occur during the window period of Episode #1. In the vertical episode merge rule, any window period greater than 60 days is considered to be equal to 60 days. However, the embodiment recognizes that complete window period durations may exist.
FIG. 6 shows the vertical merge process for a patient's episodes of ischemic heart disease (10.13), angina pectoris (10.8), and hypertension (10.2). The episodes are merged together to form one episode of ischemic heart disease (10.13).
Step 220: Horizontal Episode Merge Rule
A patient may present with non-specific signs and symptoms before a more specific medical condition is diagnosed and treated. Non-specific medical conditions do not necessarily reflect a bodily system or organ system. Instead, they can reflect signs and symptoms such as abdominal pain, chest pain, dyspnea, spleenomegaly, non-specific exanthem, and jaundice. Table 15 presents sample non-specific medical conditions.
A patient's non-specific medical condition episodes need to be merged with the patient's more specific, resource-intensive medical condition episodes. Otherwise, a patient's specific medical condition utilization would be understated and a physician's practice pattern efficiency measure would be inaccurate. The Grouper function addresses this situation using a technique called the horizontal episode merge rule.
The Grouper function performs a horizontal episode merge when a non-specific medical condition episode overlaps a more specific medical condition episode. In order to be considered for horizontal episode merge, episodes must overlap so that they have service days in common. As illustrated in FIG. 7, the episode overlap may occur towards the beginning, middle, or end of the ongoing specific medical condition. Window periods between episodes are not considered for horizontal episode merges. However, the embodiment recognizes that window periods between episodes may exist.
The horizontal episode merge rule accesses Table 15 for each non-specific medical condition and merges the non-specific episodes into the more specific medical conditions in the PMC Group order defined in the table. The rule operates as follows. When a non-specific episode is identified, examine the Horizontal Episode Merge Order by PMC Group columns and attempt to merge the non-specific episode. The rule loops over each PMC Group in the defined precedence order, starting with the medical condition number stated in Table 15. The embodiment recognizes that the PMC Groups may change in order and number.
For example, for general presenting symptoms (36.15), the horizontal episode merge rule attempts to merge the patient's non-specific episode (36.15) with medical conditions in PMC Group 9 (Respiratory Conditions), beginning with lower respiratory diseases (Medical Condition 9.3) and moving down the list from 9.3 through 9.20. If no specific medical condition for the patient is found in PMC Group 9, then the rule loops over to find a medical condition in PMC Group 10 (Heart and Pulmonary Conditions), beginning with ventricular arrhythmias (Medical Condition 10.4). The rule moves down the medical condition list from 10.4 through 10.25. If no specific medical condition for the patient is found in PMC Group 10, then the rule loops over to find a medical condition in PMC Group 13 (Digestive System Conditions).
The process continues on until either the non-specific episode (36.15) is merged with a more specific episode, or the precedence ordered PMC Groups are exhausted, and no horizontal episode merge occurs. If no merge occurs, then the patient's non-specific episode (36.15) remains as general presenting symptoms.







TABLE 15







Selected Non-Specific Medical Conditions









Medical

Horizontal Episode Merge Order by PMC Group


Condition
Medical Condition
(Condition Listed Indicates Start Point for Merge)


















Number
Abbrev Description
1
2
3
4
5
6
7
8
9
10





















2.1
Intestinal infections
3.1
20.5 
—
—
—
—
—
—
—
—


2.2
Other bacteria diseases
3.1
9.10
21.3
20.1
22.12
13.19
35.1
23.3
24.5
10.14


36.1
Complication of surgery
21.3
31.17
33.5
32.5
10.4
11.8
14.1
35.1
12.1
24.5


36.15
General presenting symptoms
9.3
10.4
13.10
3.1
17.1
15.1
16.3
18.1
19.5
4.8


36.16
Non-specific exanthem
29.4
3.1
9.1
31.1
7.1
20.1
15.7
10.4
11.2
17.4


36.17
Abdominal pain
13.4
15.3
26.1
14.1
22.5
12.1
23.3
25.2
17.1
34.4


36.18
Dyspnea
9.1
10.14
3.1
7.2
8.1
4.8
21.3
31.17
34.4
—


36.19
Chest pain
10.4
9.10
3.1
21.3
34.4
30.8
31.17
30.2
—
—


36.20
Non-newborn jaundice
15.1
13.10
3.1
31.17
21.3
20.1
19.5
—
—
—


36.23
Spleenomegaly
20.1
21.3
3.1
31.17
19.5
—
—
—
—
—


36.24
Hepatomegaly
15.1
13.10
3.1
31.17
21.3
19.5
—
—
—
—









Step 230: Episode Treatment Stage Rule

Identifying different treatment stages, including initial, active, and follow-up treatment, is important in medical conditions such as the following: breast cancer, prostate cancer, colorectal cancer, acute myocardial infarction, and lymphoma.
The Grouper function is designed to separate initial, active, and follow-up treatment episodes using key episode identification markers, or triggers, for each applicable medical condition. Then, these episode types are separately examined to perform physician efficiency measurement.
Initial, active, and follow-up treatment stages are defined using breast cancer as an example. An initial breast cancer episode is one where the patient has a surgery for the cancer (e.g., lumpectomy, modified radial mastectomy). An active breast cancer episode is one where no surgery is present, but chemotherapy or radiation treatment is observed within the episode. Here, the patient underwent surgery in a previous study period, so no surgical event is found in the patient's current ongoing breast cancer episode. Instead, during the study period, the claims data shows that the patient is being treated with chemotherapy and/or radiation. The presence of these treatments defines an active breast cancer episode. The utilization pattern and charges are different for an active breast cancer patient as compared to an initial breast cancer patient. A follow-up breast cancer episode is one where no surgery, chemotherapy, or radiation treatment is present in the patient's episode of care. After initial and active treatments, physicians will continue to code for breast cancer over the future years of patient follow-up care.
In a given study period, physicians do not treat an equal distribution of each episode type (initial, active, and follow-up). Moreover, the episode types have different average charges. The group function correctly identifies treatment stages and examines them separately to ensure that physician efficiency scores accurately reflect the physician's practice.
Table 16 presents selected triggers descriptions and the applicable procedural codes (CPT-4, HCPCS, and UB92) for trigger formation. For instance, the mastectomy trigger consists of CPT-4 codes 19120-19272, whereby a trigger event of mastectomy may be formed if one or more CLIs in a patient's episode have CPT codes 19120-19272. Table 17 lists the selected triggers as they apply to several medical conditions that require treatment staging. The episode treatment stage rule accesses Table 16 and Table 17 and determines if the appropriate triggers exist to classify a patient's episode as initial, active, inactive, or follow-up.







TABLE 16







Selected Triggers for Differentiating Initial/Active/Inactive, Active/


Inactive, Initial/Follow-Up, Active/Follow-up, and Initial/Active/Follow-up











Trigger


HCPCS
UB92


Number
Trigger Description
CPT-4 Codes
Codes
Codes














5
Breast tissue expander
11960-11971




9
Mastectomy
19120-19272




10
Breast repair
19316-19499




16
Bone marrow transplant
38230-38241,






85120




17
Repair constricted aorta
33840-33855,






33619




20
Lymphadenectomy
38562-38564




21
Lymph node excision
38300-38559




26
Liver surgeries
47001-47136,






47380-47399




28
Exploratory laparotomy
49000




39
Sterotactic brain
61720-61770





procedure





46
Emergency room visit
99281-99285,

981




90500-90560




47
Inpatient visit
99221-99239,

987




99251-99263,






99291-99298,






99431-99440,






90200-90292,






99160-99172




48
Chemotherapy drugs

J0640, J1020-
J1094,





J1040, J1100,
J1440





J1710-J1720,






J1830, J2320-






J2322, J2920-






J2930, J7505,






J8530-J8610,






Q0083



49
Chemotherapy
96400-96549

280, 289,



administration


335


50
Radiation therapy
77261-77499

330-333,






342
















TABLE 17







Selected Trigger Applications for Medical Conditions: Initial/Active/Inactive,


Active/Inactive, Initial/Follow-Up, Active/Follow-up, and Initial/Active/Follow-up













Aortic Aneurysm
Lymphoma
Malignant neoplasm, breast















Trigger

Active
Follow-Up
Active
Inactive
Initial
Active
Follow-up


Number
Trigger Description
10.21
10.22
21.5
21.6
30.8
30.9
30.10


















5
Breast tissue expander





Yes



9
Mastectomy




Yes




10
Breast repair





Yes



16
Bone marrow transplant


Yes

Yes




20
Lymphadenectomy


Yes

Yes




21
Lymph node excision


Yes

Yes




26
Liver surgeries


Yes






28
Exploratory laparotomy


Yes






39
Sterotactic brain procedure


Yes






46
Emergency room visit
Yes








47
Inpatient visit
Yes








48
Chemotherapy drugs


Yes


Yes



49
Chemotherapy administration


Yes


Yes



50
Radiation therapy


Yes


Yes









For example, a patient's malignant neoplasm of the breast episode may be classified as initial if the following trigger events are present: breast repair, bone marrow transplant, lymphadenectomy, or lymph node excision. A patient's malignant neoplasm of the breast may be classified as active if the following trigger events are present: breast tissue expander, breast repair, chemotherapy drugs, chemotherapy administration, or radiation therapy.
However, the rule also examines Table 18 to determine whether the triggers meet specific qualifying event criteria. If a trigger event does not meet one of the specified criteria in Table 18 for a medical condition, then the trigger event does not count. For instance, in order for a patient's malignant neoplasm of the breast to be classified as initial, the table shows that: (1) one of the trigger events identifying the episode as initial needs to be $150 or more; or (2) two or more trigger events need to be present in the episode.
If these criteria are not met for the episode to be assigned to the initial treatment stage, then the rule accesses the Table 18 to determine if the patient's episode of malignant neoplasm of the breast may be assigned to the active treatment stage. The active treatment stage is assigned if a specific trigger event has a claim line item (CLI) on three different days. If no specific trigger event has a CLI on three different days, then the patient's episode is classified as follow-up.







TABLE 18







Qualifying Event Criteria for Triggers to Apply to Medical Conditions:


Initial/Active/Inactive, Active/Inactive, Initial/Follow-Up, Active/Follow-up, and


Initial/Active/Follow-up










Medical





Condition
Medical Condition




Number
Long Description
Criteria Examined
Qualifying Event













10.19
Aortic aneurysm, initial
Criterion 1, or
1 trigger procedure >$150




Criterion 2, or
Need >2 different trigger proc




Criterion 3
Any 1 trigger CLI on 3 different days









10.20
Aortic aneurysm, follow-up
Episode defaults to 10.20 if Criteria 1-3 above not achieved.










21.5
Lymphoma, active
Criterion 1, or
1 trigger procedure >$150




Criterion 2, or
Need >2 different trigger proc




Criterion 3
Any 1 trigger CLI on 3 different days









21.6
Lymphoma, inactive
Episode defaults to 21.6 if Criteria 1-3 above not achieved.










30.8
Malignant neoplam of breast, initial
Critierion 1, or
1 trigger procedure >$150




Criterion 2, or
Need >2 different trigger proc




Criterion 3
Not applicable











Episode defaults to 30.9 if Criteria 1-3 not achieved.


30.9
Malignant neoplasm of breast, active
Rule now examines if episode meets following criteria:












Critierion 1, or
Any 1 trigger CLI on 3 different days




Criterion 2, or
Not applicable




Criterion 3
Not applicable









30.10
Malignant neoplasm of breast, follow-up
Episode defaults to 30.10 if Criteria 1-3 above not achieved.









Stage 240: Complex Condition Merge Rule

Certain medical conditions represent the combination of two or more medical conditions in the same PMC Group. For example, diabetes mellitus with multiple complications (17.6) is one such medical condition. The Grouper function initially formulates one or more of the following episodes of diabetes for a patient: 17.1 diabetes mellitus with no complications; 17.2 diabetes mellitus with ophthalmic manifestation; 17.3 diabetes mellitus with neurologic manifestation; 17.4 diabetes mellitus with circulatory manifestation; and 17.5 diabetes mellitus with renal manifestation.
The complex condition merge rule then examines all initially formed episodes of diabetes for a patient and determines whether the patient has any of the combinations listed in Table 19. For instance, if a patient has an episode of diabetes with no complications (17.1) and an episode of diabetes with ophthalmic manifestations (17.2), then both episodes will be merges into 17.2. The rule also accesses the table to form diabetes with multiple complications (17.6). This medical condition does not exist before the complex condition merge rule. Table 19 shows that a patient is placed into diabetes with multiple complications (17.6) if the patient has any combination of 17.2, 17.3, 17.4, and 17.5.
The final list of diabetes medical conditions is as follows: 17.1 diabetes mellitus with no complications; 17.2 diabetes mellitus with ophthalmic manifestation; 17.3 diabetes mellitus with neurologic manifestation; 17.4 diabetes mellitus with circulatory manifestation; 17.5 diabetes mellitus with renal manifestation; and 17.6 diabetes mellitus with multiple complications.







TABLE 19







Complex Condition Merge for Diabetes Mellitus











Medical
Medical
Patients Episodes are Merged



Condition
Condition
And Placed into Highest



Number 1
Number 2
Resource Intensity Episode






17.1
17.2
17.2



17.1
17.3
17.3



17.1
17.4
17.4



17.1
17.5
17.5



—
Any combination
17.6




of 17.2, 17.3,





17.4 and 17.5









Step 250: Complication Episode Merge Rule

The Grouper function uses the complication episode merge rule to identify medical conditions as complicating factors to a patient's underlying medical condition being examined. Complicating factors are patient-specific episodes that are clinically determined to be related to the underlying disease.
For example, physicians' code up to 70% of an average diabetic's charges under the related complications to diabetes (e.g., neuropathies, circulatory, eye, renal) and not diabetes care. This is because physicians frequently code only for the specific condition that they are treating at the time, which is often not diabetes. Therefore, without considering and including complication episodes with the actual diabetes episode, patient severity-of-illness and physician efficiency differences may be attributed to incomplete episode charges and utilization.
Another example is human immunodeficiency virus (HIV) conditions where tracking related complications is important or up to 80% of an average HIV patient's charges and utilization may be under-reported. These complicating conditions include pneumonia, opportunistic infections (e.g., cryptococcosis, candidiasis), nerve conditions, eye conditions, blood disorders, and malignancies. The Grouper function includes related complications and links them to the underlying condition being examined.
A third example is maternity conditions where complications before birth and complications of delivery are important to track to single and multiple newborn deliveries. Otherwise, up to 50% of an average maternity patient's charges and utilization may be under-reported.
Using HIV conditions as an example for applying the complication episode merge rule, the Grouper function initially formulates the following underlying medical condition episode for a patient: 3.1 Asymptomatic HIV infection.
One or more medical conditions then are linked as complications to the underlying medical condition of asymptomatic HIV infection. This linkage may result in the underlying medical condition episode being upcoded to a more resource intensive medical condition to reflect the physiologic progression of the disease and/or the underlying medical condition episode being moved to a higher severity-of-illness (SOI) class.
Table 20 shows the medical conditions linked to asymptomatic HIV infection (3.1) that will upcode the patient's episode to HIV with infectious complication (3.2). The rule accesses Table 20 to determine if any of the complication medical conditions are present for the patient. If yes, then the patient is upcoded to HIV with infectious complication (3.2). For all complication episodes, the charges and utilization are merged into the ongoing HIV with infectious complication episode.







TABLE 20







Complication Medical Conditions Linked to the


Underlying Medical Condition of HIV Infection











Medical

Complication

HIV with Infect Comp (3.2)













Cond

Condition
Complication Condition
SOI
SOI
SOI


Number
Verbal Description
Number
Verbal Description
Class
Class
Class
















3.2
HIV with infectious comp
2.5
Tuberculosis
1






2.5
Tuberculosis

2





2.5
Tuberculosis


3




2.11
Cytomegalic inclusion dz
1






2.16
Cryptococcosis
1






2.17
Candidiasis
1






2.17
Candidiasis

2





2.17
Candidiasis

3





2.18
Coccidioidomycosis
1






2.18
Coccidioidomycosis

2





2.18
Coccidioidomycosis


3




2.19
Histoplasmosis
1






2.19
Histoplasmosis

2





2.19
Histoplasmosis


3




2.20
Blastomycotic infection
1






2.20
Blastomycotic infection

2





2.23
Toxoplasmosis
1






2.23
Toxoplasmosis

2





2.23
Toxoplasmosis


3




2.24
Pneumocystosis
1






9.7
Pneumonia
1






9.7
Pneumonia

2





9.7
Pneumonia

3









The rule then examines the SOI class of the linked complication medical condition episode. For instance, Table 20 illustrates that toxoplasmosis episodes with SOI-1 rank will not move the patient's HIV with infectious complication episode to a higher SOI class. However, the table shows that toxoplasmosis episodes with SOI-2 rank will move the patient's HIV with infectious complication episode to the SOI-2 class.
After applying the complication episode merge rule, Table 21 shows that a patient with HIV infection may be placed into one of the following PMC Group 3 medical conditions and SOI classes.







