Department of Health and Human Services 

OFFICE OF 

INSPECTOR GENERAL 

JANET REHNQUIST 

Inspector General 

JANUARY 2003 

OEI-06-00-00570 

Comparing 

To Private 

Medicare Physician Payments 

Payers 
OFFICE OF INSPECTOR GENERAL
 

http://www.oig.hhs.gov/ 

The mission of the Office of Inspector General (OIG), as mandated by Public Law 95-452, as amended, 

is to protect the integrity of the Department of Health and Human Services (HHS) programs, as well as 

the health and welfare of beneficiaries served by those programs. This statutory mission is carried out 

through a nationwide network of audits, investigations, and inspections conducted by the following 

operating components: 

Office of Audit Services 

The OIG's Office of Audit Services (OAS) provides all auditing services for HHS, either by conducting 

audits with its own audit resources or by overseeing audit work done by others. Audits examine the 

performance of HHS programs and/or its grantees and contractors in carrying out their respective 

responsibilities and are intended to provide independent assessments of HHS programs and operations in 

order to reduce waste, abuse, and mismanagement and to promote economy and efficiency throughout the 

Department. 

Office of Evaluation and Inspections 

The OIG's Office of Evaluation and Inspections (OEI) conducts short-term management and program 

evaluations (called inspections) that focus on issues of concern to the Department, the Congress, and the 

public. The findings and recommendations contained in the inspections reports generate rapid, accurate, 

and up-to-date information on the efficiency, vulnerability, and effectiveness of departmental programs. 

Office of Investigations 

The OIG's Office of Investigations (OI) conducts criminal, civil, and administrative investigations of 

allegations of wrongdoing in HHS programs or to HHS beneficiaries and of unjust enrichment by 

providers. The investigative efforts of OI lead to criminal convictions, administrative sanctions, or civil 

monetary penalties. The OI also oversees State Medicaid fraud control units which investigate and 

prosecute fraud and patient abuse in the Medicaid program. 

Office of Counsel to the Inspector General 

The Office of Counsel to the Inspector General (OCIG) provides general legal services to OIG, rendering 

advice and opinions on HHS programs and operations and providing all legal support in OIG’s internal 

operations. The OCIG imposes program exclusions and civil monetary penalties on health care providers 

and litigates those actions within the Department. The OCIG also represents OIG in the global settlement 

of cases arising under the Civil False Claims Act, develops and monitors corporate integrity agreements, 

develops model compliance plans, renders advisory opinions on OIG sanctions to the health care 

community, and issues fraud alerts and other industry guidance. 

E X E C U T I V E S U M M A R Y 

OBJECTIVE 

To compare Medicare relative values for physician services to similar values paid by private 

insurance companies, based upon MEDSTAT’s MarketScan® database. 

BACKGROUND 

Accounting for over $40 billion each year, Medicare’s physician fee schedule contains more 

than 7,000 codes for reimbursable services. Each is assigned a relative value (RVU) 

composed of three factors– Physician Work, Practice Expense, and Professional Liability 

Insurance, designed to reflect the human and capital resources required for provision of the 

service. The RVU is multiplied by a constant dollar figure to obtain the fee schedule payment 

amount. The Secretary is required to review the RVUs for all physician services at least once 

every 5 years. To help meet this requirement, the American Medical Association’s Relative 

Value Updating Committee (RUC) reviews codes and provides recommendations regarding 

appropriate changes to the RVUs for consideration by the Centers for Medicare & Medicaid 

Services (CMS). 

This study uses proprietary claims data from MEDSTAT’s Marketscan® database to compare 

service valuation patterns between Medicare and private insurers. A data mining process 

identifies procedures that consistently appear to have moderate or extreme differences between 

the two groups. Possible reasons that differences may exist were investigated through 

interviews and literature reviews. 

FINDINGS 

Many procedure codes are not included in the current 5-year comprehensive 

review; a systematic analysis may assist code identification 

The Secretary is required to review relative values for all physician services no less than every 5 

years to adjust for changes in medical practice or coding and to reflect new data on relative 

resources. In practice, this requirement means that all codes must be eligible for review. 

Decisions to include codes in the 5-year review are based on a nomination process. The data 

mining technique presented in this study provides an alternative source of information that could 

improve CMS’ ability to identify those codes most in need of review. 

Comparing Medicare Physician 

Payments to Private Payers i OEI-06-00-00570
< Of the 681 Medicare services evaluated, 217 are valued differently from private payers 

Two-hundred seventeen procedures, 30 percent of those reviewed, were identified with 

consistent and substantial differences in relative value between Medicare and the MEDSTAT 

database. Ninety-eight procedures appear to be valued higher by Medicare; the remaining 119 

appear to be valued lower by Medicare. Reasons for these differences are unclear and may be 

attributable to errors within the RVU, to population differences, or to differing incentives to 

review codes. 

<	 Only 20 of the 217 codes identified by our analysis were reviewed in the 5-year 

comprehensive review 

CONCLUSION 

Identification of procedures in need of review is almost exclusively based on outside nominations. The 

process is limited in its ability to identify misvalued, particularly overvalued, procedures. We believe 

that the current process could be improved by supplementing physician efforts with a data-driven 

method, similar to that presented in this inspection. 

Valuations that differ significantly between Medicare and the private industry may indicate that those 

resources are not adequately or not efficiently reflected. However, further investigation of individual 

differences must take into account any changes made since the analysis year (1999) and the difficulties 

inherent to a comparison between Medicare and the private sector. 

Comparing Medicare Physician 

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T A B L E O F C O N T E N T S

PAGE
 

EXECUTIVE SUMMARY ...................................................... i
 

INTRODUCTION ............................................................. 1
 

FINDING
 

Many Procedure Codes Are Not Included in the Current 5-Year Comprehensive
 

Review; A Systematic Analysis May Assist Code Identification ....................... 7
 

CONCLUSION .............................................................. 9
 

ENDNOTES ................................................................ 10
 

APPENDICES 

A: Data description ...................................................... 11
 

B: Data cleaning ........................................................ 13
 

C: Data mining methods ................................................... 15
 

D: Valuation differences ................................................... 19
 

ACKNOWLEDGMENTS ..................................................... 29
 

Comparing Medicare Physician 

Payments to Private Payers OEI-06-00-00570 
I N T R O D U C T I O N 

OBJECTIVE 

To compare Medicare relative values for physician services to similar values paid by private 

insurance companies based on MEDSTAT’s MarketScan® database. 

BACKGROUND 

The Resource Based Relative Value System (RBRVS) 

Medicare’s current physician payment structure, the physician fee schedule, is based on a 

relative value system known as the Resource Based Relative Value System (RBRVS). The 

RBRVS assigns a value to services that can be provided by a physician under the Medicare 

program. The value, measured in relative value units (RVUs), compares each service relative 

to all other services. For example, one of the most common procedures, an office visit for an 

established patient, is currently valued as .93 RVUs while a more complex procedure, such as 

an artery bypass graft, is valued as 46.50 RVUs. This implies that the resources needed to 

perform the artery bypass graft (including physician training, time, office equipment, and liability 

insurance) are 50 times those needed for an office visit. 

