Department of Health and Human Servces


OFFICE OF


INSPECTOR GENERAL


NATIONAL DRG VALIDATION STUDY


UPDATE: TECHNICAL REPORT


AUGUST 199

OFFCE OF INSPECfOR GENRA 

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 U.S. Department of Health and 

Human Servces (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 three OIG operating 

components: Office of Audit Servces (OAS), Office of Investigations (01), and Offce 

of Evaluations and Inspections (OEI). The OIG also informs the Secretary of HHS 

program and management problems and recommends actions to correct them. 

OFFCE OF AUDIT SERVICE 

The OAS provides all auditing servces for HHS, either with its own resources or by 

overseeing work done by others. Audits examine the performance of HHS programs 

and/or its grantees and contractors in carrng out their respective responsibilties. 

Audits provide independent assessments of HHS programs and operations in order to 

reduce waste, abuse, and mismanagement; and to promote economy and effciency 

throughout the Department. 

OFFCE OF INTIGATIONS 

The 01 conducts criminal, civil, and administrative investigations of alleged 

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

providers. The investigative efforts of 01 lead to criminal convictions, administrative 

sanctions, or civil money penalties. The 01 also oversees State Medicaid fraud control 

units which investigate and prosecute fraud and patient abuse in the Medicaid 

program. 

OFFCE OF EVALUATION AN INSPECfONS 

The OEI conducts short-term management and program evaluations (called 

inspections) that focus on issues of concern to the Department, Congress, and public. 

The findings and recommendations contained in these inspection reports generate 

rapid, accurate, and up-to-date information on the efficiency, vulnerabilty, and 

effectiveness of departmental programs. 

BOTEC Analysis Corporation prepared this report under the direction of Janet 

Wilson Knight. Contract information and project participants appear in appendices 

and 2. 
Department of Health and Human Servces


OFFICE OF


INSPECTOR GENERAL


NATIONAL DRG VALIDATION STUDY


UPDATE: TECHNICAL REPORT


AUGUST 199 OEI-12-89-191

EXECUTIVE SUMMAR 


PUROSE 

This inspection reabstracted the International Classification of Diseases, 9th Edition Clinical Modification (lCD- CM) codes from a sample of Medicare discharges on a blinded basis. It compared the resulting diagnosis-related group (DRG) to the 

hospital's DRG to determine over-reimbursement or under-reimbursement. . The sample was nationally representative and covered all of calendar year 1988, the most recent data available. 

This study updates a previous inspection from the Offce of Inspector General (OIG). It found that 20.8 percent of 1985 Part A bils contained coding errors that changed the DRG and that 61.7 percent of these errors over-reimbursed the hospitals. This

improper DRG "creep" increased total prospective-payment system (PPS) disbursements by 1.9 percent or $308 milion. 

FIINGS 

DRG coding error reduced : 14.7 percent of 1988 discharges had DRG coding errors. This proportion of coding errors was statistically significantly lower than the 20. percent reported for 1985. 

DRG creep eliminated: 51 percent of DRG errors over-reimbursed the hospital and 49 percent under-reimbursed the hospital. 

DRG coding errors. overall. no longer over-reimburse hospitals: Taken together, 1988 DRG errors had the net financial effect of under-reimbursing all hospitals a 

statistically non-significant $69.8 milion, or 0. 1 percent of the $52 bilion in 1988 PPS disbursements. Projected nationally" over-reimbursements totaled $2 657.8 milion and 

under-reimbursements totaled $2 588.0 bilion. 

Mis-specification errors under-reimbursed the hospitals: Of the 361 DRG errors in the 

sample, 63.2 percent occurred because the attending physician mis-specified the narrative diagnoses. Of these 227 mis-specification errors, only 43.2 percent overreimbursed the hospitals. The statutorily-required attestation probably reminded physicians of their obligation to select accurate narrative diagnoses. 

Resequencing errors over-reimbursed the hospitall: Of the 361 DRG errors in the 

sample, another 26.6 percent occurred because the hospital substituted a secondary 

diagnosis for the (correct, narrative) principal diagnosis. Of these 96 resequencing 

errors, 66.7 percent over-reimbursed the hospitals. The sentinel effect of the Peer Review Organizations surveilance apparently did not fully prevent overreimbursement due to resequencing. 
REMMATIONS 

The Peer Revew Organtions should contiue their sureilance of hospita cog for DRG reimbmsement accmacy. 

The attestation requirement appears to have deterred over-reimbursement due to 

mis-'specifcation by attendig physicians, causing their hospitals to be underreimbursed. However, the sentinel effect did not fully prevent over-reimbursement 

due to resequencing by hospitals. Although these two trends approxiately offset each other, this equilbrium may not continue in the future. 

The Agency for Health Care Policy Research plans to reabstract the ICDcodes from a large sample of Medicare charts to determe their diagnostic

accuracy for health servces research purposes. Using 1991 data, grouping these ICD- CM codes to DRGs, and selecting reasons for any diferences would provide 

a third time point with which to track trends in reimbursement accuracy. The OIG supports this effort. 

AGENCY COMM 

In its May 29, 1992 comments to the draft of this inspection, the Health Care Financing Agency (HCFA) concurred with the OIG recommendation. The HCFA noted that the improvement in DRG coding accuracy may be attributable to increased 

hospital experience with PPS, PRO review, and HCF A educational efforts. 

The HCF A also made a number of technical comments. Based on these comments 

the OIG made several changes to this report. The full text of the HCF A comments 

appear as an appendix. 
. . . . . . . . . . . . . 

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iii 

TABLE OF CONTENTS


EXECUTIVE SUMMAY. . . 

TABLE OF CONTENTS 

INODUCfION 

ORIGIN OF TH PRESENT STUY 

1983-1988 GROUPER CHAGES


PAYMNT ISSUES


METHODOLOGY


SAMPLE DESIGN. . . . . 

DATA COLLECTION 

DRG REABSTRCTION .............................. 6 

ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

REPRESENTATIVNES .................................. 9


FININGS. . 

DRG CODING ERROR REDUCED 

EQUAL NUMBERS OF DRG ERRORS OVER-REIMBURSE AND 

UNDER-REIMURSE. . 

DRG CREEP ELIMINATED 

DRG OVER-REIMURSEMENT ELIMINATED 

MIS-SPECIFICATION UNDER-REIMBURSES, WHILE 

RESEQUENCING OVER-REIMURSES 

CERTAI DRGS ARE MORE SUSCEPTIBLE TO ERROR. . . 

RECOMMNDATIONS 

ENDNOTES 

Appendix 3: Calculation formulas 

Appendix 4: Representativeness of selected discharges, 1988 

Appendix 5: Nonresponses, 1988 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Appendix 6: Proportion of DRG coding errors by hospital demography, 1988. 

Appendix 7: Proportion of DRG coding errors by patient demography, 1988 

Appendix 1: Contra

Appendix 2: Project participants 
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. ... .. ... ............... ..................... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

. . . . . . . . . . . . . . . . . . . . ............. . . . . . . . . ... .. . . . .

1988 

Appendix 8: Interaction potential by hospital and patient demography, 1988 .


Appendix 9: Projected national CMI before recoding by hospital demography, 

Appendix 10: Projected national CMI before recoding by patient demography, 

1988 . . . . . . . . . . . . . . . . . . .


Appendix 11: Projected national CMI after recoding by hospital demography, 

1988 ... 


Appendix 12: Projected national CMI after recoding by patient demography, 

1988 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 


Appendix 13: Mean CMI change by hospital demography, 1988 . . . . . . . . . . .


Appendix 14: Mean CMI change by patient demography, 1988 ...........


Appendix 15: Mean reimbursement change by hospital demography, 1988 ...


Appendix 16: Mean reimbursement change by patient demography, 1988 . . . .


Appendix 17: Number of bils by hospital demography, 1988 


Appendix 18: Number of bils by patient demography, 1988 . . . . . . . . . . . . . .


Appendix 19: Projected reimbursement effect by hospital demography, 1988 .


Appendix 20: Projected reimbursement effect by patient demography, 1988 . .


Appendix 21: DRG frequency, error frequency, and error proportion by


proportion of errors, 1988 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 


Appendix 22: Mean weight, dollar change, and estimated national financial


effect by DRG, 1988 . . . . . . . . . . .


Appendix 23: HCFA comments. . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . 
INTRODUCTION


Since the inception of the Medicare program, health care expenditures have grown 

faster than the rest of the economy, and the Medicare program has grown even faster 

than general health care expenditures. The need for innovative reimbursement 

policies and their evaluation has become critical to medical communities, beneficiaries 

and payers of the Medicare program. 

ORIGIN OF TH PREENT STUY 

Since 1965, Medicare has provided hospital and medical insurance to the nation 

elderly and disabled. However, rapidly escalating health care costs coupled with a 

rise in the proportion of the population eligible for Medicare have burdened its 

hospital insurance trust fund (Part A). Health care costs accounted for 7.4 percent of 

the gross national product in 1970, 9. 1 percent in 1980, and 10.9 percent in 1986. In 

1970, Medicare paid 8 percent of all health care costs, but by 1986 Medicare 

proportion increased to 17 percent.


In 1983 Congress changed Medicare inpatient reimbursement from a retrospective 

reasonable-cost basis to a prospective-payment system (PPS).3 Under the PPS 

hospital payments depended upon the patient's diseases and procedures as defined by 

the International Classification of Diseases, 9th Edition, Clinical Modification (ICDCM).4 The PPS "grouped" various combinations of the approxiatelllO OOO ICDCM codes into 470 (currently 476) diagnosis-related groups (DRGs). By reimbursing the average cost of care for each DRG, the PPS provided incentives for efficient 

/ delivery of health care. The Veterans Administration Medical System Resource 

. Allocation Method emulated this change. 

A hospital fies a claim for Medicare payment at the time of patient discharge. The

attending physician writes the narrative diagnoses and procedures on the face sheet; 

and attests to the principal diagnosis, secondary diagnoses, and any procedures. The 

hospital' s medical records department then assigns numeric, ICD- CM codes to the 

narrative diagnoses and procedures, using the rules of the Uniform Hospital Discharge 

Data Set (UHDDS), "a minimum data set used by HHS programs to collect data on 

individual hospital discharges on a continuing basis."6 The hospital's billng 

department enters up to five diagnoses and three procedure codes on the Medicare 

claim form. A Fiscal Intermediary (FI) receives the hospital bils for each State. 

runs GROUPER software to select the correct DRG by assessing diagnosis and procedure codes. It then runs PRICER software that adjusts for geographic location 

teaching costs, and other factors to calculate the payment due to the hospital. 

Since 1976 the Office of the Inspector General (OIG) has had responsibilty for


protecting the integrity of the programs and program beneficiaries of the U.


Department of Health and Human Servces (HHS).7 Following this statutory


mandate, the OIG commissioned the 1985 National DRG Validation Study (1985


Study), which examined how the processes that assigned diagnosis and prQcedure

codes affected the accuracy of PPS reimbursement for Medicare discharges.s The 

1985 Study analyzed a representative, national sample of medical records to obtain 

information on the accuracy of the diagnosis and procedure coding, the impact of 

coding errors on DRG assignment, and the potential net financial impact of coding

errors. It also assessed the appropriateness and quality of the servces provided to 

Medicare patients. 

The 1985 Study found an overall error proportion of 20.8 percent in assigning DRGs. 

In 61.7 percent of the errors, the hospitals over-reimbursed themselves. Physicians 

mis-specification of narrative diagnoses and hospital biling departments' resequencing 

of diagnoses caused most errors. These errors caused $308 milion in overpayments to 

hospitals, 1.9 percent of 1985 PPS reimbursement. 

The Health Care Financing Administration (HCF A), as the payer of the Medicare 

reimbursements, made the following points in commenting on the 1985 Study. 

The PPS started in 1983. The 1985 Study data covered FY 1985. Physicians 

hospital coders, and Peer Review Organizations (PROs) needed a longer learning 

period to adjust to the new payment and quality monitoring system. 

The 1985 Study appeared in 1987, so that its conclusions derived in part from 

information and coding conventions that had undergone updating by that time. 

The HCF A and hospital associations recently had begun to conduct training 

seminars for hospital personnel. The HCF A therefore expected that coding errors 

would decrease over time. 

To examine these trends, the OIG initiated this follow-up project, implemented 

through contracts with the Health Data Institute (HDI) of Lexington, Massachusetts; 

American Medical Records Association (AMRA) of Chicago, Ilinois; and BOTEC 

Analysis Corporation (BOTEC) of Cambridge, Massachusetts using 1988 data. This 

DRG Validation Study Update (1988 Study) had the purpose of determining how the 

PPS' s coding accuracy changed over time. The OIG designed this inspection to meet the followig objectives. 

Replicate the 1985 work on coding accuracy, using 1988 data. 

Compare the findings from 1985 and 1988. 

Identify patterns of coding errors that PPS changes could modify. 

As in the previous study, this inspection assessed how coding errors affected hospital 

reimbursement and identified the coding problems most subject to error. It evaluated 

hospital and beneficiary characteristics for their relative contribution to DRG errors. 
198-1988 GROUPER CHGES 

The HCF A annually updates the taxonomy by which the ICD- CM codes group to 

DRGs.lO 11 1213 14 15 16 17 It seeks to improve the GROUPER' s fairness 

without a negative effect on patient quality of care. The adjustments respond to 

comments and suggestions from providers and administrators who work with the PPS 

in the field. The HCFAadopted the following major changes to the GROUPER from 

1985 to 1989.


DRG 471 (majQLnt procedures): In FY 1986, the HCFA created DRG 471 to 

include bilateral multiple major joint procedures. 

DRG 433-438 (alcohol and drug a : In FY 1986, the HCF A completely 

reclassified these DRGs and dropped DRG 438. The exclusion of drug and alcohol 

treatment facilties from the PPS ended as of FY 1988 (October 1, 1987). 

HIV codes: In FY 1986, the HCFA incorporated the newly created ICD- CM codes 

for HIV. This disease formerly fell into ICD- CM diagnosis code 279. 19 (other 

deficiency of cell-mediated immunity) which grouped to DRGs 398 and 399 (immunity 

disorders). Mter 1986, AIS grouped to infectious disease DRGs. 

DRG 385 (newborn transfers): In FY 1987, the HCFA reclassified DRG 385


(neonates, died or transferred) so that it applied only to transfers to another acute


care facilty.


DRG 472 (burns): In FY 1987, the HCFA changed DRG 457 to "extensive burns 

. without an operating room procedure" and created DRG 472 for "extensive burns with 

operating room procedures. 

DRG 473 (leukemia): In FY 1987, the HCFA removed acute leukemia cases in 

patients over age 17 from DRGs 401-405 and placed them in the new DRG 473. 

Age over 69: In FY 1988, the HCF A eliminated "age over 69" as a criterion in all of 

the DRG pairs in which "age over 69" and/or complication-comorbidity (CC) was a 

factor. The HCFA continues to use "age under 18" in certain pediatric DRGs and to 

use "age 35" in DRG 294 (diabetes) and "age 0-35" in DRG 295 (diabetes). 

DRG 103 (heart transplant) : This DRG did not have a relative weight assigned until

FY 1988. 

DRG 474 and DRG 475 (ventilators): In FY 1988, the HCFA created DRG 474 

(respiratory system diagnosis with tracheostomy) and DRG 475 (respiratory system 

diagnosis with ventilator support) to separate the resource intensive ventilator cases 

from other respiratory DRGs. 
Complication-comorbidity exclusions: In FY 1988, the HCF A implemented the 

exclusion list for complications and/or comorbidity, which is based on the principal 

diagnosis. The HCFA has made changes to this list each year. 

DRG 468 (unrelated operat ng room procedures): Each year, the HCFA has further 

refined this DRG by assigning more of its procedure codes to other specific DRGs. - FY 1989, two new DRGs were created in order to split DRG 468 even further: DRG 

476 (prostatic operating room procedure unrelated to principle diagnosis) and DRG 477 (non-extensive operating room procedure unrelated to principle diagnosis). 

Surgical hierarchies: Every year, the HCF A examines the surgical hierarchies for the 

GROUPER computer software logic and makes numerous changes. 

Each year, the relative weights change to reflect alterations in resource consumption 

coding, surgical hierarchy, and further DRG refinements. The HCFA presently tends to expand the DRG list with more specificity in each DRG. This taxonomic splitting allows the providers and hospitals to account for resource utilzation more accurately 

rather than averaging high and low utilzation conditions in the same DRG, but at the cost of greater reimbursement complexity. The OIG has a more detailed description of GROUPER changes that it will supply upon request. 

PAYMNT ISUE


The 1985 Study alludes to two probable sources of DRG coding error: random human 

error and systematic bias inherent to the coding system. First, error occurs naturally ./ in every human endeavor. Presumably, over the PPS's five years of operation, general 

. knowledge of the coding process increases and the overall error rate decreases. 

Whether due to time pressure or want of education, any human coding errors should 

occur stochastically, not favoring either the hospitals or Medicare. However, the 1985 

Study finds intentional "gaming" or manipulating the coding process, not random variabilty.1S 19 " 

Second, the DRG coding system may have inherent contradictions that make errors 

and inaccuracies inevitable. Certain DRGs or their underlying ICD- CM codes have 

high frequencies of coding error. For example, DRG 99 (respiratory signs and symptoms) has a high error rate because of it lacks a definite diagnosis and represents 

a cluster of symptoms. The DRG system may "build in" this tye of variation. 

In addition, some commentators propose modifyng the PPS to adjust for severity of 

ilness.20 This modification measurement would increase the precision with which 

relative weights model actual resource consumption. However, unpublished data submitted to the HCF A indicates that severity reduces DRG variance by only onethird. In addition, collecting sufficient clinical data to quantify severity imposes 

significant transaction costs. 
The PPS could also systematically overpay or underpay certain classes of hospitals. 

The most complicated and resource-intensive procedures, such as organ transplants 

are rarely scheduled in small, nonmetropolitan hospitals. They therefore have no 

opportunity for the substantial reimbursement (or under-reimbursement) that 

accompanies such servces. Conversely, medium-sized hospitals may attempt such


procedures but with relative inefficiency compared to the higher volume at large


metropolitan, teaching hospitals.


MEODOLOY 

The 1988 National DRG Validation Study Update used essentially the same methods 

as its predecessor study. 

SAPLE DESIGN


The initial study population consisted of the 10.8 milion Medicare funded discharges 

for calendar year 1988 from the 6 715 acute care, short-stay hospitals in the United 

States.21 The design then excluded discharges from specialty institutions such as 

children s hospitals, tuberculosis units, and psychiatric facilties. It also excluded 

discharges in Maryland and New Jersey, which were stil exempt from the PPS in 1988. 

It covered final bils only, omitting interim bils. It excluded bils for pediatric 

obstetric, and psychiatric DRGs (principally drug and alcohol rehabiltation performed 

by a general hospital). Unlike its fiscal year (FY) 1985 predecessor, it included 

hospitals established since the advent of PPS in 1983. 

/ The HCF A required two quarters following the close of a year to accumulate bils 

paid by its fiscal intermediaries and combine the reimbursement data into computer 

files. This administrative data consolidation imposed a continuous lag on the 

availability of information defining the study population. Accordingly, billing data for 

CY 1988 became available in the middle of 1989. 

The 1988 National DRG Validation Study Update used a two-step, non-clustered 

sampling procedure. The first step selected all bils whose Health Insurance Claim 

(HIC) numbers terminated in 95, a one percent, simple, random sample (SRS) of all 

. Medicare biling records for calendar year (CY) 1988. The OIG screened out interim 

bils, exempt States, non-acute care hospitals, and nongeriatric DRGs as described 

above (n=88 455). Starting from a random seed, the second step systematically 

sampled lout of every 33 of the biling records selected in the first step for a final 

sample size of 2 680. This process resulted in a self-weighting SRS. Oversimplified 

each sample biling record represented 3 300 biling records in the total population of 

biling records.


These discharges came from 1 744 hospitals, 26.0 percent of the acute care, short-stay hospitals that accept Medicare patients. The hospitals represented 47 of the 54 States 

or other jurisdictions (District of Columbia, Puerto Rico, Guam, Virgin Islands) that the HCF A recognizes. Since there was no stratification or clustering, most hospitals 
.. 

contributed only one discharge to the sample. No hospital contributed more than nine 

discharges. 

DATA COLLCTON 

The OIG ran SAS on the HCF A's mainframe ffM 3090 to sort the sample by HCF A 

hospital identification numbers and match-merge the sample with the HCF A fie of 

provider addresses. It then used WordPerfect software running on a Zenith Z-248 

personal computer to produce mailng labels and "personalized" letters from the 

resulting address fie. Each letter requested that the hospital's medical records 

department send complete copies of the sampled medical records to the OIG' 

contractor, HDI. Each mailng included a franked, addressed envelope and promised 

to reimburse the hospitallOC: per page for its copying costs. The OIG made 

additional mailngs and the HDI made follow up telephone calls to those medical 

records departments which did not provide the requested records. Although phrased 

as a request, all contacts communicated that hospital participation was mandatory. 

The majority of hospitals promptly supplied the requested medical records. Four 

hospitals declined to participate as requested, so the OIG issued subpoenas compellng 

their cooperation. Medical records departments could not provide 229 sampled 

records principally because they were missing, destroyed, or otherwse physically unavailable. 

The OIG contracted (HHS-100-86-0054) with the HDI to log-in and secure the 

arrving medical records. The HDI matched medical records to the sample biling 

/ records, checked medical records for completeness and legibilty, inserted each 

. medical record in an individually labeled folder, and counted the pages to be reimbursed. It also followed up incomplete medical records and handled similar 

administrative obstacles. 

Unfortunately, a change in ownership and reorganization of Baxer, the parent company of the HDI, delayed some payments to hospitals. Although both the HDI 

and this contract apparently garnered profits for the parent, Baxer elected to disband 

the HDI for insuffcient profitabilty. The HDI ceased operations prior to completing its contracted tasks, compellng the government to terminate the HDI contract for 

default. 

DRG RESTRCTON 

The HDI transmitted the accumulated records to the AMRA. The OIG separately contracted (HHS- 100-89-0022) with the AM to reabstract the ICD- CM codes 

supported by the medical record, select the principal diagnosis, and group to select the DRG. To ensure that the original ICD- CM codes and DRGs did not affect the 

AMRA' s reabstraction, the AMRA coders conducted this reabstraction without


knowledge of the original ICD- CM codes and DRGs. The AMRA also identified

the reasons why a hospital's bil differed from the correct codes. Finally, it entered its reabstracted codes into a personal computer database provided by the OIG. 

As the credentialing body for medical records practitioners the AMRA had expert 

knowledge of coding intricacies and access to nationally recognized RRA (Registered Records Administrators) and ARTs (Accredited Records Technicians) who were

experienced ICD- CM coders. Unlike most other organiztions that employed expert coders, the AMRA was (and is) independent of the hospital industry. The used the offcial HCFA GROUPER softare (3M's Codefinder) to determine the

DRG for each reabstracted record. The AM compared the DRGs that Codefinder 

produced from the reabstracted ICD- CM codes with the DRGs supplied by 

providers and noted the results of these comparisons in the database. 

An RRA who was a nationally recognized expert in ICD- CM coding and who had not participated in the initial reabstraction reviewed all records where the AMRA 

DRG differed from the provider DRG. The AMRA then grouped the revised codes and made the appropriate changes in the database. The OIG also contracted with a 

physician with current knowledge of coding and cliical issues (SA-90-0633) to identify 

the principal diagnosis, secondary diagnosis, and appropriate procedures in cases 

where the resultant DRG differed from the provider s DRG (whether the same as the

initial AMRA coder or different from both the initial AMRA coder and provider). 

An RRA who had not been involved in the initial reabstraction and coding or the 

expert review compared all records reviewed by the physician to the provider s data . and the AM' s data. Where the physician had agreed with the AMRA the 

/ did not change the database. Where the physician had agreed with the provider and 

. provided additional information overlooked by the AM or provided special insight with which the third RRA agreed, the AMRA changed the database to reflect the 

codes of the DRG of the provider. Where the third reviewer was not convinced that 

there should be a change from the AM' s coding and DRG assignment, the OIG medical officer reviewed the case arid made a final determination. The 

entered this determination as the final code and DRG determination. 

The AMRA also classified every coding error as mis-specification, miscoding,


resequencing, or "other." The AMRA entered its coding selections into a series of


database files. Its small personal computers could not hold all its coding output at


once. Computer experts from the OEI's office in Region V helped the AM set up and maintain the databases. Upon completion of the AMRA reabstraction and data 

entry, the OIG-OEI-Region V office off-loaded the fies for transmission 

headquarters. 

ANALYSIS 

The OIG contracted with BOTEC (HHS- 100-90-0023) to analyze the results of


AMRA' s reabstraction of ICD- CM codes and DRGs. BOTEC has extensive


experience in the statistical analysis of reabstracted data. It has conducted such

analyses for OIG on several previous occasions (HHS-100-89-0019, HHS-100-88-0019 

HHS-100-88-0624). BOTEC's work in this area has included the processing of medical 

records, the construction of r abstraction databases, the statistical analysis of 

reabstraction data, and policy analysis. 