TABLE 21







Human Immunodeficiency Infection Medical Conditionsand SOI


Classes After Linking of Complication Episodes









Medical

Number of


Condition
Medical Condition
Severity


Number
Long Description
Classes












3
Human Immunodeficiency Infections



3.1
HIV infection with no complications
1


3.2
HIV infection with infectious complication
3


3.3
HIV infection with CNS involvement
3


3.4
HIV infection with malignancy
3


3.5
HIV infection with multiple complications
3









Step 260: Comorbidity Marker Rule

In an embodiment, the Grouper function also uses a comorbidity marker rule to identify medical conditions as comorbidities to a patient's medical condition being examined. A comorbidity is a concurrent resource-intensive medical condition that is not related to the underlying disease state. For example, breast cancer is considered a comorbid condition to diabetes.
With respect to comorbidities, the individual physician efficiency analysis may eliminate from analysis any patient episode with a linked comorbidity. If such episodes are not eliminated, unnecessary heterogeneity may remain within condition-specific episodes. This heterogeneity adds error to any evaluation of physician efficiency.
Table 22 presents selected comorbid medical conditions. As indicated in Table 22, for a comorbid medical condition to be tracked to a medical condition episode in question, the patient's comorbid medical condition episode needs to be of a certain SOI class and total charge amount. For example, Table 22 shows that a patient's seizure disorder needs to be of SOI-2 class and at least $2,500 to be linked to another medical condition as a comorbidity. It is to be understood that the medical conditions listed in Table 22 do not need to have qualifying events, such as a charge amount or SOI level.







TABLE 22







Selected List of Medical Condition Comorbiditiesto a Patient's 


Medical Condition Being Examined












Mini-
Mini-


Medical

mum
mum


Condition
Medical Condition
Episode
SOI


Number
Long Description
Charges
Level













2.4
Septicemia
$3,500
1


2.5
Tuberculosis
$2,500
1


2.11
Cytomegalic inclusion disease
$3,500
1


3.4
HIV infection with malignancy
$1,500
1


3.5
HIV infection with multiple
$1,500
1



complications




4.11
Inflammatory diseases of CNS
$3,500
1


4.19
Multiple sclerosis
$2,500
1


4.24
Malignant neoplasm of brain, initial care
$2,000
1


4.25
Malignant neoplasm of brain, active care
$2,000
1


9.13
Emphysema
$3,000
2


9.14
Chronic obstructive pulmonary disease
$4,000
1


9.15
Spontaneous pneumothorax
$2,500
1


9.19
Malignant neoplasm of bronchus and 
$3,000
1



lung, active




10.16
Congestive heart failure
$3,000
2


10.17
Cardiomyopathy
$3,000
2


10.21
Acute myocardial infarction, active
$3,500
1


10.22
Acute myocardial infarction, follow-up
$3,000
1


11.14
Cerebrovascular hemorrhage
$2,500
1


13.20
Crohn's disease
$3,000
2


13.27
Malignant neoplasm of stomach
$2,000
1


13.30
Malignant neoplasm of colon, initial
$3,500
1


15.10
Chronic liver disease
$2,500
2


15.11
Liver transplant
$2,000
1


15.14
Malignant neoplasm of pancreas
$2,000
1


17.5
Diabetes mellitus with renal
$3,750
1



manifestation




17.6
Diabetes mellitus with multiple
$3,750
1



complications




20.9
Malignant neoplasm of spleen
$2,000
1


29.27
Kaposi's sarcoma
$2,000
1


31.19
Rheumatoid arthritis
$3,000
2


34.31
Organic dementias
$3,000
2


34.32
Schizophrenia
$3,000
2









Step 270: Partial Episode Marker Rules

The Gouper function determines partial and complete episodes of care for both acute and chronic episodes. The user decides whether to include or exclude partial episodes of care from analysis using the parameter SWITCH_DROPPARTIAL in the RUN.INI file (refer to Table 6).
In an embodiment, the system of the present invention uses different analytical approaches to identify partial episodes for acute and chronic medical conditions, as described below.
With respect to acute conditions, the partial episode marker rule states that acute episodes must pass the tests defined in Table 23 for both the beginning and the end of the study period, or the episodes will be marked as partial. The maximum allowable duration for any acute condition is 180 days.







TABLE 23







Partial Acute Episodes of Care








If the medical condition window period is:
Then the episode is marked as partial when it:










Study-Start Partial Episodes


 


(Episodes declared partial because they may have begun before the start of the study period.)








Equal to or greater than 90 days
Begins within 30 days of the start of the study period


Less than 90 days
Begins closer than 33% of the window period from the



start of the study period







Study-End Partial Episodes


(Episodes declared partial because they may not be complete at the end of the study period.)








Equal to or greater than 120 days
Begins during the last quarter of the study period


Less than 120 days
The last CLI associated with the episode is closer than



33% of the window period to the end of the study period,



unless the episode has been under way for 180 days









For acute conditions having a window period equal to or greater than 120 days, the last three months of the study period are used as a run-out interval to allow all incomplete acute episodes as of the beginning of the fourth quarter to end. Allowing for a run-out interval reduces the fragmentation of acute episodes and therefore increases the validity and reliability of treatment pattern results.
For acute conditions having a window period less than 120 days, the episode will be marked as partial if the last CLI associated with the episode is closer than 33% of the window period to the end of the study period. For example, upper respiratory infection (URI) has a window period of 60 days. Assume a patient's ongoing episode of URI has a CLI with a date of service of December 20, and the end of the study period is December 31. Then, this URI episode would be marked as partial because the episode's last CLI is less than 33% of the window period (or 20 days) to the end of the study period.
In an embodiment, all chronic medical condition episodes begin during the first half of the study period to be considered complete episodes of care. Chronic episodes beginning in the second half of the study period are treated as partial. In an embodiment, the duration for a chronic condition is 180 days for the physician efficiency analysis. However, chronic conditions may continue on indefinitely as recognized by the window period of 365 days (refer to Table 11 for chronic disease window periods of 365 days).
Step 6: Perform PATAN Output Process
The PATAN output process involves four main functions.
The first function is to eliminate episodes of care that have been marked for removal during the read in RUN.INI file step. These episodes include: (1) partial episodes of care; and (2) episodes marked with comorbidities. If these two types of episodes have not been marked for deletion, then the episodes will be presented in the PATAN output file.
The second function is to assign episodes to physicians using the episode assignment logic as defined by the parameter SWITCH_ASSIGNTHRESHOLD during the read RUN.INI file step. Generally, the user is interested in examining those episodes of care where the physician recommends treatment and follow-up services. Therefore, an assignment rule is included that allows the physician to be a key treatment provider, but also allows for the physician to refer to another specialist for ongoing treatment. This assignment rule specifies that when a physician incurs a given percent of charges in an episode of care, that episode is assigned to that physician.
For the physician efficiency analysis, an assignment value of 20% usually is employed, but the user can change the assignment rule from 1-100% using the parameter SWITCH_ASSIGNTHRESHOLD in the RUN.INI file (refer to Table 6).
Using this rule, all professional charges are added in each episode of care, including office visits, lab/path services, medical and surgical procedures, and diagnostic tests. These professional charges may occur on an office visit, clinic, hospital outpatient, hospital inpatient, or other professional setting basis (e.g., nursing home, halfway home, home visit professional charges). All facility charges and prescription drugs are excluded. However, in an embodiment, other services may be included from an episode of care for the physician assignment rule.
For example, consider an assignment rule equal to 20%. This means that when a physician has 20% or more of all professional charges, the episode is assigned to that physician. At the 20% level, this rule generally results in episodes being assigned to about 1.20 physicians (or up to 20% of episodes may be assigned to more than one physician). Chronic disease episodes (e.g., asthma) are assigned to more than one physician more often than acute episodes (e.g., acute bronchitis).
When an episode is not assigned to any physician using the 20% assignment rule, another rule is employed which assigns that episode to the physician who has the highest percent of professional charges within the episode. For example, using the 20% assignment rule, if no physician has 20% or more of the professional charges, and the physician who comes closest to meeting this rule has 17% of professional charges in the episode of interest, then the episode is assigned to this physician and no other.
The third function of the PATAN output process is to group CLIs in episodes into 11 major service categories and 21 sub-service categories. During the extract core claims data fields step, a BETOS code is assigned to each service on a CLI (e.g., CPT-4, HCPCS). The BETOS code assignment allows for CLIs to be grouped into one of 11 major service categories and 21 sub-service categories. Table 24 presents the type of service codes that match to each BETOS code. Then, the type of service codes are mapped to the 11 major service and 21 sub-service categories. Service and sub-service categories are formed during the PATAN output process.







TABLE 24







Type of Service Codes and BETOS Codes










Type Of





Service Code





Used for
Service
Type of Service



Processing
Category
Code
BETOS Code













0
Other Medical
Unknown
—



Services




1
Professional
Office Visit
M1x



Visits




2
Professional
Hospital Visit
M2x



Visits




3
Professional
ER Visit
M3



Visits




4
Professional
Other Visit
M4x, M5x, M6



Visits




5
Other Medical
Anesthesia
P0



Services




6
Med/Surg
Procedure
P1x, P2x, P3x,



Procedures

P4x, Pyx, P6x


7
Other Medical
Radiation Therapy
P7A



Services




8
Other Medical
Other Oncology
P7B



Services




9
Med/Surg
Endoscopy
P8x



Procedures




10
Other Medical
Dialysis Service
P9x



Services




11
Diagnostic
Imaging
1xx



Tests




12
Other Medical
Venipuncture
T1A



Services




13
Lab/Path
Lab Test
T1B, T1C, T1D,





T1E, T1F, T1G, 





T1H


14
Diagnostic
Functional Tests
T2x



Tests




15
Other Medical
Durable Medical
Dxx



Services
Equipment/Supplies



16
Other Medical
Ambulance
O1A



Services




17
Other Medical
Chiropractic
O1B



Services




18
Other Medical
Enteral/Parenteral
O1C



Services




19
Other Medical
Chemotherapy
O1D



Services




20
Other Medical
Other Drugs
O1E



Services




21
Other Medical
Vision/hearing/speech
O1F



Services
Services



22
Other Medical
Immunization
O1G



Services




23
Other Medical
Other NEC Services
Y1, Y2, Z1, Z2



Services









The fourth function of the PATAN output process is to implement the maximum duration rule for episodes of care, which is 180 days.
For chronic conditions (e.g., diabetes, asthma, ischemic heart disease), an episode of care begins when a CLI is initially found during the study period that has a defined ICD.9 code that has been assigned to that medical condition. Then, chronic conditions may continue on indefinitely as recognized by the window period of 365 days. However, for the purposes of physician efficiency analysis, chronic conditions are considered to have a 180-day duration. Therefore, a chronic condition ends 180 days after identifying the first CLI with a diagnosis (defined ICD.9 code) for the specific chronic condition. The rule determines that the patient is present for 180 days during the study period after the first CLI with a diagnosis for the specific chronic condition.
For acute conditions (e.g., upper respiratory infections, otitis media, conjunctivitis), the maximum allowable duration for the physician efficiency analysis also is 180 days. The embodiment recognizes that this maximum allowable duration may be varied.
Step 7: Store PATAN Output File
The PATAN Output File is stored in episode of care identifier order (Field 1 in Table 25). Table 25 lists the fields present on the PATAN Output File.







TABLE 25







Fields in the PATAN Output File









Field
Field Descriptive



Number
Name
Notes










(Section A) Non-Repeated Episode Fields









1
Episode ID
The unique episode ID for each medical condition treatment episode.


2
Medical
ConditionThe medical condition internal ID number.



Number



3
SOI
Severity of Illness index, where 1 is the least severe and 3 is the most




severe or difficult to treat as defined for the medical condition.


4
Episode Duration
The duration of the medical condition treatment episode, in days.


5
Total Episode
The total allowed charges for the treatment episode, in dollars.



Charges



6
Professional
Total allowed charges claimed by professional (excludes Rx and facility)



Charges
physicians.


7
Physician ID
Identifies each physician that had significant involvement in the treatment




for the episode. If multiple physicians were significantly involved in treating




the episode, multiple rows are output for the episode, one for each




physician.


8
Physician Specialty
Identifies the specialty number associated with the physician. Since the




specialty is determined by the PROVSPEC module, this field contains the




value 0 in the version of the output from PATAN.


9
Physician
Identifies the marketbasket number associated with the physician. Since



Marketbasket
the marketbasket is determined by the PROVSPEC module, this field




contains the value 0 in the version of the output from PATAN.


10
Physician
Identifies the aggregate grouping number associated with the physician.



Aggregate
Since the aggregate grouping number is determined by the PROVSPEC



Grouping Code
module, this field contains the value 0 in the version of the output from



Number
PATAN.


11
[not valid for
This field is not valid for the commercial population. Always contains the



commercial
value 1.



population]



12
Physician Charges
The is the charge component amount of the Professional Charges field




(see above referenced field) that is attributable to the physician identified




by the Physician ID field (see above referenced field).


13
Patient Age
The age of the patient at the beginning of the study period.







(Section B) Repeated Episode Fields for Each Service Category (11 times per row)









1
Service Category
Eleven fields that contain utilization data at the service category level.



Utilization



2
Service Category
Eleven fields, ten of which contain charges in dollars at the service



Charges
category level (field 9 is not used because the system of the present




invention does not break out charge data for inpatient admits).







(Section C) Repeated Episode Fields for Each Sub-Service Category (21 times per row)









1
Sub-Service
Twenty-one fields that contain utilization data at the sub-service category



Category Utilization
level.


2
Sub-Service
Twenty-one fields, twenty of which contain charges in dollars at the sub-



Category Charges
service category level (field 14 is not used because the system of the




present invention does not break out charge data for inpatient admits).









Step 8: Sort PATAN Output File by Provider ID: PROVSORT1

The PATAN Output File is sorted by the primary sort key of physician identifier. The secondary sort key is the episodes assigned to a physician.
Step 9: Read in Episode Assignments from PROVSORT1
The episode assignments by physician from PROVSORT1 are read into the physician specialty module (PROVSPEC). PROVSPEC completes several of the missing fields in the PATAN Output File (refer to Table 25): (1) physician specialty (Field 8); (2) physician marketbasket (Field 9); and (3) physician aggregate grouping code number (Field 10).
Step 10: Assign Specialty Type to Physician
The PROVSPEC module employs a rule to select the most appropriate physician specialty when a physician has more than one specialty type assigned in the physician provider file. This processing step is helpful in selecting a specialty type that is most reflective of the physician's actual practice during the study period.
The rule examines all episodes associated with a physician and assigns each episode to one of the 31 marketbasket specialty types (refer to Table 26). A marketbasket consists of the most common conditions treated by each physician specialty type. The term physician is used broadly, and includes other professionals delivering medical care services, such as chiropractors, acupuncturists, podiatrists, nurse practitioners, and physical therapists.
Medical conditions are tracked to a specialty-specific marketbasket if they generally account for 60% to 80% of the episodes treated by that specialist type. The medical conditions are selected for the marketbasket in work effort order, which is a function of the prevalence rate of a condition and the average charges to treat a patient's episode of care. The embodiment recognizes that additional marketbaskets may be developed for other specialty types.
Several examples of medical conditions in special-specific marketbaskets are as follows. Hypertension, low back pain, and sinusitis are within the general internist marketbasket. Otitis media, upper respiratory infections, sinusitis, and rhinitis are within the pediatric marketbasket. Obstetrics/gynecology: single newborn normal delivery, cervicitis, and endometriosis are within the obstetrics/gynecology marketbasket. External abdominal hernias, cholilithiasis, and cystic breast disease are within the general surgeon marketbasket.
The composition of medical conditions in each specialty-specific marketbasket does not (generally) change over time. This means that any trend increase reflected by the specialty-specific marketbasket is independent of changes in patient demographics and health status. Instead, the trend reflects price increases, volume increases, and intensity of service increases in the treatment of the static set of medical conditions.
The physician specialty assignment rule eliminates any specialty types not already assigned to the physician in the physician provider file. The rule then looks for the marketbaskets with the most episodes among those remaining. For example, consider a physician who has been identified in the physician provider file as a general internist and a cardiologist. During analysis, the rule finds the following marketbasket specialty types associated with the physician's episodes: 37% of episodes are associated with Marketbasket 10, gastroenterology; 34% with Marketbasket 2, general internists; and 29% with Marketbasket 4, cardiology.
Even though 37% of the physician's episodes have been identified as gastroenterology, the physician cannot be assigned to the gastroenterology marketbasket because gastroenterology was not included as a specialty type in the physician provider file.
The physician is observed to have more episodes in the general internists marketbasket than in the cardiology marketbasket. Thus, this physician might be assigned for efficiency analysis into the general internists marketbasket. However, a second rule is now applied before assigning this physician as a general internist and running the general internists marketbasket. The second rule states that if a physician has an assigned primary care physician (PCP) designation (i.e., family/general practitioner, general internist, or pediatrician), but also an assigned non-PCP specialty type, then the PCP designation is ignored and the physician is assigned to the specialty that has the next most episodes that is not a PCP designation. If another specialty type is not present, then the physician is assigned the PCP designation of family/general practitioner, general internist, or pediatrician as defined in the physician provider file.
Using this rule, the physician would be placed in Marketbasket 4, cardiology, because general internist is defined as a PCP. Therefore, the rules assign the physician for efficiency analysis as a cardiologist.