Accounting for more than $40 billion each year, the physician fee schedule contains more than 

7,000 codes for services reimbursable by Medicare. Each service is attributed an RVU 

reflecting the sum of three distinct components: 

‚ Physician Work (Work) - compensation for the time and skill required of the 

physician, 

‚ Practice Expense (PE) - cost of staff time and material resources necessary to 

perform the service, and 

‚	 Professional Liability Insurance (PLI) - reimbursement for the malpractice 

insurance carried by the physician. 

The value for each component is multiplied by a geographic adjustment factor called the 

Geographic Practice Cost Index (GPCI)1 and is then summed to obtain the full RVU total for a 

service. The total RVU is multiplied by a constant dollar figure, known as the conversion 

factor, to obtain the fee schedule payment amount. The conversion factor, about $36.20 in 

2002, is updated each January to account for inflation, but in a given year remains the same for 

all services and all specialties.2 Therefore, any changes to reimbursement for a service must be 

derived by changes to the RVU of that service. 

Comparing Medicare Physician 

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The formula is: 

Implemented in 1992, the RBRVS was phased in over the following 10 years. The first 

component, Physician Work, was completely integrated into the system in 1997, and the last 

component, Practice Expense, was completely integrated in 2002. 

Two additional statutory provisions govern the practical implementation of the RBRVS– 

budget neutrality to limit the impact of administrative adjustments and the sustainable growth 

rate (SGR) to control aggregate expenditures.3 In combination, the current provisions for 

budget neutrality and a sustainable growth rates create a system where RVU changes have little 

impact on aggregate expenditures. The RVUs act as a system of allocating fixed monetary 

resources rather than determining expenditures. 

The 5-year Comprehensive Review of Work RVUs 

The Social Security Act, §1848(c)(2)(B)(i), requires the Secretary to adjust relative values on a 

yearly basis to account for coding and coverage changes and also to comprehensively review 

the relative values for all physician services at least once every 5 years to make any needed 

adjustments. The Centers for Medicare & Medicaid Services (CMS) completed it’s second 

5-year comprehensive review of the Work component, with the update taking effect January 1, 

2002. 

For the 5-year comprehensive review, CMS developed a system utilizing the American 

Medical Association’s (AMA’s) interdisciplinary medical expertise. Through the Federal 

Register (FR), CMS solicits requests for particular codes to be reviewed. A list of the 

requested codes is provided to the AMA’s Relative Value Updating Committee (RUC) for 

recommendations. The CMS reviews the recommendations for consistency within code 

families and identifies unwanted policy implications. In the most recent review, CMS accepted 

792 of the RUC’s 857 recommendations (92 percent).4 

The current process of soliciting codes for the review is limited, particularly in its ability to 

identify overvalued codes.5 In an effort to address these limitations, CMS initiated a contract 

with a private-sector group, Health Economic Research (HER), to develop quantitative 

methods of identifying Current Procedural Terminology (CPT) codes for review.6 CMS also 

used the Federal Register to encourage public comments on the use 

Comparing Medicare Physician 

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of databases and methodologies that might lend themselves to the identification of misvalued 

procedures. Despite these attempts, no additional methods have been found. By and large, the 

seven methods proposed by the HER were discarded as not feasible or not applicable to a 

broad-scale review. The exception is an undertaking for a limited number of surgical codes. 

CMS is comparing actual time data as it appears on medical records to the time found in survey 

data collected by the AMA. 

Importance of appropriate valuation 

The Medicare Payment Advisory Commission’s (MedPAC’s) 2001 Report to Congress states 

that “to help ensure beneficiaries’ access to high-quality care, Medicare payments should 

correspond to the cost efficient providers incur in furnishing this care.”7 Payments that do not 

meet this objective may promote inappropriate incentives for care or create barriers to access. 

Specifically: 

<	 Differing payment incentives could influence choices between diagnostic and/or 

treatment plans. 

<	 Some physicians state that reductions in reimbursement will affect the number of 

Medicare beneficiaries they treat.8, 9, 10, 11 

<	 Codes that are not increased from the 5-year comprehensive review and those that 

were not reviewed at all are deflated. Because the current system is budget neutral, 

what is given to one code is taken from another. Over time this code deflation could 

contribute to access limitations for particular specialties. 

METHODOLOGY 

This study uses a proprietary commercial claims database as a comparison group to identify 

procedures in Medicare’s physician fee schedule whose relative values differ substantially from 

private payers. We used several methods of comparison, but the primary identification was the 

result of a data mining process using standardized payment data. 

The data 

We used MEDSTAT’s 1999 MarketScan® database as our primary source of data. This data 

includes commercial claims and encounters for over 50 different commercial plans and spans 

the calendar year 1999. We chose this data for its breadth and ability to provide complete 

claim payment information. No other database provides payment information (as opposed to 

charge information) at the claim level. For comparability purposes, the data is limited to 

physician payments within fee-for-service plans. 

Comparing Medicare Physician 

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The MEDSTAT data is not nationally representative; however, it includes over 21 million 

claims spread throughout all 50 states, plus Puerto Rico and the District of Columbia. The 

greatest representations are in Georgia, Michigan, and Tennessee, cumulatively accounting for 

almost 45 percent of the records. Despite limitations for national representation, we determined 

that this data was the best suited for the needs of this study. A description of population 

characteristics is provided in Appendix A. 

Other data used include: the National Physician Fee Schedule Relative Value File (RVU File), 

the Geographic Practice Cost Indices (GPCI data), census data, and Medicare claims data. 

The RVU File and the GPCI data are the actual 1999 values used by Medicare contractors to 

determine allowable reimbursement rates for physician services and procedures. 

Comparing Medicare to the private sector 

Unlike private health insurance companies, Medicare is required by law to base payments on 

resources. For this reason, comparative differences may not necessarily be indicative of errors 

in the physician fee schedule, but a reflection of a different basis for rate setting. In addition, 

population differences and the method of comparison must be taken into account. 

Consequently, we present any findings of payment differences as potential issues to be 

investigated further, rather than a need for specific change. 

Population Differences. Several difficulties exist in comparing Medicare payments to privatesector health insurance payments. First, by definition, Medicare is a unique and distinct 

population including only seniors over age 65 and individuals meeting certain disability 

requirements. While most individuals with health insurance are covered by an employer-based 

policy, Medicare is specifically designed to insure those not likely to be employed. Therefore, 

population differences between the two groups will be apparent in the type and frequency of 

medical claims. Further, the extent to which payment methods, e.g., global payments, and the 

underlying payment structure, e.g., resource-based, differ between the two groups are 

unknown. A third question exists with regard to market influences on pricing. While 

MEDSTAT payments are entirely subject to the market, Medicare’s resource-based system 

discounts market influences by basing prices on the costs of inputs, such as the cost of physician 

time and the cost of supplies, and by deflating the GPCI to reflect only 60 percent of market 

variation. 