The OIG provided BOTEC with a SAS data set containing merged biling records and 

the AM reabstraction data. The OIG also provided BOTEC with a spreadsheet 

fie containing DRG weights for all DRGs for the years 1985 through 1989. Finally, 

the AMRA provided BOTEC with an updated set of reabstraction data and billng 

record data that contained additional information. 

BOTEC match-merged these three data sets into one comprehensive SAS data set. 

At this point BOTEC constructed simple frequency distributions of all variables and 

cross-tabulations of certain pairs of variables to examine the data set for incorrect or 

inappropriate codes and/or logical inconsistencies. All such ambiguities were resolved 

or corrected in consultation with the OIG. 

BOTEC then used SAS to create several additional variables that the current analysis 

required. These variables include exact age of patient at the time of admission 

change in DRG weight as a result of reabstraction, location of provider (metropolitan 

if in an Standard Metropolitan Area, nonmetropolitan if not), teaching status of 

provider (teaching if the hospital had any interns, nonteaching otherwse), controllng 

agency of provider, and bed size of provider (small if 1-99 beds, medium if 100-299 

beds, and large if 300 or more beds). Throughout this process BOTEC kept electronic 

and printed copies of the programs used to create intermediate data sets 

/ documentation of these data sets, and the data sets themselves. 

BOTEC began its analysis of the 1988 calendar year data by ensuring that the sample 

accurately represented the population from which it was drawn with respect to both 

provider and patient demographics. It compared the distribution of biling records in 

the 1988 sample with the population of biling records from which it was drawn using 

the variables provider size, location, control, and teaching status and patient age, sex, 

and race. BOTEC used a statistic to reject the null hypothesis that the distributions 

were different. 

Hospitals were unable to provide medical records for 229 billng records in the original sample. This 8.5 percent nonresponse rate could have introduced systematic bias into 

the sample. BOTEC therefore repeated the tests for representativeness to determine 

whether there were differences in the distributions of responses and nonresponses. It 

also retested for representativeness using the same procedures as before, but with 

nonresponses removed. This slightly smaller sample stil accurately represented the 

general population. 

BOTEC then conducted "breakdown" analyses for a series of dependent variables. 

the first analysis it constructed a cross-tabulation table by cross-tabulating the four 

provider demographic categories. The resulting table contained 144 cells. For each 
cell BOTEC calculated and displayed for a given dependent variable that variable 

mean, standard error, and the number of cases in the cell. 

In the second "breakdown" analysis BOTEC constructed a cross-tabulation table by 

cross-tabulating the three patient demographic categories. The resulting table 

contained 75 cells. Again, for each cell BOTEC calculated and displayed the 

dependent variable s mean, standard error, and number of cases. By examiing the eight resulting tables for confdence intervals which had little or no overlap, BOTEC determined which provider and patient demographics has a significant impact on these 

dependent variables. 

BOTEC conducted three additional analyses on the 1988 data. The first estimated the 

total financial impact of DRG errors by hospital and patient demographics. The second analysis examined DRGs to determine which DRGs seemed to present the

most coding difficulty. The third analysis estimated the financial impact of DRG 

errors by DRG. 

To estimate the total financial impact of DRG miscoding by demographic categories BOTEC multiplied the mean change in case mix index by Medicare standardized amount in 1988 for each cell in the analysis tables. This was an estimate of the mean 

change per bil in each cell. BOTEC then multiplied this by the number of bils in each cell to get an estimate of the overall financial impact of DRG errors within each cell. They also calculated standard errors of these estimates. 

To estimate which DRGs represented the most coding dificulty BOTEC organied / DRGs in the 1988 sample by several different criteria: by frequency of occurrence in 

. the sample, by errors in DRG group, and by relative weight change. 

To estimate the financial impact of DRG miscoding by DRG, BOTEC multiplied the mean change in case mix index by Medicare standardized amount in 1988 for each 

observation in the sample and by the weight which each observation represents in the population from which the sample was drawn. The mean by DRG was then 

calculated to give an estimate of the overall financial impact of DRG errors for each 

DRG. BOTEC also calculated standard errors of these estimates. A fuller description of the calculation formulas appears in Appendix 3. 

REPREENATI 

The final sample of 2 451 medical records accurately represented the characteristics of 

the underlying population. Distributed by hospital demography, it did not differ from the population in bed size, teaching status, location, or control. (Table 1). 

The sample also accurately represented the underlying population by patient age and sex. However, the OIG made remedial efforts to classify unknowns by race. This match to other government files reduced the proportion of sample unknowns in 

comparison to the underlying population.22 The volume of cases precluded a similar 
reclassification of unknowns for 

the entire population. Without the 

OIG' s reclassification, the sample 

would also have conformed to 

racial distribution of the underlying 

population. 

Comparing the 2 680 "selected" 

discharges with the population of


all CY 1988 Medicare discharges 

(mius the exclusions for specialty 

institutions, exempt States, and 

specialty DRGs) revealed no 

significant diferences in hospital 

or patient demography, except for 

the OIG's remedial efforts to 

classify unknowns by race. 

(Appendix 4). 

The representativeness verification 

also checked for response bias by 

comparing the 2 451 "sample 

discharges with the 229 nonsample 

discharges, excluded because no 

medical records matched to these 

/ bils. Larger hospitals lost 

. significantly more of their records 

than did smaller hospitals. The 

more voluminous and complex


medical records systems of larger 

hospitals probably offered greater 

opportunity for charts to 

disappear: more personnel had 

access to the files, more 

departments requested the charts 

larger record rooms had more 

shelves on which to misfie charts 

more patients had the same 

names, etc. (Appendix 5). 

Unsurprisingly, response bias also 

occurred for hospital demographic 

characteristics that correlated with 

hospital size. Metropolitan


hospitals and teaching hospitals


tended to have more beds. 

Hospital Medicare Responses 

demography n (%) n (%) 

99 beds 1 333 250 (14. 359 (14. 

100-299 beds 3 454 578 (36. 893 (36.4) 

300+ beds 4 718 527 (49. 199 (48.9) 

Chi-square 0. , 2 df P=0.626. 

Teachig 4 076 175 (42.9) 1 008 (41.1)


Non-teaching 5,430 180 (57. 1) 1 443 (58.


Chi-square 3. , 1 df, P=0.080.


Profit 1 022 922 (10. 272 (11.1)


Nonprofit 6 858 338 (72. 769 (72.


Government 1 625 095 (17. 410 (16.


Chi-square 0.5, 2 df, P=0.798.


Metropolitan 7 270 147 (76.5) 1 845 (75. 

Non-metropolitan 2 236 208 (23.5) 606 (24. 

Chi-square 2. , 1 df, P=0. 161. 

Patient demography 

64 years 940 650 (9. 232 (9. 

65-74 years 3 932 293 (41.4) 007 (41.1) 

75-84 years 3 263 952 (34. 854 (34. 

85+ years 1 369,466 (14.4) 358 (14. 

Chi-square 0. , 3 df, P = 0.860. 

Male 4304 256 (45.3) 1 094 (44.
 Female 5 202 105 (54.7) 1 357 (55.4)


Chi-square 0.4, 1 df, P=0.523.


White 8261 646 (86. 205 (90. Black 827204 (8. 188 (7.
 Other 150380 (1.6) 35 (1.4)
 Unknown 267 131 (2. 23 (0.


Chi-square 30. , 3 df, Po:O.OOO1.


Total 506 361 . (100.0) 2 451 (100. 

. Hospital demography totals to 9 506 365 

because six bil lacked data on hospital control. 

Table 1: Representativeness of sample bils by 

hospital and patient demography, 1988 
Therefore, they also had more nonresponses. The response bias in metropolitan 

(Mantel-Haenszel1.6, 1 df, P=0.20) and teaching hospitals (Mantel-Haenszel1.4, 1 df P=0.23) disappeared upon controllng for hospital size. In contrast, hospital control 

produced no significant response bias. 

No response bias occurred with respect to age or sex. The OIG's reclassification of 

unknowns identified significantly more whites. Controllng for hospital size did not 

remove this nonresponse bias. However, upon excluding nonresponses, the sample 

stil accurately represented all discharges with respect to hospital demographic 

characteristics. 
FINDINGS


DRG CODING EROR REDUCED


Upon blinded ICD- CM reabstraction 

14.7 :! 0.7 percent of discharges had 

coding errors that changed their DRGs. 

The standard error of 0.7 indicated this 

point estimate to be quite precise, a 

secondary effect of the sample size. This 

proportion was significantly lower than the 

20.8 :! 0.5 percent errors found in 1985 

(1985-1988 difference = 0.061, 95% CI 

043 to 0.079). (Table 2). 

No hospital demographic characteristics 

had a significant effect upon the 

proportion of DRG coding errors. 

Smaller hospitals appeared to have higher 

proportions of miscodes, but this apparent 

difference did not attain statistical 

significance. (Appendix 6). 

Similarly, no patient characteristics 

/significantly affected the proportion of 

.' DRG coding errors. Younger patients 

appeared to have higher error rates, but 

this difference also failed to attain 

statistical significance. (Appendix 7). 

Crosstabulations of demographic


characteristics for interaction potential


identified no credible effects. (Appendix 

8). 

EQUAL NUERS OF DRG ERRORS 

OVE-REIMURE AN UNERREIMURSE 

The 361 DRG errors divided evenly


between errors that had over-reimbursed


the hospital (50.7 :! 2.6 percent) and


under-reimbursed the hospital (49.3


percent). This inspection s proportion of


over-reimbursements differed significantly 

Hospital Proportion:! (n) 

demography standard error 

99 beds 17.0 :! 1. (359) 

100-299 beds 14.9 :! 1.2 (893) 300+ beds 13.9 :! 1.0 (1 199) 

Chi-square 2. , 2 df, P=0.351. Phi 0.029. 

Teaching 15.5 :! 1. 1 (1,008)

Nonteaching 14.2 :! 0.9 (1 443) 

Chi-square 0. , 1 df, P=0.383. Phi 0.018. 

Profit 17.3 :! 2. (272) Nonprofit 14.1 :! 0.8 (1 769)

Government 15.6:! 1.8 (410) 

Chi-square 2. , 2 df, P=0.339. Phi 0.030. 

Metropolitan 14.9 :! 0.8 (1 845) 

Nonmetropolitan 14.4 :! 1.4 (606) 

Chi-square 0. , 1 df, P=0.766. Phi 0.006. 

Patient demography 

64 years 16.4 :! 2.4 (232) 

65-74 years 14.9:! 1.1 ( 1007) 

75-84 years 14.6 :! 1.2 (854)

85+ years 13.4 :! 1.8 (358) 

Chi-square 1.0, 3 df, P=0.794. Phi 0.020. 

Male 14.5 :! 1.1 (1094) Female 14.9 :! 1. (1357) Chi-square 0. , 1 df, P=0.807. Phi 0.005. 

Black White 14.8 :! 0. (2205)

14.4 :! 2. (188) Other 14.3 :! 6. (35) Unknown 8.7 :! 6. (23) 

Chi-square 0. , 3 df, P=0.871. Phi 0.017. 

Total 14.7 :! 0. (2451) 

Table 2: Proportion of coding errors by 

hospital and patient demography, 1988 
110, 95% CI 0.051 to 0. 168). 

(Table 3). 

For-profit hospitals overreimbursed themselves the 

more than did other tyes of hospitals. However, these 

differences did not attain 

statistical significance. This 

trend applied across all 

from the 61.7 :t 1.4 percent for Over-re Under-re­ 1985 (1985-1988 difference = Hospital imbursed imbursed Total 

hospital characteristics. The 

direction of coding error also Profit 27 (57.4) 20 (42.6) 47 (100.
 exhibited no signifcant trend Nonprofit 123 (49.2) 127 (50.8) 250 (100.
 by patient characteristics. This Government 33 (51.6) 31 (48.4) 64 (100.
 result suggested that little net Chi-square 1.2, 2 df, P=0.577. Phi 0.055.
 over-reimbursement occurred


because of coding direction. Metropolitan 138 (50.4) 136 (49.6) 274 (100.


Nonmetropolitan 45 (51.7) 42 (48.3) 87 (100. DRG CREP ELIMATED Chi-square 0. , 1 df, P=0.825. Phi - 012. 

demography n (%) n (%) n (%) 

99 beds 31 (50.8) 30 (49.2) 61 (100. 

100-299 beds 71 (53.4) 62 (46.6) 133 (100. 

300+ beds 81 (48.5) 86 (51.5) 167 (100. 

Chi-square 0. , 2 df, P=0.703. Phi 0.044. 

Teaching 79 (50.6) 77 (49.4) 156 (100.

Nonteaching 104 (50.7) 101 (49.3) 205 (100. 

Chi-square 0. , 1 df, P=0.986. Phi 0.001. 

Ths inspection used the casemix index (CMI) to calculate 

the overall financial effect of 

/ DRG coding errors. The CMI 

. quantified the complexity of


PPS discharges by annually 

averaging the relative weights 

of all bils submitted by each 

hospital. Those hospitals with 

higher mean relative weights 

served Medicare patients with 

more complex conditions and 

that therefore consumed more 

resources. This inspection


calculated CMI as (1)


submitted to the Fls for


reimbursement, (2)


Patient demography 

64 years 17 (44.7) 21 (55.3) 38 (100. 

65-74 years 77 (51.3) 73 (48.7) 150 (100. 

75-84 years 66 (52.8) 59 (47.2) 125 (100.

85+ years 23 (47.9) 25 (52. 1) 48 (100. 

Chi-square 0. , 3 df, P=0.817. Phi 0.051. Male 85 (53.5) 74 (46.5) 159 (100.
 Female 98 (48.5) 104 (51.5) 202 (100.


Chi-square 0. , 1 df, P=0.351. Phi - 049. 

Black White 166 (50.8) 161 (49. 327 (100. Other 14 (51.9) 13 (48. 27 (100.

2 (40.0) 3 (60. Unknown 1 (50.0) 1 (50. 

5 (100. 

2 (100.


Chi-square 0. , 3 df, P=0.970. Phi 0.026. 

reabstracted by the AMRA on Total 183 (50.7) 178 (49. 361 (100. a blinded basis, and (3) the 

difference or mean weight Table 3: Direction of DRG errors by hospital and 

change due to coding patient demography, 1988 

inaccuracy. 
Hospital Mean + standard error (n)

demo Before Afer Change 

99 beds 1.0914 :t 0.0312 1.0889:t 0.0312 - 0025:t 0.0139 (359)


100-299 beds 3285 :t 0.0314 1.3335:t 0.0311 0049:t 0.0116 (893)


300+ beds 3576 :t 0.0289 1.3595:t 0.0285 0019:t 0.0106 199)


Teaching 3851 :t 0.0327 1.3841:t 0.0322 - 001O:t 0.0125 (1,008) 

Nonteaching 1.2542 :t 0.0222 1.2590:t 0.0222 0047:t 0.0081 (1,443) 

Profit 1.3112 :t 0.0605 1.3274:t 0.0621 0162:t 0.0207 (272)

Nonprofit 1.3304 :t 0.0226 1.3333:t 0.0223 0028:t 0.0085 769)

Government 1.2095 :t 0.0383 1.2005:t 0.0378 - 0090:t 0.0145 (410) 

Metropolitan 3479 :t 0.0230 1.3508:t 0.0227 0029:t 0.0086 845) 

Nonmetropolitan 1.1868:t 0.0293 1.1874:t 0.0291 0006:t 0.0107 (606) 

Patient demo phy 

1.2958 :t 0.0644 1.3249:t 0.0655 0291:t 0.0215 (232) 

65- 1.3769:t 0.0329 1.3632:t 0.0319 - 0137:t 0.0120 007) 

75- 1.2535 :t 0.0291 1.257:t 0.0292 0035 :t 0.0110 (854)

85+ 1.2523 :t 0.0374 1.2799:t 0.0392 0275:t 0.0161 (358) 

Male 1.3613 :t 0.0298 1.3589:t 0.0294 - 0024:t 0.0109 094)

Female 1.2651 :t 0.0240 1.2713:t 0.0238 0062:t 0.0090 (1,357) 

White 1.3180 :t 0.0201 1.3192:t 0.0199 0012:t 0.0074 205) 

Black 1.1838:t 0.0544 1.1865:t 0.0537 0026:t 0.0241 (188) Other 1.4152 :t 0. 1598 1.4890:t 0. 1603 0737:t 0.0538 (35)

Unknown 1.2028:t 0. 1769 1.2053:t 0.1762 0025:t 0.0097 (23) 

Total 1.3080 :t 0.0188 1.3104:t 0.0186 0023:t 0.0070 451) 

Table 4: Estimated case-mix index change by hospital and patient demography, 1988 

After reabstraction, the CMI increased 0.0023 :t 0.0070, not a statistically significant 

difference. Hospitals slightly under-reimbursed themselves. This CMI increase 

differed significantly from the previous inspection s over-reimbursement, a 0.0194 :t 

0060 CMI decrease (1985-1988 difference = 0.0171, 95% CMI 0.0158 to 0.0184). 

(Table 4). 

This inspection found that only small, teaching, and government hospitals continued to 

over-reimburse themselves. (Appendix 13). Smaller and government institutions had 

lower absolute CMls, while teaching institutions had higher absolute CMls. 

(Appendices 9 and 11). 
Discharges of patients aged 65-74 and males over-reimbursed the hospitals. 

(Appendix 14). These groups of patients also had higher absolute CMls than other 

patient demographic categories. (Appendices 10 & 12). 

DRG OVER-REIMUREMNT ELIATED 

. Exrapolating this inspection s results 

to all 10.8 milion bils, Medicare 

under-reimbursed hospitals by $69. 

milion. This difference amounted to 

only 0. 1 percent of the $52 bilion in 

1988 PPS expenditures.23 In contrast 

the previous inspection found PPS 

over-reimbursement of $308 millon or 

1.9 percent of 1985 PPS disbursements. 

(Table 5). 

Hospital and patient demographic 

trend largely paralleled this trend. 

Hospital $ milion :t Number 

demography 

99 beds 

100-299 beds 

300+ beds 

Teaching 

Nonteaching 

Profit 

Nonprofit 

Government 

standard error 

14.8 :t 51.5 

59.4 :t 121.


26.0 :t 156. 

13.4 :t 158.


80. 1 :t 131. 

51.0 :t 62. 

58.8 :t 180. 

42.6 :t 69. 

of bils 

333 250 

454 578 

718 527 

076 175 

430 180 

022 922 

858 338 

625,095 

270 147 

236 208 

940 650 

932 293 

263 952 

369 466 

304 256 

202 105 

261 646 

827 204 

150 380 

267 131 

506 361 

Small, teaching, and government Metropolitan 67.0:t 195.4 

hospitals received up to $70.8 milion Nonmetropolitan 3.6:t 63.4 

in over-reimbursement from DRG 

coding errors. (Appendices 15 and 16). 

MIS-PECIFCATION UNER­

/ REIMURSES

REEQUECIG OVEREIMURSES 

Each stage of the reimbursement 

process had the potential for 

introducing error into the PPS. When 

performing its reabstractions, the 

AMRA identified the reason for each 

DRG error. 

Mis-specification: The attending 

physician wrote down the wrong 

narrative diagnoses or procedures on 

the attestation. 

Patient demography 64 80.5 :t 62. 

65-74 -171.4 :t 145.5 

75-84 46.9 :t 109. 

85 + 113.9 :t 66.4 

Male 

Female 

White 

Black 

Other 

Unknown 

Total 

30.8 :t 144. 

99.0:t 144. 

32.7 :t 188. 

6.4 :t 62.


32.4 :t 24. 

8 :t 7. 

69.8 :t 203. 

Table 5: Net financial change by hospital and 

patient demography, 1988 

Miscoding: The medical records department selected an incorrect ICD- , numeric 

code for a correct attestation. 

Resequencing: The biling department substituted a secondary diagnosis for the 

correct, principal diagnosis. 
Reason Subtotal Total 

n (%) n (%)


MIS-SPECIFICATION 227 (63.


Changed principal diagnosis 75 (20.


Altered principal diagnosis, more or less specific 30 (8.


Added complication-comorbidity or other diagnosis 46 (12.


Deleted complication-comorbidity or other diagnosis 36 (10.


Added operating room procedure 19 (5.


Deleted operating room procedure 14 (3.


Changed operating room procedure 7 (1.9)


MISCODING 33 (9.


Change due to ICD- CM rule 30 (8.


Change due to ICD- CM rule, changed C.c. status 1 (0.


Change due to ICD- CM rule, changed OR status 2 (0.


RESE UENCING 96 (26.


Moved secondary diagnosis to first diagnosis 71 (19.


Changed codes to more or less specific 15 (4.


ICD- CM code differs 10 (2.


OTHER 5 (1.4) 

Changed destination 1 (0.3) 

. Provider-FI made data entry error in DRG 4 (1.1) 

TOTAL 361 (100. 

Table 6: Reasons for errors affecting DRG assignment, 1988 

In addition, 1 352 other coding changes did not alter the DRG and did not count as 

errors for the purposes of this study. (Table 6). 

Narrative changes accounted for 63.2 percent of DRG errors. Examples of misspecification included wrting down the wrong principal diagnosis; selecting too nonspecific a principal diagnosis; and adding or deleting a complication, comorbidity, or operating room procedure. 

Miscoding made up 9. 1 percent of the DRG errors. These changes primarily took the 

form of changes in the principal diagnosis, rather than of complications, comorbidities 

or operating room procedures. A few errors represented the AMRA reviewers 

disagreeing with the providers' assigned discharge destinations or apparent 

tyographical errors. 

Resequencing comprised 26.6 percent of the DRG errors. In all cases, the 

reviewers in all cases disagreed with the providers listing sequence. In most cases, the 
biling department had substituted a secondary diagnosis for the correctly attested and 

coded principal diagnosis. In other cases, the diagnosis should have been more 

specific. ICD- CM ruling changes accounted for the remaining sequence changes. 

Mis-specification significantly n (%) Over-re- Under-re- Total
 under-reimbursed hospitals; while imbursed imbursed


resequencing significantly over-


reimbursed them. Thus, the Mis-specification 98 (43.2) 129 (56.8)227 (100.
 attending physicians select their Miscoding 18 (54.5) 15 (45.5) 33 (100.
 patients' diagnoses and Resequencing 64 (66.7) 32 (33.3) 96 (100.
 procedures with caution, earning Other 3 (60.0) 2 (40.0) 5 (100.


their hospitals less


reimbursement than they should Total 183 (50.7) 178 (49.3)361 (100. have received. The biling Chi-square 15. , 3 df, P=0.002. Phi 0.206. department behaved more 

aggessively, obtaining greater Table 7: Reason for DRG changes by direction of 

reimbursement that the PPS DRG change, 1988 

entitled their employers to 

receive. Either the hospitals had greater influence over employees, or the employees identified closely with the economic interests of the hospital. The attestation 

requirement apparently deterred up coding due to mis-specification, but the sentinel 

effect of Peer Review Organization surveilance did not fully prevent over-


reimbursement due to resequencing. (Table 7). 

These two trends, mis-specification resulting in under-reimbursement and resequencing 

/ causing over-reimbursement, offset each other. So, overall hospitals received the 

. correct reimbursement. This inspection cannot predict whether this equilbrium will 

continue in the future. 

CERTAI DRGS AR MORE SUSCEPTLE TO ERROR 

In this random sample of discharges, vascular disorders such as heart failure, angia stroke, and arrhythmias cause Medicare hospitalizations most frequently. Overall, 28 of the 476 DRGs accounted for half of the total bils, and 10 DRGs accounted for 28. 

percent of all bils. Most coding errors fell into these DRGs, but not in direct ratio to 

the DRGs' volume. (Table 8). 

This report identified DRGs with high proportions of coding errors by dividing the number of errors by the frequency of bils for specific DRGs. Many of these DRGs 

covered vague or nonspecific diagnoses such as atherosclerosis (DRG 132), other circulatory system procedures (DRG 120), respiratory signs and symptoms (DRG 99), 

and other nervous system disorders (DRG 34). This indeterminateness suggests 

inherent ambiguities in medical taxonomy. For example, DRG 99 includes apnea 

dyspnea, hemoptysis, hypercapnia, pleurodynia, stridor, and ventilatory failure. (Table 

9). 
DRG description n (%) 

127 Heart failure and shock 133 (5.4) 140 Angina pectoris 89 (3. 14 Specific cerebrovascular disorders except TIA 75 (3. 89 Simple pneumonia 74 (3. 182 Esophagitis, gastrointestinal, and miscellaneous digestive disorders 66 (2. 96 Bronchitis and asthma with complications 63 (2. 209 Major joint procedure 55 (2. 15 Transient ischemic attacks 47 (1.9) 138 Cardiac arrhythmia and conduction disorders 45 (1. 296 Nutritional and Other 1
 miscellaneous metabolic disorders with complications 44 (1.