TABLE 26







Marketbasket Specialty Types








Market-



Basket



Number
Marketbasket Specialty Type











1
Family and General Physicians


2
General Internists


3
Allergy


4
Cardiology


5
Cardiothoracic Surgery


6
Chiropractic


7
Dermatology


8
Emergency Medicine


9
Endocrinology


10
Gastroenterology


11
General Surgery


12
Nephrology


13
Neurology


14
Neurosurgery


15
Obstetrics/Gynecology (OB/GYN)


16
Oncology/Hematology


17
Ophthalmology


18
Oral Maxillary


19
Orthopedics


20
Otolaryngology (ENT)


21
Pediatrics


22
Plastic Surgery


23
Podiatry


24
Psychiatry


25
Psychology


26
Pulmonology


27
Rheumatology


28
Sports/Physical Medicine


29
Urology


30
Vascular Surgery


31
Critical Care (Intensivist)









Step 11: Assign Physician to Marketbasket Based on Specialty Type

After the physician has been assigned to a specialty type, the physician is then assigned to a marketbasket. The physician specialty codes in Table 3 are mapped to the marketbasket specialty types in Table 26. Both Table 3 and Table 26 are accessed to assign physicians to a marketbasket.
Step 12: Assign Physician to Report Group
Report group structures are important because they allow the formation of peer groups to which physicians can be compared. PROVSPEC provides a tool to build report group structures that interest the user. The tool provides flexibility in building report groups reflecting comparisons that are relevant to the user. Example report groups include geographic regions, physician groups, and benefit plan designs.
The basis for creating report groups is the Detailed Grouping Code (refer to Table 1, Field 35). A Detailed Grouping Code is a client-specified identifier that is the base data element aggregated to form a report group. For example, zip codes or tax identification numbers can be Detailed Grouping Codes.
An Aggregate Grouping Code represents a group of Detailed Grouping Codes (refer to Table 25, Section A, Field 10). The Aggregate Grouping Code is a number the user chooses. The output of the system of the present invention contains information organized by Aggregate Grouping Code. Therefore, the aggregate groups the user develops are the foundation for report group structures contained in output files and printed reports.
The process of developing a report group structure is a now described. First, the user decides on a grouping structure. When formulating a grouping structure, the user needs to consider the nature of the comparison. For example, one comparison may be geographic comparisons based on zip code of physician place of service. The grouping structure should assure that each group has a large enough member base to make comparisons meaningful.
Second, an Aggregate Grouping Code is assigned to each group that has been defined. The code is a positive integer that has been selected. It is used by the system of the present invention to represent the groups. For example, when comparing on the basis of geographic regions, each Aggregate Grouping Code might represent a specific region that has been defined by identifying individual zip codes.
Detail codes are then determined based on the comparison to be made. For example, for geographic comparisons, the detail codes might be physician office address zip codes.
Each Detailed Grouping Code is then assigned to an Aggregate Grouping Code. The user does this by creating a simple two-column table in which the first column is the Detailed Grouping Code and the second column is the Aggregate Grouping Code. The task is accomplished by developing a spreadsheet for relatively small groups or with a database program for larger groups.
The grouping map is then saved as a file, and referenced in the RUN.INI File. The user may name the file as desired, and the user needs to edit the RUN.INI File so that it includes the correct file name. Output files and reports are organized using the report group structure that has been defined.
A geographic region analysis might use physician office zip codes as the basis for forming groups. The user would employ the following process to build the report group structure: identify the geographic regions of interest; assign each region an arbitrary code number; each physician must then be identified as belonging to a region; and assign or map physician office zip codes to the code numbers representing geographic regions. Table 27 shows how the user can map zip codes to regions.







TABLE 27







Grouping by Geographic Region










Detailed Grouping Code
Aggregate Grouping Code







Physician's office Zip Code
Code number representing a client-




defined geographic region










A physician group analysis might use physician identification numbers as the basis for forming groups. In this embodiment, the user employs the following process to build the report group structure: identify the physician groups of interest; assign each physician group an arbitrary code number; identify each physician as belonging to a group; and assign or map physician identification numbers to the code numbers representing physician groups. Table 28 shows how the user would map physician identification numbers to the code numbers representing physician groups.







TABLE 28







Grouping by Physician Group










Detailed Grouping Code
Aggregate Grouping Code







Physician ID
Number representing a physician group










Step 13: Determine Eligible Physicians and Episode Assignments

This step involves three main functions. The first function is to filter or eliminate physicians with an assigned specialty type that cannot be assigned to one of the 31 marketbaskets. For example, there is no radiologist marketbasket, so radiologists would be removed by this rule.
The second function is to eliminate physicians that are not in a report group of interest. This rule examines the physician's assigned Detailed Grouping Code as compared to the Aggregate Grouping Codes of Interest. If the Detailed Grouping Code does not match to an Aggregate Grouping Code of interest for an established RUN.INI File run, then the physician is filtered out from further analysis.
The third function is to filter out episode assignments not in a marketbasket. For physicians in a Report Group of interest for an established RUN.INI File run, episode assignment rows in the PROVSORT1 input file that are not relevant to the marketbasket in which the physician will be profiled are filtered by PROVSPEC processing. This PROVSPEC rule checks to ensure that the medical conditions treated by the physician are included in the FILE_MBCONDITIONS File for the physician's marketbasket (refer to Table 6, Parameters in the RUN.INI File). Medical conditions that are not in the physician's marketbasket are removed from analysis.
Another PROVSPEC rule checks to ensure that the age of the patient falls within the age range specified in the FILE_SPECAGE File for a defined marketbasket (refer to Table 6, Parameters in the RUN.INI File). If not, that patient's episode of care is removed from analysis. The user can modify the FILE_SPECAGE File.
With respect to the FILE_MBCONDITIONS File, both commercial and Medicare marketbaskets have been defined. There are a total of 31 commercial marketbaskets by physician specialty type. Commercial means a population of individuals under 65 years of age that are not eligible to receive Medicare benefits. There are a total of 31 Medicare marketbaskets by physician specialty type. Medicare means a population of individuals 65 years of age and older that are eligible to receive Medicare benefits.
Each medical condition in a specialty-specific marketbasket is assigned a weight factor that reflects the importance or relevance of that medical condition to the marketbasket. However, in an embodiment, no one medical condition receives more than a 30% weight factor to prevent a physician's treatment pattern for that condition from dominating the results of a marketbasket.
The weight factors are used to compute the overall marketbasket weighted average value of a charge or utilization service category—across medical conditions—for a peer group or a physician. The sum of the weight factors in a marketbasket equals 1.00.
Therefore, regardless of a physician's (or peer group's) actual episode work effort, the rule standardizes each physician's actual work effort to a static set of weight factors. These weight factors represent the work effort that an average specialty-specific physician treats in medical practice, where work effort is a function of the prevalence rate and the average charges to treat an episode of care. This standardized weighting allows for an apples-to-apples comparison of one physician's marketbasket results to another physician's marketbasket results.
Tables 29-60 present the 31 commercial marketbaskets listed in Table 26, Marketbasket Specialty Types. The last column in each marketbasket table presents the weight factor for each medical condition. It is to be understood that the medical conditions and severity-of-illness levels may change for a marketbasket.







TABLE 29







1. FAMILY AND GENERAL PRACTITIONERS












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
10.2
1
Hypertension
0.100


2
31.9
1
Low back pain
0.050


3
31.8
1
Cervical spine pain
0.025


4
31.4
1
Bursitis
0.050


5
33.15
1
Degenerative joint disease
0.025


6
17.1
1
Diabetes w/no complications
0.050


7
7.2
1
Sinusitis
0.050


8
7.1
1
Rhinitis
0.050


9
9.4
1
Acute bronchitis
0.050


10
9.1
1
Upper respiratory infections
0.050


11
9.7
1
Pneumonia
0.050


12
13.13
1
Noninfect gastroent & colitis
0.050


13
9.11
1
Asthma
0.025


14
10.13
1
Ischemic heart disease
0.025


15
36.19
1
Chest pain
0.025


16
13.6
1
Gastroesophageal reflux
0.025


17
13.5
1
Gastritis and duodenitis
0.025


18
19.4
1
Disorders of lipid metabolism
0.025


19
16.3
1
Hypothyroidism
0.025


20
22.3
1
Urinary tract infections
0.025


21
34.17
1
Nonpsychotic depression
0.025


22
34.14
1
Personality & disturb dsdr
0.025


23
29.9
1
Dermatitis and eczema
0.025


24
4.3
1
Headaches
0.020


25
31.3
1
Other arthropathy disorders
0.020


26
20.4
1
Anemia disorders
0.020


27
36.17
1
Abdominal pain
0.020


28
29.6
1
Skin keratoses
0.015


29
29.1
1
III-defined integument sym
0.015


30
36.15
1
General presenting symptoms
0.015






1.000
















TABLE 30







2. GENERAL INTERNISTS












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level 
Short Description
Weight














1
10.2
1
Hypertension
0.100


2
31.9
1
Low back pain
0.050


3
31.8
1
Cervical spine pain
0.025


4
31.4
1
Bursitis
0.050


5
33.15
1
Degenerative joint disease
0.025


6
17.1
1
Diabetes w/no complications
0.050


7
7.2
1
Sinusitis
0.050


8
7.1
1
Rhinitis
0.050


9
9.4
1
Acute bronchitis
0.050


10
9.1
1
Upper respiratory infections 
0.050


11
9.7
1
Pneumonia
0.050


12
13.13
1
Noninfect gastroent & colitis
0.050


13
9.11
1
Asthma
0.025


14
10.13
1
Ischemic heart disease
0.025


15
36.19
1
Chest pain
0.025


16
13.6
1
Gastroesophageal reflux
0.025


17
13.5
1
Gastritis and duodenitis
0.025


18
19.4
1
Disorders of lipid metabolism
0.025


19
16.3
1
Hypothyroidism
0.025


20
22.3
1
Urinary tract infections
0.025


21
34.17
1
Nonpsychotic depression
0.025


22
34.14
1
Personality & disturb dsdr
0.025


23
29.9
1
Dermatitis and eczema
0.025


24
4.3
1
Headaches
0.020


25
31.3
1
Other arthropathy disorders
0.020


26
20.4
1
Anemia disorders
0.020


27
36.17
1
Abdominal pain
0.020


28
29.6
1
Skin keratoses
0.015


29
29.1
1
III-defined integument sym
0.015


30
36.15
1
General presenting symptoms
0.015






1.000
















TABLE 31







3. ALLERGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
7.1
1
Rhinitis
0.175


2
7.2
1
Sinusitis
0.150


3
9.11
1
Asthma
0.150


4
9.1
1
Upper respiratory infections
0.075


5
9.2
1
Dz upper respiratory tract
0.050


6
9.10
1
Chronic bronchitis
0.050


7
9.4
1
Acute bronchitis
0.050


8
7.4
1
Deviated nasal septum
0.050


9
9.3
1
Lower respiratory diseases
0.050


10
29.8
1
Urticaria
0.050


11
36.12
1
Toxic effects of substances
0.050


12
29.9
1
Dermatitis and eczema
0.025


13
5.2
1
Conjunctivitis
0.025


14
6.5
1
Otitis media
0.025


15
9.5
1
Hypertrophy tonsils & aden
0.025






1.000
















TABLE 32







4. CARDIOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
10.13
1
Ischemic heart disease
0.150


2
10.13
2
Ischemic heart disease
0.050


3
17.4
1
Diabetes with circulatory
0.050


4
17.4
2
Diabetes with circulatory
0.050


5
10.21
1
Acute myocardial infrct, active
0.075


6
10.22
1
Acute myocardial infrct, fup
0.025


7
10.2
1
Hypertension
0.075


8
10.5
1
Supraventricular arrhythmias
0.050


9
10.4
1
Ventricular arrhythmias
0.050


10
10.1
1
Abnormal heart beat
0.050


11
10.14
1
Heart value disorders
0.050


12
36.19
1
Chest pain
0.050


13
10.10
1
Conduction disorders
0.050


14
10.16
1
Congestive heart failure
0.050


15
10.17
1
Cardiomyopathy
0.050


16
19.4
1
Disorders of lipid metabolism
0.025


17
10.11
1
Other heart disease
0.025


18
10.8
1
Angina pectoris
0.025


19
10.12
1
Rheumatic heart disease
0.025


20
36.18
1
Dyspnea
0.025






1.000
















TABLE 33







5. CARDIOTHORACIC SURGERY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
10.13
1
Ischemic heart disease
0.175


2
10.13
2
Ischemic heart disease
0.025


3
10.21
1
Acute myocardial infrct, active
0.100


4
10.22
1
Acute myocardial infrct, fup
0.025


5
17.4
1
Diabetes with circulatory
0.050


6
17.4
2
Diabetes with circulatory
0.025


7
9.12
1
Benign neop bronchus & lung
0.050


8
9.19
1
Malig neop bron/lung, active
0.050


9
11.8
1
Generalized arteriosclerosis
0.050


10
12.5
1
Varicose veins lower extrem
0.050


11
9.9
1
Pleurisy
0.050


12
9.15
1
Spon pneumothorax
0.050


13
10.12
1
Rheumatic heart disease
0.050


14
10.10
1
Conduction disorders
0.025


15
10.14
1
Heart value disorders
0.025


16
10.19
1
Aortic aneurysm, initial
0.025


17
10.20
1
Aortic aneurysm, fup
0.025


18
10.16
1
Congestive heart failure
0.025


19
10.17
1
Cardiomyopathy
0.025


20
11.7
1
Disorders of arteries
0.025


21
15.4
1
Cholelithiasis
0.025


22
30.2
1
Cystic breast disease
0.025


23
11.12
1
Occlusion of cerebral arteries
0.025






1.000
















TABLE 34







6. CHIROPRACTIC












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
31.9
1
Low back pain
0.225


2
31.9
2
Low back pain
0.075


3
31.6
1
Nonallopathic lesions
0.150


4
31.6
2
Nonallopathic lesions
0.050


5
31.8
1
Cervical spine pain
0.150


6
31.8
2
Cervical spine pain
0.050


7
31.3
1
Other arthropathy disorders
0.100


8
4.7
1
Nerve root and plexus dsdr
0.050


9
31.13
1
Minor injury of trunk
0.050


10
31.12
1
Scoliosis
0.025


11
33.15
1
Degenerative joint disease
0.025


12
31.4
1
Bursitis
0.025


13
4.1
1
Neuritis upper, lower limbs
0.025






1.000
















TABLE 35







7. DERMATOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight





1
29.17
1
Acne
0.125


2
29.19
1
Benign neoplasm of skin
0.075


3
29.9
1
Dermatitis and eczema
0.075


4
29.23
1
Psoriasis and pityriasis
0.075


5
29.26
1
Other malignancy of skin
0.075


6
29.14
1
Dermatophytoses
0.050


7
2.9
1
Viral warts
0.050


8
29.6
1
Skin keratoses
0.050


9
29.13
1
Rosacea
0.050


10
30.1
1
Inflammatory disease of breast
0.050


11
29.21
1
Dz of hair and hair follicles
0.050


12
29.5
1
Other dsdr skin/subcutan tiss
0.025


13
29.15
1
Sebaceous cyst
0.025


14
29.24
1
Carcinoma in situ of skin
0.025


15
29.8
1
Urticaria
0.025


16
29.22
1
Erythematous condition
0.025


17
21.2
1
Hemangioma
0.025


18
29.10
1
Cellul & abscess, finger/toe
0.025


19
2.8
1
Herpes simplex
0.025


20
29.28
1
Malig melanoma of skin, initial
0.025


21
29.20
1
Dz of nail, excluding infections
0.025


22
11.1
1
Pigmented nevus
0.025






1.000
















TABLE 36







8. EMERGENCY MEDICINE












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level 
Short Description
Weight