Limitations of a dollar comparison. To address issues associated with a dollar comparison, 

we chose to identify procedures where the relative valuation is inconsistent between the private 

industry and Medicare. A dollar to dollar comparison between the two groups is of limited 

value. Although procedures can be ranked within each group according to price, the actual 

payments for procedures are not comparable. First, Medicare need not pay the same as 

private payers. A difference in payment rate could be the result of an intention to pay providers 

more or less than Medicare rather than a 

Comparing Medicare Physician 

Payments to Private Payers 4 OEI-06-00-00570
different assessment of the procedure’s worth in relation to other services. There are further 

difficulties in using a straight (non-standardized) dollar-figure comparison, such as our inability 

to account for differences in management practices, e.g., capitation. Unlike the RBRVS, some 

management practices may distribute reimbursements in ways that are not related to specific 

procedures, such as per-capita payments, which pay physicians based on the number of 

individuals they treat or the diagnoses they handle. Such reimbursements are not captured in 

our data. 

Data mining to identify outliers in standardized payment rates 

Standardizing payment rates. Standardizing data is a method that provides a common basis 

of comparison for things that are measured on different scales. In this instance, we want to 

compare the relative value of procedures between Medicare and private insurers. For our 

analysis, the entire allowable amount (including copayments and deductibles) for each service 

provided under a private plan was divided by the total Medicare RVU associated with the 

service. 

This standardization allows us to compare what is, in theory, a constant conversion factor 

similar to the one found in Medicare’s reimbursement formula (shown on page 2). The 

rationale for a constant conversion factor is that if we assume that Medicare’s RBRVS 

correctly values every service in terms of RVUs, then we can also assume that the entirety of 

variation in payments would be captured by the RVUs. Consequently, if we divide the 

allowable charge by the associated RVU, we would identify a constant conversion factor. The 

same conversion factor would be found regardless of the procedure chosen. If this constancy is 

not found in our data, the private sector, as demonstrated by the data, does not place relative 

value between services the same as Medicare. 

Data mining process. To identify inconsistencies in assessed value between MEDSTAT’s 

MarketScan® data and Medicare RVU data, we used a process called stepwise elimination. 

In this process, regression models were used to identify procedures and procedure groups 

whose standardized payments, or conversion factor, differ significantly from the expected value. 

Every procedure (681 procedures) and procedure group (111 procedure groups) meeting a 

minimum sample size and several other data requirements were included in the model as 

dichotomous variables. Those variables were systematically dropped in accordance with their 

significance in determining the mean conversion factor. In essence, we are identifying 

procedures in which the variation that exists in private payments is not captured by Medicare’s 

relative values. A procedure’s relative value in the private industry differs from its Medicare 

RVU to the extent that the conversion factors are different. This process was conducted 

separately on two independent data partitions. The procedures presented in this report were 

identified in both partitions.12 For additional information on the data mining process, see 

Appendix B: Data cleaning and Appendix C: Data mining methods. 

Comparing Medicare Physician 

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Statistical methods 

Stepwise elimination was used as an exploratory data mining technique rather than the more 

customary hypothesis testing. For this reason, tests of fit are not included. Basic statistical 

methods, including the F-test, were used to interpret the regression results. A nonresponse 

analysis is not applicable to this study. However, generalizability of the data is a concern. 

Representation is limited to those private insurance plans that have proprietary agreements with 

the MEDSTAT Group. Information on nonparticipating plans is not available. 

Qualitative methods 

In order to understand potential reasons for the presence of outliers and to fully understand the 

process of assigning values and updating the fee schedule, we conducted telephone interviews 

with representatives of particular specialty societies and carrier medical directors, in-depth 

interviews with CMS staff, and a literature review of relevant government documents and both 

special interest and academic articles. 

Quality standards 

This study was conducted in accordance with the Quality Standards for Inspections issued by 

the President’s Council on Integrity and Efficiency. 

Comparing Medicare Physician 

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F I N D I N G S 

By applying a data mining technique to a proprietary database of claims for physician services provided 

in the private sector, we identified procedure codes with relative values that are substantially and 

consistently different from corresponding Medicare values. Of the 681 codes that we reviewed, 217 

exhibit moderate or extreme differences in relative value. Reasons for these differences are unclear and 

may be attributable to errors within the relative values themselves, or to population differences. 

Although the Secretary is required to review relative values for accuracy every 5 years, only 20 of the 

217 codes identified were included in the most recent 5-year comprehensive review. The absence of 

so many of these codes in the 2002 Review suggests that augmenting the current system with one or 

more data driven methods may help to assure appropriate relative value assessments. 

MANY PROCEDURE CODES ARE NOT INCLUDED IN THE CURRENT 

5-YEAR COMPREHENSIVE REVIEW; A SYSTEMATIC ANALYSIS 

MAY ASSIST CODE IDENTIFICATION 

Section 1848(c)(2)(B)(i) of the Social Security Act requires the Secretary to review relative 

values for all physician services no less than every 5 years to adjust for changes in medical 

practice or coding and to reflect new data on relative resources. In practice, this requirement 

means that all codes must be eligible for review.13 Decisions to include codes in the review are 

based on a nomination process, whereby CMS solicits in the Federal Register for codes to 

include in the review. The process depends almost entirely on outside information to identify 

codes that may be inappropriately valued. There is an obvious incentive for specialty groups to 

identify codes that are undervalued, but there may be less of an incentive for them to bring forth 

codes that have been overvalued. 

The data mining technique, presented in this study, provides a supplemental source of 

information that could improve CMS’ ability to identify those codes most in need of review. 

Without assurance that every code will be reviewed, it would be prudent to have a systematic 

process in place to identify the codes most in need of review. 

Of the 681 Medicare codes evaluated, 217 are valued differently from private 

payers; 98 appear higher and 119 appear lower than Medicare payment rates 

Our data mining process identified 217 procedures that consistently exhibit moderate or 

extreme differences in value between Medicare and the private industry. Listed in Appendix D, 

these procedures represent 30 percent of the 681 codes analyzed. Many of the approximately 

7,000 codes for reimbursable services were excluded from the review for failure to meet 

minimum sample size requirements or because data was inadequate for 

Comparing Medicare Physician 

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the chosen analysis. However, the codes reviewed represent over 70 percent of Medicare 

allowed charges for physician services during the analysis year (1999). 

Of the 217 codes, 98 procedures appear to be valued higher by Medicare; the remaining 119 

appear to be valued lower by Medicare. These differences were evaluated through the private 

sector’s theoretical conversion factor for each service. With respect to Medicare’s payment of 

$34.73 per RVU (in 1999), the private data reflects a payment range of $1,065.07 per RVU 

for allergy skin tests – the highest comparative value reflected in the private data, and $0.30 for 

aspiration of a thyroid cyst – the lowest. 

In the assessed value of services, we do expect variability resulting from differences in 

professional judgment or from differing plan characteristics. However, the procedures 

presented in this report consistently showed differences that were statistically significant, and 

thus, raise questions of potential mis-valuation. 