760 (71. 

Total 451 (100. 

Table 8: DRGs biled most frequently, 1988 

Myeloproliferative 

DRG description Miscoded 

Number (%) 

132 Atherosclerosis 3 (75. 

413 4 (66.


185 Dental except extractions 2 (66.


120 Other circulatory system procedures 3 (66.


! 99 Respiratory signs and symptoms 5 (62.


403 Lymphoma and nonacute leukemia 3 (60.


Other nervous system disorders 3 (60.


Other 420 341 (14.


Total 451 361 (14. 

Table 9: DRGs with high proportions of coding errors, 1988 

Over-reimbursement concentrated in selected DRGs and certain tyes of hospitals. This report identified DRGs with maxmum savings potential by multiplying the error 

frequency by reimbursement change for each DRG. Although this inspection found no overall over-reimbursement to hospitals, certain DRGs stil significantly over- reimbursed the hospitals. In particular, 13 DRGs each had over $20 milion in 

projected overpayments. This group consisted primarily of DRGs with operating room 

procedures, probably because of their high relative weights. (Table 10). 

Additionally, small and for-profit hospitals made more errors that over-reimbursed 

themselves than did other tyes of hospitals. This net over-reimbursement totaled 

$842.2 milion. 
DRG description 

104 Cardiac valve procedure with pump & cath 

468 Unrelated operating room procedures 

475 Respiratory system diagnosis with ventilator 

110 Major reconstructive vascular procedures 

191 Major pancreas, liver, & shunt procedures 

154 Stomach, esophageal, & duodenal procedures 

Pulmonary edema & respiratory failure 

Respiratory system operating room procedures 

Respiratory neoplasms 

121 Myocardial infarction discharged alive


415 Operating room procedure for infection


148 Major large & small bowel procedures


217 Wound debridement & skin graft


Other 

Total 

Table 10: DRGswith maxmum savings potential, 1988


Over-reimbursement $ per $ milion 

discharge total 

4915 81.1 

1128 78.


791 49.


682 47.


3313 43.


1114 40.


571 37.


764 25.


306 24.


189 23.


858 22.


202 22.


333 22.


235 263 -587.


451 69.

RECOMMENDA TIONS


~ The Peer Revew Organtions should contiue their sureilance of hospita


cog for DRG reimburement accurcy.


The attestation requirement appears to have .deterred over-reimbursement due to 

mis-specification by attending physicians, causing their hospitals to be underreimbursed. However, the sentinel effect did not fully prevent over-reimbursement 

due to resequencing by hospitals. Although these two trends approximately offset 

each other, this equilbrium may not continue in the future. 

The Agency for Health Care Policy Research plans to reabstract the ICDcodes from a large sample of Medicare charts to determne their diagnostic 

accuracy for health servces research purposes. Using 1991 data, grouping these 

ICD- CM codes to DRGs, and selecting reasons for any differences would provide 

a third time point with which to track trends in reimbursement accuracy. The OIG 

supports this effort. 

AGENCY COMM 

In its May 29, 1992 comments to the draft of this inspection, the HCF A concurred 

with the OIG recommendation. The HCFA noted that the improvement in DRG 

coding accuracy may be attributable to increased hospital experience with PPS, PRO 

review, and HCF A educational efforts. 

/ The HCF A also made a number of technical comments. Based on these comments 

the OIG made several changes to this inspection. The full text of the HCF 

comments appear as an appendix. 
ENDNOTES 

1. Schweiker R S. Report to Congress: hospital prospective payment for medicare.


Washington, DC: U.S. Department of Health and Human Servces, 1982.


2. Social Security Amendments of 1965. Pub. L. No. 89- , 79 Stat 286 (1965). 

3. Social Security Amendments of 1983. Pub. L. No. 98- , 97 Stat 65 (1983). 

4. Commission on Professional and Hospital Activities. International classification of


diseases, 9th edition, clinical modifications. Ann Arbor, MI: Edward Brothers, 1980.


5. Fetter R B, Shin Y, Averill R & Freedman A T. The new ICD- CM diagnostic related groups classification scheme user s manual: fial report. New Haven, Cf: Yale School of Organization and Management, Health Systems Management Group, 1981. 

6. Fed Reg, July 31, 1985; 50 (147): 31038. 

7. Shriners' Hospital for Crippled Children -- Colorado Corporation -- Conveyance.


Pub. L. No. 94-505; October 15, 1976: Title II 201-07.


8. Delaney A M & Hsia D C, eds. 1985 national DRG validation study. Lexington 

MA: Health Data Institute, 1987. Report prepared for the Office of Inspector 

General. U.S. Department of Health and Human Servces; contract HHS-100-87­

0015. 

9. Hsia D C, Krshat W M, Fagan A B, Tebbutt J A, & Kusserow R P. Accuracy of 

diagnostic coding for medicare patients under the prospective-payment system. N Engl J Med, 1988; 318: 352-55. 

10. Health Care Financing Administiation, U.S. Department of Health and Human 

Servces. Medicare program: prospective payments for medicare inpatient hospital 

servces. Fed Reg, September 1, 1983; 48: 39752-39886. 

11. Health Care Financing Administration, U.S. Department of Health and Human 

Servces. Medicare program: changes to the inpatient hospital prospective payment 

system and fiscal year 1985 rates. Fed Reg, August 31, 1984; 49: 34728-90. 

12. Health Care Financing Administration, U.S. Department of Health and Human 

Servces. Medicare program: changes to the inpatient hospital prospective payment 

system and fiscal year 1986 rates. Fed Reg, September 3, 1985; 50: 35646-759. 

13. Health Care Financing Administration, U.S. Department of Health and Human 

Servces. Medicare program: changes to the inpatient hospital prospective payment 

system and fiscal year 1987 rates. Fed Reg, September 3, 1986; 51: 31454-603. 
14. Health Care Financing Administration, U.S. Department of Health and Human 

Servces. Medicare program: changes to the inpatient hospital prospective payment 

system and fiscal year 1988 rates. Fed Reg, September 1, 1987; 52: 33033- 165. 

15. Health Care Financing Administration, U.S. Department of Health and Human 

Servces. Medicare program: changes to the inpatient hospital prospective payment system and fiscal year 1989 rates. Fed Reg, September 30, 1988; 53: 38475-640. 

16. Health Care Financing Administration, U.S. Department of Health & Human 

Servces. Medicare program: changes to the inpatient hospital prospective payment system and fiscal year 1990 rates. Fed Reg, September 1989; 54: 36451-589. 

17. Health Care Financing Administration, U.S. Department of Health & Human


Servces. Medicare program: changes to the inpatient hospital prospective payment
 system and fiscal year 1991 rates. Fed Reg, September 1990; 55: 35989-6175.


18. Simborg D W. DRG creep: a new hospital-acquired disease. N Engl J Med, 1981; 

304: 1602-04. 

19. Carter G M & Ginsburg P B. The Medicare case mi index increase: medical 

practice changes, aging, and DRG creep. Santa Monica, CA: RA Corporation
 1985. Publication no. R-3292-HCFA.


20. Thomas J W & Longo D R. Application of severity measurement systems for hospital quality management. Hospital and Health Servces Administration, 1990: 35 

/ (2): 221-23. 

21. Division of Information Analysis, Offce of Statistics and Data Management


Bureau of Data Management and Strategy, Health Care Financing Administration


S. Department of Health & Human Servces. 1989 HCFA Statistics. Baltimore


MD: Health Care Financing Administration, 1989: 16 & 34.


22. Ruther M, Reily T W, Silverman H A, & Abbott D B. Medicare and Medicaid 

data book, 1990. Baltimore, MD: Offce of Research and Demonstrations, Health Care Financing Administration, U.S. Department of Health & Human Servces, 1991:

15. HCFA pub. no. 03314. 

23. Division of Information Analysis, Office of Statistics and Data Management


Bureau of Data Management and Strategy, Health Care Financing Administration


S. Department of Health and Human Servces. 1989 HCFA statistics. Baltimore


MD: Health Care Financing Administration, 1989: 25. HCFA publication no. 03294.

Appendix 1: Contract inormation 

Contractor 

BOTEC Analysis Corporation 

1698 Massachusetts Avenue 

Cambridge, MA 02138 

Project Offcer 

David Hsia, J. , M. , M. 

Offce of Inspector General 

330 Independence Avenue 

Washigton, D.C. 20201 

Contract 

HHS-100-90-0023 

Fir-Fixed Price Contract 

$203 257 
Appendix 2: Project participants 

OIG


Cathaleen A Ahern, B.


Evan J. Buckigham, B.


David C. Hsia, J. , M. , M.


Thomas F. Komaniecki, M.


W. Mark Krshat, M.


Lida M. Moscoe, B.


Brian P. Ritchie, B.


Barr L. Steelef


John M. Traczyk, B. 

HCFA


Timothy F. Greene, M. , M.B.A


Stephen F. Jencks, M.


Michael R. McMullan, M.


Harr L. Savitt, Ph.


Jeanette M. Smith, M. , M.


Malcolm A Sneen, B.S.


RAN Corporation


Haya P. Rubin, M. , Ph.


Baxer-Health Data Institute 

/ Patricia J. Baxer, R. 

. Patricia Cassidy-Tsnosas, R. 

Anette M. Delaney, R. , M.


Ellen B. Inghileri, R.


Janet Mathews, AR.


Laurie H. Moore, R.


Claire Shannon, AR.


Michele A. Wiese, B.


Margret K. Amatayakul, M. , R.


Mary Converse, R.


Nicholas J. Cotsonas, M.


1. Institutions appear in chronological order of involvement. 

2. Now at Health Audit Servces, Ellcott City, MD. 

3. Now at the Journal of the American Medical Association, Chicago, IL. 

4. Now at Johns Hopkis Medical Institutions. 

5. Ceased operations February 16, 1990. 

6. Outside contractor. 
Linda Ertl, R.


Rita M. Finnegan, R.


Desla Mancila, A.R. T.


Barbara Manny, R.


Sonia Martyiuk, R. 

Toula Nicholas, A. 

Charlotte Razor, R.


LouAn Schraffenberger, R.


Lynn Smetko, R.


Dawn Smith, AR.


Joan Zacharias, A.


BOTEC Analysis Corporation 

Geraldine M. Berenholz, R. 

Andrew H. Chalsma, B. 

David P. Cavanagh, M. , Ph. 

Janet W. Knight, R. , Ph. 

Amy L. Lockwood, B.A. 
Appendix 3: Calculation formulas 

Proporton of bil with cog errors 

Appendixes 6-7 display for various subsets of hospitals and patients, the proportion of sample discharges whose DRGs were changed by AM (i.e., whose origial DRG 

was incorrect). Since the 1988 Study self-weights, these proportions comprise unbiased direct estimates of the proportion of all CY 1988 bilg records withi each subset 

which have an incorrectly coded DRG. Each presentation includes the proportion, its standard error, and the number of sampled bils in the cell. 

Because the proportions in these tables derive from a sample there exists a


quantifable possibilty that the actual proportions of all Medicare bils with miscoded
 DRGs may difer by some amount from the proportions presented in the appendixes.
 The standard error is a statistic that allows calculation of the probabilty that the true population proportion differs from the sample proportion. Put over-simply if p is the
 sample proportion and s is the standard error, then there is a 95 percent chance that
 the true population proportion lies between p - (2.04 * s) and p + (2.04 * s), and
 there is a 99 percent chance that the true population proportion lies between p - (2.
 * s) and p + (2.72 * s). 

The relation among the sample proportion, the standard error, and the number of sample bils is as follows: assume there are n bils in a subset of the sample and e of these bils have DRG coding errors. Then the sample proportion is: p = e / n. The standard error is: s = (p * (1 - p) / (n - 1))% 

For example, in Appendix 6 the upper left-most cell gives the percent of miscoded bils from large, for-profit, teaching hospitals in metropolitan areas. There are eight records in this subset of the sample. Two of these discharges have miscoded DRGs. Therefore the proportion of DRG coding errors in the sample is p = 2/8 = 0.25 = 25 percent. Ths also comprises the unbiased estimate of the proportion of bilg records which large, metropolitan, for-profit, teaching hospitals submitted in CY 1988 and which contained miscoded DRGs. 

The standard error of this proportion is: s = ((0.25 * (1 - 0.25)) / (8 - 1))% = 0.164 = 

16.4 percent. Ths means that there is a 95 percent probabilty that the proportion of miscoded biling records submitted by all these hospitals in CY 1988 was between 0 

percent (0.25 - (2.04 * 0. 164)) and 58 percent (0.25 + (2.04 * 0. 164)). There is a 99 percent probabilty that this proportion is between 0 percent (0.25 - (2.72 * 0. 164)) and 69 percent (0.25 + (2.72 * 0. 164)). 

Researchers can combine particular cells of these appendixes in the followig manner: if the cells have proportions of biling errors P1 and P2' standard errors of S1 and S and numbers of sample bils nl and n2 respectively; then the combined proportion errors: Pt = ((n * P1) + (n2 * P2)) / (n1 + n )' The standard error of this proportion: 

t = ((Pt * (1 - Pt)) / (n1 + n2 - 1))% 
For example, the proportion of errors among biling records submitted by large and medium, for-profit, teaching hospitals in metropolitan areas is Pt = ((8 * 0.25) + (15 * 20)) / (8 + 15) = 0.217 = 21.7 percent. This calculation is based on data from the 

first and thireenth cells in column one of the appendix in the preceding example. This combined proportion has a standard error: St = ((0.217 * (1.000 - 0.217)) / (8 + 15 - 1))% = 0.088 = 8.8 percent. 

Signcace testig 

By calculating the frequencies summaried by these proportions, researchers constructed the underlying contingency table and calculated its statistical signficance 

measures of the degree of association between dependent and independent variable. 

Appendix 8 displayed the interaction analysis for coding error. 

These calculations deleted certain cases and collapsed certain categories of 

independent variables to simplif the analysis. To decrease the degrees of freedom this testing ignored bils that coded patient race as "other" or "unknown." These 58 

cases comprised too small a cell to determine whether billng records with these race 

codes showed statistically significant propensities to miscode DRGs. Furthermore it 

did not make sense to combine these biling records with biling records with race

codes of either ''white '' or "black". Evidence from other sources suggested that biling records of "other" and "unknown" differed in significant ways both from biling records

of ''white '' and ' 'black'' 

Preliminary analysis suggested that age affected differences in the propensity to / miscode DRGs, particularly in two age groups. The first comprised patients under 65 

. (i.e., those eligible for Medicare because of disabilties). The second comprised

patients 85 and over (i.e., those patients who were extremely elderly). Therefore we 

recoded patient age into three categories for these tables: oe65, 65- , and 85+. 

Table 2 summarizes data from Appendies 6-7. Thus, rather than reporting the within-cell distribution of cases between miscoded and correctly coded biling records 

these tables report only the proportion of incorrectly coded biling records within each cell. Researchers can construct the original three-way contingency tables from these 

summary tables if they wish. 

Each of these tables calculates two statistics: chi-square and phi. Chi-square measures only statistical significance. It quantifies the relationship between variables poorly. The phi statistic measures the strength of relationship between variables in a table 

better. Phi is the square root of chi-square divided by the number of cases in a table. 

Phi ranges between 0 and 1. The closer phi is to 0 the weaker the relation displayed 

in a table. The closer phi is to 1 the stronger the relation. 
Ca mi index and changes 

Appendixes 9-12 show for various subsets of hospitals and patients the average DRG 

weight or CMI, before and after AMRA reabstraction. This information also includes 

the CMI standard error and cell size. The following formulas calculate the CMI 

assuming n biling records in cell and the ith biling record has a relative weight of w 

then: CMI -= I: Wi / n. ThisCMI has a standard error: SE = / nYz where 
 = ((I:

(CMI - Wi)2) / (n - 1))% 

Appendixes 13-14 calculation of the CMI change used identical formulas, but 

substituted the relative weight after recoding minus the relative weight before recoding 

for the DRG weights. Negative mean values suggest that the original reimbursement 

to be higher than it should have been, while positive values suggest original underreimbursement. For individual biling records this calculation provides the change in 

DRG weight. Averaged over a subset of biling records it provides the change in CMI 

as a result of DRG recoding. The diference between the CMI in any cell of a 

before" table and the corresponding cell of an "after" table appears in the same cell 

of the "change" table. Each corresponding cell has the same n. However, no simple 

formula relates the standard errors of corresponding cells. 

Researchers can combine particular cells within any of these appendixes as follows: 

the cells have CMls C and Cz, CMI standard errors of S1 and S2' and numbers of 

sample bils n1 and n2 respectively; then the combined CMI: = (( n1 * C ) + (n2 * 

ez)) / cr1 + n2)' This CMI has standard error: St = (((n1 * (n1 -1) * s/) + (n2 * (n2 ­

1) * S2 )) / ((n1 + n ) * (n1 + n2 - 2)))%. For an explanation of these formulas see 

/ McNemar Q, Psychological statistics, 4th ed., New York, NY: John Wiley, 1969: 114­

. 15. 

For example, the CMI before recoding for biling records submitted by large and 

medium, for-profit, teaching hospitals in metropolitan areas is c = ((8 * 1.0205) + (15 

* 1.2991)) / (8 + 15) 1.2022. This calculation is based on data from the first and 

thirteenth cells in column one. The standard error of this CMI is St = (((8 * (8 - 1) *

1390 ) + (15 * (15 - 1) * 0.2401 )) / ((8 + 15) * (8 + 15 - 2)))% = 0. 1652. 

Mea change in reimburement 

Appendixes 15-16 show for various subsets of hospitals and patients the average 

change in dollar reimbursement per bil that would have resulted from correct DRG 

coding. Negative means suggest that the government' s reimbursements to providers 

were higher than they should have been, while positive means suggest that the 

government s reimbursements to providers were lower than they should have been. 

other words negative means in these tables suggest that the government has lost 

money as a result of DRG coding errors while positive means suggest that the 

government has gained money as a result of DRG coding errors. 
These appendixes incorporate a simplifyng assumption: that the actual reimbursement

hospitals receive for patients is the standardized amount times the DRG weight. 

variety of factors can slightly modif the standardized amount including whether a 

hospital is metropolitan or nonmetropolitan, teaching or nonteaching, etc. Most of these modifications have minor overall effects on reimbursement and in the aggregate 

tend to cancel each other. 

The exception is the diference between the standardized amount paid to metropolitan hospitals versus the standardized amount paid to nonmetropolitan hospitals. The standardized amount to metropolitan hospitals averaged $3 118 (current dollars) in CY

1988, whie the standardized amount to nonmetropolitan hospitals averaged $2 637 (current dollars) durig the same period. These averages were based on a total of 

10.8 milion billing records. 

The means, standard deviations,. and difference for reimbursement use formulas 

identical to the CMI calculations. Combining cells also uses the same calculations as 

for combining CMI entries. 

Projections of national reimburement change 

Appendixes 17-18 show the total number of bils submitted to HCFA in CY 1988 for various subsets of hospitals and patients. These appendixes provide the basis for projecting total savings or losses due to improper DRG coding. Negative amounts 

constitute an estimated loss to the government (over-reimbursement), while positive 

amounts represent too Iowa payment by the government (under-reimbursement). 

, Appendixes 19-20 contain the average under-reimbursement or over-reimbursement to 

the government per biling record as a result of DRG coding errors for a particular

tye of hospital or patient as well as the standard error. The corresponding cell in this appendix gives the total number of bils submitted by this particular tye of hospital or for this particular tye of patient in CY 1988. Multiplying the average dollar change 

per bil by the corresponding number of bils in each cell estimates the total dollar 

effect on the government. Multiplying the standard error per bil by the corresponding number of bils in each cell produces the standard errors of the dollar projection. 

This technique has one important caveat. The 1988 Study final sample excluded
 certain CY 1988 biling records a priori and certain other CY 1988 biling records


because of nonresponse. Thus the means and standard errors in apply to slightly
 different populations of biling records from appendixes to appendix. Practically this
 means that the standard errors in the projections of dollar change may actually be a very small amount smaller than an extremely conservative estimate would make them. 

However, this limitation has no impact upon the findings of this study. 
Appendix 4: Representativeness of selected discharges, 1988 

Hospital 

demo 

99 beds 

100-299 beds 

300+ beds 

Teaching 

Nonteaching 

Profit 

Nonprofit 

Government 

Metropolitan 

Nonmetropolitan 

Patient demo 

64 years 

65-74 years


75-84 years


85 + years 

/ Male 

. Female


White


Black


Other


Unknown


Total 

ulation 

n (%)


333 250 (14. 

454 578 (36. 

718 527 (49. 

076 175 (42. 

430 180 (57. 

022 922 (10. 

858 338 (72. 

625 095 (17. 

270 147 (76.5) 

236 208 (23. 

940 650 (9. 

932 293 (41.4) 

263 952 (34.3) 

369 466 (14.4) 

304 256 (45.3) 

202 105 (54. 

261 646 (86. 

827 204 (8. 

150 380 (1.6) 

267 131 (2. 

506 361 . (100. 

Selected 

n (%)


385 (14.4) 

943 (35. 

352 (50.4) 

130 (42. 

550 (57. 

291 (10. 

933 (72. 

456 (17. 

038 (76. 

642 (24. 

254 (9. 

110 (41.4) 

924 (34.5) 

392 (14. 

202 (44. 

478 (55. 

398 (89. 

215 (8.0) 

43 (1.6) 

24 (0. 

680 (100. 

Chi-square 

1.6, 2 df, P=0.459 

, 1 df, P=0.455 

, 2 df, P=0.983 

, 1 df, P=0.598 

, 3 df, P=0.901 

, 1 df, P=0.657 

38.4, 3 df, P-c0.0001 

not applicable


. Hospital demography totals to 9 506 355 because six bils lacked data on hospital 

control. 
Appendix 5: Nonresponses, 1988 

Hospital Res onses 

demo phy n (%) 

99 beds 359 (14. 

100-299 beds 893 (36.4) 

300+ beds 199 (48. 

Teaching 008 (41.4) 

Nonteaching 443 (58. 

Profit 272 (11.1) 

Nonprofit 769 (72. 

Government 410 (16. 

Metropolitan 845 (75. 

Nonmetropolitan 606 (24. 

Patient demo 

64 years 232 (9.5) 

65- 74 years 007 (41.1) 

75-84 years 854 (34. 

85 + years 358 (14. 

/ Male 094 (44. 

. Female 357 (55.4) 

White 205 (90. 

Black 188 (7. 

Other 58 (2.4) 

Unknown 35 (1.4) 

Total 451 (100. 

Nonres onses Chi-square 

n (%) 

26 (11.4) 27. , 2 df, Pc:O.OOOl 

50 (21.8) 

153 (66. 

122 (53. 12. , 1 df, Pc:O.OOOl 

107 (46. 

19 (8. , 2 df, P=0.233 

164 (71.6) 

46 (20. 

193 (84. 9.3, 1 df, P=0.002 

36 (15. 

22 (9. 1.9, 3 df, P=0.596 

103 (45. 

70 (30. 

34 (14. 

108 (47. , 1 df, P=0.462 

121 (52. 

193 (84.3) , 3 df, P=0.032 

27 (11.8) 

9 (3. 