1
32.5
1
Open wound hand & fingers
0.075


2
8.5
1
Open wound face & mouth
0.075


3
36.19
1
Chest pain
0.050


4
11.3
1
Contusion of head and neck
0.050


5
11.5
1
Cerebral laceration
0.025


6
11.4
1
Concussion
0.025


7
32.13
1
Fracture of radius and ulna
0.050


8
32.11
1
Fracture of hand bones
0.050


9
32.1
1
Contusion of upper limb
0.050


10
33.2
1
Sprain/strain of foot and ankle
0.050


11
33.1
1
Contusion of lower limb
0.050


12
33.6
1
Open wound of leg
0.050


13
33.22
1
Derangement of knee
0.025


14
13.13
1
Noninfect gastroent & colitis
0.050


15
9.1
1
Upper respiratory infections
0.050


16
9.4
1
Acute bronchitis
0.025


17
36.17
1
Abdominal pain
0.025


18
31.9
1
Low back pain
0.025


19
31.8
1
Cervical spine pain
0.025


20
31.4
1
Bursitis
0.025


21
10.22
1
Acute myocardial infrct, fup
0.025


22
17.1
1
Diabetes w/no complications
0.025


23
4.3
1
Headaches
0.020


24
9.11
1
Asthma
0.020


25
10.2
1
Hypertension
0.020


26
22.11
1
Calculus of kidney and ureter
0.020


27
15.4
1
Cholelithiasis
0.020






1.000
















TABLE 37







9. ENDOCRINOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
25.2
1
Infertility female
0.175


2
23.10
1
Endometriosis
0.125


3
17.1
1
Diabetes w/no complications
0.125


4
17.2
1
Diabetes with ophthalmic
0.050


5
16.3
1
Hypothyroidism
0.075


6
16.4
1
Hyperthyroidism
0.050


7
16.2
1
Goiter
0.050


8
23.7
1
Menstrual disorders
0.050


9
23.6
1
Ovarian dysfunction
0.050


10
23.11
1
Ovarian cyst
0.025


11
19.4
1
Disorders of lipid metabolism
0.050


12
19.4
2
Disorders of lipid metabolism
0.025


13
18.1
1
Other endocrine disorders
0.025


14
19.6
1
Other disorders of metabolism
0.025


15
18.3
1
Disorders of pituitary gland
0.025


16
18.4
1
Benign neop of pituitary gland
0.025


17
18.2
1
Disorders of adrenal gland
0.025


18
10.2
1
Hypertension
0.025






1.000
















TABLE 38







10. GASTROENTEROLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
13.13
1
Noninfect gastroent & colitis
0.125


2
13.9
1
Irritable colon
0.050


3
13.6
1
Gastroesophageal reflux
0.100


4
13.4
1
Other disorders of esophagus
0.050


5
13.17
1
Benign neop colon/rectum
0.075


6
13.5
1
Gastritis and duodenitis
0.075


7
13.20
1
Crohn's disease
0.075


8
13.10
1
Peptic ulcer
0.075


9
13.11
1
Diverticula of intestine
0.050


10
13.21
1
Gastrointestinal hemorrhage
0.050


11
13.12
1
Other diseases of intestine
0.050


12
12.2
1
Hemorrhoids
0.050


13
14.2
1
Diaphragmatic hernia
0.025


14
13.8
1
Dsdr stomach & duodenum
0.025


15
13.7
1
Functional digestive diseases
0.025


16
15.7
1
Hepatitis
0.020


17
15.10
1
Chronic liver disease
0.020


18
15.9
1
Diseases of pancreas
0.020


19
15.4
1
Cholelithiasis
0.020


20
36.17
1
Abdominal pain
0.020






1.000
















TABLE 39







11. GENERAL SURGERY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
14.3
1
External abdominal hernias
0.125


2
15.4
1
Cholelithiasis
0.125


3
30.1
1
Inflammatory disease of breast
0.075


4
30.2
1
Cystic breast disease
0.050


5
30.3
1
Benign neoplasm of breast
0.050


6
12.2
1
Hemorrhoids
0.050


7
29.15
1
Sebaceous cyst
0.050


8
29.18
1
Lipoma
0.050


9
13.14
1
Appendicitis
0.050


10
30.8
1
Malig neop of breast, initial
0.050


11
30.10
1
Malig neop of breast, fup
0.025


12
12.1
1
Anal fissure and fistula
0.050


13
13.17
1
Benign neop colon/rectum
0.025


14
13.13
1
Noninfect gastroent & colitis
0.025


15
13.18
1
Intestinal obstruction
0.025


16
13.12
1
Other diseases of intestine
0.025


17
29.19
1
Benign neoplasm of skin
0.025


18
12.5
1
Varicose veins lower extrem
0.025


19
29.16
1
Pilonidal cyst
0.020


20
29.6
1
Skin keratoses
0.020


21
2.9
1
Viral warts
0.020


22
13.30
1
Malig neop of colon, initial
0.020


23
29.26
1
Other malignancy of skin
0.020






1.000
















TABLE 40







12. NEPHROLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
22.15
1
Renal failure
0.150


2
22.15
2
Renal failure
0.075


3
17.5
1
Diabetes with renal
0.100


4
17.5
2
Diabetes with renal
0.075


5
22.12
1
Glomerulonephritis
0.075


6
10.2
1
Hypertension
0.075


7
22.9
1
Cong anom kidney and ureter
0.075


8
22.10
1
Disorders of kidney and ureter
0.075


9
22.17
1
Kidney transplant, follow-up
0.050


10
19.2
1
Dsdr of fluids and electrolytes
0.050


11
22.11
1
Calculus of kidney and ureter
0.050


12
19.4
1
Disorders of lipid metabolism
0.050


13
19.6
1
Other disorders of metabolism
0.050


14
22.3
1
Urinary tract infections
0.050






1.000
















TABLE 41







13. NEUROLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
4.3
1
Headaches
0.150


2
4.18
1
Seizure disorders
0.125


3
31.9
1
Low back pain
0.075


4
31.8
1
Cervical spine pain
0.050


5
4.5
1
Carpal tunnel syndrome
0.050


6
4.20
1
Other CNS diseases
0.075


7
4.19
1
Multiple sclerosis
0.050


8
4.2
1
Peripheral neuropathy
0.050


9
4.1
1
Neuritis upper, lower limbs
0.050


10
6.8
1
Vertiginous syndromes
0.050


11
4.8
1
Tremor disorders
0.050


12
4.17
1
Parkinson's disease
0.025


13
11.12
1
Occulsion of cerebral
0.025





arteries



14
11.10
1
Transient cerebral ischemia
0.025


15
4.21
1
Muscular dystrophies
0.025


16
4.12
1
Paralytic syndromes
0.025


17
4.4
1
Disorders of cranial nerves
0.025


18
34.20
1
Sleep apnea
0.025


19
4.14
1
Benign neoplasm of CNS
0.025


20
31.3
1
Other arthropathy disorders
0.025






1.000
















TABLE 42







14. NEUROSURGERY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
31.9
1
Low back pain
0.200


2
31.9
2
Low back pain
0.100


3
31.8
1
Cervical spine pain
0.125


4
4.5
1
Carpal tunnel syndrome
0.075


5
4.14
1
Benign neoplasm of CNS
0.075


6
4.24
1
Malig neop brain, initial
0.075


7
18.4
1
Benign neop of pituitary gland
0.050


8
31.21
1
Fracture of vertebra
0.050


9
11.4
1
Concussion
0.050


10
4.20
1
Other CNS diseases
0.050


11
4.16
1
Cong anomalies nerv sys
0.050


12
31.2
1
Congenital anomalies of spine
0.050


13
4.4
1
Disorders of cranial nerves
0.025


14
11.10
1
Transient cerebral ischemia
0.025






1.000
















TABLE 43







15. OBSTETRICS/GYNECOLOGY (OB/GYN)












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
26.4
1
Single newborn, normal
0.225


2
26.5
1
Single newborn, complicated
0.075


3
23.2
1
Cervicitis and vaginitis
0.050


4
23.1
1
Disorders of cervix and vagina
0.050


5
23.9
1
Benign neoplasm of uterus
0.050


6
1.2
1
Gynecological exam
0.050


7
23.10
1
Endometriosis
0.050


8
23.4
1
Other disorders of uterus
0.025


9
23.5
1
Other dsdr female genital org
0.050


10
23.7
1
Menstrual disorders
0.050


11
23.8
1
Menopausal symptoms
0.050


12
23.11
1
Ovarian cyst
0.050


13
23.3
1
Uterovaginal prolapse
0.050


14
25.2
1
Infertility female
0.025


15
26.3
1
Spont and induced abortions
0.025


16
25.1
1
Contraceptive management
0.025


17
30.2
1
Cystic breast disease
0.025


18
30.1
1
Inflammatory disease of breast
0.025


19
22.3
1
Urinary tract infections
0.025


20
2.9
1
Viral warts
0.025






1.000
















TABLE 44







16. ONCOLOGY/HEMATOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
30.8
1
Malig neop of breast, initial
0.075


2
30.9
1
Malig neop of breast, active
0.100


3
30.10
1
Malig neop of breast, fup
0.050


4
24.9
1
Malig neop of prostate, active
0.075


5
24.10
1
Malig neop of prostate, inactive
0.075


6
9.19
1
Malig neop bron/lung, active
0.075


7
9.20
1
Malig neop bron/lung, inactive
0.050


8
13.31
1
Malig neop of colon, active
0.025


9
13.32
1
Malig neop of colon, fup
0.025


10
20.3
1
Diseases of white blood cells
0.075


11
20.6
1
Thrombocytopenia
0.050


12
20.5
1
Aplastic anemias
0.050


13
20.4
1
Anemia disorders
0.050


14
20.2
1
Dz of blood forming organs
0.050


15
21.6
1
Lymphoma, inactive
0.050


16
21.11
1
Leukemia, inactive
0.050


17
21.8
1
Hodgkin's disease, inactive
0.050


18
23.9
1
Benign neoplasm of uterus
0.025






1.000
















TABLE 46







17. OPHTHALMOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
5.17
1
Cataract
0.175


2
5.17
2
Cataract
0.075


3
5.16
1
Glaucoma
0.100


4
5.16
2
Glaucoma
0.050


5
5.10
1
Strabismus
0.075


6
5.20
1
Retinal detach & defects
0.050


7
5.18
1
Other retinal disorders
0.050


8
17.2
1
Diabetes with ophthalmic
0.050


9
5.2
1
Conjunctivitis
0.050


10
5.3
1
Other dsdr of conjunctiva
0.025


11
5.4
1
Infections of the eyelids
0.025


12
5.14
1
Disorders of vitreous body
0.025


13
5.6
1
Dsdr of lacrimal system
0.025


14
5.15
1
Other eye disorders
0.025


15
5.7
1
Keratitis
0.025


16
5.8
1
Other disorders of cornea
0.025


17
5.21
1
Blindness & visual disturb
0.025


18
5.19
1
Macular degeneration
0.025


19
5.9
1
Dsdr iris and ciliary body
0.025


20
5.11
1
External eye injury
0.025


21
5.13
1
Internal eye injury
0.025


22
5.5
1
Disorders of eyelids
0.025






1.000
















TABLE 47







18. ORAL MAXILLARY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
8.12
1
Diseases of jaw
0.125


2
8.10
1
TMJ disorder
0.125


3
8.6
1
Anomalies of jaw size
0.125


4
8.7
1
Other dentofacial anom
0.100


5
8.4
1
Disorders of teeth
0.100


6
8.14
1
Diseases of oral soft tissue
0.075


7
8.16
1
Jaw fracture
0.075


8
8.5
1
Open wound face & mouth
0.075


9
8.13
1
Diseases of salivary glands
0.050


10
8.15
1
Benign neop of oral cavity
0.050


11
8.9
1
Other dz supporting struct
0.050


12
8.2
1
Cong anomalies oral cavity 
0.050






1.000
















TABLE 48







19. ORTHOPEDICS












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
33.22
1
Derangement of knee
0.100