While differences in valuation are evident, the reasons are unclear and may be 

attributable to errors within the RVU or to population differences 

The analysis used in this study allows us to recognize which procedures are valued differently 

between Medicare and private insurers, but is not able to pinpoint the exact source of 

difference. If our results show that Medicare values a procedure higher than the private 

industry, either Medicare is paying more than necessary or the private industry is not paying 

sufficiently, or both. Differences could reflect errors within one or more of the three RVU 

components, or could reflect market variation that is not captured in the GPCI. Further, no 

standard exists to determine whether private sector values or Medicare values are correct. 

Several possibilities exist and further investigation of these procedures will be necessary to 

determine whether RVU adjustments are indicated. 

Only 20 of the 217 codes identified by our analysis were reviewed in the 5-year 

comprehensive review in 2002 

The absence of many of our identified codes in the 2002 review of the Work component 

indicates that the current process of nomination does not yield the same results as our datadriven method. Only 26 of the identified codes were reviewed in the 1997 5-year 

comprehensive review. If differences that we identified are indicative of needed adjustment, 

many of these adjustments would not have been made by CMS. 

Comparing Medicare Physician 

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C O N C L U S I O N 

In order to ensure that Medicare beneficiaries have adequate access to services and 

appropriate treatments, and physician reimbursements are commensurate with the service 

performed, every reasonable effort should be given to assessing Medicare relative values 

appropriately. Valuations that differ significantly between Medicare and the private industry 

may indicate that those resources are not adequately or not efficiently reflected. However, 

further investigation of individual differences must take into account any changes made since the 

analysis year (1999) and the difficulties inherent to a comparison between Medicare and the 

private sector. 

The current process of identifying codes that may need adjustment is dependent on the 

motivation, available time, and resources of individual physicians and physician groups to 

research and develop arguments supporting change. The process is limited, particularly with 

respect to the identification of overvalued procedures. Appropriately, the nomination of 

procedures by independent groups ensures that physicians will have a voice in the process; 

however, it is important that CMS supplement physicians’ efforts with a more systematized 

method of identification. The data mining method that we have presented in this inspection may 

provide a feasible method that CMS could utilize in cooperation with the nomination process to 

better accomplish the task of identifying codes for the 5-year comprehensive review. 

Comparing Medicare Physician 

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E N D N O T E S 

1. 	 Prior to implementation, the RBRVS was critiqued for not accounting for market variation. 

GPCIs were created to capture market influences in the cost of resources. Each Medicare 

locality has its own set of GPCIs that are used to adjust each component of the RVU for 

market variation. Separate indices are used to measure cost differences for each of the three 

fee schedule components. 

2.	 Initially, the conversion factor varied between specialties. This was the result of significant 

variation in payment policies of Medicare carriers. One of the requirements of the Omnibus 

Budget Reconciliation Act of 1989 was that a single conversion factor should be used for all 

physicians. 

3. SSA§1848(c)(2)(F) and SSA§1848(f) 

4. 66 FR 31031 (June 8, 2001) 

5. 64 FR 59380 (November 2, 1999) 

6.	 Health Economics Research, “5-year review of Work Relative Value Units”; November 2, 

1999. www.hcfa.gov/medicare/wrvu-toc.htm 

7.	 “Report to Congress: Medicare Payment Policy,” Medicare Payment Advisory Commission, 

March 2001: Page 21. 

8. 	 “Doctor Medicare pay faces cut next year; The AMA suggests that the government adjust 

the way it calculates some figures to make the pay formula fairer.” www.amednews.com: 

Sept. 17, 2001. 

9. 	 “AMA says slow economy may reduce Medicare payments,” www.kaisernetwork.org: 

Sept. 13, 2001. 

10. 	 Flaherty, Timothy T., MD, “Payment cuts could mean patient access problems,” 

www.amednews.com: February 25, 2002. 

11.	 Phalen, Kathleen, “Opting out: Physicians exiting Medicare program,” AMNews: June 

25, 2001. 

12. 	 In simulation studies, the duplication of results in two separate partitions of the data were 

effective in ruling out erroneous identification of procedures. 

13. 56 FR 59502 (November 25, 1991) 

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Appendix A 

Data description
 

Demographics 

The demographic information below describes the percent of line item claims in the MEDSTAT data 

that fit individual characteristics. 

Age Range Sex Regional Distribution 

0-17 13.6% Male 47.4% Northeast 16.2% 

18-34 24.2% Female 52.6% North Central 25.3% 

35-44 18.2% South 40.9% 

45-54 21.1% West 15.2% 

55-64 22.7% Unknown 2.4% 

65 and older 0.2% 

Source of Data 

MEDSTAT data are based on a selection of employer’s health benefit packages. Although specific 

information about companies is not available, the industry with a percentage of claim representation is 

below. Claims may represent the spouse or dependent of an employee associated with a particular 

industry. 

Oil & Gas Extraction, Mining 3.8% 

Manufacturing, Durable Goods 21.7% 

Manufacturing, Nondurable Goods 30.7% 

Transportation, Communications, 

Utilities 

23.5% 

Retail Trade 0.3% 

Finance, Insurance, Real Estate 5.9% 

Services 6.8% 

Missing/Unknown 7.4% 

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Appendix A 

Plan Payment Information 

The amount paid may vary within a plan when a provider network is in place. For almost half the data, 

we do not know if the service was provided within or outside of a plan network, or if a network exists 

at all. All remaining claims were paid ‘in plan’ with the exception 7.1 percent paid ‘out of plan.’ 

Different plan types were represented in our data as indicated below. 

Basic/Major Medical 4.4% 

Comprehensive 40.0% 

Exclusive Provider Organization (EPO) 2.7% 

Point Of Service (POS) 8.2% 

Preferred Provider Organization (PPO) 44.1% 

Health Maintenance Organization (HMO) -

excluded 

0% 

POS with Capitation - excluded 0% 

Missing/Unknown 0.5% 

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Appendix B 

Data cleaning 

The proprietary claims data used in this study is subject to all of the problems that are inherent to 

administrative medical claims data. We conducted broad validity checks to determine the level of 

accuracy of the data. There was a need for significant ‘data cleaning’ of the critical data elements prior 

to analysis. We found that it was necessary to drop large segments of the data for one or more of the 

reasons described below. As a result, we significantly reduced our number of observations. The 

process began with 21 million claims divided into three partitions of approximately 7 million each. Line 

item deletions reduced each partition by almost 40 percent. Although the reduction was considerable, 

we believe that these modifications were necessary to maintain the integrity of the data and subsequent 

analysis. Additionally, we found some data that needed adjustment or was unsuitable for review. 

Our data cleaning resulted in the following: 

1. Deletion of services inconsistent with the needs of the analysis 

•	 Anesthesia services for which Medicare provides reimbursement using a separate 

conversion factor 

•	 Procedure codes that required modifiers to determine the RVUs attributed to the 

service (modifier information was not available through MEDSTAT) 

2. Deletion of data flaws 

• Critical data elements were missing or invalid 

• Orphan claims1 with payments equal to zero or less 

•	 Outliers (defined as line items having a payment amount that were beyond three 

standard deviations from the mean of the service) 

3.	 Deletion of services that are currently incompatible with Medicare’s 

Physician Fee Schedule 

• Procedure codes that are not active 

• Procedure codes that are not covered under the Medicare Physician Fee Schedule 

• Procedure codes that Medicare pays only as a technical component 

• Procedure codes in which payment is not based on the relative value scale 

• Procedure codes with a relative value of zero 

1

 Orphan claims are line item adjustments that MEDSTAT could not match to the appropriate claim. 