1 (0.4) 

229 (100. not applicable 
Appendix 6: Proportion of DRO coing errors by hospital demography, 1988 

Proportion :I standard errr (n) 

99 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

100-299 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

30+ bes Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

Metropolitan 

16.7 :I 16.7 (6) 

10.0 :I 6.9 (20) 

11.5 :I 6.4 (26) 

50.0 :I 50.0 (2) 

25.7 :I 7.5 (35) 

27.0 :I 7.4 (37) 

0:1 0.0 (1) 

15.4 :I 7.2 (26) 

14.S:I 7.0 (27) 

22.2:1 14.7 (9)


1S.5 :I 4.3 (Sl)


1S.9 :I 4.1 (90)


20.0 :I 10.7 (15) 

13.7:1 3.2 (117) 

14.4 :I 3.1 (132) 

17.3 :I 3.1 (145) 

15.4 :I 2.2 (267) 

16.0:1 1.S (412) 

27.8 :I 10.9 (lS) 

13.1 :I 5.0 (46) 

17.2 :I 4.8 (64) 

1S.5 :I 2.9 (17S) 

14.7:1 1.7 (430) 

15.S :I 1.5 (60) 

25.0 :I 16.4 (S) 

22.0:1 6.5 (41) 

22.5 :I 6.0 (49) 

14.5:1 1.3 (703) 

7:1 1.7 (276)


12.9 :I 1.1 (979) 

20.0 :I 5.0 (65) 

20.4 :I 5.5 (54) 

20.2:1 3.7 (119) 

15.1 :I 1.3 (776) 

11.9:1 1.7 (371) 

14.0 :I 1.0 (1147) 

20.7 :I 7.7 (29) 

15.2 :I 2.7 (17S) 

16.0:1 2.6 (207) 

15.1 :I 1.2 (S50) 

12.S :I 1.4 (57S) 

14.2 :I 0.9 (1428) 

21.4 :I 4.5 (84) 

16.7:1 3.3 (126) 

1S.6 :I 2.7 (210) 

15.S :I 1.2 (%3) 

13.S :I 1.2 (882) 

14.9 :I O.S (1845) 

Nonmetropolitan 

no 

30.3 :I S.l (33) 

30.3 :I S.l (33) 

0 :I 0.0 (1) 

17.1 :I 3.4 (123) 

16.9 :I 3.4 (124) 

33.3 :I 33.3 (3) 

11.0 :I 3.0 (109) 

11.6 :I 3.0 (112) 

25.0:1 25.0 (4) 

16.2:1 2.3 (265) 

16.4:1 2.3 (269) 

no 

12.5 :I 5.9 (32) 

12.5 :I 5.9 (32) 

S:I 4.S (21)


13.2:1 2.7 (159) 

12.2 :I 2.4 (180) 

33.3 :I 33.3 (3) 

14.3 :I 4.2 (70) 

15.1 :I 4.2 (73) 

3 :I 5.S (24) 

13.4 :I 2.1 (261) 

13.0 :I 2.0 (285) 

no case 

no case 

no case 

7 :I 6.7 (15) 

1S.2 :I S.4 (22) 

13.5 :I 5.7 (37) 

0 :I 0.0 (2) 

7 :I 7.7 (13) 

7 :I 6.7 (15) 

9 :I 5.9 (17) 

14.3 :I 6.0 (35) 

11.5 :I 4.5 (52) 

no 

21.5 :I 5.1 (65) 

21.5 :I 5.1 (65) 

5.4 :I 3.S (37) 

15.1 :I 2.1 (30) 

14.1 :I 1.9 (341) 

25.0 :I 16.4 (S) 

12.0 :I 2.3 (192) 

12.5 :I 2.3 (200) 

9 :I 4.3 (45) 

14.S:I 1.5 (561) 

14.4 :I 1.4 (60) 

Metropolitan & nonmetropolitan 

16.7 :I 16.7 (6) 

22.7 :I 5.S (53) 

22.0 :I 5.4 (59) 

33.3 :I 33.3 (3) 

19.0 :13.1 (15S) 

19.3:1 3.1 (161) 

25.0 :I 25.0 (4) 

11.9 :I 2.S (135) 

12.2:1 2.S (139) 

23.1 :I 12.2 (13) 

16.S :I 2.0 (34) 

17.0:1 2.0 (359) 

20.0 :I 10.7 (15) 

13.4:1 2.S (149) 

14.0 :I 2.7 (164) 

15.7 :I 2.S (166) 

14.6:1 1.7 (426) 

14.9 :I 1.5 (592) 

28.6 :I 10.1 (21) 

13.S :I 3.2 (116) 

16.1 :I 3.1 (137) 

17.3:1 2.7 (202) 

14.2 :I 1.3 (691) 

14.9:1 1.2 (S93) 

25.0 :I 16.4 (S) 

22.0:1 6.5 (41) 

22.5 :I 6.0 (49) 

14.4 :I 1.3 (71S) 

9.4 :I 1.7 (29S) 

12.9 :11. (1016) 

19.4 :I 4.9 (67) 

17.9:1 4.7 (67) 

1S.7 :I 3.4 (134) 

14.9 :I 1.3 (793) 

12.1 :I 1.6 (406) 

13.9:1 1.0 (1199) 

20.7 :I 7.7 (29) 

16.9 :I 2.4 (243) 

17.3 :I 2.3 (272) 

14.7 :I 1.2 (887) 

13.6 :I 1.2 (882) 

14.1 :I O.S (1769) 

21.7:1 4.3 (92) 

13.S :I 1.9 (31S) 

15.6:1 1.S (410) 

15.5 :I 1. (100) 

14.2 :I 0.9 (1443) 

14.7:1 0.7 (2451) 
Appendix 7: Proportion of DRO coing errors by patient demography, 1988 

Proportion :t standard errr (n) 

Male 

0-0 vea 

White 19.5 :I 3.7 (113) 

Black 95:1 6.6 (21) 

Other 12.5:1 12.5 (S) 

Unknow no case 

All race 17.6:1 3.2 (142) 

65-74 vea 

White 14.0:t 1.6 (45S) 

Black 13.3 :I 6.3 (30) 

Other 0 :t 0.0 (5) 

Unknow 0.0 :I 0.0 (3) 

All race 13.7:1 1.5 (496) 

75-8 vea 

Whte 13.7 :t 1.9 (328) 

Black 15.4 :I 7.2 (26) 

Other 20.0 :I 20.0 (5) 

Unknow 0.0:1 0.0 (4) 

All race 13.S:t 1.S (363) 

S5+ ears


Whte 17.1 :t 4.2 (S2)


Black 25.0 :t 16.4 (S)


Other 0 :t 0.0 (2)


Unknow 0.0:t 0.0 (1)


Al race 17.2:t 3.9 (93)


AII ae:es


White 14.S:t 1. (9S1)


Black 14.1 :t 3.S (S5)


Other 10.0 :t 6.9 (20)


Unknown 0.0 :t 0.0 (S) 

All race 145:t 1.1 (1094) 

Female 

16.2:t 4.5 (68) 

6 :t 5.6 (lS) 

33.3 :t 33.3 (3) 

0:t 0.0 (1) 

14.5 :t 3.7 (90) 

16.2:t 1.7 (46) 

15.S :t 6.0 (38) 

12.5 :t 12.5 (S) 

0:t 0.0 (1) 

16.1 :t 1.6 (511) 

15.4 :t 1.7 (456) 

1S.5 :t 7.6 (27) 

0 :I 0.0 (2) 

0:t 0.0 (6)


15.3 :t 1.6 (491) 

11.0 :t 2.0 (23) 

15.0 :t S.2 (20) 

50.0 :t 50.0 (2) 

28.6 :t 1S.4 (7) 

12.1 :t 2.0 (265) 

14.9 :t 1.0 (1224) 

14.6 :t 3.5 (103) 

20.0 :t 10.7 (15) 

13.3 :t 9.1 (15) 

14.9 :t 1.0 (1357) 

Male & female 

1S.2 :t 2.9 (lSl) 

7 :t 4.3 (39) 

1S.2:t 12.2 (11) 

0:t 0.0 (1) 

16.4 :t 2.4 (232) 

15.1 :t 1.2 (922) 

14.7 :t 4.3 (68) 

7 :t 7.7 (13) 

0 :t 0.0 (4) 

14.9 :t 1. (1007) 

14.7 :t 1.3 (784) 

17.0:t 5.2 (53) 

14.3 :t 14.3 (7) 

0 :t 0.0 (10) 

14.6 :t 1.2 (S54) 

12.6 :t 1.9 (31S) 

17.9 :t 7.4 (28) 

25.0:t 25.0 (4) 

25.0 :t 16.4 (S) 

13.4 :I 1.S (35S) 

14.S :t O.S (2205) 

14.4 :t 2.6 (188) 

14.3 :t 6.0 (35) 

7 :t 6.0 (23) 

14.7:t 0.7 (2451) 
Appendix S: Interaction potential by hospital and patient demography, 1988 

Proportion (n) 

Race be siz 

Whte


Black


Total


(Chi-square)
 (Phi)


Race loction 

White 

Black 

Total 

(Chi-square)


(Phi)


Race control 

Whte 

Black 

Total 

(Chi-suare) 

(Phi) 

Race teachi


White


Black


Tota


(Chi-suare)


(Phi)


Race 

White


Black


Total


(Chi-square)


(Phi)


Race 

White 

Black 

Total 

(Chi-square) (Phi) 

Sex bed siz 

Male 

Female 

Total 

(Chi-square) (Phi) 

Sex loction 

Male 

Female 

Total 

(Chi-square) (Phi) 

Sex b control 

Male 

Female 

Total 

(Chi-square) (Phi) 

99 bes 

17.1S (326) 

10.00 (20) 

16.76 (34)


(0.696, 2 dC, P=O.40)


(0.045) 

Metro litan


14.S5 (1657)


17.45 (149) 

15.06 (180) 

(0.724, 1 dC, P=0.395) 

(0.20) 

Non rofit 

14.37 (1621) 

13.27 (113) 

14.30 (1734)


(0.104, 2 dC, P=0.747)


(0.00) 

status Teachin 

15.S2 (885) 

15.15 (99) 

15.75 (984)


(0.30, 1 P=0.863)


(0.00) 

Male


14.7S (9S1)


14.12 (S5) 

14.23 (106) 

(0.27 P=0.869) 

(0.005) 

0-6 

1S.23 (lSl) 

69 (39) 

16.36 (220) 

(2. dC, P=0.107) 

(0.109) 

99 bes 

16.56 (151) 

16.92 (195) 

16.76 (346)


(0.00, 2 dC, P=0.928)


(0.005) 

Metro litan 

14.61 (801) 

15.42 (1005) 

15.06 (lS06)


(0.232, 1 P=0.63O)


(0.011) 

Non rofit 

14.53 (771) 

14. 12 (963) 

14.30 (1734) 

(0.057 P=O.Sl1) 

(0.00) 

100-29 bes 

15.15 (S12) 

11.11 (63) 

14.86 (S75)


(0.753, 2 P=0.385)


(0.029) 

Nonmetro litan


14.7S (548)


56 (39) 

13.97 (5S7) 

(4.522, 1 dC, P=0.33) 

(0.08) 

Profit 

17.01 (241) 

22.73 (22) 

17.49 (263)


(0.456, 2 P=0.499)


(0.042) 

Nonteachin 

14.17 (1320) 

13.48 (S9) 

14.12 (140) 

(0.032, 1 P=0.S5S) 

(0.005) 

Female


14.S7 (1224)


14.56 (103) 

14.S5 (1327) 

(0.007, 1 P=0.933) 

(0.002) 

65-8 

14.S9 (1706) 

15.70 (121) 

14.94 (lS27) 

(0.059, 2 dC, P=O.80S) 

(0.00) 

100-299 beds 

15.32 (385) 

14.49 (490) 

14.86 (S75)


(0.119, 2 dC, P=0.73O)


(0.012) 

Nonmetro litan 

15.09 (265) 

13.04 (322) 

13.97 (5S7)


(0.509, 1 dC, P=0.476)


(0.029) 

Profit 

19. 13 (115) 

16.22 (14S) 

17.49 (263) 

(0.381 , 2 P=0.537) 

(0.38) 

30+ bes 

13.S7 (1067) 

17.14 (105) 

14.16 (1172)


(0.842, 2 P=0.359)


(0.27) 

Total 

14.83 (2205) 

14.36 (188) 

14.79 (2393) 

(0.030, 1 dC, P=0.862) 

(0.00) 

Government 

15.45 (343) 

13.21 (53) 

15.15 (396) 

(0.180 dC, P=0.671) 

(0.021) 

Total 

14.83 (2205) 

14.36 (188) 

14.79 (2393) 

(0.030, P=0.862) 

(0.00) 

Total


14.S3 (2205)


14.36 (188) 

14.79 (2393) 

(0.30, 1 P=0.862) 

(0.00) 

S5+ 

12.5S (31S) 

17.8 (28) 

1301 (34)


(0.634, dC, P=0.426) 

(0.043) 

30+ beds 

13.77 (530) 

14.49 (642) 

14.16 (1172) 

(0.121 dC, P=0.728) 

(0.010) 

Total 

14.73 (106) 

14.S5 (1327) 

14.79 (2393) 

(0. , 1 dC, P=0.936) 

(0.002) 

Government 

12.7S (180) 

17.13 (216) 

15.15 (396) 

(1.44 P=0.229) 

(0.06) 

Total 

14.S3 (2205) 

14.36 (188) 

14.79 (2393) 

(0.30, dC, P=0.862) 

(0.00) 

Total 

14.S3 (2205) 

14.36 (188) 

14.79 (2393) 

(0.30 dC, P=0.862) 

(0.00) 

Total 

14.S3 (2205) 

14.36 (188) 

14.79 (2393) 

(0.30, 2 P=0.862) 

(0.00) 

Total 

14.73 (106) 

14.S5 (1327) 

14.79 (2393) 

(0. , 2 dC, P=0.936) 

(0.002) 

Total 

14.73 (106) 

14.S5 (1327) 

14.79 (2393) 

(0. P=0.936) 

(0.002) 
. Sex teachin status Teachin 

Male 16.16 (427) 

Female 15.44 (557) 

Total 15.75 (984) 

(Chi-suare) (0. , 1 df, P=0.759) 

(Phil (0.010) 

Sex 0-6 

Male 17.91 (134)


Female 13.95 (86)


Total 16.36 (220)


(Chi-square) (0.599, 2 df, P=0.439)


(Phi) (0.052)


be siz 99 bes 

0-0 1S.75 (32) 

65-8 16.94 (242) 

85+ 15.28 (72) 

Total 16.76 (34) 

(Chi-square) (0.210, 4 df, P=O.90) 

(Phi) (0.025) 

loction Metro litan 

0-0 16.67 (168) 

65-8 15.41 (1402) 

85+ 11.86 (23) 

Total 15.06 (lS06) 

(Chi-square) (2.355, 2 df, P=O.30) 

(Phil (0.043) 

control Non rofit 

0-0 16.7S (149) 

65-8 13.9S (1345) 

85+ 14.5S (24) 

Total 14.3 (1734) 

(Chi-square) (0.S76, 4 df, P=0.645) 

(Phil (0.022) 

teachin sta tus Teachin 

0-0 17.17 (99) 

65-8 16.09 (75S) 

S5+ 12.60 (127) 

Total 15.75 (984) 

(Chi-square) (1.69, 2 df, P=0.557) 

(Phil (0.034) 

Bed siz loction Metro litan 

99 19.77 (86) 

100-299 bes 15.72 (59S)

30+ bes 14.35 (1122) 

Total 15.06 (180) 

(Chi-square) (2.136, 2 df, P=O.34) 

(Phil (0.034) 

Bed siz control Non rofit 

99 19.75 (157) 

100-299 14.95 (5S2)

30+ bes 1307 (995) 

Total 14.30 (1734) 

(Chi-square) (5.235, 4 df, P=0.73) 

(Phil (0.055) 

Bed siz teachin status Teachin 

99 25.00 (12) 

100-299 bes 17.17 (19S)

30+ bes 15.25 (774) 

Total 15.75 (984) 

(Chi-square) (1.224, 2 df, P=0.542) 

(Phil (0.035) 

Nonteachin 

13.77 (639) 

14.42 (770) 

14.12 (140) 

(0.119, 1 df, P=0.730) 

(0.00) 

65-8 

13.90 (842) 

15.84 (98) 

14.94 (lS27) 

(1.347, 2 df, P=O.24) 

(0.027) 

100-29 bes 

13.24 (68) 

15.24 (676) 

13.74 (131) 

14.86 (S75)


(0.34, 4 df, P=O.84)


(0.020) 

Nonmetro litan 

15.38 (52) 

13.41 (425) 

15.45 (110) 

13.97 (5S7)


(0.399, 2 df, P=0.S19)


(0.26) 

Profit 

17.86 (28) 

16.41 (195) 

22.50 (40) 

17.49 (263)


(0.S56, 4 df, P=0.652)


(0.057) 

Nonteachin 

15.70 (121) 

14.13 (1069) 

13.24 (219) 

14.12 (140)


(0.389, 2 df, P=O.S23)


(0.017 

Nonmetro litan 

15.77 (26) 

13.00 (277) 

10.00 (50) 

13.97 (5S7)


(1.575, 2 df, P=0.455)


(0.052) 

Profit 

23.21 (56) 

13.66 (161) 

23.91 (46) 

17.49 (263)


(4.219, 4 df, P=0.121)


(0.127) 

Nonteachin 

16.47 (334) 

14.1S (677) 

12.06 (39S) 

14.12 (1409)


(2.911, 2 df, P=0.233)


(0.045) 

Total 

14.73 (106) 

14.85 (1327) 

14.79 (2393) 

(0.06, 1 df, P=O.93) 

(0.002) 

S5+


17.7S (90)


11.33 (256) 

13.01 (34)


(2.44, 2 df, P=O.l1S)


(0.84) 

30+ be 

17.50 (120) 

14.19 (90) 

11.19 (143) 

14.16 (1172) 

(2140, 4 df, P=0.343) 

(0.43) 

Total 

16.36 (220) 

14.94 (lS27)


1301 (34)


14.79 (2393) 

(1.340, 2 df, P=0.512) 

(0.024) 

Government 

13.95 (43) 

1S.47 (287) 

1.52 (66) 

15.15 (396)


(12.04, 4 df, P=0.OO2)


(0.174) 

Total 

16.36 (220) 

14.94 (lS27) 

13.01 (34) 

14.79 (2393) 

(1.34 2 df, P=0.512) 

(0.24) 

Total 

16.76 (34) 

14.86 (S75) 

14.16 (1172) 

14.79 (2393)


(1.436, 2 df, P=O.48)


(0.024) 

Government 

10.53 (133) 

15.91 (132) 

19.08 (131) 

15.15 (396)


(3.84, 4 df, P=O.l46)


(0.09) 

Total 

16.76 (34) 

14.86 (S75) 

14.16 (1172) 

14.79 (2393) 

(1.436 2 df, P=O.48) 

(0.024) 

14.73 (106)


14.S5 (1327)


14.79 (2393) 

(0. , 2 df, P=0.936) 

(0.002) 

Total 

16.36 (220) 

14.94 (1827) 

13.01 (34) 

14.79 (2393) 

(1.34 4 df, P=0.512) 

(0.24) 

Total 

16.36 (22) 

14.94 (lS27) 

1301 (34) 

14.79 (2393) 

(1.340, 4 df, P=0.512) 

(0.024) 

Total 

16.76 (346) 

14.86 (S75) 

14.16 (1172) 

14.79 (2393) 

(1.436, 4 df, P=O.48) 

(0.024) 
Lotion by control Nonprofit

Metropolitan 14.33 (1403) 

Nonmetropolitan 14.20 (331) 

- Total 14.30 (1734) 

(Chi-square) (0.04, 2 dr, P=0.953) . (PhO (0.001) 

Lotion by teachine: status Teachine: 

Metropolitan 16.08 (939) 

Nonmetropolitan S.S9 (45) Total 15.75 (984) 

(Chi-square) (1.674, 1 dr, P=o.l96) (PhO (0.041) 

Control by teachine: status Teachine: Profit 22.22 (27) Nonprofit 14.86 (86)
 Government 22.47 (S9)
 Total 15.75 (984)


(Chi-square) (4.399 2 dr, P=0.1l1) (PhO (0.067) 

Profit 

16.08 (199) 

21.S7 (64) 

17.49 (263) 

(1.127 2 dr, P=O.28) 

(0.065) 

Nonteachine: 

13.96 (867) 

14.39 (542) 

14.12 (140) 

(0.052, 1 dr, P=0.S2O) 

(0.00) 

Nonteachine: 

16.95 (23) 

13.74 (86) 

1303 (307) 

14.12 (140) 

(1.961

, 2 dr, P=0.375) 

(0.037) 

Government 

19.12 (20) 

10.94 (192) 

15.15 (396)


(5.148, 2 dr, P=o.23)


(0.114) 

Total 

15.06 (180) 

13.97 (5S7) 

14.79 (2393) 

(0.419, 1 dr, P=0.51S) 

(0.013 

Total 

17.49 (263) 

14.30 (1734) 

15.15 (396) 

14.79 (2393) 

(1.S90, 2 dr, P=0.389) 

(0.028) 

Total 

15.06 (180) 

13.97 (5S7) 

14.79 (2393) 

(0.419, 2 dr, P=O.SlS) 

(0.013) 
- Appendix 9: Projected national CMI before recing by hospital demography, 1988 

CMI :t standard errr (n) 

99 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

100-29 be Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

30+ bes Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

Metropolitan 

9102:t 0.24 (6) 

2243:t 0.1764 (20) 

151S :t 0.146 (26) 

1.0622 :t 0.1379 (2) 

lS17:t 0.1162 (35) 

1.752:t 0.1101 (37) 

5912:t 0.00 (1) 

1.0317 :t 0.1165 (26) 

1.0154 :t 0.1132 (27) 

90 :t 0.1630 (9) 

1.441 :t 0.75S (Sl) 

1.205 :t 0.0703 (90) 

1.2991 :t 0.241 (15) 

1.4367 :t 0.1194 (117) 

1.4210 :t 0.1091 (132) 

1.3973 :t 0.079S (145) 

1.2974 :t 0.0520 (267) 

3326 :t 0.0438 (412) 

1.4597 :t 0.2500 (lS) 

2830 :t 0.1287 (46) 

1.327 :t 0.1155 (64) 

1.3953 :t 0.0722 (17S) 

1.3338 :t 0.047S (430) 

351S :t 0.039S (60) 

1.0205 :t 0.1390 (S) 

1.0912 t 0.0952 (41) 

0797 t 0.0824 (49) 

1.4133 t 0.04 (703) 

1.3396 t 0.0544 (276) 

1.3925 t 0.0331 (979) 

1.242 :t 0.1190 (65) 

1.23 :t 0. 1180 

1.2426 t 0.08 (119) 

1.3954 t 0.038 (776) 

1.2970 t 0.0453 (371) 

3636 t 0.029S (1147) 

1.41S t 0.1391 (29) 

1.3332 :t 0.083 (17S)

1.30 t 0.0751 (207) 

1.40S t 0.036 (SSO) 

1.3105 t 0.036 (57S) 

1.3696 t 0.0261 (1428) 

1.2857 t 0.1065 (84) 

1.110 t 0.0730 (126) 

1.2409 t 0.0610 (210) 

1.390 t 0.0337 (963) 

1.30 t 0.030 (882) 

1.3479 t 0.0230 (1845) 

Nonmetropolitan 

no 

1.201 :t 0.1121 (33) 

201 :t 0.1121 (33) 

1.0774:t 0.00 (1) 

1.06 :t 0.0538 (123) 

067 :t 0.0533 (124) 

1.099 :t 0.3745 (3) 

1.0620 :t 0.043 (109) 

1.0629 :t 0.047S (112) 

1.09 :t 0.26 (4) 

0815 :t 0.34 (265) 

0817 :t 0.034 (269) 

no 

4473 :t 0.124 (32) 

1.4473 :t 0.124 (32) 

1.46 :t 0.2593 (21) 

1.20 :t 0.0654 (159) 

1.23 :t 0.0652 (180) 

1.0029 :t 0.151S (3) 

1.3385 :t 0.09 (70) 

1.3247:t 0.09 (73) 

1.4034 :t 0.2289 (24) 

1.2675 :t 0.0499 (261) 

1.27S9 :t 0.0495 (285) 

no case 

no case 

no 

1.48 :t 0.1257 (15) 

2235 t 0.1889 (22) 

1.931 t 0.1221 (37) 

768 :t 0.2545 (2) 

1.38 :t 0.1889 (13) 

3054 t 0.1740 (15) 

1.039:t 0.1167 (17)

28 t 0.136 (35) 

1.2255 t 0.097 (52) 

no case 

1.326 t 0.08 (65) 

1.326 t 0.08 (65) 

3237 t 0.1561 (37) 

1.469 t 0.0428 (304) 

1.661 :t 0.0417 (341) 

9795 :t 0.1489 (S) 

1.849 t 0.0471 (192) 

1.766 t 0.0456 (20) 

1.2625 t 0.1320 (45) 

1.807 t 0.0299 (561) 

1.86 t 0.0293 (60) 

Metropolitan & nonmetropolitan 

9102:t 0.24 (6) 

1.2148:t 0.954 (53)


lS39 :t 0.0893 (59)


1.0673 :t 0.798 (3) 

1.09 :t 0.0491 (15S) 

091 :t 0.482 (161) 

9705:t 0.2934 (4)


1.0561 :t 0.04 (135)


0537:t 0.041 (139)


9650 :t 0.1351 (13) 

092:t 0.0320 (34)


0914 :t 0.0312 (359)


1.291 :t 0.241 (15) 

1.4390 :t 0.093 (149)


4262 :t 0.0910 (164)


4053:t 0.0767 (166) 

2611 :t 0.047 (426) 

1.3015 :t 0.36 (592) 

1.3944 :t 0.2171 (21) 

1.3165 :t 0.0769 (116) 

1.328 :t 0.0728 (137) 

1.3963 :t 0.0690 (202) 

307:t 0.0352 (691) 

1.3285 :t 0.0314 (S93) 

0205 t 0.1390 (S) 

1.0912 t 0.0952 (41) 

1.0797 t 0.0824 (49) 

407S :t 0.041 (71S) 

1.3310 t 0.0522 (29S) 

1.3853 t 0.0322 (1016) 

2338 t 0.1160 (67) 

2655 :t 0.1016 (67) 

1.2497 t 0.0768 (134) 

3892:t 0.0377 (793) 