2
33.21
1
Other joint derangement
0.050


3
31.4
1
Bursitis
0.100


4
31.4
2
Bursitis
0.025


5
31.9
1
Low back pain
0.075


6
31.9
2
Low back pain
0.025


7
31.8
1
Cervical spine pain
0.050


8
33.15
1
Degenerative joint disease
0.075


9
32.11
1
Fracture of hand bones
0.050


10
32.13
1
Fracture of radius and ulna
0.050


11
32.14
1
Fracture of humerus
0.050


12
33.16
1
Fracture of foot bones
0.025


13
33.17
1
Fracture of ankle
0.025


14
33.19
1
Fracture of tibia and fibula
0.025


15
4.5
1
Carpal tunnel syndrome
0.050


16
33.9
1
Dislocation of knee
0.050


17
31.12
1
Scoliosis
0.025


18
32.2
1
Sprain/strain of wrist & finger
0.025


19
33.2
1
Sprain/strain of foot and ankle
0.025


20
33.3
1
Sprain/strain of leg
0.020


21
4.1
1
Neuritis upper, lower limbs
0.020


22
31.3
1
Other arthropathy disorders
0.020


23
32.1
1
Contusion of upper limb
0.020


24
33.1
1
Contusion of lower limb
0.020






1.000
















TABLE 49







20. OTOLARYNGOLOGY (ENT)












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
6.5
1
Otitis media
0.150


2
7.2
1
Sinusitis
0.075


3
7.2
2
Sinusitis
0.050


4
7.1
1
Rhinitis
0.075


5
9.5
1
Hypertrophy tonsils & aden
0.075


6
7.4
1
Deviated nasal septum
0.075


7
6.10
1
Hearing loss
0.050


8
6.8
1
Vertiginous syndromes
0.050


9
9.2
1
Dz upper respiratory tract
0.050


10
9.1
1
Upper respiratory infections
0.050


11
7.5
1
Nasal bone fracture
0.025


12
6.1
1
Otitis externa
0.025


13
6.6
1
Dsdr of tympanic membrane
0.025


14
6.7
1
Disorders of middle ear
0.025


15
6.4
1
Other disorders of ear
0.025


16
4.3
1
Headaches
0.025


17
6.2
1
Wax in ear
0.025


18
2.10
1
Infectious mononucleosis
0.025


19
8.13
1
Diseases of salivary glands
0.025


20
8.15
1
Benign neop of oral cavity
0.025


21
8.14
1
Diseases of oral soft tissue
0.025


22
16.2
1
Goiter
0.025






1.000
















TABLE 50







21. PEDIATRICS












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
6.5
1
Otitis media
0.175


2
9.1
1
Upper respiratory infections
0.125


3
7.2
1
Sinusitis
0.100


4
9.4
1
Acute bronchitis
0.075


5
9.11
1
Asthma
0.050


6
7.1
1
Rhinitis
0.050


7
9.7
1
Pneumonia
0.050


8
13.13
1
Noninfect gastroent & colitis
0.050


9
13.3
1
Infect diarrhea/gastroenteritis
0.025


10
29.9
1
Dermatitis and eczema
0.050


11
2.6
1
Other viral diseases
0.025


12
5.2
1
Conjunctivitis
0.025


13
22.3
1
Urinary tract infections
0.025


14
6.1
1
Otitis externa
0.025


15
36.16
1
Non-specific exanthem
0.025


16
34.14
1
Personality & disturb dsdr
0.025


17
2.9
1
Viral warts
0.025


18
29.7
1
Impetigo
0.025


19
29.14
1
Dermatophytoses
0.025


20
36.17
1
Abdominal pain
0.025






1.000
















TABLE 51







22. PLASTIC SURGERY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
30.1
1
Inflammatory disease of breast
0.175


2
30.2
1
Cystic breast disease
0.075


3
29.19
1
Benign neoplasm of skin
0.125


4
8.5
1
Open wound face & mouth
0.100


5
32.5
1
Open wound hand & fingers
0.075


6
6.3
1
Open wound of ear
0.025


7
4.5
1
Carpal tunnel syndrome
0.050


8
29.6
1
Skin keratoses
0.050


9
29.26
1
Other malignancy of skin
0.050


10
21.2
1
Hemangioma
0.050


11
29.15
1
Sebaceous cyst
0.050


12
29.18
1
Lipoma
0.050


13
29.5
1
Other dsdr skin/subcutan tiss
0.050


14
7.4
1
Deviated nasal septum
0.025


15
29.28
1
Malig melanoma of skin, initial
0.025


16
30.10
1
Malig neop of breast, fup
0.025






1.000
















TABLE 52







23. PODIATRY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
33.14
1
Hammer toe
0.125


2
33.14
2
Hammer toe
0.050


3
29.20
1
Dz of nail, excluding infections 
0.100


4
31.4
1
Bursitis
0.100


5
29.10
1
Cellul & abscess, finger/toe
0.075


6
2.9
1
Viral warts
0.075


7
31.3
1
Other arthropathy disorders
0.075


8
33.11
1
Cong deformities lower limb
0.075


9
31.9
1
Low back pain
0.050


10
33.22
1
Derangement of knee
0.050


11
29.14
1
Dermatophytoses
0.050


12
4.1
1
Neuritis upper, lower limbs
0.050


13
33.16
1
Fracture of foot bones
0.050


14
33.15
1
Degenerative joint disease
0.025


15
33.13
1
Benign neop of lower limb
0.025


16
29.25
1
Chronic skin ulcer
0.025






1.000
















TABLE 53







24. PSYCHIATRY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
34.21
1
Major depression
0.175


2
34.21
2
Major depression
0.050


3
34.14
1
Personality & disturb dsdr
0.150


4
34.14
2
Personality & disturb dsdr
0.050


5
34.17
1
Nonpsychotic depression
0.100


6
34.13
1
Anxiety disorders
0.075


7
34.6
1
Other neurotic disorders
0.075


8
34.24
1
Bipolar depression
0.050


9
34.20
1
Sleep apnea
0.025


10
34.5
1
Insomnia
0.025


11
34.18
1
Obsessive-compulsive dsdr
0.025


12
34.29
1
Alcohol dependence
0.025


13
34.30
1
Drug dependence
0.025


14
34.32
1
Schizophrenia
0.025


15
34.31
1
Organic dementias
0.025


16
34.12
1
Phobic disorders
0.025


17
34.23
1
Manic depression
0.025


18
34.15
1
Other nonorganic psychoses
0.025


19
34.25
1
Bulimia
0.025






1.000
















TABLE 54







25. PSYCHOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
34.14
1
Personality & disturb dsdr
0.175


2
34.14
2
Personality & disturb dsdr
0.075


3
34.21
1
Major depression
0.125


4
34.21
2
Major depression
0.050


5
34.17
1
Nonpsychotic depression
0.125


6
34.13
1
Anxiety disorders
0.075


7
34.6 
1
Other neurotic disorders
0.075


8
34.18
1
Obsessive-compulsive dsdr
0.050


9
34.29
1
Alcohol dependence
0.050


10
34.30
1
Drug dependence
0.025


11
34.26
1
Anorexia nervosa
0.025


12
34.25
1
Bulimia
0.025


13
34.12
1
Phobic disorders
0.025


14
34.8 
1
Sexual deviations
0.025


15
34.24
1
Bipolar depression
0.025


16
34.31
1
Organic dementias
0.025


17
34.15
1
Other nonorganic psychoses
0.025






1.000
















TABLE 55







26. PULMONOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
9.14
1
COPD
0.150


2
9.11
1
Asthma
0.150


3
34.20
1
Sleep apnea
0.075


4
9.10
1
Chronic bronchitis
0.075


5
9.4
1
Acute bronchitis
0.050


6
9.7
1
Pneumonia
0.050


7
9.3
1
Lower respiratory diseases
0.050


8
10.2
1
Hypertension
0.050


9
7.2
1
Sinusitis
0.050


10
7.1
1
Rhinitis
0.050


11
9.9
1
Pleurisy
0.050


12
19.7
1
Cystic fibrosis
0.050


13
9.1
1
Upper respiratory infections
0.050


14
36.18
1
Dyspnea
0.050


15
9.19
1
Malig neop bron/lung, active
0.025


16
9.20
1
Malig neop bron/lung, inactive
0.025






1.000
















TABLE 56







27. RHEUMATOLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
31.19
1
Rheumatoid arthritis
0.175


2
31.18
1
Diffuse connective tiss dsdr
0.150


3
33.15
1
Degenerative joint disease
0.125


4
31.9
1
Low back pain
0.075


5
31.8
1
Cervical spine pain
0.050


6
31.3
1
Other arthropathy disorders
0.050


7
31.4
1
Bursitis
0.075


8
29.23
1
Psoriasis and pityriasis
0.050


9
19.5
1
Gout
0.050


10
4.5
1
Carpal tunnel syndrome
0.050


11
31.14
1
Osteoporosis
0.025


12
31.5
1
Other dsdr bone & cartilage
0.025


13
4.7
1
Nerve root and plexus dsdr
0.025


14
11.7
1
Disorders of arteries
0.025


15
19.4
1
Disorders of lipid metabolism
0.025


16
33.22
1
Derangement of knee
0.025






1.000
















TABLE 57







28. SPORTS/PHYSICAL MEDICINE












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
31.4
1
Bursitis
0.175


2
31.4
2
Bursitis
0.025


3
31.9
1
Low back pain
0.100


4
31.8
1
Cervical spine pain
0.050


5
33.22
1
Derangement of knee
0.075


6
33.15
1
Degenerative joint disease
0.075


7
33.21
1
Other joint derangement
0.075


8
31.3
1
Other arthropathy disorders
0.050


9
32.3
1
Sprain/strain of upper arm
0.075


10
32.2
1
Sprain/strain of wrist & finger
0.050


11
33.2
1
Sprain/strain of foot and ankle
0.050


12
33.3
1
Sprain/strain of leg
0.050


13
33.4
1
Sprain/strain of hip and thigh
0.050


14
11.4
1
Concussion
0.050


15
32.13
1
Fracture of radius and ulna
0.025


16
4.5
1
Carpal tunnel syndrome
0.025






1.000
















TABLE 58







29. UROLOGY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
22.11
1
Calculus of kidney and ureter
0.150


2
24.6
1
Prostatic hypertro & prostatitis
0.125


3
23.3
1
Uterovaginal prolapse
0.075


4
22.10
1
Disorders of kidney and ureter
0.075


5
22.3
1
Urinary tract infections
0.075


6
24.4
1
Disorders of penis
0.075


7
24.9
1
Malig neop of prostate, active
0.075


8
24.10
1
Malig neop of prostate, inactive
0.025


9
22.5
1
Urethral stricture
0.050


10
24.3
1
Dsdr of male genital organs
0.050


11
25.4
1
Infertility male
0.050


12
22.4
1
Urethritis
0.025


13
24.2
1
Orchitis and epididymitis
0.025


14
12.4
1
Varicose veins of other sites
0.025


15
22.6
1
Other disorders of bladder
0.025


16
24.1
1
Hyrocele
0.025


17
14.3
1
External abdominal hernias
0.025


18
2.9
1
Viral warts
0.025






1.000
















TABLE 59







30. VASCULAR SURGERY












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
14.3
1
External abdominal hernias
0.100


2
15.4
1
Cholelithiasis
0.100


3
30.2
1
Cystic breast disease
0.075


4
30.1
1
Inflammatory disease of breast
0.075


5
30.3
1
Benign neoplasm of breast
0.050


6
12.5
1
Varicose veins lower extrem
0.075


7
11.8
1
Generalized arteriosclerosis
0.050


8
11.8
2
Generalized arteriosclerosis
0.025


9
13.14
1
Appendicitis
0.050


10
12.3
1
Other peripheral vascular dz
0.050


11
11.12
1
Occulsion of cerebral arteries
0.050


12
11.7
1
Disorders of arteries
0.050


13
29.18
1
Lipoma
0.050


14
29.15
1
Sebaceous cyst
0.050


15
13.17
1
Benign neop colon/rectum
0.025


16
12.6
1
Thrombophlebitis
0.025


17
29.19
1
Benign neoplasm of skin
0.025


18
12.2
1
Hemorrhoids
0.025


19
17.1
1
Diabetes w/no complications
0.025


20
17.4
1
Diabetes with circulatory
0.025






1.000
















TABLE 60







31. CRITICAL CARE (INTENSIVIST)












Medical


Market-


Order
Condition
SOI
Medical Condition
basket


Number
Number
Level
Short Description
Weight














1
9.14
1
COPD
0.150


2
9.11
1
Asthma
0.150


3
34.20
1
Sleep apnea
0.075


4
9.10
1
Chronic bronchitis
0.075


5
9.4
1
Acute bronchitis
0.050


6
9.7
1
Pneumonia
0.050


7
9.3
1
Lower respiratory diseases
0.050


8
10.2
1
Hypertension
0.050


9
7.2
1
Sinusitis
0.050


10
7.1
1
Rhinitis
0.050


11
9.9
1
Pleurisy
0.050


12
19.7
1
Cystic fibrosis
0.050


13
9.1
1
Upper respiratory infections
0.050


14
36.18
1
Dyspnea
0.050


15
9.19
1
Malig neop bron/lung, active
0.025


16
9.20
1
Malig neop bron/lung, inactive
0.025






1.000









Step 14: Perform PROVSPEC Output Process

The PROVSPEC output process involves the completion of Fields 8-10 in Table 25, Fields in the PATAN Output File. Field 8 indicates the physician specialty. Field 9 indicates the physician marketbasket. Field 10 indicates the physician aggregate grouping code number.
Step 15: Store PROSPEC Output File
The PROSPEC Output File is stored with the same fields and in the same order as Table 25, Fields in the PATAN Output File. However, Fields 8-10 have now been completed.
Step 16: Sort PROVSPEC Output File: PROVSORT2
In an embodiment, the PROVSPEC Output File is sorted by three main sort keys. The primary sort key is report group. The secondary sort key is marketbasket identifier. The third sort key is physician identifier.
Step 17: Read in Episode Assignments to PROVAN from PROVSORT2
The episode assignments from PROVSORT2 are read into the physician analysis module (PROVAN). PROVAN produces the physician efficiency scores and several output files at the conclusion of processing.
Step 18: Perform High Outlier Analysis
There are two high-end outlier analysis rules. Both rules are performed at the marketbasket and physician specialty level. Both rules are performed after episodes have been assigned to individual physicians (or physician groups, if the analysis is at the physician group level instead of the individual physician level).
The first high-end outlier rule is as follows. A percent of a physician's most expensive episodes are eliminated by medical condition and severity-of-illness (SOI) level. The user select the percent to be eliminated from the choices available for the parameter SWITCH_HIGHOUTPERCENT in the RUN.INI file (refer to Table 6, Parameters in the RUN.INI File). Episodes are removed from each medical condition in the physician's marketbasket separately, starting with the most expensive episode and continuing in order of expense until the specified percent of episodes is reached.
If a physician has fewer than the number of condition-specific episodes required to satisfy the high outlier rule described above (for example, fewer than 20 episodes when the threshold is set at 5%), then the user may analyze the condition further, as described below under the SWITCH_HIGHOUTDIFF parameter.
In determining the number of condition-specific episodes available for this analysis, all episodes are excluded from the count if they fall below the low outlier threshold set by the parameter SWITCH_LOWOUTDOLLAR, which is described in the low outliers step.
The second high-end outlier rule is as follows. The parameter SWITCH_HIGHOUTDIFF in the RUN.INI file is used to determine whether a single episode should be removed as a high-outlier (refer to Table 6, Parameters in the RUN.INI File). This high-end outlier parameter is applied when one high-end outlier cannot be removed under the SWITCH_HIGHOUTPERCENT parameter. The user sets the value of this parameter to a whole number representing a percentage. If the charges for the most expensive episode are at least the defined percentage greater than the charges for the next most expensive episode, the most expensive episode is removed as a high outlier.
For example, consider a physician whose highest upper respiratory infection episode charge is $500 and whose second highest upper respiratory infection charge is $165 and SWITCH_HIGHOUTDIFF set at 200%. To be eliminated, the physician's most expensive episode must be 200% of the next most expensive episode. Since $500 is more than 200% of $165, the high charge episode will be removed as a high outlier. If the high-charge episode had been $300, it would not be removed, since $300 is only 82% greater than $165.
A maximum of one episode for each medical condition in the physician's marketbasket may be removed by this analysis. Although the user can set SWITCH_HIGHOUTDIFF to any amount, for most effective analysis, the recommended setting is between 150% and 250%.
Step 19: Perform Low Outlier Analysis
There are two low-end outlier analysis rules. Both rules are performed at the marketbasket and physician specialty level. Both rules are performed before episodes have been assigned to individual physicians (or physician groups, if the analysis is at the physician group level instead of the individual physician level).
The first low-end outlier analysis is performed with respect to all episodes by medical condition and severity-of-illness (SOI) level that are assigned to a report group. For this analysis, all physicians are examined within the same medical specialty and within the same Aggregate Report Group.
A percent of the least expensive episodes is eliminated by medical condition and SOI level. The user selects the percent to be eliminated from the choices available for the parameter SWITCH_LOWOUTPERCENT in the RUN.INI file (refer to Table 6, Parameters in the RUN.INI File). Episodes are removed from each medical condition separately, starting with the least expensive episode and continuing until the specified percent of episodes is reached. For example, assume there are 500 episodes of upper respiratory infection (URI), SOI-1 level, assigned to a peer group of general internists, and the user selects 5% low-end outliers. Then, the 25 lowest charge episodes (500×0.25) are removed from analysis.
The second low-end outlier rule is as follows. Any remaining condition-specific episodes are eliminated with less than a defined threshold of charges. The user sets the threshold, which can be any whole number representing dollars in the RUN.INI file using the parameter SWITCH_LOWOUTDOLLAR (refer to Table 6, Parameters in the RUN.INI File). In the above example, assume after applying the 5% low-end outlier analysis, the user found that episodes of URI, SOI-1 level remained that are less than $20. By setting the parameter SWITCH_LOWOUTDOLLAR to $20, any remaining URI, SOI-1 level episodes less than $20 would be removed from analysis.
Step 20: Calculate Physician Condition-Specific Episode Statistics
For condition-specific, SOI-level episodes assigned to a physician, the episode means (averages) and standard deviations are calculated for utilization and charges in the following service and sub-service categories: (1) overall condition-specific, SOI-level episode duration (in days; refer to Table 61); (2) overall condition-specific, SOI-level episode charges (refer to Table 62); (3) service category condition-specific, SOI-level episode utilization (refer to Table 61); (4) service category condition-specific, SOI-level episode charges (refer to Table 62); (5) sub-service category condition-specific, SOI-level episode utilization (refer to Table 63); and (6) sub-service category condition-specific, SOI-level episode charges (refer to Table 64).
In an embodiment, there are 11 service category utilization fields (Fields 1-11 in Tables 61 and 62) that are set up within the service category utilization section of the PATAN and PROVSPEC output displays. The system of the present invention does not break out charges for inpatient facility admissions so Field 9 is not used and contains a zero as a placeholder (refer to Table 62).
In an embodiment, there are 21 category utilization fields (Fields 1-21 in Tables 63 and 64) that are set up within the service category utilization section of the PATAN and PROVSPEC output displays. The system of the present invention does not break out charges for inpatient facility admissions so Field 14 is not used and contains a zero as a placeholder (refer to Table 64).
The zero field in the service and sub-service categories for utilization data (Tables 61 and 63) corresponds to the average episode duration. The zero field in the service and sub-service categories for charges (Tables 62 and 64) corresponds to the average charges per episode.
It is to be understood that other statistics can be calculated for condition-specific, SOI-level episodes assigned to a physician. In an embodiment, different service and sub-service categories may be calculated for episode utilization and charges. In an embodiment, episodes can be assigned to physician groups (and not only individual physicians), and the physician group's episode means and standard deviations may be calculated for utilization and charges.