MEDSTAT advises that these claims be included in aggregate or summary statistics, but need not be 

included when looking at individual line items. 

Comparing Medicare Physician 

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Appendix B 

4.	 Procedures represented in the MEDSTAT data with fewer than 100 claims 

remain in the data, but were not reviewed 

Similar to the second partition, the first partition contained claims for 4,589 different procedure 

codes after line item deletions. However, only 681 procedure codes had a sufficient number of 

claims to be eligible for the review. 

5. 	 Differential use of the units variable 

In particular cases, the units variable is meaningful and can affect the calculated averages. For 

this reason, any procedure where more than 5 percent of the billing reflected a unit of greater 

than one was judged for legitimacy of multiple units. The determination was made with the 

assistance of a Medicare Contractor Medical Director and also a Private Health Insurance 

Medical Director. 

Comparing Medicare Physician 

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Appendix C 

Data mining methods
 

Theory of Data Mining 

As a relatively new field in analytics, data mining allows us to explore the wealth of data that 

now exists in almost every industry conceivable. Generally speaking, data mining is the 

utilization of a number of tools, including statistics, artificial intelligence and pattern recognition, 

to better understand and describe very large data sets. Data mining is not hypothesis testing, a 

method that uses data to confirm or reject hypotheses. Rather, it uses data to develop 

hypotheses in the absence of preconceived theories. With this distinction comes an increased 

probability of Type I error, i.e., an erroneous finding. However, utilized in its appropriate 

context, data mining has the ability to find valid patterns and inconsistencies that may not 

otherwise have been noticed. 

Focus 

For this particular study, we sought to identify inconsistencies between Medicare and the 

private industry in the value of services relative to other services from the same payer group. 

Understanding that absolute differences in reimbursement rates have interpretation problems, 

we determined that evaluating payments per Medicare-RVU allowed us to compare 

reimbursement rates among different procedures, thus eliminating the need to make a direct 

comparison between Medicare and private payments. We are looking at private payments in 

the context of Medicare RVUs; procedures that do not fit that context smoothly in relation to 

other procedures may have been evaluated differently in Medicare than in the private industry. 

Model 

To identify procedures that appear to be evaluated differently between the two sectors, we 

used two data mining techniques. These techniques were validated through extensive simulation 

testing. The techniques include stepwise elimination of procedures through linear regression and 

a requirement for confirmation, whereby a procedure must be identified in two independent 

partitions. 

For the regression model, the theoretical conversion factor is the dependent variable. 

Independent variables include a dummy (or dichotomous) variable for each individual 

procedure (N = 681) and procedure group (N = 111)1 meeting our requirements, as well 

1

 Procedure groups are groups of codes representing similar procedures. These groups were defined by 

MEDSTAT. 

Comparing Medicare Physician
 

Payments to Private Payers 15 OEI-06-00-00570
 
Appendix C 

as controls – for the health care plan, rural/urban, and specialist/generalist. We did not control 

for geographic location because the GPCI was adjusted to reflect the full market variation in 

each Medicare locality.2 The initial regression model was the same in both partitions (see 

below). 

ì= $0 + [$1 (Xproc1) + $2 (Xproc2) + ... +$681 (Xproc681) ] + [$682 (Xgroup1) 

+ $683 (Xgroup2) + ... + $792 (Xgroup111) ] + [$793 (Xplan1) + $794 (Xplan2) + ... 

+ $839 (Xplan47) ] + $840 (Xspecialist) + $841 (X%urban

2

) + ,

ì = (payment for claimi / calculated RVU for procedurei) 

The regression was repeated more than 35 times, systematically dropping the independent 

variables (procedures and procedure groups) that appeared least likely to have a significant 

influence on the dependent variable (the theoretical conversion factor). After each iteration, we 

eliminated a pre-determined number of independent variables (i.e., procedures) exhibiting the 

largest p-value. The number of variables eliminated from each iteration was related to the 

number of variables remaining in the model, specifically twice the hundredth place of the 

number of independent variables. The regression sequence ceased at the point when all 

procedures and procedure groups remaining had a degree of significance that exceeded our 

threshold of p (where p is solved from: (1-p)# variables = 0.95).3 A further significance level was 

determined for the combined effect of the procedure and the procedure group on the 

dependent variable.4 Procedures with a combined significance of p (where p is solved from: 

(1-p) # of F tests = 0.95) are considered outliers in the distribution of procedures. The elimination 

process was repeated on a second randomly assigned partition of the MEDSTAT data. 

(Claims were randomly assigned into one of three independent partitions.) The results of the 

2 The GPCI, by design, reflects only about 60 percent of market variation. Policy makers believed that the 

Physician Work component of the RVU, reflecting the time and skill required of the physician, is not 

significantly affected by geographic variation. The CMS provided us with the formula used to squash the 

variation, so that we could adjust our data to fully reflect geographic variation as measured through the 

GPCIs. 

3

 In data mining, the conventional level of significance does not apply. “Lovell has suggested that if there 

are c candidate regressors out of which k are finally selected on the basis of data mining, then the true level 

of significance is related to the nominal level of significance as follows: alpha*=1-(1-alpha)c/k or 

approximately alpha*=(c/k)alpha. For this reason we kept our determining level of significance extremely 

conservative. So that variables would remain significant.” (Source: Guijarati, Damodar N., Basic 

Econometrics, Third Ed., McGraw-Hill Inc; New York: 1995. P.460-461.) 

4 An F-test using Restricted Least Squares (Testing for Linear Equality Restrictions) was used to determine 

the significance of the combined beta coefficients for procedure and procedure group. 

Comparing Medicare Physician 

Payments to Private Payers 16 OEI-06-00-00570
Appendix C 

two stepwise regressions were compared. Only procedures found to be significant in both 

partitions are reported. 

As mentioned, the simulation studies provide support for the accuracy of our findings. Artificial 

data were created with the same overall structure of the original data. Simulations were 

conducted in a number of ways. First, data were created with no deviant procedures. Hence, 

our data mining process should have no remaining variables, or procedures. Additional data 

was created with manufactured outlier procedures. In those cases, our data mining process 

should have identified the appropriate outliers. We found that the step-wise regression did yield 

some erroneous results, but that the requirement of findings to be in two independent partitions 

eliminated this problem. To further minimize the incidence of erroneous findings, we used 

exceptionally small p-values. The combination of these two techniques used was successful in 

eliminating erroneous results. 