1.296 t 0.0430 (40) 

1.3576 t 0.0289 (1199) 

1.41S t 0.1391 (29) 

1.3314 t 0.0657 (243) 

1.3112 t 0.065 (272) 

1.4062 t 0.0355 (887) 

1.2541 t 0.0279 (882) 

1.330 :t 0.0226 (1769) 

1.2590 t 0.0984 (92) 

1.952 t 0.045 (31S) 

205 t 0.0383 (410) 

1.3851 :t 0.0327 (l00S) 

1.2542 t 0.0222 (1443) 

1.30 t 0.0188 (2451) 
Appendix 10: Projected national CMI before reing by patient demography, 1988 

CMI:I standard errr (n)


Male Female Male & female
 0-6 ears


White 3911 :I 0.1076 (113) 1.2161 :I 0.0972 (68) 1.3253:1 0.0765 (lSl)

Black 1.4755 :I 0.2295 (21) 9S99 :I 0.07S1 (lS) 1.2514 :I 0.1331 (39) Other S347 :I 0.1370 (S) 1.5011 :I 0.5568 (3) 1.0165 :I 0.lS7S (11) Unknow no case 7493:1 0.00 (1) 7493:1 0.00 (1) All race 1.3722 :I 0.0928 (142) 1.751 :I 0.0774 (90) 1.295S :I 0.06 (232) 

65-74 ears 

White 1.4345 :I 0.0526 (45S) 1.3235 :I 0.0455 (46) 1.3786 :I 0.034 (922) Black 5131 :I 0.1795 (30) 1.543 :I 0.1014 (38) 1.2567 :I 0.1005 (68) Other 1.4375:1 0.1785 (5) 22316 :I 0.5628 (S) 922 :I 0.36 (13) Unknow 1.3814 :I 0.2750 (3) S535 :I 0.00 (1) 1.2494 :I 0.2350 (4) All race 1.4389 :I 0.049S (496) 1.3168:1 0.0432 (511) 1.3769 :I 0.329 (1007) 

75-8 yea 

Whte 1.2776 :I 0.0432 (328) 1.2631 :I 0.0434 (456) 2692 :I 0.0310 (784) Black 1.S33 :I 0.1373 (26) 9396 :I 0.689 (27) 1.0591 :I 0.0771 (53) Other 1.5S5 :I 0.0675 (5) 1.3692 :I 0.370 (2) 1.21S7 :I 0.090 (7) Unknow 7977:1 0.1495 (4) 262:1 0.5112 (6) 1.0752 :I 0.305 (10) 

Al race 1.2639 :I 0.043 (363) 1.2457:1 0.0410 (491) 1.2535 :I 0.0291 (S54) 

S5+ ears 

White 3333 :I 0.0934 (S2) 1.2326 :I 0.0425 (23) 1.2586 :I 0.0396 (31S) Black 1.51S :I 0.20 (S) 1.477:1 0.1759 (20) 1.489:1 0.1370 (28) Other 1802 :I 0.2574 (2) 2104 :I 0.lS74 (2) 1953:1 0.1302 (4) Unknow 1.0222:1 0.00 (1) 1.4490 :I 0.369 (7) 1.3956 :I 0.3239 (S) 

Al race 1.110 :I 0.0843 (93) 1.2317:1 0.0411 (265) 1.2523 :I 0.0374 (35S) 

AII al!es 

White 1.36 :I 0.0320 (9S1) 2775 :I 0.0256 (1224) 1.3180 :I 0.0201 (2205) Black 1.369 :I 0.09 (S5) 1.0311 :I 0.0551 (103) 1.S38 :I 0.0544 (188) Other 1.00 :I O.OS99 (20) l.S343 :I 0.3289 (15) 1.4152 :I 0.159S (35) Unknow 046 :I 0.1527 (S) 1.2871 :I 0.262 (15) 1.2028 :I 0.1769 (23) All race 1.3613 :I 0.029S (1094) 1.2651 :I 0.0240 (1357) 30 :I 0.0188 (2451) 
99 

Appendix 11: Projected national CMI after recing by hospital demography, 1988 

CMI t standard errr (n) 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Goernment Nonteaching 

Teaching & nonteaching 

Teaching 

Nonteaching 

Teaching & nonteaching 

100-299 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

30+ bes Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

Metropolitan 

9536 t 0.2322 (6) 

1.2292 t 0.1749 (20) 

1656 t 0.144 (26) 

1.0630 t 0.1371 (2) 

1.402 t 0.1156 (35) 

1.36 t 0.1095 (37) 

5912 t 0.00 (1) 

9450 t 0.0859 (26) 

9319 t 0.0836 (27) 

9376 t 0.1585 (9) 

1.095 t 0.717 (Sl) 

1.0833 t 0.06 (90) 

1.3773 t 0.2935 (15) 

1.4339 t 0.l1S5 (117) 

1.4274 t 0.109 (132) 

1.399 t 0.771 (145)


1.3214 t 0.521 (267)


347 t 0.0433 (412) 

1.5520 t 0.24 (lS) 

2494 t 0.1211 (46) 

1.3345 t 0.1111 (64) 

1.4127 t 0.0714 (17S) 

1.343 t 0.0474 (430) 

363 t 0.395 (60) 

9125 t 0.1588 (S) 

1.798 t 0.109 (41) 

1362 t 0.0955 (49) 

1.402 t 0.399 (703)


1.3516 t 0.0550 (276) 

390 t 0.325 (979) 

1.2723 t 0.1232 (65) 

1.205 t 0.l1S9 (54) 

2438 t 0.0859 (119) 

1.3899 t 0.0376 (776) 

1.3120 t 0.0460 (371) 

1.367 t 0.0295 (1147) 

1.614 t 0.1667 (29) 

1.3524 t 0.083 (17S) 

1.3256 t 0.762 (207)


1.401 t 0.355 (S50)


1.324 t 0.363 (57S)


3720 t 0.257 (1428)


3241 t 0.1091 (84) 

1695 t 0.0700 (126) 

1.2314 t 0.06 (210) 

1.3899 t 0.331 (963) 

1.3082 t 0.30 (882) 

1.508 t 0.227 (1845)


Nonmetropolitan Metropolitan & nonmetropolitan 

no 9536 t 0.2322 (6) 

1.233 t 0.126 (33) 1.2323 t 0.101S (53) 

1.233 t 0.126 (33) 1.20 t 0.945 (59) 

1.0774 t 0.00 (1) 1.067S t 0.0793 (3)

1.06 t 0.0510 (123) 1.0827 t 0.0471 (15S)

1.06 t 0.0506 (124) 1.0824 t 0.043 (161) 

1.222 t 0.399 (3) 9S94 t 0.3123 (4) 

1.742 t 0.0522 (109) 1.0493 t 0.0454 (135) 

1.0755 t 0.0516 (112) 0476 t 0.04 (139) 

1.110 t 0.2829 (4) 9910 t 0.1352 (13) 

1.905 t 0.0356 (265) 1.09 t 0.0320 (34) 

1.09 t 0.353 (269) 1.089 t 0.0312 (359) 

no 3773 t 0.2935 (15) 

4354 t 0.1410 (32) 1.4342 t 0.0976 (149) 

1.4354 t 0.1410 (32) 1.4290 t 0.09 (164) 

1.4546 t 0.2599 (21) 1.4061 t 0.0746 (166)

201 t 0.063 (159) 1.27S3 t 0.04 (426)

231 t 0.063 (180) 1.3141 t 0.036 (592) 

980 t 0.1726 (3) 1.4704 t 0.2140 (21) 

2877 t 0.08 (70) 2725 t 0.0707 (116) 

1.2751 t 0.0837 (73) 1.328 t 0.062 (137) 

1.3954 t 0.2297 (24) 1.4106 t 0.06 (202) 

2561 t 0.04 (261) 1.110 t 0.034 (691) 

1.267S t 0.04 (285) 3335 t 0.311 (S93) 

no case 9125 t 0.1588 (S) 

no case 1.798 to.109 (41) no 1362 t 0.0955 (49) 

1499 t 0.1255 (15) 40 t 0.0392 (71S) 

2490 t 0.lS70 (22) 34 t 0.0527 (29S)

20 t 0.1211 (37) 1.3842 t 0.317 (1016) 

768 t 0.2545 (2) 1.2573 t 0.120 (67) 

4267 t 0.188 (13) 2517 t 0.1026 (67) 

3389 t 0.1747 (15) 2545 t 0.786 (134) 

1.050 t 0.1166 (17) 1.3838 t 0.0369 (793) 

3150 t 0.135S (35) 1.3122 t 0.0436 (40)

243 t 0.093 (52) 1.3595 t 0.0285 (1199) 

no 1.614 t 0.1667 (29) 

3333 t 0.0947 (65) 1.3473 t 0.06 (243) 1.3333 t 0.0947 (65) 3274 t 0.0621 (272) 

1.320 t 0.1563 (37) 1.407 t 0.34 (887) 

1.527 t 0.041S (30) 1.2655 t 0.279 (882) 

1709 t 0.0409 (341) 3333 t 0.223 (1769) 

980 t 0.1591 (S) 1.2943 t 0.100 (92) 

1.759 t 0.045S (192) 1734 t 0.0391 (31S) 

1.681 t 0.04 (200) 1.205 t 0.037S (410) 

1.26 t 0.1324 (45) 1.381 t 0.0322 (l00S) 

1.S15 t 0.296 (561) 1.2590 t 0.0222 (1443) 

1.S74 t 0.0291 (60) 1.3104 t O.Ql86 (2451) 
Appendix 12: Projected national CMI after recing by patient demography, 1988 

CMI t standard eITr (n) 

Male Female Male & female
 0-6 ears


White 1.4053 t 0.1070 (113) 2675 t 0.1083 (68) 3535 t 0.07S2 (lSl) 

Black 1.4144 t 0.2245 (21) 1.00 t 0.0796 (lS) 223 t 0.1293 (39) 

Other 1.342 t 0.243 (S) 1.6164 t 0.4901 (3) 2657 t 0.2216 (11)

Unknow no case 7493 t 0.00 (1) 7493 t 0.00 (1) 

Al race 1.3914 t 0.091 (142) 220 t 0.0855 (90) 3249 t 0.0655 (232) 

65-74 ears 

White 1.403 t 0.0508 (45S) 1.3233 t 0.04 (46) 36 t 0.0337 (922) 

Black 1.4652 t 0.1741 (30) 1.0727 t O.09S (38) 1.2459 t 0.0971 (68) 

Other 1.4375 t 0.1785 (5) 2121 t 0.5697 (S) 1.9142 t 0.3639 (13)

Unknow 1.3814 t 0.2750 (3) S535 t 0.00 (1) 2494 t 0.2350 (4) All race 1.4101 t 0.041 (496) 1.3177 t 0.0422 (511) 3632 t 0.0319 (1007) 

75-8 ears 

White 277S t 0.04 (328) 1.2653 t 0.0428 (456) 2705 t 0.0310 (784) 

Black 228 t 0.140 (26) 9794 t 0.0837 (27 1017 t 0.0822 (53) 

Other 1.055 t 0.1100 (5) 1.392 t 0.370 (2) 1.80 t 0.1177 (7) Unknow 7977 t 0.1495 (4) 262 t 0.5112 (6) 1.0752 t 0.35 (10) All race 26 t 0.0414 (363) 1.2500 t 0.045 (491) 2570 t 0.0292 (S54) 

S5+ vea 

Whte 1.4226 t 0.1010 (S2) 1.241S t 0.0436 (23) 28 t 0.0417 (31S) 

Black 2314 t 0.196 (S) 1.1191 t 0.1788 (20) 1.512 t 0.1379 (28)

Other 1.802 t 0.2574 (2) 3409 t 0.0569 (2) 1.265 t 0.1172 (4)

Unknow 1.0222 t 0.00 (1) 1.4573 t 0.362 (7) 1.4029 t 0.3201 (S)

All race 1.396 t 0.09 (93) 1.2390 t 0.0421 (265) 2799 t 0.0392 (35S) 

All ae:es


White 36 t 0.0317 (9S1) 1.2829 t 0.0254 (1224) 1.3192 t 0.0199 (2205) 

Black 1.35S3 t 0.0943 (S5) 1.047 t 0.0563 (103) 1.865 t 0.0537 (188) 

Other 1.2075 t 0.1127 (20) 1.86 t 0.324 (15) 4890 t 0.1603 (35) 

Unknown 1.04 t 0.1527 (S) 1.2910 t 0.2591 (15) 1.2053 t 0.1762 (23) All race 35S9 t 0.0294 (1094) 1.2713 t 0.023 (1357) 1.3104 t 0.0186 (2451) 
Appendix 13: Mean CMI change by hospital demogrphy, 1988 

CMI change :t standard errr (n) 

99 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

Nonteaching 

Teaching & nonteaching 

100-299 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

Nonteaching 

30+ bes Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

Nonteaching 

Teaching & nonteaching 

Metropolitan 

0433:t 0.0433 (6) 00 :t 0.0145 (20) 

0137 :t 0.0148 (26) 

00 :t 0.00 (2) 

-0.0415 :t 0.0538 (35) 

-0.0392 :t 0.0509 (37) 

00 :t 0.00 (1) 

-0.087 :t 0.065 (26) 

-0.0835 :t 0.05S3 (27) 

029 :t 0.028 (9) 

-0.045 :t 0.030 (Sl) 

-0.0372 :t 0.276 (90) 

07S2 :t 0.1457 (15) 

-0.0027 :t 0.0231 (117) 00 :t 0.0261 (132) 

0017:t 0.0341 (145) 

0239 :t 0.0245 (267) 

0160 :t 0.0199 (412) . 

09 :t 0.0915 (lS) 

-0.0335 :t 0.0373 (46) 

OOlS :t 0.0374 (64) 

0173:t 0.316 (17S)


0105 :t 0.0169 (430) 

0124 :t 0.0151 (60) 

-0.108 :t 0.752 (S) 08 :t 0.0621 (41) 

0565 :t 0.541 (49) 

-0.0071 :t 0.0157 (703) 

0120 :t 0.015S (276) 

-0.0017 :t 0.0121 (979) 

0241 :t 0.030 (65) 

-0.026 :t 0.0560 (54) 

0012 :t 0.305 (119) 

-0.0055 :t 0.0145 (776) 

0149:t 0.0159 (371) 

0010 :t 0.0110 (1147) 

. 0.0196 :t 0.786 (29) 

0191 :t 0.0210 (17S) 

0192 :t 0.0211 (207) 

-O.0056:t 0.0142 (S50) 

0142 :t 0.0140 (57S) 00 :t 0.0102 (1428) 

038 :t 0.030 (84) 

-0.0414 :t 0.0301 (126) 

-0.005 :t 0.0220 (210) 

-0.0010 :t 0.0130 (963) 

0073 :t 0.0110 (882) 

0029 :t 0.00 (1845) 

Nonmetropolitan 

no 

0251 :t 0.09 (33) 

0251 :t 0.099 (33) 

00 :t 0.00 (1) 

0017 :t 0.020 (123) 

0017 :t 0.019S (124) 

0252 :t 0.0252 (3) 

0.122 :t 0.0177 (109) 

0.125 :t 0.0172 (112) 

0.lS9 :t 0.01S9 (4) 

009:t 0.0164 (265) 

001 :t 0.0161 (269) 

no 


-0.0119 :t 0.05S9 (32)


-0.0119 :t 0.05S9 (32)


-0.0059 :t 0.0059 (21) 

001 :t 0.0194 (159) 

007 :t 0.0172 (180) 

-0.0222 :t 0.0222 (3) 

-0.0508 :t 0.0451 (70) 

-0.0496 :t 0.0433 (73) 

-0.00 :t 0.005S (24) 

-0.0113 :t 0.0184 (261) 

-0.0110 :t 0.0168 (285) 

no 

no 

no 

0013 :t 0.0013 (15) 

0254 :t 0.020 (22) 

0156 :t 0.0123 (37) 

00 :t 0.00 (2) 

0.38 :t 0.038 (13) 

0334 :t 0.0334 (15) 

0011 :t 0.0011 (17) 

0303 :t 0.0190 (35) 

020 :t 0.0129 (52) 

no00 :t 0.0550 (65) 00 :t 0.0550 (65) 

-0.0028 :t 0.0034 (37) 

0057 :t 0.0130 (30) 00 :t 0.0116 (341) 

0011 :t 0.0134 (S) 

-0.009 :t 0.0195 (192) 

-0.005 :t 0.01S7 (20) 

-0.0021 :t 0.0036 (45) 00 :t 0.0116 (561) 00 :t 0.0107 (60) 

Metropolitan & nonmetropolitan


0433:t 0.0433 (6)


0175 :t 0.057S (53)


0201 :t 0.0520 (59)


0.005 :t 0.005 (3)


-O.007S :t 0.195 (15S)


-0.0077 t 0.0192 (161)


01S9:t 0.01S9 (4)


-0.00 :t 0.0186 (135)


-0.00 :t 0.0180 (139)


0259 :t 0.0203 (13)


-0.0035 :t 0.0144 (34)


-0.0025 :t 0.0139 (359)


07S2 :t 0.1457 (15)


-0.007 :t 0.0220 (149)
 00 :t 0.0239 (164) 

0.007 :t 0.029S (166)


0172 :t 0.0170 (426)


0126 :t 0.0148 (592)


0759 :t 0.0786 (21) 

-0.0439 :t 0.030 (116) 

-0.0256 :t 0.0289 (137) 

0143 :t 0.027S (202) 

0022 :t 0.0126 (691) 

009 :t 0.0116 (S93) 

-0.108 :t 0.752 (S) 08 :t 0.0621 (41)


0565 :t 0.0541 (49)


-0.009 :t 0.0154 (71S) 

0130 :t 0.0147 (29S) 

-0.0011 :t 0.0117 (1016) 

023 :t 0.030 (67) 

-0.0138 :t 0.045S (67) 00 :t 0.0273 (134) 

-0.0054 :t 0.0142 (793) 

0162:t 0.0146 (406) 

0019 :t 0.0106 (1199) 

0196 :t 0.0786 (29)


015S :t 0.0212 (243)


0162 :t 0.0207 (272)


-0.0055 :t 0.0136 (887) 

0113 :t 0.0102 (882) 

0028 :t 0.OOS5 (1769) 

0352 :t 0.0281 (92) 

-O.021S :t 0.0167 (31S) 

-0.00 :t 0.0145 (410) 

-0.0010 :t 0.0125 (l00S) 

007 :t 0.001 (1443)


0023 :t 0.0070 (2451)

Appendix 14: Mean CMI change by patient demography, 1988 

CMI change :I standard errr (n) Male Female Male & female 

0-6 vea 

White 0142 :I 0.0338 (113) 0514 :I 0.034 (68) 0281 :I 0.0247 (lSl) 

Black -0.0611 :I 0.0595 (21) 0107 :I 0.0107 (lS) -0.0279 :I 0.325 (39) Other 2995 :I 0.2172 (S) 1153 :I 0.1153 (3) 2492 :I 0.1594 (11) Unknow no case 00 :I 0.00 (1) 00 :I 0.00 (1) All race 0.191 :I 0.0311 (142) 04 :I 0.0263 (90) 0291 :I 0.215 (232) 

65-74 ears 

White -0.0281 :I 0.0166 (45S) -0.0001 :I 0.0192 (46) -0.0140 :I 0.0127 (922)


Black -0.0479:1 0.919 (30) 0184 :I 0.434 (38) -0.0108 :I 0.0470 (68)
 Other 00 :I 0.00 (5) -0.0194:1 0.0194 (S) -0.0119 :I 0.0119 (13)
 Unknow 00 :I 0.00 (3) 00 :I 0.00 (1) 00 :I 0.00 (4)
 All race -0.028 :I 0.0163 (496) 00 :I 0.0177 (511) -0.0137 :I 0.0120 (1007)


75-8 ears 

White 0.001 :I 0.0179 (328) 0022 :I 0.0147 (456) 0013 :I 0.0114 (784) 

Black 0453 :I 0.0775 (26) 0.39S :I 0.797 (27) 0425 :I 0.0551 (53) Other -0.0530 :I 0.0530 (5) 00 :I 0.00 (2) -0.0379 :I 0.0379 (7) Unknow 00 :I 0.00 (4) 00 :I 0.00 (6) 00:1 0.00 (10) All race 0026 :I 0.0171 (363) 002:1 0.0143 (491) 0035 :I 0.0110 (S54) 

S5+ ears


White 0892 :I 0.0535 (S2) 001 :I 0.0156 (23) 029S :I 0.0180 (31S)
 Black 0.795 :I 0.538 (S) -0.028 :I 0.0165 (20) 0022 :I 0.020 (28)
 Other 00 :I 0.00 (2) 1305 :I 0.1305 (2) 0652:1 0.0652 (4)
 Unknow 00 :I 0.00 (1) 003 :I 0.335 (7) 0072 :I 0.0291 (S)
 All race 0855:1 0.0474 (93) 0072 :I 0.0140 (265) 0.275 :I 0.0161 (35S)


All ae:es


White -0.0039 :I 0.0115 (9S1) 0053 :I 0.007 (1224) 0012 :I 0.0074 (2205)

Black -0.0106 :I 0.0429 (S5) 0135 :I 0.0263 (103) 0026 :I 0.0241 (188) Other 1065 :I 0.091S (20) 030 :I 0.0307 (15) 0.737 :I 0.0538 (35) Unknow 00 :I 0.00 (S) 0038 :I 0.0150 (15) 0025 :I 0.007 (23) All race -0.0024 :I 0.0109 (1094) 002 :I 0.00 (1357) 0023 :I 0.0070 (2451) 
Appendix 15: Mean reimbursment change by hospital demography, 1988 

$ :t standard errr (n) 

99 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

100-29 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

30+ bes Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

Metropolitan 

135.16 :t 135.16 (6) 

15.16 :t 45.22 (20) 

42.86 :t 46.27 (26) 

2.49 :t 2.49 (2) 

129.47:t 167.91 (35) 

122.34 :t 15S.79 (37) 

00 :t 0.00 (1) 

270.5S :t 188.75 (26) 

26.56 :t 1Sl.90 (27) 

90.66 :t 90.04 (9) 

139.05:t 94.94 (Sl) 

116.08 :t 86.13 (90) 

243.S2 :t 454.56 (15) 

-8.66 :t 72.29 (117) 

20.02 :t S1.61 (132) 

5.3 :t 106.40 (145) 

74.55 :t 76.64 (267) 

50.19 :t 62.14 (412) 

287.84 :t 285.36 (lS) 

104.64 :t 116.31 (46) 

73 :t 116.70 (64) 

54.00 :t 9S.64 (17S) 

32.74:t 52.97 (430) 

38.96 :t 47.26 (60) 

336.74:t 23.56 (S) 

276.34 :t 193.68 (41) 

176.24 :t 168.93 (49) 

22.32 :t 49.12 (703) 

37.63 :t 49.48 (276) 

5.42 :t 37.93 (979) 

75.38 :t 96.50 (65) 

-82.48 :t 174.91 (54) 

74 :t 95.11 (119) 

17.38:t 45.30 (776) 

46.53 :t 49.62 (371) 

29:t 34.59 (1147)


61.S :t 245.20 (29) 

59.65 :t 65.64 (17S) 

59.S7 :t 65.79 (207) 

17.54:t 44.47 (850) 

44.57:t 43.73 (57S) 

7.59 :t 31.84 (1428) 

120.01 :t 96.04 (84) 

129.39 :t 94.07 (126) 

29.62 :t 68.64 (210) 

17 :t 40.S0 (963) 

22.76 :t 34.34 (882) 

22 :t 26.88 (1845) 

Nonmetropolitan 

no 

66.38 :t 245.17 (33) 

66.38 :t 245.17 (33) 

00 :t 0.00 (1) 

53:t 52.79 (123)


49 :t 52.37 (124) 

66.62 :t 66.62 (3) 

32.26:t 46.67 (109) 

33.18 :t 45.44 (112) 

49.97 :t 49.97 (4) 

23.64 :t 43.28 (265) 

24.03 :t 42.64 (269) 

no 

31.56 :t 155.51 (32) 

31.56 :t 155.51 (32) 

15.74 :t 15.74 (21) 

16.11 :t 51.38 (159) 

12.39 :t 45.41 (180) 

58.2 :t 5S.62 (3) 

134.08 :t 119.1S (70) 

13O.9S :t 114.28 (73) 

21.0 :t 15.32 (24) 

30.01 :t 48.56 (261) 

29.26 :t 44.48 (285) 

no case


no case


no 

51 :t 3.51 (15) 

67.19 :t 54.46 (22) 

41.37:t 32.52 (37) 

00 :t 0.00 (2) 

101.86 :t 101.86 (13) 

88.28 :t 88.28 (15) 

10 :t 3.10 (17) 

80.07 :t 50.20 (35) 

54.91 :t 34.02 (52) 

no case


1S.16 :t 145.13 (65)


1S.16 :t 145.13 (65)