TABLE 61







Service Category Fields Used for Utilization Data










Utilization Field
Service Category













0
Episode Duration (Days)



1
Professional Visits



2
Laboratory/Pathology



3
Diagnostic Tests



4
Medical/Surgical



5
Prescription Drugs



6
Inpatient Professional



7
Outpatient Facility



8
Inpatient Facility Days



9
Inpatient Facility Admits



10
Alternate Facility



11
Other Medical Care
















TABLE 62







Service Category Fields Used for Charge Data










Charge Field
Service Category













0
Overall Charges



1
Professional Visits



2
Lab/Path



3
Diagnostic Tests



4
Medical/Surgical



5
Prescriptions Drugs



6
Inpatient Professional



7
Outpatient Facility



8
Inpatient Facility Days



9
[Not used]



10
Alternate Facility



11
Other Medical Care
















TABLE 63







Sub-Service Category Fields Used for Utilization Data










Utilization Field
Sub-service category













0
Episode Duration (Days)



1
Professional Visits



2
Lab



3
Pathology



4
Imaging



5
Invasive Testing



6
Functional Testing



7
Medical Procedures



8
Surgical Procedures



9
Prescription Drugs



10
Inpatient Professional



11
Emergency Room Facility



12
Other Outpatient Facility



13
Inpatient Facility Days



14
Inpatient Facility Admits



15
Alternate Facility



16
Physical Therapy



17
Dialysis



18
Chemotherapy/Radiology



19
Anesthesia



20
Durable Medical Equipment



21
Other Medical Care
















TABLE 64







Sub-Service Category Fields Used for Charge Data










Charge Field
Sub-service category













0
Overall charges



1
Professional Visits



2
Lab



3
Pathology



4
Imaging



5
Invasive Testing



6
Functional Testing



7
Medical Procedures



8
Surgical Procedures



9
Prescription Drugs



10
Inpatient Professional



11
Emergency Room Facility



12
Other Outpatient Facility



13
Inpatient Facility Days



14
[Not used]



15
Alternate Facility



16
Physical Therapy



17
Dialysis



18
Chemotherapy/Radiology



19
Anesthesia



20
Durable Medical Equipment



21
Other Medical Care









Step 21: Determine Minimum Episode Number

A physician should have a minimum number of non-outlier episodes for medical conditions within a marketbasket of medical conditions. The system of the present invention recognizes that a physician should have a minimum number of non-outlier episodes in each of three specialty-specific medical conditions to receive an efficiency measurement score. This episode is called the N×3 rule because it requires N episodes in each of three medical conditions.
The user specifies the number of episodes (N) using the parameter SWITCH_MINEPCOUNT in the RUN.INI file (refer to Table 6, Parameters in the RUN.INI File). This parameter sets the requirement for the number of episodes a physician should treat to be included in the analysis, thus implementing part of the N×3 rule. For example, if the N value is changed from two to four, the rule would require four non-outlier episodes in each of three conditions, and the rule would become, in effect, a “4×3” rule.
In the N×3 rule, the N equals the number of episodes of a specific medical condition a physician should treat during the study period. The user can change this number. The three equals the minimum number of medical conditions in which the physician should treat episodes. The medical conditions need to be in the physician's marketbasket.
For example, if N in the N×3 rule is set to two, then a physician needs to have two non-outlier episodes in three medical conditions (2×3) in a respective specialty-specific marketbasket. Therefore, regardless of specialty type, each physician needs to have a minimum six non-outlier episodes of care to receive an efficiency score.
Continuing our example, with N set to two episodes, and assuming a physician meets the minimum episode number criteria in three medical conditions (e.g., 2×3), then the following method is employed before formulating a weighted average treatment pattern. For a physician with less than two episodes for any medical condition in a marketbasket, the physician-specific results are replaced with that of the peer group results for the medical condition of interest. For the scenario just defined, the peer group's condition-specific results will be used when formulating the physician's weighted average treatment pattern results for at least one medical condition in the marketbasket.
Therefore, an additional rule applies when a physician has fewer than the required number of condition-specific episodes (as set by the value of N). Substitute the specialty-specific, peer group results for a medical condition when a physician has less than the required number of condition-specific episodes.
It is to be understood that other, similar methods and rules may be employed to ensure a physician has a minimum number of assigned, non-outlier episodes for medical conditions.
Step 22: Remove Physicians Failing Minimum Episode Number
This rule involves removing those physicians from further analysis that do not meet the minimum number of assigned episodes rule. For example, using the N×3 rule and assuming N is set to 2 episodes, then physicians without a minimum of 6 non-outlier episodes meeting the 2×3 rule are removed from further analysis.
Step 23: Calculate Peer Group Condition-Specific Episode Statistics
Using only those episodes of care assigned to physicians meeting the minimum non-outlier episode rule (i.e., physicians that passed the minimum episode rule and, therefore, are included in further analysis), the peer group medical condition, SOI-level episode means (averages) and standard deviations are calculated for utilization and charges. Each episode of care is counted once and only once in formulating the peer group condition-specific, SOI-level means and standard deviations.
Similar to the physician-level episode statistics, the peer group condition-specific, SOI-level statistics are calculated for utilization and charges using the same service and sub-service categories as defined in Tables 61-64.
For condition-specific, SOI-level episodes assigned to the peer group, the episode means (averages) and standard deviations are calculated for utilization and charges in the following service and sub-service categories: (1) overall condition-specific, SOI-level episode duration (in days; refer to Table 61); (2) overall condition-specific, SOI-level episode charges (refer to Table 62); (3) service category condition-specific, SOI-level episode utilization (refer to Table 61); (4) service category condition-specific, SOI-level episode charges (refer to Table 62); (5) sub-service category condition-specific, SOI-level episode utilization (refer to Table 63); and (6) sub-service category condition-specific, SOI-level episode charges (refer to Table 64). It is to be understood that other statistics can be calculated for the peer group condition-specific, SOI-level episodes, and that different service and sub-service categories may be calculated for episode utilization and charges.
Step 24: Calculate Peer Group Weighted Episode Statistics Across Medical Conditions
Each medical condition in a specialty-specific marketbasket is assigned a weight factor that reflects the importance or relevance of that medical condition to the marketbasket. The weight factors are used to compute the overall marketbasket weighted mean and standard deviation across all medical conditions in the marketbasket. The sum of the weight factors in a marketbasket equals 1.00 (refer to the specialty-specific marketbaskets, Tables 29-60). This step is referred to as the indirect standardization rule.
The system of the present invention uses an indirect standardization technique for weighting together the episodes within the core group of medical conditions. The weighted mean and standard deviation are computed as the sum of the condition-specific utilization or charge amounts per episode multiplied by the weight value assigned to that condition in the marketbasket. Both the condition-specific means and variances (i.e., the square of the standard deviation) are multiplied by the weight values. The sum of all the condition-specific products is the weighted mean and standard deviation for the peer group in the marketbasket.
An example of the indirect standardization rule is presented for general internists. The general internist marketbasket consists of episodes in 30 medical conditions, SOI-1 class only (refer to Table 30, general internist marketbasket). Upper respiratory infections (URIs), sinusitis, acute bronchitis, and low back pain are medical conditions within the general internist marketbasket.
For simplicity, assume only four medical conditions comprise the general internist marketbasket: upper respiratory infections (URIs), sinusitis, acute bronchitis, and low back pain. A total of four medical conditions in the marketbasket classes will receive a weight factor. Assume the standardized weights are distributed as follows: URI=0.30; sinusitis=0.30; and acute bronchitis=0.20; and back pain=0.20. These weight factors sum to 1.00. The peer group treats a total of 4,500 non-outlier episodes: 1,350 episodes of URI; 1,350 episodes of sinusitis; 900 episodes of acute bronchitis; and 900 episodes of low back pain.
The weighted average is now formulated for the peer group's overall episode charges. The peer group's condition-specific means and standard deviations (SD) are as follows: URI=$150 per episode (SD=$50); sinusitis=$200 per episode (SD=$70); acute bronchitis=$175 per episode (SD=$55); and back pain=$300 per episode (SD=$90).
Using these assumptions, the marketbasket weighted mean and standard deviation (SD) are calculated for the general internist peer group. The weighted overall charge mean is $200 ((0.30×$150)+(0.30×$200)+(0.20×$175)+(0.20×$300)). The calculation does not use the peer group's actual episode composition to calculate the weighted average. Instead, the predetermined standard marketbasket weights are used.
The variances are weighted together, which is the SD squared. After adding the variances together, the square root is performed to formulate the weighted average SD, which is $67 ((0.30×$2,500)+(0.30×$4,900)+(0.20×$3,025)+(0.20×$8,100)=$4,445; and the square root of $4,445=$67).
Therefore, the general internist peer group's weighted overall charge mean and SD are as follows: mean=$200 per episode; SD=$67 per episode; number of episodes N=4,500.
In a similar manner, the weighted statistics are calculated for the peer group's episode duration (in days), service category utilization and charges (refer to Tables 61 and 62), and sub-service category utilization and charges (refer to Tables 63 and 64).
Step 25: Calculate Physician Weighted Episode Statistics Across Medical Conditions
For the individual physician (or alternatively, physician group), the same indirect standardization weighting calculations are performed using the physician's condition-specific utilization and charges per episode and the same specialty-specific marketbasket weights. The sum of all the condition-specific products is the weighted mean and standard deviation result for the physician.
Assume there continue to be only four medical conditions that comprise the general internist marketbasket: upper respiratory infections (URIs), sinusitis, acute bronchitis, and low back pain. A total of four medical conditions in the marketbasket classes will receive a weight factor. Also, assume the same standardized weights as for the peer group: URI=0.30; sinusitis=0.30; and acute bronchitis=0.20; and back pain=0.20. These weight factors sum to 1.00.
Without detailing the calculations here, assume the physician's weighted overall charge mean and SD are $254 per episode and $56 per episode, respectively. The number of physician episodes (N) is 53.
In a similar manner, the weighted statistics are calculated for the physician's episode duration, service category utilization and charges, and sub-service category utilization and charges.
Step 26: Determine Physician's Efficiency Scores
The physician's marketbasket weighted statistics are now compared to that of the specialty-specific peer group. This comparison is more meaningful (than just comparing treatment patterns for one medical condition) because the weighted statistics present a more realistic efficiency evaluation of the physician's overall work effort.
The overall efficiency score for the physician (or physician group) is calculated by dividing the physician's weighted overall mean charges by the peer group's weighted overall mean charges. Using the general internist example, the overall efficiency score equals 1.27 (or $254 per episode/$200 per episode. The 1.27 ratio may be interpreted as follows. The efficiency of the physician's weighted average treatment pattern is 27% more resource intensive than the peer group's weighted average treatment pattern. The general internist in the example had $54 per episode in excess charges ($254 per episode versus the peer group of $200 per episode).
If the efficiency score is more than 1.00, then the physician's treatment pattern efficiency is more resource intensive than the peer group's treatment pattern. On the other hand, if the efficiency score is less than 1.00, then the physician's treatment pattern efficiency is less resource intensive than the peer group's treatment pattern.
An efficiency score may be calculated for each medical condition in a specialty-specific marketbasket. The medical condition efficiency score for the physician is calculated by dividing the physician's condition-specific mean charges by the peer group's condition-specific mean charges.
An efficiency score may be calculated for each service category in an episode of care. The overall service efficiency score for the physician is calculated by dividing the physician's weighted service category mean utilization or charges by the peer group's weighted service category mean utilization or charges, respectively.
The medical condition service efficiency score for a physician is calculated by dividing the physician's condition-specific service mean utilization or charges by the peer group's condition-specific mean utilization or charges, respectively.
In addition, an efficiency score may be calculated for each sub-service category in an episode of care. The overall sub-service efficiency score for the physician is calculated by dividing the physician's weighted sub-service category mean utilization or charges by the peer group's weighted sub-service category mean utilization or charges, respectively. The medical condition sub-service efficiency score for a physician is calculated by dividing the physician's condition-specific sub-service category mean utilization or charges by the peer group's condition-specific sub-service mean utilization or charges, respectively.
An efficiency score may be calculated for the duration of an episode of care. The overall duration efficiency score for the physician is calculated by dividing the physician's weighted overall mean duration by the peer group's weighted overall mean duration. A condition-specific duration efficiency score may be calculated by dividing the physician's condition-specific mean duration by the peer group's condition-specific mean duration.
Step 27: Perform Test to Determine Whether Physician's Efficiency Scores are Statistically Different from Peer Group
The student t-test is used to determine whether the physician's (or physician group's) efficiency score is statistically significantly different from the peer group. In the calculation, the physician's actual number of episodes is used as well as the peer group's actual number of episodes. For the general internist example, the physician's number of episodes is N equals 53, and the peer group's number of episodes is N equals 4,500.
At a determined level of confidence, the physician's marketbasket treatment pattern is determined to be statistically significantly different from the peer group average. The user chooses the desired level of confidence (either 0.10 level or 0.25 level) using the parameter SWITCH_CONFLEVEL in the RUN.INI file, which sets the p-value for statistical confidence (refer to Table 6, Parameters in the RUN.INI File). However, different p-values may be selected other than the 0.10 and 0.25 levels.
Step 28: Assign Physicians to an Interval
After receiving an efficiency score, physicians of a specific specialty type are separated into quartiles (1, 2, 3, and 4). Quartile 1 physicians use fewer medical resources to treat a marketbasket of condition-specific episodes as compared to their physician peer group. Quartile 2 and Quartile 3 physicians are the next quartiles of physicians in terms of the amount of resources used to treat the same marketbasket of condition-specific episodes. Quartile 4 physicians use greater medical resources to treat the same marketbasket of condition-specific episodes as compared to the physician peer group.
Physicians of a specific specialty type also are separated into deciles (1, 2, 3, 4, 5, 6, 7, 8, 9, and 10). Decile 1 physicians use fewer medical resources to treat a marketbasket of condition-specific episodes as compared to their physician peer group. Decile 2 through 9 physicians are the next deciles of physicians in terms of the amount of resources used to treat the same marketbasket of condition-specific episodes. Decile 10 physicians use the greatest amount of medical resources to treat the same marketbasket of condition-specific episodes as compared to the physician peer group.
The quartile and decile assignments are fields displayed on the PROVAN Output File. The embodiment recognizes that other physician interval assignments may be used other than quartile and decile.
Step 29: Store PROVAN Output Files
The system of the present invention stores two output files at the conclusion of processing. One file is entitled the Weighted Average Results File (default file name in RUN.INI File is Score.tab). The other file is entitled the Medical Condition Results File (default file name in RUN.INI File is Detail.tab).
These files are output from the PROVAN module. Table 65 provides an overview of the two output files. The table shows that the Weighted Average Results File produces physician-level (or physician group-level) results for the 11 service categories and 21 sub-service categories. However, the Medical Condition Results File produces physician-level (or physician group-level) results only for the 11 service categories. The embodiment recognizes that both PROVAN Output Files may produce results for the 21 sub-service categories as well as other formulated service and sub-service categories.







TABLE 65







PROVAN Output Files












Default 

11 Service
21 Sub-



File

Category 
service


Descriptive
Name in

Level
Category 


File Name
RUN.INI
Description of Content
Output
Output





Weighted
Score.tab
Physician-level 
YES
YES


Average

weighted average 




Results File

marketbasket results on






utilization and charges






per episode of care 






within a marketbasket






of interest




Medical
Detail.tab
Physician-level 
YES
NO


Condition

medical condition level 




Results File

results on utilization and






charges per episode of






care within a






marketbasket of interest









The Weighted Average Results File presents the weighted average specialty-specific marketbasket results for a physician versus the comparator peer group. The file contains one output row per physician. Fields in each row show a weighted average result for each of the 11 service categories and each of the 21 sub-service categories. Fields are delimited by tab characters and, therefore, field width is variable. The fields in the Weighted Average Results File are divided into sections as presented in Table 66.








TABLE 66







Sections in the Weighted Average Results File










Section
Title






A
Non-Repeated Physician Fields



B
Repeated Physician Fields for Each Service Category



C
Non-Repeated Peer Group Fields



D
Repeated Peer Group Fields for Each Service Category



E
Repeated Physician Fields for Each Sub-Service Category



F
Repeated Peer Group Fields for Each Sub-Service Category









Section A contains non-repeated physician fields (16 fields). The fields described in Section A contain physician data. Each field appears once in the Weighted Average Results File (refer to Table 67).
Section B contains repeated physician fields for each service category (6 fields repeated 11 times). Section B lists six fields that contain physician output data at the service category level. For convenience, the six fields, taken together, are called a group. In the Weighted Average Results File, the group of six fields listed in Section B repeats 11 times, once for each of the service categories, in the order listed in Tables 61 and 62.
Section C contains non-repeated peer group fields (2 fields). The fields described in Section C contain peer group data. Each field appears once in the Weighted Average Results File, in the order they are listed in Table 67.
Section D contains repeated peer group fields for each service category (2 fields repeated 11 times). Section D lists two fields that contain peer group output data at the service category level. The two fields, taken together, are a group. In the Weighted Average Results File (Table 67), the group of two fields listed in Section D repeats 11 times, once for each of the service categories in the order listed in Tables 61 and 62.
Section E contains repeated physician fields for each sub-service category (4 fields repeated 21 times). Section E lists four fields that contain physician output data at the sub-service category level. The four fields, taken together, are a group. In the Weighted Average Results File, the group of four fields listed in Section E repeats 21 times, once for each of the sub-service categories in the order listed in Tables 63 and 64.
Section F contains repeated peer group fields for each sub-service category (2 fields repeated 21 times). Section F lists two fields that contain peer group output data at the sub-service category level. The two fields, taken together, are a group. In the Weighted Average Results file, the group of two fields listed in Section F repeats 21 times, once for each of the sub-service categories in the order listed in Tables 63 and 64.
Table 67 presents the fields included in the Weighted Average Results File, listed in the order in which they appear. In the repeated field sections, the asterisk (*) indicates a sequential number of the service category or sub-service category number as presented in Tables 61-64.







TABLE 67







Fields in the Weighted Average Results File









Field




Number
Field Descriptive Name
Notes










Section A - Non-Repeated Physician Fields (16 fields)









1
Physician ID
The unique physician ID for each profiled physician,



Field name: ProvID
as defined in the input files.


2
Physician Specialty Number
The specialty number, as defined in the data



Field name: ProvSpec
mapping section.


3
Physician marketbasket number
The marketbasket number, as defined in the data



Field name: MktBasket
mapping section.


4
Aggregate group number
The aggregate group number, as defined in the



Field name: AggGroup
grouping structure table.


5
Pass NxN rule
1 = The physician passed the Nx3 rule



Field name: PassNxN
0 = The physician failed the Nx3 rule


6
Quartile number
The quartile number of the physician based on



Field name: Quartile
overall charge efficiency.




1 = lowest relative resource intensity




4 = highest relative resource intensity


7
Decile number
The decile number of the physician based on overall



Field name: Decile
charge efficiency.