Interpretation 

Identified codes, i.e., codes that remained as variables throughout both stepwise regressions, 

are the focus of our study. We suggest not that the values are incorrect, but that differences 

noted give cause for further study. Further, we suggest that a data-driven method is a feasible 

option in identifying codes for the 5-year review. However, the particular codes identified 

should be considered within the appropriate context. As these codes are the results of a data 

mining process, i.e., not standard statistical analysis, no confidence intervals or p-values are 

reported. Statistical tests of significance are used in the data mining process, but cannot be 

interpreted as results, for there was no defined hypotheses to test; rather our process identified 

outlier procedures. These procedures are outliers in the sense that per Medicare RVU 

payment is consistently different from the average procedure. 

Even though the construct of statistics does not uniformly apply, our analysis does use statistical 

methods. Those methods are susceptible to violations of statistical assumptions. In particular, 

the regression analysis included multicollinear variables, such that individual procedures are 

subsets of their respective procedure groups and potentially heteroskedastic variances resulting 

from any correlation between the plan variables and the residual error term. These limitations 

were known and considered before analysis began. 

Multicollinearity: We chose to include both procedures and procedure groups so that we 

might be able to identify differences affecting a whole family of codes as well as individual 

procedures. 

Comparing Medicare Physician 

Payments to Private Payers 17 OEI-06-00-00570
Appendix C 

Heteroskedasticity: The variance of our dependent variable may be influenced by the plan 

variable. A dummy variable was included for each plan present in our data, however, this does 

not capture interactions between plans and individual procedures. We chose not to include 

interaction variables because our model might have been compromised by a degrees of 

freedom problem, and also because the processing of such a voluminous model would have 

been too difficult for parameters of our study. A simulation study is underway to determine the 

extent to which heteroskedastic variances may have affected our results. Early indications 

suggest that heteroskedasticity did not influence our results. 

Comparing Medicare Physician 

Payments to Private Payers 18 OEI-06-00-00570
Appendix D 

Valuation differences
 

The codes identified in our study as being valued differently between Medicare and the private sector
 

are listed in this Appendix. These services’ relative values for the private insurers differ substantially
 

from those of Medicare’s RBRVS. Statistics are provided to give contextual information that may
 

assist the reader in interpreting the extent of difference.
 

.
 

Variable Names and Definitions 

CPTTM Current Procedural Terminology Code (used for billing purposes) 

Description Short description of the CPTTM code 

N	 Frequency of the procedure in the Commercial Claims and 

Encounters data. 

Beta	 Combined beta coefficient (from the step-wise regression) for the 

procedure and procedure group variables. Reflects the procedure’s 

impact on the theoretical conversion factor. 

Index The median of an index created for each procedure describing what 

Median percent of the Medicare Physician Fee Schedule was actually paid 

by the private industry, as represented in our data. 

Medicare The dollars (in thousands) allowed by Medicare in 1999 for each 

Volume service (includes deductibles and co-payments paid by the 

beneficiary). The total amount allowed for 1999 was $44.7 billion. 

The combined beta coefficient (Beta) may be interpreted as an addition or subtraction (as indicated by 

positive or negative value) to the average theoretical conversion factor. Recall that the conversion 

factor is the number you would multiply by the RVU to determine the total payment amount. The 

expected value is the average conversion factor for all services, which was found to be $34.07. This 

means that the Beta values would substantially add to or subtract from this number. For example, the 

Beta for CPTTM 10040 (-10.66) implies that the theoretical conversion factor for acne surgery is 

$23.41 ($34.07 - $10.66). If the RVU used for standardization reflected the entire variation between 

services, the payment for the service would have been the RVU multiplied by $34.07. As it stands, the 

payment for the service is the RVU multiplied by $23.41. 

Comparing Medicare Physician 

Payments to Private Payers 19 OEI-06-00-00570
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

10040 Acne Surgery 6776 -10.66 62.05% $1,404 

11042 Cleansing of Skin/Tissue 1060 9.9 114.04% $27,748 

11100 Biopsy of Skin Lesion 11171 -4.77 89.74% $66,232 

11200 Removal of Skin Tag 4060 -4.6 86.06% $4,837 

11300 Shave Skin Lesion 2511 -7.11 75.96% $2,410 

11400 Removal of Skin Lesion 2381 -9.59 66.43% $3,301 

11401 3313 -8.38 73.76% $6,971 

11402 2391 -4.26 87.70% $9,177 

11421 1264 -6.33 80.46% $3,824 

11440 1259 -6.77 82.57% $5,238 

11719 Trim Nail(s) 294 -17.02 34.88% $9,969 

11732 Remove Additional Nail Plate 411 7.52 110.62% $3,396 

11750 Removal of Nail Bed 3733 8.72 131.44% $28,863 

11900 Injection into Skin Lesion 2764 -5.22 81.83% $2,581 

12031 Layer Closure of Wound(s) 693 -6.64 83.21% $2,509 

17000 Destruction of Facial Lesion 36014 -3.79 84.46% $130,619 

17003 Destroy Lesions, 2-14 21042 15.04 99.55% $137,151 

17110 Destruction of Skin Lesions 3383 -6.82 77.85% $2,814 

17340 Cryotherapy of Skin 953 -17.03 58.31% $829 

19100 Biopsy of Breast 732 17.36 103.85% $2,706 

19290 Place Needle Wire, Breast 1196 10.67 113.31% $4,921 

20550 Inject Tendon/Ligament/Cyst 11520 -7.93 74.15% $50,316 

20600 Drain/Inject Joint/Bursa 4353 -6.39 74.85% $16,302 

20605 5590 -8.38 68.61% $20,232 

20610 13770 -9.13 79.12% $133,139 

21320 Treatment of Nose Fracture 108 19.81 147.38% $197 

Comparing Medicare Physician
 

Payments to Private Payers 20 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

29065 Application of Long Arm Cast 334 -15.46 56.39% $1,041 

29075 Application of Forearm Cast 1478 -17.27 47.99% $4,292 

29085 Apply Hand/Wrist Cast 160 -16.57 48.42% $288 

29125 Apply Forearm Splint 811 -8.3 61.31% $1,500 

29405 Apply Short Leg Cast 1073 -14.29 65.34% $3,272 

29425 956 -12.55 58.19% $3,221 

29540 Strapping of Ankle 2545 -6.08 87.97% $5,028 

29880 Knee Arthroscopy/Surgery 505 13.09 140.43% $24,381 

29881 2328 7.91 118.07% $38,313 

29888 694 7.03 112.66% $822 

30130 Removal of Turbinate Bones 304 -10.05 60.64% $676 

31254 Revision of Ethmoid Sinus 357 15.8 147.45% $2,024 

31255 Removal of Ethnoid Sinus 907 21.16 154.11% $10,402 

31256 Exploration Maxillary Sinus 714 12.58 128.28% $2,408 

31575 Diagnostic Laryngoscopy 2460 6.16 114.22% $31,208 

36000 Place Needle in Vein 1273 17.03 133.59% $1,644 

36005 Injection, venography 171 22.16 146.93% $2,895 

36410 Drawing Blood 1414 -5.78 65.78% $3,666 

36425 Drawing Blood 116 -33.15 8.87% $296 

36489 Insertion of Catheter, Vein 453 21.93 154.35% $54,502 

42820 Remove Tonsils and Adenoids 1054 17.41 160.99% $5 

45300 Proctosigmoidoscopy 931 -15.73 49.40% $5,332 

45330 Sigmoidoscopy, Diagnostic 7845 -3.56 70.57% $42,585 

45384 Colonoscopy 1541 21.58 178.26% $77,739 

46083 Incise External Hemorrhoid 177 -13.96 64.19% $288 

50590 Fragmenting of Kidney Stone 1050 11.96 149.77% $23,062 

Comparing Medicare Physician
 

Payments to Private Payers 21 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