51 :t 9.08 (37) 

15.12 :t 34.49 (30) 

12.67 :t 30.76 (341) 

99 :t 35.56 (S) 

23.66 :t 51.0 (192) 

22.60 :t 49.45 (20) 

64 :t 9.57 (45) 

20 :t 30.62 (561) 

1.61 :t 28.36 (60) 

Metropolitan & nonmetropolitan 

135.16 :t 135.16 (6) 

47.06 :t 152.72 (53) 

56.02 :t 137.68 (59) 

66 :t 1.66 (3) 

25.15 :t 55.30 (15S) 

24.65 :t 54.27 (161) 

49.97 :t 49.97 (4) 

26.06 :t 52.95 (135)


23.S7 :t 51.45 (139)


7S.14 :t 62.95 (13) 

14.44 :t 40.01 (34) 

11.09 :t 38.63 (359) 

243.S2 :t 454.56 (15) 

135S:t 65.61 (149)


95 :t 72.16 (164) 

67 :t 9292 (166) 

52.74:t 51.69 (426) 

38.70:t 45.38 (592) 

23.34 :t 245.1S (21) 

122.41 :t S5.11 (116)


-67.11 :t S1.64 (137)


45.08 :t 86.93 (202) 

03 :t 37.71 (691) 

17.19:t 35. 17 (S93) 

336.74 :t 23.56 (S) 

276.34 :t 193.68 (41) 

176.24:t 168.93 (49) 

21.7S :t 48.10 (71S) 

39.S1 :t 45.99 (29S) 

71 :t 36.56 (1016) 

73.13 :t 93.61 (67) 

-4.71 :t 142.29 (67) 

13.21 :t S5.00 (134) 

16.94 :t 44.33 (793) 

49.42:t 45.54 (40)


5.52 :t 33.12 (1199) 

61.S :t 245.20 (29) 

48.56 :t 61.64 (243) 

49.90 :t 60.77 (272) 

17.12:t 42.62 (887) 

34.42 :t 31.01 (882) 

57 :t 26.38 (1769) 

109.84 :t S7.76 (92) 

-65.55 :t 48.54 (31S) 

26.20 :t 42.59 (410) 

28 :t 38.9S (100) 

14.76 :t 24.12 (1443) 

34 :t 21.41 (2451) 
Appendix 16: Mean reimbursment change by patient demography, 1988 

$ t standard errr (n) Male Female Male & female 

0-6 vea


White 40.71 t 104.51 (113) 155.88 :I 107.13 (68) 83.98 t 76.5S (lSl)


Black 190.50 t 185.56 (21) 33.43 t 33.43 (lS) -87.5 :I 101.57 (39)
 Other S91.56 t 667.32 (S) 30.13 :I 30.13 (3) 731.35 t 48.46 (11)


Unknown no case 00 t 0.00 (1) 00 t 0.00 (1)
 All race 54.45 :I 96.00 (142) 134.60 t S1.73 (90) S5.54 t 66.69 (232)


65-74 vea 

White -8.72 t 50.63 (45S) 02:1 59.08 (46) -4.61 t 38.94 (922) 

Black 149.44 t 28.54 (30) 57.57 t 135.40 (38) 33.75 t 146.61 (68) Other 00 t 0.00 (5) -6.68 t 60.68 (S) 37.3 t 37.3 (13)

Unknow 00 t 0.00 (3) 00 t 0.00 (1) 00 t 0.00 (4) All race -87.26 t 49.77 (496) 1.23 t 54.57 (511) -43.60 t 36.99 (1007) 

75-8 vea 

White 1.27 t 55.41 (328) 12.31 t 44.47 (456) 69 t 34.71 (784) 

Black 141.35 t 241.91 (26) 121.3 t 24.39 (27) 131.7 t 171.S1 (53) Other 139.91 t 139.91 (5) 00 :I 0.00 (2) 99.94 :I 99.94 (7) Unknow 00 :I 0.00 (4) 00:1 0.00 (6) 00 t 0.00 (10) 

Al race 35 :I 52.94 (363) 1S.11 :I 43.44 (491) 14.38 t 33.60 (S54) 

S5+ vea


White 272.41 t 159.53 (S2) 26.74 t 47.21 (23) 90.09 t 54.21 (31S)


Black 247.99 t 167.79 (S) -89.17 t 51.65 (20) 16 t 65.46 (28)
 Other 00 t 0.00 (2) 344.12 t 344.12 (2) 172.06 t 172.06 (4)
 Unknown 00 t 0.00 (1) 34.32 t 99.43 (7) 30.03 t 86.22 (S)


All race 261.53 t 141.30 (93) 20.59 t 42.39 (265) S3.1S t 48.49 (35S) 

All al!es


White 11.66 t 35.07 (9S1) 16.50 t 29.S9 (1224) 96 t 22.77 (2205)


Black 33.23 :I 133.S2 (S5) 41.5S t S2.19 (103) 75 t 75.25 (188)


Other 321.64 t 279.65 (20) 74.34 t S3.35 (15) 215.65 t 163.21 (35)


Unknown 00 t 0.00 (S) 16.01 t 44.70 (15) 10.44 t 28.84 (23) All race 16 t 33.50 (1094) 19.03 t 27.69 (1357) 34 t 21.41 (2451) 
Appendix 17: Number of bills by hospital demography, 1988 

- 1-99 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

100-299 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

30+ bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

Metropolitan 

S76 

977 

853 

174 

196,312 

569 

337 

S29 

345,242 

38,071 

50, 

450,101 

501,049 

593,S74 

692 

642 566 

52,050 

211 194 

263 

696 S72 

709,9S7 

S59 

320 

176 753 

216 073 

751 312 

984,754 

736 

345 560 

1S5,51S 

531 07S 

136 192 

347,025 

483 217 

144 

710 S31 

975 

570 

374 

574 944 

402,179 

483 049 

885 228 

867 S93 

402,254 

270 147 

Nonmetropolitan 

691 

92,955 

037 

439 549 

586 

419 

405 219 

411 638 

147 

032 

953 179 

116,651 

119 297 

74, 

590 S59 

11,592 

251 962 

263 554 

247 

959 472 

047 719 

695 

695 

639 

301 

169,940 

23,249 

41,426 

675 

102, 

132,422 

235,310 

337 

610 

212 947 

162 685 

120 709 

283 394 

69S 607 

739 867 

282 

027, 

Ii " 

Metropolitan & nonmetropolitan 

10,567


175 241


1S5


421


614,477


64,S9S


10,988


491 556


502,544


976


281 274


333,250


53,594


566 752


620


667 883


639,551


307,434


642


463 156


526,79S


7S5 119


669,459


454 57S


320


177


216 768


S3O,951 

075 055 

36, 

226,944 

595 753 

239,


479 447


71S 527


103 481


919 441


022 922


529,255


329 083


S5S,338


443,439


lSl 656


625,095


076,175 

430 180 

506 355 
Appendix 1S: Number of bils by patient demography, 1988 

Male Female Male & female . 0-6 ears 

White 433,869 341 720,210 

Black 765 170 173 

Other 413 761 32,174 

Unknow 621 472 093 

All race 555, 9S2 940,650 

65-74 ears


White 067 736 299 424,


Black 142 841 170 281 313 122


Other 32,047 889


Unknow 59,395 474 125 869


All race 922 350 943 932,293


75-8 ears


White 017 303 S94 32O


Black 100 353 137 S71 23,224


Other 111 117 

Unknow 761 530 291 

All race 1,394 242 869 710 263 952 

S5 + ears 

White 383 775 838 975 750 

Black 695 105,685 

Other 338 S15 13,153 

Unknow l88 690 S7S 

All race 431 937 470 369 

All ae:es


White 739,728 521 91S 261, 

Black 369,654 457 550 S27 

Other 73,471 150 

Unknown 117 965 149,166 267 

All race 256 202 105 506,361 

, This total includes six bils not in the prevous table beus they could not be classified by hospital control. 
99 

Appendix 19: Projected reimbursment effect by hospital demography, 1988 

$1,00 t standard errr 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

100-29 bes 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

30+ bes Teaching & nonteaching 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

All hos itals 

Teaching 

Profit Nonteaching 

Teaching & nonteaching 

Teaching 

Nonprofit Nonteaching 

Teaching & nonteaching 

Teaching 

Government Nonteaching 

Teaching & nonteaching 

Teaching 

All Nonteaching 

Teaching & nonteaching 

Metropolitan 

20 t 1


273 t 3,797 

980 t 4,296 

53t53 

64 t 29 372 

24,017 t 31,172 

0 t 0


23,361 t 16 296 

68 t 16 536 

15S t 3,136 

-4,00 t 32 777 

119 t 32,736 

422 t 23,159 

898 t 32,538 

031 t 4O,S91 

171 t 63 188 

7S,18O t 80 372 

44 t 102 069 

9S2 t 14 S53 

09 t 24 564 

508 t 30 721 

631 t 68 739 

55,9S5 t 9O 57S 

771 t 113 748 

241 t 9,223 

84 t 34 

081 t 36 501 

-61 40 t 135 144 

056 t 48 726 

249 t 141 709 

04 t 33 347 

302 t 32 449 c 

986 t 50 511 

507 t 142 069 

62,677 t 66 S39 

14,750 t 155 074 

06 t 24,310 

42,401 t 46,659 

48,493 t 53, 

050 t 149 711 

427 t 96 572 

314 t 177 506 

26 t 38 625 

-62 502 t 45 440 

26,220 t 60,762 

261 t 157 S10 

435 t 116 S33 

031 t 195 422 

Nonmetropolitan 

no 


05S t 22 375


170 t 22,790


0 to 

991 t 23 

014 t 23 492 

428 t 428 

13,072 t 1S,912 

65S t 1S 705 

S57 t 857


128 t 40 511


22,905 t 40


no 


682 t 1S,14O


765 t 1S,552


165 t 1 165 

519 t 3O 35S 

23 t 30,192 

-6 t 68


7S3 t 30 029 

520 t 30,119 

862 t 1 352 

794 t 46 592 

656 t 46,603 

no case 

no case 

no case 

28 t 28 

067 t 4 91S


030 t 5,526


0 to 

220 t 4,220


710 t 5 710


319 t 319 

603 t 6 

921 t S 005 

no 

788 t 30 276 

867 t 30 905 

222 t 1,477 

945 t 38,653 

261 t 39 477 

123 t 1,467 

16,529 t 35 97S 

721 t 36 586 

175 t 1,993


461 t 62,095


60 t 63,419


A'7 

Metropolitan & nonmetropolitan 

428 t 1,428


247 t 26,763


40 t 2S 5S2


SOt 50 


454 t 33 9S1


15,S97 t 34,


549 t 549


12,S10 t 26 028


99 t 2S S56


061 t 3 272


502 t 51,


14,786 t 51 503


13,067 t 24 362


696 t 37 lS5


172 t 44,764


783 t 62,


470 t 84 748


29S t 104,711


168 t 15


695 t 39 419


353 t 43,


393 t 68,250


24,105 t 100 665


38 t 121,49S


241 t 9 223


036 t 34


203 t 36 619


-61 65S t 136 169


79S t 49 442


491 t 142


971 t 34 524


601 t 32 292


S70 t 50 639


54,S70 t 143 588


114 t 67 374


04 t 156 27S


331 t 25,374 

64 t 56,674 

51,04 t 62 163 

421 t 150,417 

114 5S7 t 103,235 

776t 180 

48,707 t 38 916 

45S t 57 35S 

-42 577 t 69 213 

370 t 15S 889 

80,149 t 130 976 

777 t 203 531 
. Appendix 20: Projected reimbursment effect by patient demography, 1988 

$1,00 :I standard error Male Female Male & female 

0-6 ears


White 663 :I 45 635 :I 30,676 48 :I 55,154


Black 17,672:1 17 213 588 :I 2,588 14,S31 :I 17


Other 416 :I 12,287 lS5 :I 4 lS5 23,530 :I 15,716


Unknow no 0:1.0 0:1 0


All race 256 :I 53 S19 :I 31,465 80,463 :I 62 732


65-74 yea 

Whte 143 013:1 S5 467 716 :I 102 5S1 152,761 :I 133 345 

Black 34 :I 40 930 803:1 23,056 568 :I 45 907 

Other 0:1 0 23 :I 2 574 :I 2,574

Unknow 0:1 0 0:1 0 0:1 0 

All race 167,744 :I 95 675 -2,472 :I 109 171 44:1 145,456 

75-8 ears 

White 567:1 68;377 438 :I 73 257 :I 100 462 

Black lS5 :I 24,276 732 :I 34, 31,24 :I 40 929 

Other S14 :I 2 S14 0:1 0 610 :I 3,610 

Unknow 0:1 0 .0 :I 0 0:1 0 

All race 13,036 :I 73,Sl1 33,86 :I Sl 22O 936 :I 109,669 

S5 + yea 

White 104,544 :I 61,224 434 :I 39 110 15S :I 66 285 

Black 356 :I 5,654 -6,419 :I 3 71S 757 :I 6 91S 

Other 0:1 0 345 :I 2 345 263 :I 2 263 

Unknown 0:1 0 676 :I 1 95S S37 :I 2, 

All race 112 980 :I 61,041 303 :I 39 739 113,912 :I 66 405 

All ae:es


White -43,605 :I 131 152 74,612 :t 135 160 716 :t 188,l1S 

Black 12,28 :t 49 467 025 :t 37 411 :t 62,247 

Other 737:t 21,508 462 :t 6 124 429 :t 24 544 

Unknow O:t 0 38 :t 6 7S9 :t 7,704 

All race SlS :t 144 193 9S,99 :t 144 046 777 :t 203 531 
(%) 

Appendix 21: DRG fruency, errr freuency, and errr proportion by proportion of errrs, 1988 

102 

11S 

126 

152 

164 

173 

17S 

1S7 

193 

194 

199 

201 

202 

221 

224 

227 

232 

235 

237 

242 

259 

262 

269 

274 

285 

287 

292 

301 

31S 

323 

334 

339 

342 

357 

363 

394 

397 

399 

420 

447 

471 

474 

476 

DRG desription 

Craniotomy for trauma age ::=lS


Spinal proure 

Peripheral & crnial nelVe & other nelVOUS sytem proure age ::=70 &/or cc

Nonspeifc cerebroasular disorders with cc 

Nonspefic cerebroasular disorders w/o cc 

Traumatic stupor & coma, coma ::1 hr 

Concussion age ::=70 and/or cc


Concusion age 1S-69 w/o cc


Other disrders of the eye age ::=lS w/o cc


Salivar gland proure except sialoadenectomy


Ear, nOs & throt malignancy


Nasl trauma & deformity


Major chest trauma age -:70 w/o cc


Pneumothora age ::=70 and/or cc


Pneumothora age -:70 w/o cc


Other repiratory diagnos age -:70 

Cardiac pacemaker pulse generator replacement only 

Acute & subacute endocrditis


Minor small & large boel proure age ::=70 and/or cc


Appendectomy with complicated principal diagnosis age:: =70 and/or cc


Digestive malignancy age -:70 w/o cc


Uncomplicated peptic ulcer -:70 w/o cc


Dental exractions & restorations


Bilary tract proure except total cholectectomy age ::=70 &/or cc


Bilary tract proure except total cholectectomy age -:70 w/o cc


Hepatobiliary diagnostic proure for malignancy 

Other hepatobiliary or pancrea OR proures CilThosis & alcoholic hepatitis


Knee proures age ::=70 and/or cc


Upper exremity proures except humeru & hand age -:70 w/o cc


Soft tisue proure age -:70 w/o cc


Arhropy


Fracture of femur


Sprains, strains, & disloctions of hip, pelvis & thigh


O!\teomyelitis


Se'ptic arthritis


SiJbtotal mastectomy for malignancy age :: =70 and/or cc 

Brest biops & locl excision for non-malignancy 

Skin grafts for skin ulcer or cellulitis age -:70 w/o cc 

Other skin, subcutaneous tissue & breast OR procure age :: =70 &/or cc 

Malignant bret disrders age :: =70 and/or cc 

Amputations for endocrine, nutritional & metabolic disorders 

Skin grafts & wound debride for endocrine, nutritional & metabolic disrders 

Other endocrine, nutritional & metabolic OR procure age ::70 &/or cc

Endocrie disorders age ::=70 and/or cc 

Endocrine disorders age -:70 w/o cc 

Kidney, ureter & major bladder procure for non-malignancy age ::=70 &/or cc 

Kidney & urinary tract neoplasms age :: =70 and/or cc 

Urinary stones age :: =70 and/or cc 

Major male pelvic proure with cc 

Testes procure, non-malignant age :: = 1S 

Circumcision age ::=lS 

Uteru & adnex proures, for malignancy 

D&C, coniztion & radioimplant, for malignancy 

Infections, female reprouctive sytem 

Other OR procure of the bloo & bloo forming organs 

Cogulation disrders


Reticuloendothelial & immunity disorders age -:70 w/o cc 

Fever of unknown origin age 1S-69 w/o cc 

Allergic rections age ::=lS 

Signs & syptoms w/o cc Bilateral or multiple major joint procure of lower exremities 

Respiratory sytem diagnosis with tracheotomy 

Protatic or proure unrelated to principal diagnosis 

Peripheral & cranial nelVe & other nelVOUS system procure age -:70 w/o cc

Multiple sclerois & cerebellar ataa 

1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.)


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.


. 1\0 (0. 

1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.)


1\0 (0.


1\0 (0.


1\0 (0.


1\0 (0.


1\0 (0.)


1\0 (0.)


2\0 (0. 

2\0 (0.)

\(\ 

- 44 

168 

1S9 

217 

231 

233 

245 

253 

302 

324 

338 

354 

355 

41S 

105 

115 

146 

159 

179 

219 

225 

228 

249 

261 

271 

283 

290 

172 

247 

341 

350 

443 

113 

128 

134 

157 

15S 

1Sl 

21S 

325 

356 

129 

205 

35S 

160 

Cranial & peripheral nerve disrders age ..70 w/o cc


Other disrders of nervous sytem age ..70 w/o cc 

Exraoclar proure except orbit age:. = 1S


Acute major eye infections


Sinus & mastoid proure age :.=lS


Other ear, nos & throat diagnos age:. = 


Major chest trauma age :.=70 and/or cc


RespiratOlY signs & syptoms age ..70 w/o cc


Proure on the mouth age:. =70 and/or cc 

Other digestive system diagnos age 18-69 w/o cc 

Wound debridement & skin graft except hand for musculoskeletal & connective tissue disorders Lol excision & removal of internal fIXtion devce of hip & femur

Lol exciion & removal of internal fIXtion devce except hip & femur 

Other musuloskeletal sytem & connective tisue OR proure age:. =70 &/or cc 

Bone dis & septic arthropathy age ..70 w/o cc 

Fracture, sprains, strains & disloctions of upper arm, lower leg except foot age :.=70 &/or cc 

Trauma to the skin, subcutaneous tisue & bret age:' =70 &lor cc 

Kidney transplant 

Urinary stones age ..70 w/o cc


Testes proures, for malignancy 

Non-radical hysterectomy age:. =70 and/or cc


Non-radical hysterectomy age ..70 w/o cc


Myeloproliferative disrder or porly diferentiated neoplasm with minor OR proure
 Postoprative & pot-traumatic infections


Hyprtensive encephalopathy


. Neurological eye disorders 

oc head & neck procures 

Epistas 

Cardiac valve procure with pump & w/o cardiac catheterition 

Permanent cardiac pacemaker implant with AMI or CHF


Rectal retion age:. =70 and/or cc


Hernia proure except inguinal & femoral age:. =70 and/or cc


Infammatory bowel disese


Disorders of the bilary tract age ..70 w/o cc 

Loer exremity & humerus procures except hip, foot, femur age 1S-69 w/o cc


Foot proures


Ganglion (hand) proures


Aftercare, musuloskeletal sytem & connective tisue


Brpst proure for non-malignancy except biopsy & locl excision


Ski ulcers


Minor skin disrders age:. =70 and/or cc


Thyrid procures


Minor bladder procures age:. =70 and/or cc


Lymphoma or leukemia with major OR procure


Lymphoma or leukemia age 1S-69 w/o cc


Intraocr proure except retina, iri & lens


Digestive malignancy age:. =70 and/or cc


Upper exremity procure except humeru & hand age:. =70 and/or cc


Signs & syptoms of musuloskeletal sytem & connective tissue


Penis proure


Inflmmation of the male reproductive system


Other OR procure for injuries age ..70 w/o cc


Amputation for circulatory system disorders except upper limb & toe


Dep vein thrombophlebitis


Hyprtension


Anal procures age:. =70 and/or cc 

Anal proures age ..70 w/o cc


Gastrointestinal Obstruction age ..70 w/o cc


Lower exremity & humerus proure except hip, foot, femur age:. =70 &/or cc


Kidney & urinary tract signs & symptoms age :'=70 and/or cc


Female reproductive system recnstructive procures


Craniotomy age :.=lS except for trauma


Nervous system neoplasms age :.=70 and/or cc


Lens proures


Cardiac arrt


Disorders of liver except malignancy, cirrhosis, alcoholic hepatitis age :.=70 and/or cc


Bone disese & septic arthropathy age:. =70 and/or cc


Uteru & adnex procure for non-malignancy except tubal interrpt


Major chest procures


Hernia procure except inguinal & femoral age 1S-69 w/o cc


2\0 (0. 

2\0 (0. 

2\0 (0.)


2\0 (0.)


2\0 (0.


2\0 (0.


2\0 (0.


2\0 (0.)


2\0 (0.)


2\0 (0.)


2\0 (0. 

2\0 (0.)


2\0 (0. 

2\0 (0.)


2\0 (0.


2\0 (0.


2\0 (0.)


2\0 (0.


2\0 (0.


2\0 (0.)


2\0 (0. 

2\0 (0.)


2\0 (0.)


2\0 (0.)


3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0. 

3\0 (0.)


3\0 (0.)


3\0 (0.)


3\0 (0.)


3\0 (0.)


3\0 (0. 

3\0 (0.)


3\0 (0. 

3\0 (0. 

3\0 (0. 

4\0 (0. 

4\0 (0.)


4\0 (0. 

4\0 (0. 

4\0 (0. 

4\0 (0.)


4\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

5\0 (0. 

6\0 (0. 

6\0 (0. 

6\0 (0. 

6\0 (0. 

6\0 (0. 

6\0 (0. 

6\0 (0. 

7\0 (0. 

7\0 (0. 
27S 

316 

- 131


257 

321 

116 

395 

123 

410 

140 

336 

337 

106 

294 

296 

239 

125 

107 

127 

215 

122 

475 

197 

148 

174 

311 

415 

112 

143 

121 

243 

214 

303 

310 

110 

130 

442 

138 

139 

416 

25S 

142 

162 

210 

154 

124 

1S2 

109 

150 

161 

315 

331 

39S 

320 

141 

195 

Cellulitis age 1S-69 w/o cc


Renal failure w/o dialyis


Exracrnial vasular proure


Peripheral vascular disrders age ..70 w/o cc


Tota mastectomy for malignancy age =70 and/or cc


Kidney & urinary tract infections age 1S-69 w/o cc


Fracture of hip & pelvs 

Permanent cardiac pacemaker implant w/o AMI or CHF


Red bloo cell disrders age =lS


Circulatory disorders with AMI, exire


Chemotherapy


Major joint proures


Angina petori


Spefic cerebroasular disrders except tia 

Transurethrl protatectomy age =70 and/or cc 

Transurethral protatectomy age ..70 w/o cc 

Respiratory infections & inflammations age =70 and/or cc 

Coronary by with cardiac catheterition Diabetes age =36 

Transient ishemic attacks 

Nutritional & miscllaneous metabolic disorders age =70 and/or cc

Pathological fracture & musuloskeletal malignancy 

Cirulatory disrders except AMI, with cardiac catheterition without complex diagnosis 

Simple pneumonia & pleurisy age =70 and/or cc 

Coronary by w/o cardiac catheterition 

Pulmonary embolism 

Bronchitis & asthma age =70 and/or cc


Heart failure & shock


Back & neck proures age ..70 w/o cc


Seizure & headache age =70 and/or cc 

Circlatory disorders with AMI w/o CV complications discharged alive 

Respiratory sytem diagnosis with ventilator 

Total cholectectomy w/o CDE Age =70 and/or cc


Major small & large bowel procures age =70 and/or cc
 Gastrointestinal Hemorrhage age =70 and/or cc


Transurethral proures age ..70 w/o cc


OR proure for infectious & paraitic disese


Vascular procures except major recnstruction


9est pain 


Ircu atory ISO!' ers Wit AMI
 comp lcatlons ISC arg a Ive 

Medical back problems


Back & neck proure age =70 and/or cc


Kidney, ureter & major bladder procure for neoplasm
 Trnsurethral procures age =70 and/or cc


Major renstructive vascular procure age =70 and/or cc
 Peripheral vascular disorders age =70 and/or cc 

Other OR proure for injuries age =70 and/or cc Cardiac arrhythmia & conduction disrders age =70 and/or cc 

Cardiac arrhythmia & conduction disorders age ..70 w/o cc 

Septicemia age =lS 

Total mastectomy for malignancy age ..70 w/o cc 

Syncope & collaps age ..70 w/o cc 

Inguinal & femoral hernia proure age 1S-69 w/o cc 

Respiratory neoplasms 

Hip & femur proure except major joint age =70 and/or cc 

Stomach, esphageal & duodenal proure age =70 and/or cc 

Circulatory disrders except AMI with cardiac catheterition & complex diagnosis Esphagitis, gastronteritis & miscllaneous digestive disorders age =70 &/01' cc 

Seizure & headache age 1S-69 w/o cc 

Cardiothoracic procures w/o pump 

Peritoneal adhesiolysis age =70 and/or cc 

Inguinal & femoral hernia procures age =70 and/or cc 

Other kidney & urinary tract OR procures Other kidney & urinary tract diagnos age =70 and/or cc Reticuloendothelial & immunity disorders age =70 and/or cc 

Disorders of pancres except malignancy


Kidney & urinary tract infections age =70 and/or cc Syncope & collaps age =70 and/or cc 

Diseuilbrium 

Total cholectectomy with CDE Age =70 and/or cc 

7W (0. 