1 = lowest relative resource intensity




10 = highest relative resource intensity


8
Episode volume category
Indicates relative volume of total episodes for the



Field name: epcountbin
physician. 1 = 25 or fewer episodes, 2 = 26 to 50




episodes, 3 = greater than 50 episodes.


9
Physician episode count
The total number of episodes for the physician, after



Field name: provider_episode_count
outliers are removed.


10
Peer group episode count
The total number of episodes forming the peer



Field name: peergroup_episode_count
group, after outliers are removed.


11
Physician weighted average episode
Weighted average episode duration in days.



duration




Field name: Prov_MBCCatUtl0



12
Physician relative efficiency score based
Score as compared to peer group based on relative



on episode duration
weighted average episode duration in days.



Field name: Prov_ScoreCatUtl0



13
Physician episode duration t-test
1 = result of physician t-test for average weighted



statistical significance indicator
episode duration is statistically significant at the



Field name: Prov_TScoreCatUtl_sigdiff0
selected confidence level.




0 = not statistically significant at selected confidence




level.


14
Physician overall weighted average
Overall weighted average episode charges in dollars,



episode charges
across all service categories.



Field name: Prov_MBCCatChg0



15
Physician overall relative efficiency score
Score as compared to peer group based on overall



based on episode charges
relative weighted average episode charges in



Field name: Prov_ScoreCatChg0
dollars.


16
Physician episode charges t-test
1 = result of physician t-test for average weighted



statistical significance indicator
episode charges is statistically significant at the



Field name:
selected confidence level.



Prov_TScoreCatChg_sigdiff0
0 = not statistically significant at selected confidence




level.







Section B - Repeated Physician Fields for Each Service Category (6 fields repeated 11 times)









1
Physician weighted average per episode
Weighted average per episode utilization for the



utilization for the service category
service category (service category 8 contains



Field name: Prov_MBCCatUtl*
inpatient days per episode, service category 9




contains inpatient admits per episode)


2
Physician relative efficiency score based
Score as compared to peer group based on relative



on per episode utilization for the service
weighted average per episode utilization for the



category
service category



Field name: Prov_ScoreCatUtl*



3
Physician per-episode utilization t-test
1 = result of physician t-test for average weighted



statistical significance indicator
utilization for the service category is statistically



Field name: Prov_TScoreCatUtl_sigdiff*
significant at the selected confidence level.




0 = not statistically significant at selected confidence




level.


4
Physician weighted average episode
Weighted average episode charges in dollars, for the



charges for the service category
service category



Field name: Prov_MBCCatChg*



5
Physician relative efficiency score based
Score as compared to peer group based on relative



on episode charges for the service
weighted average episode charges in dollars, for the



category
service category



Field name: Prov_ScoreCatChg*



6
Physician episode charges t-test
1 = result of physician t-test for average weighted



statistical significance indicator for the
episode charges for the service category is



service category
statistically significant at the selected confidence



Field name:
level.



Prov_TScoreCatChg_sigdiff*
0 = not statistically significant at selected confidence




level.







Section C - Non-Repeated Peer Group Fields (2 fields)









1
Peer Group overall weighted average
Peer Group overall weighted average episode



episode duration
duration in days



Field name: Peer_MBCCatUtl0



2
Peer Group overall weighted average
Peer Group overall weighted average episode



episode charges in dollars
charges in dollars, across all service categories



Field name: Peer_MBCCatChg0








(Section D) Repeated Peer Group Fields for Each Service Category (2 fields repeated 11 times)









1
Peer Group weighted average episode
Peer Group weighted average episode utilization for



utilization for the service category
the service category



Field name: Peer_MBCCatUtl*



2
Peer Group weighted average episode
Peer Group weighted average episode charges in



charges in dollars for the service
dollars for the service category



category




Field name: Peer_MBCCatChg*








Section E - Repeated Physician Fields for Each Sub-Service Category (4 fields repeated 21 times)









1
Physician weighted average per episode
Weighted average per episode utilization for the sub-



utilization for the sub-service category
service category (sub-service category 13 contains



Field name: Prov_MBCSubUtl*
inpatient days per episode, sub-service category 14




contains inpatient admits per episode)


2
Physician per-episode utilization t-test
1 = result of physician t-test for average weighted



statistical significance indicator
utilization for the sub-service category is statistically



Field name: Prov_TScoreSubUtl_sigdiff*
significant at the selected confidence level.




0 = not statistically significant at selected confidence




level.


3
Physician weighted average episode
Weighted average episode charges in dollars, for the



charges for the sub-service category
sub-service category



Field name: Prov_MBCSubChg*



4
Physician episode charges t-test
1 = result of physician t-test for average weighted



statistical significance indicator for the
episode charges for the sub-service category is



sub-service category
statistically significant at the selected confidence



Field name:
level.



Prov_TScoreSubChg_sigdiff*
0 = not statistically significant at selected confidence




level.







Section F - Repeated Peer Group Fields for Each Sub-Service Category (2 fields repeated 21 times)









1
Peer Group weighted average episode
Peer Group weighted average episode utilization for



utilization for the sub-category
the sub-service category



Field name: Peer_MBCSubUtl*



2
Peer Group weighted average episode
Peer Group weighted average episode charges in



charges in dollars for the sub-service
dollars for the sub-service category



category




Field name: Peer_MBCSubChg*









The Medical Condition Results File presents the specialty-specific medical condition results for a physician versus the comparator peer group. Table 65 shows that medical condition average utilization and charge results are available for each of the 11 service categories tracked in the system of the present invention (e.g., lab/path services).
The Medical Condition Results File contains rows of data on medical conditions for each physician. There are up to 36 rows per physician (up to 35 medical conditions, plus the weighted average row). These rows of data are identified by the Marketbasket Condition Number field (Field 11 in Table 68).
The overall weighted average information has been carried over for each physician from the Weighted Average Results File and reported in the Medical Conditions Results file as well. For each physician, the weighted average output row is identified in the Marketbasket Condition Number field with the number “0”. The rows of medical condition information for each physician begin with row “1” and continue until there is a row for the weighted average of each medical condition in the physician's specialty marketbasket.
Table 68 presents the fields included in the Medical Condition Results File, listed in the order in which they appear. In the repeated field sections, the asterisk (*) indicates a sequential number of the service category number as presented in Tables 61 and 62.







TABLE 68







Fields in the Medical Condition Results File









Field




Number
Field Descriptive Name
Notes










Section A - Fundamental Information (19 fields)









1
Physician ID
The unique physician ID for each profiled physician, as defined



Field name: ProvID
in the input files.


2
Physician Specialty Number
The specialty number, as defined in the data mapping section.



Field name: ProvSpec



3
Physician marketbasket
The marketbasket number, as defined in the data mapping



number
section.



Field name: MktBasket



4
Aggregate group number
The aggregate group number, as defined in the grouping



Field name: AggGroup
structure table.


5
Pass NxN rule
1 = The physician passed the Nx3 rule



Field name: PassNxN
0 = The physician failed the Nx3 rule


6
Quartile number
The quartile number of the physician based on overall charge



Field name: Quartile
efficiency.




1 = lowest relative resource intensity




4 = highest relative resource intensity


7
Decile number
The decile number of the physician based on overall charge



Field name: Decile
efficiency.




1 = lowest relative resource intensity




10 = highest relative resource intensity


8
Episode volume category
Indicates relative volume of total episodes for the physician.



Field name: epcountbin
1 = 25 or fewer episodes




2 = 26 to 50 episodes




3 = greater than 50 episodes


9
Physician episode count
The total number of episodes for the physician, after outliers



Field name:
are removed.



provider_episode_count



10
Peer group episode count
The total number of episodes forming the peer group, after



Field name:
outliers are removed.



peergroup_episode_count



11
Marketbasket condition
The sequential number of the condition within the



number
marketbasket, as defined in the market conditions table which



Field name: MBCondition
is specified by the RUN.INI parameter FILE_MBCONDITIONS.


12
Physician average episode
Average episode duration in days. For the “0” row, this field



duration
contains the weighted average episode duration in days. For all



Field name:
other rows, this field contains the average medical condition



Prov_MBCatUtl0
duration in days.


13
Physician relative efficiency 
Score as compared to peer group based on relative average



score based on episode
episode duration in days.



duration




Field name:




Prov_ScoreCatUtl0



14
Physician t-score for average 
t-test score result as compared to peer group on relative



episode duration
average episode duration in days.



Field name:




Prov_TScoreCatUtl0



15
Physician episode duration t- 
1 = result of physician t-test for average episode duration is



test statistical significance 
statistically significant at the selected confidence level.



indicator
0 = not statistically significant at selected confidence level.



Field name:




Prov_TScoreCatUtl_sigdiff0



16
Physician average episode
Average episode charges in dollars, across all service



charges
categories. For the “0” row, this field contains the weighted



Field name:
overall average episode charges. For all other rows, this field



Prov_MBCCatChg0
contains the overall average medical condition charges per




episode.


17
Physician relative efficiency
Score as compared to peer group based on relative average



score based on episode
episode charges in dollars.



charges




Field name:




Prov_ScoreCatChg0



18
Physician t-score for average
t-test score result as compared to peer group on relative



episode charges
average episode charges in dollars.



Field name:




Prov_TScoreCatChg0



19
Physician episode charges t-
1 = result of physician t-test for average episode charges is



test statistical significance
statistically significant at the selected confidence level.



indicator
0 = not statistically significant at selected confidence level.



Field name:




Prov_TScoreCatChg_sigdiff0








Section B - Repeated Physician Fields for Each Service Category (8 fields repeated 11 times)









1
Physician average per
Average per episode utilization for the service category



episode utilization for the
(service category 8 contains inpatient days per episode,



service category
service category 9 contains inpatient admits per episode). For



Field name:
the “0” row, this field contains the weighted average utilization



Prov_MBCCatUtl*
for the service category. For all other rows, this field contains




the average medical condition utilization for the service




category.


2
Physician relative efficiency
Score as compared to peer group based on relative average



score based on per episode
per episode utilization for the service category



utilization for the service




category




Field name:




Prov_ScoreCatUtl*



3
Physician t-score for the
t-test score result as compared to peer group on relative



service category utilization
average per episode utilization for the service category



Field name:




Prov_TScoreCatUtl*



4
Physician per-episode
1 = result of physician t-test for average utilization for the



utilization t-test statistical
service category is statistically significant at the selected



significance indicator
confidence level.



Field name:
0 = not statistically significant at selected confidence level.



Prov_TScoreCatUtl_sigdiff*



5
Physician average episode
Average episode charges in dollars, for the service category.



charges for the service
For the “0” row, this field contains the weighted average



category
charges for the service category. For all other rows, this field



Field name:
contains the average medical condition charges for the service



Prov_MBCCatChg*
category.


6
Physician relative efficiency
Score as compared to peer group based on relative average



score based on episode
episode charges in dollars, for the service category



charges for the service




category




Field name:




Prov_ScoreCatChg*



7
Physician t-score for average
t-test score result as compared to peer group on relative



episode charges for the
average episode charges in dollars for the service category



service category




Field name:




Prov_TScoreCatChg*



8
Physician episode charges t-
1 = result of physician t-test for average episode charges for



test statistical significance
the service category is statistically significant at the selected



indicator for the service
confidence level.



category
0 = not statistically significant at selected confidence level.



Field name:




Prov_TScoreCatChg_sigdiff*








Section C - Non-Repeated Peer Group Fields (2 fields)









1
Peer Group average episode
Peer Group average episode duration in days. For the “0” row,



duration
this field contains the weighted average episode duration in



Field name:
days. For all other rows, this field contains the average medical



Peer_MBCCatUtl0
condition duration in days.


2
Peer Group average episode
Peer Group average episode charges in dollars, across all



charges in dollars
service categories. For the “0” row, this field contains the



Field name:
weighted overall average episode charges. For all other rows,



Peer_MBCCatChg0
this field contains the overall average medical condition




charges per episode.







Section D - Repeated Peer Group Fields for Each Service Category (2 fields repeated 11 times)









1
Peer Group average episode
Peer Group average episode utilization for the service category



utilization for the service
(service category 8 contains inpatient days per episode,



category
service category 9 contains inpatient admits per episode). For



Field name:
the “0” row, this field contains the weighted average utilization



Peer_MBCCatUtl*
for the service category. For all other rows, this field contains




the average medical condition utilization for the service




category..


2
Peer Group average episode
Peer Group average episode charges in dollars for the service



charges in dollars for the
category. For the “0” row, this field contains the weighted



service category
average charges for the service category. For all other rows,



Field name:
this field contains the average medical condition charges for



Peer_MBCCatChg*
the service category.