51700 Irrigation of Bladder 445 -21.45 44.89% $3,240 

51720 Treatment of Bladder Lesion 378 -12.60 62.40% $17,684 

52000 Cystoscopy 3334 4.94 112.29% $107,817 

53660 Dilation of Urethra 228 -21.29 42.52% $2,222 

53661 367 -23.35 36.65% $3,858 

53670 Insert Urinary Catheter 1237 -24.88 33.16% $6,718 

54161 Circumcision 279 14.19 153.56% $2,728 

56501 Destruction, Vulva Lesion(s) 335 -11.2 65.92% $255 

57452 Examination of Vagina 943 7.08 114.72% $1,075 

57454 Vagina Examination & Biopsy 3617 15.64 141.06% $3,111 

57460 Cervix Excision 347 32.86 192.37% $408 

57522 Conization of Cervix 377 24.18 151.27% $721 

58120 Dilation and Curettage (D&C) 935 10.17 116.95% $7,387 

59425 Antepartum Care Only 573 -21.44 17.22% $146 

59426 Antepartum Care Only 1338 -9.76 82.48% $252 

59430 Care After Delivery 602 -6.45 82.27% $43 

60001 Aspirate/Inject Thyroid Cyst 242 -33.77 6.85% $129 

62275 Inject Spinal Anesthetic 185 34.09 159.15% $4,983 

62278 730 22.57 153.63% $21,919 

62279 277 56.68 228.44% $10,316 

62284 Injection for Myelogram 1238 33.87 202.28% $15,492 

62289 Injection into Spinal Canal 2608 20.71 159.76% $78,602 

64443 Injection for Nerve Block 790 19.18 132.45% $17,781 

64450 1295 -6.02 74.23% $7,723 

64550 Apply Neurostimulator 350 22.97 170.08% $384 

64721 Carpal Tunnel Surgery 1074 8.82 117.99% $30,164 

Comparing Medicare Physician
 

Payments to Private Payers 22 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

66761 Revision of Iris 189 12.77 137.83% $19,175 

66821 Lasering, Secondary Cataract 562 19.75 167.52% $198,749 

66984 Remove Cataract, Insert Lens 2656 3.37 118.20% $1,854,895 

67210 Treatment of Retinal Lesion 721 7.84 139.16% $111,761 

67800 Remove Eyelid Lesion 405 -17.29 51.81% $2,711 

68761 Close Tear Duct Opening 907 -16.74 51.84% $18,322 

69210 Remove Impacted Ear Wax 4445 -11.56 64.90% $31,396 

69421 Incision of Eardrum 145 29.18 188.88% $131 

69424 Remove Ventilating Tube 116 31.96 127.57% $75 

69436 Create Eardrum Opening 3693 14.7 148.38% $1,960 

69990 Microsurgery Add-on 366 27.17 175.38% $5,878 

77263 Radiation Therapy Planning 1004 16.19 129.89% $38,249 

77336 Radiation Physics Consult 1969 -14.3 60.28% $44,926 

77408 Radiation Treatment Delivery 132 32.62 117.55% $5,309 

77413 4389 3.65 121.32% $93,484 

77414 1133 5.3 122.54% $40,010 

77416 492 9.08 121.32% $10,224 

77419 Weekly Radiation Therapy 262 46 242.31% $18,071 

77420 273 53.28 288.17% $7,313 

77425 252 53.11 241.52% $11,024 

77430 4748 35.42 236.43% $189,271 

80500 Lab Pathology Consultation 455 12.76 148.91% $1,326 

85102 Bone Marrow Biopsy 402 -10.91 64.85% $10,038 

86580 TB Intradermal Test 6925 -10.27 68.29% $1,010 

86585 TB Tine Test 2298 -9.96 70.62% $189 

88141 Cytopath, C/V, Interpret 84.20 -4.4 94.48% $3,634 

Comparing Medicare Physician
 

Payments to Private Payers 23 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

88329 Pathology Consult in Surgery 407 18.3 146.70% $1,914 

90781 IV Infusion, Additional Hour 3160 13.85 123.97% $15,404 

90782 Injection (SC)/(IM) 30039 6.56 127.64% $7,095 

90784 Injection (IV) 3177 3.25 116.40% $1,150 

90788 Injection of Antibiotic 3112 7.01 130.54% $62 

90801 Psychiatric Interview 7182 -7.71 79.09% $111,387 

90804 PSYTX, Office, 20-30 Min. 2182 -6.73 89.17% $31,838 

90805 PSYTX, Off, 20-30 Min w/E&M 15060 -4.81 85.17% $83,314 

90806 PSYTX, Off, 45-50 Min 23072 -5.34 84.46% $281,209 

90807 PSYTX, Off, 45-50 Min w/E&M 18329 -3.29 90.03% $105,222 

90847 Special Family Therapy 1920 -7.8 77.86% $8,280 

90862 Medication Management 30111 -2.73 97.31% $196,791 

90870 Electroconvulsive Therapy 538 23.1 146.50% $13,220 

90925 ESRD Related Services, Day 1952 147.56 133.65% $79,236 

90937 Hemodialysis, Repeated Eval. 105 19.61 113.74% $26,561 

92002 Eye Exam, New Patient 1649 -9.44 76.58% $13,585 

92004 6373 -11.54 69.83% $136,603 

92012 Eye Exam, Established Patient 10760 -15.22 59.71% $238,022 

92014 13915 -11.52 71.82% $431,473 

92020 Special Eye Evaluation 938 -9.58 74.63% $13,013 

92225 Special Eye Exam, Initial 1678 -11.17 63.66% $29,074 

92226 Special Eye Exam, Subseq 1996 -12.52 56.96% $49,906 

92504 Ear Microscopy Examination 886 -13.58 63.14% $2,335 

92552 Pure Tone Audiometry, Air 2416 -10.07 71.86% $1,550 

92553 Audiometry, Air & Bone 826 -10.44 71.51% $1,702 

92555 Speech Threshold Audiometry 562 -10.13 74.51% $122 

Comparing Medicare Physician
 

Payments to Private Payers 24 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