7\0 (0. 

8\0 (0. 

S\O (0.)


9\0 (0. 

9\0 (0.)


10\0 (0. 

14\0 (0. 

14\0 (0.)


250 (0. 

34\0 (0. 

55\1 (l. 

S9\2 (2;2) 

75' (2. 

31\1 (3.

29 (3.4) 

23\1 (4. 

17\1 (5. 

17\1 (5. 

47\ (6. 

44\3 (6. 

14\1 (7. 

2S (8.0) 

74\6 (S. 

12\1 (S. 

11\1 (9.


63\6 (9.


133\13 (9.


10\1 (10.)


20\2 (10. 

30\3 (10.)


19\ (10.


1S\2 (11.)


33\4 (12. 

33\4 (12. 

S\l (12.


S\l (12.


32\4 (12.5) 

32\4 (12.5) 

38\5 (13. 

22\3 (13. 

7\1 (14.


7\1 (14.


7\1 (14.


21\ (14.


13\2 (15. 

13\2 (15.4) 

45\7 (15. 

19\ (15.


31\5 (16. 

6\1 (16.


12\ (16.


12\2 (16. 

24\4 (16. 

23\4 (17.4) 

11\2 (lS. 

21\4 (19. 

6613 (19. 

5\1 (20.


5\1 (20.


5\1 (20.) 

5\1 (20.


5\1 (20.


5\1 (20.


5\1 (20.


10\2 (20. 

40\8 (20.)


19\4 (21.)


9\ (22.


9\2 (22.


" 1

359	 Tubal interrption for non-malignancy 

452 Complications of tretment age;: =70 and/or cc


1S3 Esphagitis, gastronteritis & miscllaneous digestive disorders age 1S-69 w/o cc


- 36	 Retinal proure 

Otitis media & upper repiratory infection age 1S-69 w/o cc 

177	 Uncomplicated peptic ulcer ;:=70 and/or cc 

Other musuloskeletal system & connective tisue OR proure age c:70 w/o cc

254 Fracture, sprains, strains & disloctions of upper ann, lower leg except foot age 1S-69 w/o cc 

461 OR proure with diagnos of other contact with health servce 

Aftercare w/o history of malignancy as sendary diagnosis 

Respiratory infections & inflammations age 1S-69 w/o cc


'17 Disorders of the bilary tract age;: =70 and/or cc


188 - Other digestive sytem diagnos age;: =70 and/or cc


449 Toxc effects of drugs age ;:=70 and/or cc


297 Nutritional & misllaneous metabolic disrders age 1S-69 w/o cc


Unrelated or proure OR proure on the repiratory sytem except major chest with cc
 Carpl tunnel relea


Pleurl effusion age ;:=70 and/or cc


111 Major renstructive vasular proure age c:70 w/o cc


155 Stomach, esphagea & duodenal proure age 1S-69 w/o cc


170 Other digestive sytem prour age ;:=70 and/or cc


176 Complicated peptic ulcer


Protatecomy age;: =70 and/or 

332 Other kidney & urinary tract diagnos age 1S-69 w/o cc


450 Toxic effects of drugs age 1S-69 w/o cc


Degenerative nelVous sytem disrders


149 Major small & large boel proure age c:70 w/o cc


175 Gastrointestinal Hemorrhage age c:70 w/o cc


'13 Malignancy of hepatobilary system or pancreas


263 Skin grafts for skin ulcer or cellulitis age;: =70 and/or cc


419 Fever of unknow origin age;: =70 and/or cc


180 Gastrointestinal Obstruction age;: =70 and/or cc


Pulmonary edema & repiratOl)' failure 

Bronchitis & asthma age 1S-69 w/o cc


277 Cellulitis age ;:=70 and/or cc


104 Cardiac valve procure with pump & with cardiac catheterition


144 Other circulatory diagnos with cc


19S Total cholectectomy w/o CDE Age c:70 w/o cc


Chronic obstructive pulmonary disease 

211	 Hip & femur procures except major joint age 1S-69 w/o cc


Simple pneumonia & pleurisy age 1S-69 w/o cc


Otitis media & uri age;: =70 and/or cc


OR proure on the respiratory system except major chest w/o cc


135 Cardiac congenital & valvular disorders age;: =70 and/or cc


151 Peritoneal adhesioIyis age c:70 w/o cc


216 Biopsies of musculoskeletal sytem & connective tissue


222 Knee proure age c:70 w/o cc


241 Connective tisue disrders age c:70 w/o cc


Tendonitis, myositis & bursitis


270 Other skin, subcutaneous tissue & brest OR procure age c:70 w/o cc
 Minor skin disorders age c:70 w/o cc


299 Inborn errors of metabolism


305 Kidney, ureter & major bladder procure for non-malignancy age c:70 w/o cc


440 Wound debridements for injuries 


455 Other injuries, poisonings & toxic effects diagnosis age c:70 w/o cc


462 Rehabiltation


473 Acute leukemia w/o major or procure age;:17


NelVous sytem neoplasms age c:70 w/o cc


Cranial & peripheral nelVe disorders age;: =70 and/or cc


101 Other respiratory diagnos age;: =70 and/or cc


191 Major pancreas, liver & shunt procures


Malignancy, male reproductive sytem, age;: =70 and/or cc


421	 Viral ilnes age ;:=lS 

Other disorders of nelVous system age;: =70 and/or cc


403	 Lymphoma or leukemia age ;:=70 and/or cc 

Respiratory signs & syptoms age ;:=70 and/or 1 '1 Other OR proures on the circulatory sytem 

1S5 Dental & oral disse except exractions & restorations age ;:=lS 413 Other myeloproliferative disorder or porly differentiated neoplasm diagnosis age;: =70 &/or cc 

9\2 (22.


9\ (22.


22\5 (22. 

4\1 (25.


4\1 (25.


4\1 (25.


4\1 (25.


4\1 (25.


4\1 (25.


4\1 (25.


S\2 (25. 

S\2 (25. 

11\3 (27. 

7\ (28.


14\4 (28.


21\6 (28.


10\3 (30.


3\1 (33.3)


3\1 (33.


3\1 (33.


3\1 (33.


3\1 (33.


3\1 (33.


3\1 (33.


3\1 (33.3)


3\1 (33.


6\ (33.


6\ (33.


6\ (33.


6\ (33.3)

6\ (33.3) 

6\ (33.


15\5 (33. 

'1\7 (35.


14\5 (35. 

19\7 (36. 

5\2 (40.


10\4 (40.)


10\4 (40. 

21\9 (42. 

9\4 (44.4)


22\10 (45. 

2\1 (50.


2\1 (50.


2\1 (50.


2\1 (50.) 

2\1 (50.


2\1 (50.


2\1 (50.


2\1 (50.) 

2\1 (50.


2\1 (50.) 

2\1 (50.


2\1 (50.) 

2\1 (50.


2\1 (50.) 

2\1 (50.


2\1 (50.


4\2 (50.) 

4\2 (50.


4\2 (50.


4\2 (50.


4\2 (50.


6\ (50.


S\ (60.


5\3 (60.


S\5 (62.5) 

3\2 (66. 

3\2 (66.


3\2 (66.

132	 Atheroslerois age :: =70 and/or cc


Traumatic stupor & coma, coma oe 1 hr age :: =70 and/or cc


Miscllaneous ear, nos & throat proure


- 92 Interstitial lung disese age ::=70 and/or cc 

Interstitial lung disse age oe70 w/o cc


133 Atherolerois age :'70 w/o cc


136 Cardiac congenital & valvular disorders age 1S-69 w/o cc


Hepatobilary diagnostic proure for non-malignancy 

Connective tisue disorders age ::=70 and/or cc


265	 Skin grafts except for skin ulcer or cellulitis with cc 

Skin, subcutaneous tissue & breast plastic proures
 307 Prostatectomy age oe70 w/o cc


335 Major male pelvc proures w/o 


Benign protatic hyprtrophy age :: =70 and/or 


365 Other female reprouctive sytem OR proures


Malignancy, female reprouctive sytem age :: =70 and/or cc
 367 Malignancy, female reproductive system age oe70 w/o cc


401 Lymphoma or leukemia with minor OR procure age :: =70 and/or cc


Myeloproliferative disorder or neoplasm with major OR proure &

463 Signs & syptoms with cc Nontrumatic stupor & coma 

117 Cardc pacemaker replace & reion except puls generator replacement only 

145 Other circulatory diagnos w/o 

153 Minor small & large boel proures age oe70 w/o cc 

213 Amputations for musculoskeletal system & connective tisue disrders 

453 Complications of treatment age oe70 w/o cc 

Total 

4\3 (75.


1\1 (100.) 

1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1 \1 (100. 

1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


1\1 (100.


2\ (100.


2\ (100.


2\ (100.


2\2 (100.


2\2 (100.


3\3 (100.


2451\31 (14. 
Appendix 22: Mean weight, dollar change, and estimated national financial effect by DRO, 1988 

DRO desription 

Craiotomy age =lS except for trauma


Craniotomy for trauma age =lS 

Spinal proure Exracranial vasular proures 

Carpl tunnel relea Peripheral & cranial nelVe age =70 and/or cc 

Peripheral & cranial nelVe proure age 0:70 w/o cc 

NelVous sytem neoplasms age =70 and/or cc 

NelVous sytem neoplasms age c:70 w/o cc 

Degenerative nelVous sytem disrders 

Multiple sclerois & cerebellar ataa 

Spefic cerebroasular disorders except tia 

Transient ishemic attacks 

Nonspeific cerebroasular with cc 

Nonspeifc cerebroasular disrders w/o 

Peripheral nelVe age ;"70 and/or cc 

Crnial & peripheral nelVe age c:70 w/o cc

Hypensive encephalopathy 

Nontraumatic stupor & coma 

Seizre & headache age =70 and/or cc 

Seizure & headache age 1S-69 w/o cc


Traumatic stupor & coma 1 hr 

Traumatic stupor 0:1 hr age =70 and/or cc 

Concusion age =70 and/or cc 

Concusion age 1S-69 w/o cc 

NelVous sytem age =70 and/or cc 

Other nelVous system age c:70 w/o cc 

Retinal procures 

Lens proures 

Exraocular procures except orbit age =lS 

Intraocular proure except retina, iris 

Acute major eye infections 

Neurological eye disrders


Other disorders of the eye age =lS w/o cc


jor head & neck proure 

Salivary gland except sialoadenectomy 

Sinus & mastoid proure age =lS 

Miscllaneous ear, nos & throat procures 

Ear, nos & throat malignancy 

Disuilbrium 

Epistas 

Otitis media & uri age =70 and/orcc 

Otitis media & uri age 1S-69 w/o cc 

Nasl trauma & deformity 

Other ear, nos & throt diagnos age =lS or chest procures 

OR repiratory except major chest with cc 

OR procure on the respiratory except chest w/o cc 

Pulmonary embolism 

Respiratory infections age =70 and/or cc 

Respiratory infections age 1S-69 w/o cc


Respiratory neoplasms 

Major chest trauma age =70 and/or cc 

Major chest trauma age c:70 w/o cc 

Pleural effusion age =70 and/or cc 

Pulmonary edema & repiratory failure 

Chronic obstructive pulmonary disese 

Simple pneumonia age =70 and/or cc 

Simple pneumonia age 1S-69 w/o cc 

Interstitial lung disese age =70 and/or cc 

Interstitial lung dise age c:70 w/o cc 

Pneumothora age =70 and/or cc 

Pneumothora age c:70 w/o cc 

Bronchitis & asthma age =70 and/or cc 

Bronchitis & asthma age 1S-69 w/o cc


Mean chan2e t standard errr 

Relative weight 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

0270 t 0.0270 

00 t 0. 

00 t 0. 

00 t 0. 

1481 t 0.1036 

-0.1054 t 0.0679 

00 t 0. 

017S t 0.0281 

0455 t 0.0395 

00 t 0. 

00 t 0. 

-0.136 t 0. 

00 t 0. 

00 t 0. 

20 t 0.2376 

-0.0052 t 0.24 

-0.0157 t 0.0157 

00 t 0. 

-0.24 t 0. 

00 t 0. 

00 t 0. 

-0.0591 t 0.1383 

00 t 0. 

0071 t 0.0071 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

1561 t 0. 

00 t 0. 

0175 t 0.0116 

00 t 0. 

-0.0334 t 0.0334 

019S t 0.019S 

00 t 0. 

00 t 0. 

00 t 0. 

-0.2452 t 0.1329 

045 t 0.045 

0542 t 0.0542 

-0.038 t 0.38 

0.870 t 0.940 -O.09S2 t 0.0494 

00 t 0. 

00 t 0. 

-0.0410 t 0.0410 

-0.1915 t 0. 

-0.003 t 0.0540 

042 t 0.024 

242 t 0.756


-0.4557 t 0. 

-0.041 t 0. 

00 t 0. 

00 t 0. 

-0.00 t 0.0104 

0570 t 0.0356 

o t 0


o to 

o t 0


o t 0


84t84 

o t 0


o to 

o t 0


461 t 322


328 t 211


o t 0


59 t 86


138 t 122


o t 0


o t 0


-425 t 


o to 

o to 

66 t 734 

16 t 76


-49 t 49


o to -650 t 0


o t 0


o t 0


120 t 392


o t 0


22t22 

o t 0


o to 

o t 0


o t 0


o t 0


o to 

o t 0


o t 0


o t 0


411 t 0


o t 0


54 t 36


o t 0


-87 t S7


61 t 61


o t 0


o t 0


o t 0


764 t 414


122 t 122


142 t 142


120 t 120


271 t 293


30 t 154


o t 0


o to 108 t 108


570 t 


22 t 168


134 t 74


704 t 205


420 t 0


143 t 0


o t 0


o t 0


2 t 30


168 t 107


National effect 

($1,00) 

o t 0


o t 0


o t 0


o t 0


S32 t S32


o t 0


o t 0


o t 0 

095 t 4 263 

509 t 4 195 

o t 0 

80 t 21,381 

539 t 19 033 

o t 0


o t 0


621 t 3,434 

o t 0


o t 0


362 t 4,845 

062 t 5,019 

-8 t 80


o t 0


146 t 0


o t 0


o t 0


986 t 6,47S 

o to 292 t 292


o t 0


o t 0


o t 0


o t 0


o t 0


o t 0


o t 0


o t 0


o t 0


35S t 0


o t 0 

619 t 1 071 

o t 0


580 t 580


S16 t S16


o t 0


o t 0


o t 0 

227 t 13 673 

80 t 80 

186 t 5 186 

174 t 9,174 

15S t 7 737 

24,24 t 12 

o t 0


o t 0


069 t 1 069 

671 t 13 643 

572 t 11 647 

S32 t 1S 153 

15S t 14,955 

689 t 0


-474 t 0


o t 0


0 t 0 

447 t 6 

794 t 4 948 

'\4 
100 

101 

- 102


104 

105 

106 

107 

109 

110 

111 

112 

113 

115 

116 

117 

11S 

120 

121 

122 

123 

124 

125 

126 

127 

128 

129 

130 

131 

132 

133 

134 

135 

136 

138 

139 

140 

141 

142 

143 

144 

145 

146 

148 

149 

150 

151 

152 

153 

154 

155 

157 

15S 

159 

160 

161 

162 

164 

168 

170 

172 

173 

174 

175 

176 

177 

I7S 

179 

180 

1Sl 

Respiratory signs age =70 and/or cc 

Respiratory signs & syptoms age c:70 w/o cc 

Other repiratory age =70 and/or cc 

Other repiratory diagnos age c:70 

Cardiac valve with pump & cardiac catheterition 

Cardiac valve with pump & w/o cardiac catheterition 

Coronary byss with cardiac catheterition 

Coronary byss w/o cardiac catheterition 

Cardiothoracic proure w/o pump 

Major vascular age =70 and/or cc 

Major renstructive vasular age c:70 w/o 


Vasular procures except reconstruction


Amputation except upper limb & toe 

Cardiac pacemaker implant with AMI or CHF 

Cardiac pacemaker implant w/o AMI or CHF 

Cardiac pacemaker replacement except pulse generator 

Cardac pacemaker generator replacement


OR proure on the circulatory sytem


AMI & CV complications discharged alive


AMI w/o CV complications disharged alive


Circulatory disrders with AMI, exired 

Circulatory except AMI with card catheterition


Circulatory except AMI with card catheterition


Acute & subacute endocrditis


Heart failure & shock


Deep vein thrombophlebitis 

Cardiac arrt
 Peripheral vasular age =70 and/or cc


Peripheral vascular disorders age c:70 w/o cc 

Atherolerois age =70 and/or cc


Atherolerois age -:70 w/o cc


Hyprtension


Cardiac congenital age =70 and/or cc


Cardiac congenital age 1S-69 w/o cc


Arhythmias age =70 and/or cc 

Arhythmia & conduction age -:70 w/o cc 

Angina petori


Sycope & collaps age =70 and/or cc 

Sypcope & collaps age c:70 w/o cc 

Chest pain 

Other circulatory diagnos with cc 

Other circulatory diagnos w/o 

Rectal restion age =70 and/or cc

Loer GI procure age =70 and/or cc 

Bowel proure age c:70 w/o cc 

Peritoneal adhesiolyis age =70 and/or cc 

Peritoneal adhesiolyis age -:70 w/o cc 

Minor boel proure age =70 and/or cc 

Minor boel proure age c:70 w/o cc 

Upper GI procure age =70 and/or cc 

Upper GI proures age 1S-69 w/o cc 

Anal proure age =70 and/or cc 

Anal procure age c:70 w/o cc

Hern except inguinal age =70 and/or cc 

Hernia except inguinal age 1S-69 w/o cc 

Hernia procures age =70 and/or cc 

Inguinal hernia procures age 1S-69 w/o cc 

Appendectomy age =70 and/or cc

Proure on the mouth age =70 and/or cc 

Digestive proure age =70 and/or cc 

Digestive malignancy age =70 and/or cc 

Digestive malignancy age c:70 w/o cc 

GI hemorrhage age =70 and/or cc 

GI Hemorrhage age c:70 w/o cc 

Complicated peptic ulcer 

Uncomplicated peptic ulcer =70 and/or cc 

Uncomplicated peptic ulcer c:70 w/o cc 

Inflammatory bowel disese 

GI Obstruction age =70 and/or cc 

GI Obstruction age ':70 w/o cc 

2896 t 0.1515 

00 t 0. 

-O.089S t 0.0703 

00 t 0. 

5763 t 1.2239 

00 t 0. 

-0.0739 t 0.0739 

104 t 0.104 

-0.1777 t 0.1777 

-O.21S9 t 0.120 

4693 t 0.4693 

0611 t 0.0693 

00 t 0. 

00 t 0. 

00 t 0. 

6697 t 0.S736 

00 t 0. 

-0.3202 t 0.3813 

-0.0627 t 0.0269 

0108 t 0.034 

00 t 0. 

-0.0396 t 0.0459 

01S9 t 0.0197 

00 t 0. 

0491 t 0.0263 

00 t 0. 

00 t 0. 

00 t 0.0071 

00 t 0. 

-0.081 t 0.0679 

-0.0745 t 0. 

00 t 0. 

-0.0123 t 0.0123 

2432 t 0. 

-0.0190 t 0.0215 

04 t 0.0267 

0026 t 0.0036 

0126 t 0.0325 

0217 t 0.0150 

06 t 0.041 

-0.0586 t 0.0255 

1995 t 0.331S 

00 t 0. 

-0.06 t 0.0784 

701S t 0.3138 

-0.23 t 0.232 

5956 t 0.5956 

00 t 0. 

1231 t 0.6545 

-0.3760 t 0.2713 

-0.3657 t 0.3657 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

0.4967 t 0.4967 

lS51 t 0.1634 

00 t 0. 

00 t 0. 

-O.5S13 t 0.5S13 

00 t 0. 

00 t 0. 

06 t 0. 

1093 t 0.0691 

-0.0273 t 0.0273 

0511 t 0.0511 

00 t 0. 

00 t 0. 

-0.0714 t 0.0336 

00 t 0. 

80 t 397


o t 0


279 t 219


o t 0 

914 t 3 S16 

o t 0


23 t 23 

326 t 326


554 t 554


-6 t 376 

463 t 1,463 

190 t 216 

o t 0


o to 

o to 

765 t 2,303 

o t 0 

99S t 1,188 

188 t Sl


25 t 103


o t 0


112 t 137


5S t 61


o to 153 t Sl


o to 

o t 0


22 t 1S


o to 211 t 179


232 t 0


o to 

32 t 32 

75S t 0 

59 t 66 

149 t S3 

6 t 9 

43 t 100 

61 t 41 

199 t 150 

lS2 t 79 

653 t 1 002 

o t 0


201 t 221


075 t 933


742 t 742


S57 t 1 S57 

o t 0


383 t 2,040 

114 t S27


96 t 96 o t 0


o t 0


o t 0


o to 548 t 1 548 

566 t 509 

o t 0


o to S12 t 1 S12 

o t 0


o t 0


216 t 


34 t 215 

-85 t S5


134 t 134


o to 

o to 210 t 96


o t 0


229 t 10 496 

o t 0


694 t 2,S95 

o t 0 

-81 09 t 62 

o t 0


12,92 t 12,920 

92 t 12, 

141 t 9,141 

-47,295 t 26,103 

48 t 14 

130 t 22,S12 

o t 0


o t 0 

o to 

11,656 t 15, 

o t 0 

88 t 11,770 

693 t 10 169 

512 t 10 235 

o t 0 

777 t 9 559 

86 t 5 077 

o to 

67,522 t 35 

o t 0


o t 0


974 t 


o t 0


788 t 2,3 

767 t 0 

o t 0


213 t 213


502 t 0


80 t 9,938 

38 t 5 224 

035 t 2,801 

736 t 6 296 

434 t 1,654 

08 t 15,S53 

033 t 2 625 

315 t 6 61S 

o t 0


21,952 t 24 142 

09 t 1S, 

257 t 12,257 

257 t 12 257 

o t 0


532 t 13


-40 454 t 30 029 

547 t 9 547 

o t 0


o t 0


o t 0


o t 0 

554 t 25 554 

452 t 20,164 

o t 0


o t 0 

943 t 17 943 

o t 0


o t 0


525 t 29,276 

746 t 4 

-8 t 844 

779 t 1,779 

o t 0


. 0 t 0


10,40 t 4 786 

o t 0


'i'i 
1S2 

1S3 

1S5 

- 1S7


188 

1S9 

191 

193 

194 

195 

197 

19S 

199 

201 

202 

203 

205 

207 

210 

211 

213 

214 

215 

216 

217 

21S 

219 

221 

222 

224 

227 

231 

232 

233 

235 

237 

239 

241 

242 

243 

245


247


249 

253 

254 

257 

25S 

259 

261 

262 

263 

265 

269 

270 

Upper gastrointestinal age:: =70 and/or cc 

Uppe gastrointestinal dis age 1S-69 w/o cc


Dental & oral except exractions age ::=lS


Dental exractions & retorations


Other digestive diagnos age ::=70 and/or cc


Other digestive sytem age 1S-69 w/o cc


Major pancreas, liver & shunt procures
 Bilal) tract procure age:: =70 and/or cc


Bilal) .tract procure age c:70 w/o cc


Cholectectomy & CDB age:: =70 and/or 


Cholectectomy w/o CDB age:: =70 or cc


Cholectectomy w/o CDB Age c:70 w/o cc


Hepatobilal) proure for malignancy


Hepatobilal) proure for non-malignancy


Hepatobilal) or pancre OR proure 

Cirosis & alcoholic hepatitis


Malignncy of hepatobilial) or pancre
 Disrders of pancre except malignancy 

Liver except malignancy, age ::=70 and/or cc


Bilial) tract age ::=70 and/or cc


Disrders of the bilal) tract age c:70 w/o cc


or jrnnt procures


Hip proure except joint age:: =70 and/or cc


Hip proure except joint age 1S-69 w/o cc


Amputations for musuloskeletal


Back & neck proure age ::=70 and/or cc


Back & neck procure age c:70 w/o cc


Biopsies of musculoskeletal


Wound debridement & skin graft except hand


Loer exremity proure age:: =70 and/or cc


Loer exremity & humeru proure age 1S-69 w/o cc


Knee proures age:: =70 and/or cc


Knee proure age c:70 w/o cc


Upper exremity proure age:: =70 and/or cc


Upper exremity procure age c:70 w/o cc


Foot proures


Soft tissue proures age c:70 w/o cc


Ganglion (hand) procures
 Lol excision internal fIXtion devce of hip & femur


ybl excision except hip & femur


Arhrospy


Musuloskeletal OR proure age ::=70 and/or cc


Musuloskeletal OR proure age c:70 w/o cc


Fractures of femur 

Fracture of hip & pelvi 

Sprains, strains, & disloctions 

Osteomyelitis 

Musuloskeletal & connective tissue malignancy 

Connective tissue age:: =70 and/or cc


Connective tissue disorders age c:70 w/o cc 

Septic arthritis 

Medical back problems 

Bone arthropathy age ::=70 and/or cc 

Bone & septic arthropathy age c:70 w/o cc 

Signs & syptoms of musculoskeletal 

Tendonitis, myositis & bursitis 

Aftercare, musuloskeletal & connective tissue 

Fracture, sprains, strains & disloctions age ::=70 and/or cc 

Fracture, sprains, strains & disloctions age 1S-69 w/o cc 

Total mastectomy age ::=70 and/or cc 

Mastectomy for malignancy age c:70 w/o cc 

Mastectomy malignancy age ::=70 and/or 


Breast proure for non-malignancy except biopsy 

Breast biopsy & excision for non-malignancy 

Skin grafts for skin ulcer age:: =70 and/or cc 

Skin grafts for ulcer age c:70 w/o cc 

Skin grafts except for ulcer or cellulitis with cc 

Skin, subcutaneous tissue & breast procures 

Skin, subcutaneous & breast procure age:: =70 and/or cc 

Skin, subcutaneous & breat OR age c:70 w/o cc 

0414 t 0.0341 

192 t 0.1521 

5944 t 0. 