Step 30: Produce Reports

The open structure of the PROVAN Output Files allows the user to produce many types of physician-level (or physician group-level) reports.
The system of the present invention also produces reports using the PROVAN Output Files that provide the user with physician-level (or physician group-level) information to help understand what underlies the physician's overall efficiency score. These reports are called the Practitioner Efficiency Measurement Reports.
Practitioner Efficiency Measurement Reports provide statistical analysis at the overall weighted average level that identifies physician charges and utilization that are significantly different from peer group results. The Reports may also provide statistical analysis at the medical condition level.
For each of the 31 specialty types with a marketbasket of medical conditions, there is a corresponding Practitioner Efficiency Measurement Report. The Practitioner Efficiency Measurement Reports present the details behind a practitioner's efficiency measurement score.
The Practitioner Efficiency Measurement Report consists of two reports for each of the 31 practitioner specialty types. Report 1 is entitled Average Charges per Episode of Care. This report presents a physician's overall weighted average charges per episode as well as the overall weighted average charge per episode for the peer group. These two charge values form the foundation for the practitioner's efficiency score. Report 2 is entitled Average Utilization per Episode of Care. This report presents a physician's corresponding weighted average utilization patterns per episode as well as the peer group's weighted average utilization patterns per episode.
FIG. 8 presents a detailed description of Report 1, the Average Charges per Episode of Care. Results from a general internist are compared to a peer group of general internists.
The headings at the top of the FIG. 8 report are as follows. The practitioner name is the name of the physician receiving an efficiency score. Specialty type refers to the specialty of the physician receiving an efficiency score. The attached general internist's specialty type is shown as General Internist. The practitioner ID is the unique identification number that is assigned to the physician receiving an efficiency score. The system of the present invention organizes the information output and reports based on aggregate group name. Aggregate group name is the name of the aggregate group relevant to the current report. For example, if a comparison is made on the basis of geographic regions, the aggregate group name might represent a specific region defined by identifying individual zip codes. The quartile is assigned to each physician after each specialty-specific physician in a region receives an efficiency score. The decile is assigned to each physician after each specialty-specific physician in a region receives an efficiency score. The efficiency score for a physician is calculated by dividing the physician's weighted average overall mean charge by the peer group's weighted average overall mean charge. The attached general internist's efficiency score is 1.32, indicating that the internist's treatment pattern efficiency is 32% more resource intensive than the peer group's practice. The significant difference allows the user to observe whether the physician's efficiency score is statistically significantly different from the peer group average. ‘Yes’ means the physician's efficiency score is significantly different from the peer group's efficiency score. The user may employ two different levels of confidence (0.10 confidence level and 0.25 confidence level). The attached general internist's efficiency score is statistically significantly different than the peer group—indicated by the Yes in this field.
The body of the report headings are as follows. The medical condition name is the condition within a specialty-specific marketbasket. For the general internist marketbasket, this column lists the conditions generally treated by general internists. The peer group weighted average is at the top of the medical condition column. This row presents the peer group's weighted average charge per episode results. For example, the general internist peer group's overall weighted average charges are $205 per episode (see Column 4 of the FIG. 8 report). The practitioner weighted average row is directly under the peer group weighted average row, and entitled “Practitioner Weighted Avg.” This row presents each physician's weighted average charge per episode results. For example, the general internist's overall weighted average charges are $269 per episode (see Column 4 of the FIG. 8 report). The star next to the $269 per episode indicates that the weighted average results are statistically significantly different (p<0.25) from the peer group's weighted average results.
The SOI column presents the severity-of-illness (SOI) of the episodes being examined for a medical condition. There are up to three SOI levels for each medical condition, with SOI-1 being the least severe (routine, noncomplicated), and SOI-3 being the most severe. The episode count column presents the number of eligible episodes being examined for the peer group and the physician. For the general internist peer group, there are 46,656 eligible episodes. For the general internist physician, there are 217 eligible episodes. The general internist's 217 eligible episode count is the sum of the condition-specific episodes listed in this column. The Report shows the general internist treated 43 episodes of hypertension, 23 episodes of diabetes with no complications, 3 episodes of diabetes with circulatory involvement, 26 episodes of disorders of lipid metabolism, etc.).
The average charge per episode column presents the overall weighted average charge per episode results for the specialty-specific peer group. For example, the general internist peer group's overall weighted average charges are $205 per episode (see Column 4 of the FIG. 8 report). Directly under the peer group weighted average row is the physician's weighted average charge per episode. For the general internist, the overall weighted average charges are $269 per episode. The star next to the physician's $269 per episode indicates that the overall weighted average results are statistically significantly different (p<0.25) from the peer group's weighted average results.
The average charge per episode column is followed by service categories related to charges. The sum of these service category columns equals the overall average charge per episode. The service category report headings are as follows. There are five professional outpatient and ambulatory services columns that present professional outpatient and ambulatory charges. The services are physician-related and are not facility-billed services. The first column is professional visits (prof visits). This column presents the average charges per episode for professional visits incurred in the physician office, clinic, or outpatient department of a hospital. The second column is diagnostic tests (diag tests). This column presents the average charges per episode for diagnostic tests incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. Diagnostic tests represent imaging tests (X-rays, CAT scans, MRIs, etc.), functional tests (EKGs, echocardiograms, etc.), and invasive tests. The third column is laboratory and pathology (lab/path). This column presents the average charges per episode for laboratory and pathology services incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. The fourth column is medical and surgical procedures (med/surg). This column presents the average charges per episode for medical and surgical procedures incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. The fifth column is prescription drugs (Rx). This column presents the average charges per episode for outpatient and ambulatory prescription drugs.
There is one professional inpatient services column. This service-related column presents professional inpatient services. These services are physician related, and not facility billed services. This column presents the average charges per episode for all inpatient professional services.
There is one outpatient facility column and one inpatient facility column. These service-related columns present facility services. These services are facility-related and are not professional-billed services. The facility outpatient services (outpt facility) column presents the average charges per episode for all outpatient facility services incurred in an outpatient department of a hospital or surgicenter. The facility inpatient admissions (hosp inpt admits) column presents the average charges per episode for all hospital inpatient facility services.
There is one alternative care site services column. This service-related column presents facility services incurred in skilled nursing facilities and halfway homes. These services are facility-related and are not professional-billed services. This column presents the average charges per episode for skilled nursing facility and halfway home services.
There is one other medical services column. This service-related column presents other professional medical services. These services are physician-related and are not facility-billed services. The other medical services (other med) column presents the average charges per episode for other medical services incurred in the physician office, clinic, outpatient department of a hospital, and dialysis center. Other medical services include physical therapy, chiropractic services (other than professional visits), chemotherapy and radiation, dental, durable medical equipment, and ambulance services.
FIG. 9 presents a detailed description of Report 2, the Average Utilization per Episode of Care. Results are observed from an actual general internist as compared to a peer group of general internists.
The headings at the top of the FIG. 9 report are the same as for Report 1, Average Charges per Episode (refer to FIG. 8).
The body of the report headings are as follows. The medical condition name is the condition within a specialty-specific marketbasket. For the general internist marketbasket, this column lists the conditions generally treated by general internists. The peer group weighted average is at the top of the medical condition column. This row presents the peer group's weighted average utilization per episode results. The service categories present the peer group's corresponding average utilization per episode to the Report 1 defined average charges per episode. The practitioner weighted average row is directly under the peer group weighted average row is a row entitled Practitioner Weighted Average. This row presents each physician's weighted average utilization per episode results. The service category columns present the physician's corresponding average utilization per episode to the Report 1 defined average charges per episode. The star next to a physician's average utilization per episode result indicates that weighted average results are statistically significantly different (p<0.25) from the peer group's weighted average results.
The SOI column presents the severity-of-illness (SOI) of the episodes being examined for a medical condition. There are up to three SOI levels for each medical condition, with SOI-1 being the least severe (routine, noncomplicated), and SOI-3 being the most severe. The episode count column presents the number of eligible episodes being examined for the peer group and the physician. For the general internist peer group, there are 46,656 eligible episodes; and for the general internist physician, there are 217 eligible episodes.
The average episode duration (days) column presents the weighted average episode duration per episode results for the specialty-specific peer group. For example, the general internist peer group's weighted average duration is 122.8 days per episode (see Column 4). Directly under the peer group weighted average row is the physician's weighted average duration per episode. For the general internist physician, the overall weighted average duration is 123.6 days per episode. There is no star next to the physician's 123.6 days per episode. This indicates that the weighted average duration results are not statistically significantly different (p<0.25) from the peer group's weighted average duration results. Column 4 also presents the average duration per episode for each medical condition treated by the general internist physician. For instance, the general internist treated SOI-1 hypertension for an average 180.0 days per episode, SOI-1 low back pain for 29.4 days per episode, and acute bronchitis for 1.2 days per episode.
The average episode duration column is followed by 11 service categories related to utilization. The service category report headings are as follows. There are five professional outpatient and ambulatory services columns that present the physician's corresponding average utilization per episode to the Report 1 defined average charges per episode. The services are physician related, and not facility billed services. The first column is professional visits (prof visits). This column presents the average number of visits per episode for professional visits incurred in the physician office, clinic, or outpatient department of a hospital. The numerator unit is visits. The second column is diagnostic tests (diag tests). This column presents the average number of diagnostic tests per episode for diagnostic tests incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. The numerator unit is services or tests. The third column is laboratory and pathology (lab/path). This column presents the average number of lab/path services per episode for laboratory and pathology services incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. The numerator unit is services. The fourth column is medical and surgical procedures (med/surg). This column presents the average number of med/surg procedures per episode for medical and surgical procedures incurred in the physician office, clinic, outpatient department of a hospital, or surgicenter. The numerator unit is services or procedures. The fifth column is prescription drugs (Rx). This column presents the average number of prescription drug fills per episode for outpatient and ambulatory prescription drugs. The numerator unit is prescription drug fills.
There is one professional inpatient services column. This service-related column presents professional inpatient services. This column presents the physician's corresponding average inpatient professional services to the Report 1 defined average charges per episode. These services are physician related, and not facility billed services. Professional inpatient services (prof inpt): This column presents the average professional services per episode for all inpatient professional services. The numerator unit is services.
There are three facility services columns (one outpatient facility and two inpatient facility). These service-related columns present the facility services. The columns present the facility's corresponding average utilization per episode to the Report 1 defined average charges per episode. These services are facility related, and not professional billed services. The facility outpatient visits (outpt facility) column presents the average visits per episode for all outpatient facility services incurred in an outpatient department of a hospital or surgicenter. The numerator unit is visits. The facility inpatient admissions (hosp inpt admits) column presents the average number of admissions per episode for all hospital inpatient facility services. The numerator unit is admissions. The facility inpatient days (hosp inpt days) column presents the average number of inpatient days per episode for all hospital inpatient facility services. The numerator unit is hospital inpatient days.
There is one alternative care site services column. This service-related column presents facility services incurred in skilled nursing facilities and halfway homes. This column presents the facility's corresponding average services per episode to the Report 1 defined average charges per episode. These services are facility related, and not professional billed services. The alternative sites (altern sites) column presents the average services per episode for all skilled nursing facility and halfway home services. The numerator unit is services.
There is one other medical services column. This service-related column presents other professional medical services. This column presents the physician's corresponding average services per episode to the Report 1 defined average charges per episode. These services are physician related, and not facility billed services. The numerator unit is services.
While various embodiments for physician efficiency measurement and patient health risk stratification has been described and illustrated in detail, it is to be understood that various modifications can be made to embodiments of the present invention without departing from the spirit thereof.

## Claims

1. A healthcare analytics computer system for statistical analysis of medical care information for a medical care provider efficiency measurement, said healthcare analytics computer system comprising a memory device for storing data and a processor in communication with said memory device, said processor programmed to:
receive a plurality of scores defining an efficiency of care wherein each of the plurality of scores is associated with one of a plurality of physician identifiers identifying one of a plurality of physicians;
receive a plurality of episodes of care records, wherein each of the plurality of episodes of care records is associated with one of the plurality of physician identifiers identifying one of the plurality of associated physicians;
receive a plurality of patient treatment information data, wherein each of the plurality of patient treatment information data includes associated claim characteristics associated with a particular episode of care record, wherein the associated claim characteristics are a subset of a plurality of claim characteristics, wherein the plurality of claim characteristics includes a medical condition, a severity of illness classification, an average charge per episode of the medical condition at the severity of illness classification for a plurality of service categories, and an average utilization per episode of the medical condition at the severity of illness classification for the plurality of service categories, and wherein the average charge per episode and the average utilization per episode are weighted according to a predetermined relevance of the associated medical condition in a practice area associated with the plurality of physicians;
determine a relationship score between each of the plurality of claim characteristics and score calculations by performing a statistical analysis using the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data;
identify at least one of the plurality of claim characteristics for at least one of the physicians as having an associated relationship score exceeding a minimum threshold; and
report the identified at least one claim characteristic as a driver of efficiency for the at least one of the physicians.

2. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
receive a plurality of input files defining the association between each of the plurality of episodes of care records and each of the plurality of patient treatment information data; and
link each of the plurality of episodes of care records with the associated patient treatment information data based on the plurality of input files.

3. The healthcare analytics computer system of claim 2, wherein each of the plurality of input files includes a structured data relationship between each of the plurality of episodes of care records and each of the plurality of patient treatment information data.

4. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
identify a behavior adjustment associated with each of the efficiency drivers; and
recommend the plurality of behavior adjustments based on each identified efficiency driver.

5. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
receive with the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data, an associated geographic identifier; and
determine the relationship score for each of the associated geographic identifiers.

6. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
receive the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data for a plurality of physician practice areas; and
determine the relationship score for each of the associated physician practice areas.

7. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
identify a minimum threshold for episodes of care records;
filter the plurality of episodes of care records based on the identified minimum threshold; and
determine a filtered relationship score that is based on only episodes of care records that satisfy the identified minimum threshold.

8. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
determine the relationship score by performing a Pearson's correlation analysis.

9. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
receive a plurality of input files defining the association between each of the plurality of episodes of care records and each of the plurality of patient treatment information data, each of the plurality of input files having a hierarchical structure including at least four different record types; and
flatten the hierarchical structure of the plurality of input files to generate the plurality of patient treatment information data, such that the plurality of patient treatment information data includes only one record type, wherein a CPU processing time of said processor reading the flattened plurality of patient treatment information data is significantly reduced relative to a CPU processing time for the plurality of input files.

10. The healthcare analytics computer system of claim 1, wherein said processor is further configured to:
calculate the plurality of scores defining the efficiency of care based on the plurality of episodes of care records, wherein the score for each of the physicians is calculated utilizing a subset of medical conditions clinically related to that physician's specialty type, the subset including the medical conditions most commonly treated by that physician's specialty type, and wherein each medical condition included in the subset of medical conditions is associated with the severity-of-illness classification, the severity of illness classification representing a severity level from a plurality of severity levels for the corresponding medical condition, each of the subset of medical conditions weighted by a factor representing a prevalence of the corresponding medical condition relative to other medical conditions included within the subset.

11. A computer-implemented method for statistical analysis of medical care information for a medical care provider efficiency measurement, said method implemented by a healthcare analytics computer system comprising a memory device for storing data and a processor in communication with the memory device, said method comprising:
receiving a plurality of scores defining an efficiency of care wherein each of the plurality of scores is associated with one of a plurality of physician identifiers identifying one of a plurality of physicians;
receiving a plurality of episodes of care records, wherein each of the plurality of episodes of care records is associated with one of the plurality of physician identifiers identifying one of the plurality of associated physicians;
receiving a plurality of patient treatment information data, wherein each of the plurality of patient treatment information data includes associated claim characteristics associated with a particular episode of care record, wherein the associated claim characteristics are a subset of a plurality of claim characteristics, wherein the plurality of claim characteristics includes a medical condition, a severity of illness classification, an average charge per episode of the medical condition at the severity of illness classification for a plurality of service categories, and an average utilization per episode of the medical condition at the severity of illness classification for the plurality of service categories, and wherein the average charge per episode and the average utilization per episode are weighted according to a predetermined relevance of the associated medical condition in a practice area associated with the plurality of physicians;
determining a relationship score between each of the plurality of claim characteristics and score calculations by performing a statistical analysis using the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data;
identifying at least one of the plurality of claim characteristics for at least one of the physicians as having an associated relationship score exceeding a minimum threshold; and
reporting the identified at least one claim characteristic as a driver of efficiency for the at least one of the physicians.

12. The method of claim 11, further comprising:
receiving a plurality of input files defining the association between each of the plurality of episodes of care records and each of the plurality of patient treatment information data; and
linking each of the plurality of episodes of care records with the associated patient treatment information data based on the plurality of input files.

13. The method of claim 12, wherein each of the plurality of input files includes a structured data relationship between each of the plurality of episodes of care records and each of the plurality of patient treatment information data.

14. The method of claim 11, further comprising:
identifying a behavior adjustment associated with each of the efficiency drivers; and
recommending the plurality of behavior adjustments based on each identified efficiency driver.

15. The method of claim 11, further comprising:
receiving with the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data, an associated geographic identifier; and
determining the relationship score for each of the associated geographic identifiers.

16. The method of claim 11, further comprising:
receiving the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data for a plurality of physician practice areas; and
determining the relationship score for each of the associated physician practice areas.

17. The method of claim 11, further comprising:
identifying a minimum threshold for episodes of care records;
filtering the plurality of episodes of care records based on the identified minimum threshold; and
determining a filtered relationship score that is based on only episodes of care records that satisfy the identified minimum threshold.

18. The method of claim 11, further comprising:
determining the relationship score by performing a Pearson's correlation analysis.

19. A computer-readable storage device, having processor-executable instructions embodied thereon, for statistical analysis of medical care information for a medical care provider efficiency measurement using a healthcare analytics computer system, wherein the healthcare analytics computer system includes at least one processor and a memory device coupled to the processor, wherein, when executed by the healthcare analytics computer system, the processor-executable instructions cause the healthcare analytics computer system to:
receive a plurality of scores defining an efficiency of care wherein each of the plurality of scores is associated with one of a plurality of physician identifiers identifying one of a plurality of physicians;
receive a plurality of episodes of care records, wherein each of the plurality of episodes of care records is associated with one of the plurality of physician identifiers identifying one of the plurality of associated physicians;
receive a plurality of patient treatment information data, wherein each of the plurality of patient treatment information data includes associated claim characteristics associated with a particular episode of care record, wherein the associated claim characteristics are a subset of a plurality of claim characteristics, wherein the plurality of claim characteristics includes a medical condition, a severity of illness classification, an average charge per episode of the medical condition at the severity of illness classification for a plurality of service categories, and an average utilization per episode of the medical condition at the severity of illness classification for the plurality of service categories, and wherein the average charge per episode and the average utilization per episode are weighted according to a predetermined relevance of the associated medical condition in a practice area associated with the plurality of physicians;
determine a relationship score between each of the plurality of claim characteristics and score calculations by performing a statistical analysis using the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data;
identify at least one of the plurality of claim characteristics for at least one of the physicians as having an associated relationship score exceeding a minimum threshold; and
report the identified at least one claim characteristic as a driver of efficiency for the at least one of the physicians.

20. The computer-readable storage device of claim 19, wherein the processor-executable instructions cause the healthcare analytics computer system to:
receive a plurality of input files defining the association between each of the plurality of episodes of care records and each of the plurality of patient treatment information data; and
link each of the plurality of episodes of care records with the associated patient treatment information data based on the plurality of input files.

21. The computer-readable storage device of claim 20, wherein the processor-executable instructions cause the healthcare analytics computer system to:
identify a behavior adjustment associated with each of the efficiency drivers; and
recommend the plurality of behavior adjustments based on each identified efficiency driver.

22. The computer-readable storage device of claim 19, wherein the processor-executable instructions cause the healthcare analytics computer system to:
receive with the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data, an associated geographic identifier; and
determine the relationship score for each of the associated geographic identifiers.

23. The computer-readable storage device of claim 19, wherein the processor-executable instructions cause the healthcare analytics computer system to:
receive the plurality of scores, the plurality of episode of care records, and the plurality of patient treatment information data for a plurality of physician practice areas; and
determine the relationship score for each of the associated physician practice areas.

24. The computer-readable storage device of claim 19, wherein the processor-executable instructions cause the healthcare analytics computer system to:
identify a minimum threshold for episodes of care records;
filter the plurality of episodes of care records based on the identified minimum threshold; and
determine a filtered relationship score that is based on only episodes of care records that satisfy the identified minimum threshold.

25. The computer-readable storage device of claim 19, wherein the processor-executable instructions cause the healthcare analytics computer system to:
determine the relationship score by performing a Pearson's correlation analysis.

26. The computer-readable storage device of claim 19, wherein the processor-executable instructions cause the healthcare analytics computer system to:
identify a minimum threshold for episodes of care records;
filter the plurality of episodes of care records based on the identified minimum threshold; and
determine a filtered relationship score that is based on only episodes of care records that satisfy the identified minimum threshold.