92556 Speech Audiometry, Complete 387 -10.10 76.67% $553 

92557 Comprehensive Hearing Test 5393 -10.34 71.96% $36,788 

92567 Tympanometry 10426 -11.34 69.93% $13,189 

92568 Acoustic Reflex Testing 1563 -10.40 74.51% $3,824 

93000 Electrocardiogram, Complete 53768 -1.72 88.92% $260,332 

93010 Electrocardiogram Report 20110 14.80 123.24% $175,713 

93016 Cardiovascular Stress Test 5406 14.64 120.38% $26,600 

93018 Cardiovascular Stress Test 6810 34.08 135.89% $24,606 

93041 Rhythm ECG, Tracing 161 46.39 127.68% $1,078 

93042 Rhythm ECG, Report 2097 23.70 167.88% $14,123 

93227 ECG Monitor/Review, 24 hrs 1107 23.43 137.93% $10,670 

93233 ECG Monitor/Review, 24 hrs 235 26.54 146.72% $4,102 

93539 Injection, Cardiac Cath 190 25.07 168.13% $4,211 

93540 206 19.59 172.81% $6,018 

93543 Injection for Heart X-Rays 2372 35.49 163.72% $20,708 

93544 Injection for Aortography 202 49.13 178.22% $2,469 

93545 Injection for Coronary X-Rays 2546 44.44 194.76% $34,958 

93798 Cardiac Rehab/Monitor 1616 8.89 144.86% $9,304 

94668 Chest Wall Manipulation 186 50.35 175.24% $201 

94760 Measure Blood Oxygen Level 7613 -3.19 79.31% $16,911 

95004 Allergy Skin Tests 6378 1031.06 2869.69% 

% 

$13,852 

95010 Sensitivity Skin Tests 153 143.13 315.71% $370424 

95015 242 121.88 268.39% $563 

95024 Allergy Skin Tests 5157 406.57 954.58% $9,722 

95027 Skin End Point Titration 171 148.24 85.13% $301 

95028 Allergy Skin Tests 181 327.63 656.18% $1,817 

Comparing Medicare Physician
 

Payments to Private Payers 25 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

95044 Allergy Patch Tests 571 154.48 63.36% $2,481 

95115 Immunotherapy, One Injection 83613 -16.15 57.91% $19,867 

95117 Immunotherapy Injections 88880 -14.67 59.21% $23,785 

95144 Antigen Therapy Services 1961 95.58 400.19% $3,016 

95147 213 43.17 126.75% $304 

95148 135 48.26 120.11% $244 

95165 29245 203.57 590.67% $39,070 

95851 Range of Motion Measurements 716 12.06 106.26% $1,329 

96400 Chemotherapy, (SC)/(IM) 1117 13.11 112.66% $3,955 

96408 Chemotherapy, Push Techniques 4828 -3.38 92.95% $25,300 

96412 Chemotherapy, Infusion Method 4897 5.88 99.17% $49,708 

96900 Ultraviolet Light Therapy 858 -8.96 70.88% $1,075 

96910 Photochemotherapy with UV-B 1869 -9.78 67.57% $3,245 

96912 Photochemotherapy with UV-A 1713 -7.98 74.29% $2,763 

97001 PT Evaluation 2043 4.17 107.29% $25,121 

97002 PT Re-Evaluation 699 11.28 139.01% $2,766 

97012 Mechanical Traction Therapy 1813 7.22 116.28% $3,848 

97014 Electric Stimulation Therapy 6823 9.47 118.47% $26,831 

97022 Whirlpool Therapy 1562 8.12 116.72% $3,003 

97032 Electrical Stimulation 3821 8.09 110.13% $21,704 

97033 Electric Current Therapy 1095 17.14 151.31% $985 

97035 Ultrasound Therapy 10195 8.21 110.01% $41,306 

97112 Neuromuscular Re-Education 3178 8.47 117.30% $20,806 

97113 Aquatic Therapy/Exercises 465 41.02 203.42% $6,296 

97116 Gait Training Therapy 443 14.07 141.19% $5,512 

97124 Massage Therapy 2447 10.36 124.67% $33,919 

Comparing Medicare Physician
 

Payments to Private Payers 26 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

97140 Manual Therapy 9037 28.54 173.71% $40,579 

97530 Kinetic Therapy 6698 20.84 144.59% $49,135 

97703 Prosthetic Checkout 211 71.65 202.86% $65 

97750 Physical Performance Test 296 18.82 145.75% $1,897 

97770 Cognitive Skills Development 142 78.39 279.50% $881 

99183 Hyperbaric Oxygen Therapy 442 47.64 155.12% $19,566 

99195 Phlebotomy 735 -11.47 71.89% $941 

99201 Office/Outpatient Visit, New 20043 -8.46 82.26% $22,976 

99202 78872 -9.32 76.57% $151,700 

99203 90193 -9.61 75.66% $299,082 

99204 39612 -9.07 76.48% $287,602 

99205 17179 -8.14 79.53% $160,215 

99211 Office/Outpatient Visit, Est. 73020 -11.66 67.99% $139,113 

99212 431696 -8.02 81.68% $845,031 

99213 1002696 -6.74 81.84% $3,611,097 

99214 270251 -7.8 77.89% $2,219,555 

99215 Office/Outpatient Visit, Est. 60972 -6.16 83.73% $572,393 

99231 Subsequent Hospital Care 4122 7.07 114.96% $836,347 

99232 5815 3.83 105.53% $1,962,425 

99241 Office Consultation 6759 -5.09 86.69% $23,416 

99242 17564 -6.52 83.83% $104,737 

99243 32037 -6.24 83.17% $289,705 

99244 29912 -6.39 84.74% $452,636 

99245 12572 -5.64 85.41% $267,320 

99281 Emergency Dept. Visit 2600 17.67 153.51% $6,106 

99282 17006 15.75 139.30% $49,780 

Comparing Medicare Physician
 

Payments to Private Payers 27 OEI-06-00-00570
 
Appendix D 

CPTTM Description N Beta Index 

Median 

Medicare 

Volume 

(in $1,000s) 

99283 44568 9.77 134.93% $279,184 

99284 21491 9.91 135.33% $425,949 

99285 6531 8.77 118.30% $462,377 

99292 Critical Care, Add’l 30 Min. 152 19.20 128.27% $26,845 

99433 Normal Newborn Care, Hospital 940 7.51 122.42% $1 

A4263 Permanent Tear Duct Plug* 279 29.86 162.74% $3,038 

A4550 Surgical Trays* 7016 30.41 149.25% $4,647 

G0101 CA Screen; Pelvic/Breast Exam 6388 42.36 219.11% $10,097 

Q0091 Scrn Pap Smear Obtain Prep&Con 574 -26.67 22.93% $8,284 

*Codes now bundled with primary service for global payment. 

Comparing Medicare Physician 

Payments to Private Payers 28 OEI-06-00-00570
A C K N O W L E D G M E N T S 

This report was prepared under the direction of Judith V. Tyler, Regional Inspector General for 

Evaluation and Inspections in Dallas, TX. Inspections staff who contributed include: 

DALLAS 

Amy Ashcraft, Project Leader 

Kevin Golladay, Team Leader 

SAN FRANCISCO 

Robert Gibbons 

Comparing Medicare Physician 

Payments to Private Payers 

HEADQUARTERS
 

Stephanie Lattin, Program Specialist
 

29 OEI-06-00-00570