00 t 0. 

0.887 t 0.670 

00 t 0. 

1.514 t 0.667 

00 t 0. 

00 t 0. 

-0.1338 t 0.0899 

-0.08 t 0.05S1 

30 t 0.124 

00 t 0. 

5521 t 0. 

00 t 0. 

00 t 0. 

-0.1141 t 0.928 

-0.0631 t 0.0504 

00 t 0. 

2628 t 0.2626 

00 t 0. 

-0.0146 t 0.0146 

-0.0162 t 0.0734 

2521 t 0. 

0.3 t 0. 

-0.1455 t 0.1455 

-0.0422 t 0.0422 

-0.0937 t 0.0937 

1.0690 t 1.0690


00 t 0. 

00 t 0. 

00 t 0. 

0176 t 0.0176 

1256 t 0.1256 

00 t 0. 

00 to. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

0282 t 0.0282 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

002 t 0.062


193Ot 0. 

2310 t 0.2310 

00 t 0. 

0169 t 0.0145 

00 t 0. 

00 t 0. 

00 t 0. 

0.391 t 0.391 

00 t 0. 

00 t 0. 

2917 t 0.2917 

00 t 0. 

0331 t 0.0331 

00 t 0. 

00 to. 

00 t 0. 

-0.2911 t 0.2679 

00 t 0. 

-0.704 t 0. 

-0.1336 t 0. 

00 t 0. 

-0.1020 t 0.1020 

129 t 106


579 t 473


S53 t 1211


o t 0


271 t 


o t 0


313 t 1, 

o to 

o t 0


390 t 267


263 t 1Sl


S76 t 359


o to 

455 t 0


o to 

o t 0


34 t 289


172 t 133


o t 0


S19 t SlS


o t 0


-45 t 45


50 t 228


755 t 


055 t S55


-453 t 453


131 t 131


292 t 292


333 t 3,333 

o to 

o t 0


o to 

46t46 

331 t 331


o t 0


o to 

o t 0


o to 

o t 0


o to 

o t 0


o t 0


88t88 

o t 0


o to 

o t 0


o t 0


19 t 19


601 t 0


720 t 720


o t 0


52 t 45


o t 0


o to 

o t 0


121 t 121


o t 0


o t 0


90 t 90 o t 0


103 t 103


o t 0


o t 0


o t 0


777 t 70S


o t 0


196 t 0


-416 t 0


o t 0


317 t 317


28,120 t 23 133 

42,054 t 34, 

34 t l1 9S9 

o t 0 

S39 t 7 572 

o t 0 

-43 732 t 25 424 

o t 0


o t 0


5S3 t 7 931 

673 t 10,751 

92 t 11 S7S 

o t 0


80 t 0 

o t 0


o to S56 t 5 728 

696 t 4 420 

o t 0 

21,633 t 21,615 

o to 

-8,274 t S 274 

833 t 17,369 

22,44 t S 910 

967 t 5, 

10,47S t 10 47S 

-4,3 t 4,3 

927 t 1,927 

21,99 t 21, 

o t 0


o t 0


o t 0


305 t 305


370 t 4,370 

o t 0


o t 0


o t 0


o t 0


o to 

o t 0


o t 0


o t 0 

162 t 1 162 

o to 

o t 0


o t 0


o t 0


S97 t S97


986 t 0


753 t 4,753 

o to SlS t 3,289 

o t 0


o t 0


o to 

80 t 80 o t 0


o to 

12,005 t 12,005 

o t 0 

043 t 2 043 

o t 0


o to 

o t 0 

38 t 13 967 

o t 0


24 t 0 

-1,375 t 0 

o t 0 

09S t 2 09S 
271 

274 

277 

- 27S


283 

285 

287 

290 

292 

294 

296 . 

297 

301 

302 

303 

305 

307 

310


311


315


316


31S


320


321


323


324


325


331


332


334


335


336


337


338


339


341


342


350 

354 

355 

356 

357 

35S 

359 

363 

365 

367 

394 

395 

397 

39S 

399 

401 

403 

404 

406 

410 

Skin ulcers


Malignant brest age =70 and/or cc


Cellulitis age =70 and/or cc


Cellulitis age 1S-69 w/o cc


Trauma to skin, & brest age =70 and/or cc
 Minor skin disorders age =70 and/or cc


Minor skin disrders age 0:70 w/o cc


Amputations for endocrine & metabolic


Skin grafts & debridement for metabolic disorders


Thyrid proures 

Nutritional & metabolic OR proure age 70 and/or cc 

Diabetes age =36 

Nutritional & metabolic age =70 and/or cc 

Nutritional & metabolic age 1S-69 w/o cc


Inborn errrs of metabolism


Endocne disrders age =70 and/or cc 

Endocne disrders age 0:70 w/o cc 

Kidney transplant 

Urinary tract proure for neoplasm 

Urinary proure non-malignancy age =70 and/or cc 

Urinary proure for non-malignancy age 0:70 w/o cc 

Protatecomy age =70 and/or cc 

Protatectomy age 0:70 w/o 

Bladder proures age =70 and/or cc 

Transurethral proures age =70 and/or cc


Transurethrl proure age 0:70 w/o cc


Other kidney & urinary tract OR proures
 Renal failure w/o dialysis 

Urinary tract neoplasms age =70 and/or cc Urinary tract infections age =70 and/or cc 

Urinary tract infections age 1S-69 w/o cc


Urinary stones age =70 and/or cc 

Urinary stones age 0:70 w/o cc


Urinary tract signs age =70 and/or cc 

Other urinary tract age =70 and/or cc


Urinary tract diagnos age 1S-69 w/o cc


Major male pelvic procures with 


Major male pelvc procures w/o 


?,nsurethral protatectomy age =70 and/or cc 

1;ransurethral protatectomy age 0:70 w/o cc

Testes procure, for malignancy


Testes proures, non-malignant age =lS


Penis proure
 Circumcision age =lS
 Malignancy, male reprouctive age =70 and/or cc Protatic hyprtrophy age =70 and/or cc


Inflmmation male reproductive sytem


Non-radical hysteretomy age =70 and/or cc


Non-radical hysterectomy age 0:70 w/o cc


Female reprouctive renstructive proures


Uteru & adnex procures malignancy


Uteru & adnex procure for non-malignancy


Tubal interrption for non-malignancy


D&C, coniztion & radio-implant malignancy 

Other female reproductive OR proures Malignancy, female reproductive age =70 or cc 

Malignancy, female reproductive age 0:70 w/o cc 

Infections, female reproductive sytem 

OR proure bloo & bloo forming organs Red bloo cell age =lS 

Cogulation disorders 

Reticuloendothelial age =70 and/or cc 

Reticuloendothelial age 0:70 w/o cc


Lymphoma or leukemia major OR procure 

Lymphoma OR procure age =70 and/or cc Lymphoma or leukemia age =70 and/or cc 

Lymphoma or leukemia age 1S-69 w/o cc 

Myeloproliferative with major OR procure & cc 

Myeloproliferative or neoplastic with minor OR procure Chemotherapy 

00 t 0. 

00 t 0. 

1330 t 0.1224 

00 t 0. 

00 t 0. 

00 t 0. 

144 t 0.144 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

0075 t 0.0075 

0019 t 0.0122 

2107 t 0.138 

lS73 t 0.lS73 

00 t 0. 

00 t 0. 

00 t 0. 

-0.0438 t 0.0438 

00 t 0. 

0.499 t 0.499 

-0.1201 t 0.1201 

-0.005 t 0. 

00 t 0. 

-0.0287 t 0.0287 

20 t 0. 

-0.34 t 0.


00 t 0.


00 t 0.


-0.0392 t 0.0202 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

-0.0311 t 0.0311 

104 t 0.104 

00 t 0. 

5157 t 0. 

-0.0105 t 0.0105 

0113 t 0.0113 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

-0.1227 t 0.1194 

242 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

0870 t 0.0576 

00 t 0. 

1.077 t 0.


1469 t 0.


5435 t 0.


00 t 0. 

00 t 0. 

00 t 0. 

00 t 0. 

0149 t 0.0149 

00 t 0. 

00 t 0. 

-0.6495 t 0. 

-0.3744 t 0.1534 

00 t 0. 

9735 t 0. 

00 t 0. 

00 t 0. 

o to 

o t 0


373 t 355


o t 0


o t 0


o to 450 t 450


o to 

o t 0


o t 0


o t 0


23t23 

1 t 35


657 t 432


584 t 584


o t 0


o t 0


o to 136 t 136


o to 556 t 1 556 

316 t 316 

29 t 0 

o t 0


-89 t S9 

64 t 64 

062 t 1,062 

o to 

o t 0


122 t 61


o t 0


o to 

o to 

o t 0


97 t 97


326 t 326


o t 0


607 t 0


32 t 32


29t29 

o t 0


o t 0


o to 

o t 0


323 t 314


767 t 0


o t 0


o t 0


o t 0


o t 0


o t 0


o to 271 t 179


o t 0


453 t 0


45S t 0


694 t 0


o t 0


o t 0


o t 0


o t 0


39 t 39


o t 0


o t 0


025 t 0


103 t 450


o t 0


153 t 0


o t 0


o t 0


o t 0


o t 0


23,40 t 22, o t 0


o t 0


o t 0 

971 t 2 971 

o t 0


o t 0


o to 

o t 0 

320 t 1 320 

267 t 5 137 

30,:355 t 20 001 

S54 t 3 S54 

o to 

o t 0


o to 157 t 3 157 

o t 0 

275 t 10,275 

134 t 3 134 

9S t 0 

o t 0


06 t 2 

023 t 17 023 

531 t 17 531 

o to 

o t 0 

132 t S,l25 

o t 0


o to 

o t 0


o t 0


602 t 1,602 

228 t 3 228 

o t 0


30 t 0 

36 t 3 

845 t 2 845 

o t 0


o t 0


o t 0


o t 0


271 :t 4 155 

533 :t 0 

o t 0


o t 0


o t 0


O:t 0


O:t 0 

O:t 0


059 :t 5 330 

o t 0


39S :t 0 

512 t 0


592 t 0


o t 0


O:t 0 

o t 0


o t 0


650 t 650


o t 0


O:t 0 

683 t 0 

202 t 7 439 

o t 0


20,30 t 0 

O:t 0 

o t 0

413 Myeloproliferative or neoplasm age =70 or cc 

415 OR proure for infectious & parasitic 

416 Septicemia age =lS - 41S	 Postoperative & pot-traumatic infections 

419 Fever of unknow origin age =70 and/or cc 

420 Fever of unknow origin age 1S-69 w/o cc 

421 Viral ilnes age = 1S 

Wound debridements for injuries 

442 Other OR for injuries age =70 and/or cc


443 OR proures for injuries age c:70 w/o cc


447 Allergic rections age = 1S


449 Toxic effects of drugs age =70 and/or cc 

450 Toxc effects of drugs age 1S-69 w/o cc 

452 Complications of tretment age =70 and/or cc 

453 Complications of trtment age c:70 w/o cc 

455 Injuries, poisnings & toxc age c:70 w/o cc


461 OR proure with diagnos of other contact


462 Rehabiltation


463	 Signs & syptoms with cc


Signs & syptoms w/o cc
 Aftercre w/o history of malignancy


Unrlated OR proure 

471 Multiple major joint proure of lower exremities 

473 Acute leukemia w/o major OR procure age 

474 Respiratory sytem with tracheotomy 

475 Respiratory with ventilator support 

476 Protatic OR proure unrelated to diagnosis 

Total 

6295 t 0.6540 

-0.3252 t 0.3252 

0.207 t 0.0740 

00 t 0. 

-O.019S t 0.0767 

00 t 0. 

2911 t 0.2374 

-0.861 t 0.861 

-0.0163 t 0.067 

00 t 0. 

00 t 0. 

0276 t 0.0327 

1002 t 0.1002 

22 t 0.186 

4903 t 0.106 

0550 t 0.0550 

4370 t 0.4370 

-0.6397 t 0.6397 

442 t 0. 

00 t 0. 

0454 t 0.0454 

-0.319 t 0.1434 

00 t 0. 

-0.7123 t 0.7123 

00 t 0. 

-0.2535 t 0.138 

00 t 0. 

0023 t 0.0070 

970 t 2 035 19,510 t 20 147 

-857 t S57 22,64 t 22, 

64 t 23 616 t 23 

0 t 0 0 t 0 

-61 t 239 220 t 4 734 

0 t 0 0 to 

88 t 740 504 t 14 65S 

706 t 2,706 17,863 t 17,863 

50 t 214 lS3 t 9 lS9 0 t 0 0 t 0 

0 t 0 0 t 0 

88 t 101 036 t 2,342 

312 t 312 092. t 3 

687 t 5S2 425 t 17 301 

416 t 219 020 t 2 169 

171 t 171 131 t 1 131 

362 t 1,362 9S7 t 17 9S7 

994 t 1,994 164 t 13 164 

385 t 0 571 t 0 

0 t 0 0 t 0 

141 t 141 86 t 1 128 t 447 196 t 30 

0 t 0 0 t 0 

220 t 2, 657 t 14 657 

0 t 0 0 t 0 

790 t 430 -49 568 t 26 9S1 

0 t 0 0 t 0 

7 t 21 401 t 173 214 

4:R 
Appendix 23: HCF A comments 
...

Health Care DEPARTMENT OF HEALTH & HUMAN SERVICES Financing Administration 

"'''10 

Date 

From 

Subject 

Memorandum 

MAY 2 9 


Wilam Toby; Jr.


Actig Admintrtor


OIG Draft Report: "National DRG Valdation Study Update: Summary
 Report" (OEI-12-89-O190) and "National DRG Valdation Study Update:
 Technical Report" (OEI-12-89-O191)


Inspector General 

Offce of the Secretary 

We have reviewed the above-referenced dr report which are


updates to a previous OIG study which re-abstrctd the International


Clasification of Diseaes 9th Edtion, Clica Modcation coes from a
 saple of 1985 Medicae discharges. Thes report update the previous study


by: replicating the 1985 work on cog accuracy using 1988 data comparg
 the findings from 1985 and 1988, and identig pattrns of cog errors that


the Prospectie Payment System (PPS) changes cold mod. The saple
 was nationally representative and covered al of caenda yea 1988, the most


recnt year for which data were available. 

OIG found a signifcat improvement in hosita cog of PPS cas 

, between 1985 and 1988. In the 1985 study, OIG found that 20.8 percent of 

. 1985 Par A bil contaed cog errors that changed the diosc related 

group (DRG) and that 61.7 percent of thes errors over-reimbursd the 

hospitals. This improper DRG cog incread tota PPS diurments 


9 percent or $308 mion. Durig the 1988 study, OIG found that


14.7 percent of the diharges had-DRG cog errors 51 percnt of DRG
 errors over-reimbursed the hospita and 49 percnt under-reimburd the
 hospita. Taken together, the 1988 DRG errors rested in no net


overpayment of hospita.


We believe thes report are a useful addition to the contiuing 

. research and evaluation of cae mi change among hosita paid under PPS.


We agree with OIG' s recommendation that Peer Review Organtions
 contiue their surveilance of hospita cong of DRG reimbursment


accuracy. Our detailed comments on these two report are attcbed for your
 consideration.

Page 2 - Inspector General 

Thank you for the opportnity to review and comment on these draft 

report. Please advise us if you agree with our position on the report' 

recommendation at your earliest convenience. 

Attachment 
Comments of the Health Care Financing Administration (HCFA) on OIG's Draft Reports: "National DRG Validation Study Update: 

Summary Report" OEI- 12-89-00190 and "National DRG Validation 

Study Update: Technical Report" OEI-12-89-00191 

OIG Recommendation 

The Peer Review Organizations (PROs) should continue their surveilance of 

hospital coding for DRG reimbursement accuracy. 

HCF A Response


We agree. The PROs wil continue their surveilance of hospital coding of 

diagnostic related group (DRG) reimbursement accuracy. 

We are pleased to note the decrease in DRG coding errors identifed by the 

1988 study, as compared to the 1985 study. We believe this improvement may 

be attributed to a combination of factors including increased hospital , experience under the prospective payment system (PPS), the impact of PRO 

review and the effect of HCFA educational efforts to enhance coding accuracy. 

General Comments 

Summary Report. OEI- 12-89-00190 

1 This 
report includes a brief but excellent description of the payment process 

including the role of coding. Three tyes of errors are defined at each stage of the payment process. However, no statement is made as to whether or not the 

errors are mutually exclusive, and if the 361 records with errors contained only 

1 of each tye. We believe this information should be included in the final report. 

Although the representativeness of the sample is thoroughly addressed, there is no discussion as to how adequately each DRG is represented. We would like 

to know how the distribution by DRG of the sample relates to the universe of 

DRGs, and if any correlation exists between high volume DRGs and errors 

the sample. Also, we note that most hospitals contributed only one discharge to the sample. We question whether it is statistically valid for 

1 record in 1 hospital to represent 3 300 other records in the total population 

of records.


It is not made clear in the report how payment projections are calculated. The 

amount used to estimate payment is not stated, although mention is made 
Page 2


of using a rate of $3 118 for metropolitan hospitals and $2 637 for 

nonmetropolitan hospitals (page 29, Technical Report). It is stated that these 

are "current dollars " but there is no discussion as to the actual figures used to 

project payment amounts. While the calculation for case-mix index (CMI) is 

clearly defined, as is the DRG difference before and after coding, it is not clear how the payment amount is determined. The final report should include 

a more complete description of payment calculation. 

Executive Summary, page ii DRG coding errors, overall, no longer over-
 reimburse hospitals." The figure for under-reimbursements is stated to be


588.0 bilion." The correct figure is $2 588 millon (also Executive

Summary, page iii, Technical. Report). 

Findings, pages 5, 9 - While it is unwise to ignore magnitudes and only pay
 attention to statistical significance, we do not believe effects that are not


statistically significant should be highlighted. For example, the report notes that for-profit hospitals "over-reimburse themselves" but that "these results did 

not attain statistical significance" (also CMI discussion, pages 13, 14, Technical Report). 

Findings, page 6 - The narrative incorrectly states that the overall CMI 

decreased after the study s recoding. For hospitals to have underpaid


themselves, the CMI would have to increase after recoding, as is correctly
 stated on page 13 of the Technical Report. 

Findings, page 6, Figure 6 - The 1988 pie chart does not match the numbers in 

the text immediately below the chart. The resequenced and miscoded pieces

of the pie do not represent the 27 percent and 9 percent respective figures and 

may have been reversed in the pie chart. 

Technical Report 

Introduction, page 1, paragraph 3 - The original number of DRGs in 1983 was 

470, not 476. 

Introduction, page 1, paragraph 4 - The narrative implies that there is a fiscal 

intermediary for each State. The sentence should be rewrtten to state: " 

fiscal intermediary receives the hospital bils for each State. 
. . .

Page 3


Page 2, paragraph 3, under the heading "The HCFA. . . made the following 

points in commenting on the 1985 Study" - It was HCF A' s intent to point out 

that the 1985 study was published in November 1987; and conclusions set forth 

in that report were based in part on information and coding conventions which 

had been updated by the time the report .was released. The phrasing " 

needed a longer learning period to adjust to the new payment and quality 

monitoring system" does not encompass the concept that changes have been 

made to the whole International Classification of Diseases, 9th Edition, Clinical 

ModifcationlProspective Payment SystemlDRG system since its conception. 

Such changes and improvements continue to be made. 

Page 4 - We do not believe the data support some of the assertions and 

language which the report uses. For example, the report describes the findings of the earlier OIG report as showing "intentional. gaming . or manipulating (of 

the 1 coding process" by hospitals. The note cites unrelated sources while the 

earlier report used much more restrained language. 

The report consistently characterizes coding disagreements as provider "errors. 

A recent Rand study used charts re-abstracted at SuperPRO to examine the 

1987-88 increase in the Medicare CM!. Rand estimated that changes in coding 

common to SuperPRO and hospitals accounted for almost one-third of the 

1987-88 CMI increase. Since SuperPRO coders have no incentive to upcode this probably reflects changes in explicit and implicit coding rules between 

original coding (1987) and recoding (1988). While the CMI may increase 1 payments to hospitals will not. However, disagreements which may reflect the 

evolution of coding practice over time are not strictly provider "errors." Rand 

and OIG studied slightly different problems, and the Rand findiIJg may be 

unique to 1988. However, since American Medical Records Association staff 

should be able to provide insight on this matter, we recommend that OIG 

explore and report on the question of whether the increase in the CMI is 

attributable to provider errors or the evolution of coding practices. 

Page 4, paragraph 3 - "Each year, the relative weights change to reflect 

alterations in resource consumption, DRG title, coding and. . .." The change

in relative weights is not related to the title of the DRG. 
.. 

..

c. 

Page 4


Page 10 - The report does not fid net overpayment due to coding error. 

Inclusion of a table of DRGs with "maxmum savings potential (to Medicare)" 

due to upcoding, without a parallel table of DRGs with maxmum potential 

payment increase, gives an impression of lack of balance. Financial impact 

(savings) estimates could be presented in the context of the argument that 

while ". . . trends to over-pay and under-pay approximately offset each other, 

this equilbrium may not continue in the' future. 

Page 12 - OIG reports that coding errors (incidence of coding error capable 

influencing DRG assignment) declined signifcantly between 1985 and 1988. . 

While true, the report overstates the change. The 1985 report used a twostage sampling design and reported error rates for the nation of 20.8 percent 

(hospital-weighted) and 18.6 percent (case-weighted). The update report finds 

a 1988 error rate of 14.7 percent but compares it to the 1985 hospital-weighted 

statistic. The 1988 value, based on a simple random sample of cases, is 

equivalent to a case-weighted statistic and should not be compared with 

hospital-weighted value. 

Page 15 - Some PPS details in the draft report are obscured. For example, the 

report discusses "base payment amounts" when it means standardized amounts. 

Discussion of reimbursement effects states that financial impacts "paralleled CMI changes" when they are simply calculated from and are logically 

equivalent to such changes.


" Appendix 5 - There appears to be an error for hospitals with 300 or more 

beds. The response rate of 66.8 percent should be changed to 48.9 percent 

(1, 199 responses of 2 451). 

There is some disagreement between the narrative and the appendices. Table 

9 ilustrates the number of records per DRG and the number miscoded. 

Appendix 21 lists each DRG with the number of records selected and the 

error frequency and the proportion of errors. Whle the number of records 

selected is consistent between the table and the appendix the number of 

errors is not. There is no indication why these numbers differ, the source 

this data, or which is correct. However, the errors reported in appendix 21 do

total 361, the correct total for the study.