Department of Health and Human Services 

OFFICE OF 

INSPECTOR GENERAL 

DRG 296 VALIDATION UPDATE: 

NUTRITIONAL AND MISCELLANEOUS 

METABOLIC DISORDERS 

OCTOBER 1992 
OFFICE OF INSPECTOR GENERAL 

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

452, as amended, is to protect the integrity of the Department of Health and Human 

Services (HHS) programs as well as the health and welfare of beneficiaries served by 

those programs. This statutory mission is carried out through a nationwide network of 

audits, investigations, and inspections conducted by three OIG operating components: 

the Office of Audit Services, the Office of Investigations, and the Office of Evaluations 

and Inspections. The OIG also informs the Secretary of HHS program and 

management problems and recommends courses to correct them. 

OFFICE OF AUDIT SERVICES 

The OIG’S Office of Audit Services (OAS) provides all auditing semices for HHS, 

either by conducting audits with its own audit resources or by overseeing audit work 

done by others. Audits examine the performance of HHS programs and/or its 

grantees and contractors in carrying out their respective responsibilities and are 

intended to provide independent assessments of HHS programs and operations in 

order to reduce waste, abuse, and mismanagement and to promote economy and 

efficiency throughout the Department. 

OFFICE OF INVESTIGATIONS 

The OIG’S Office of Investigations (01) conducts criminal, civil, and administrative 

investigations of allegations of wrongdoing in HHS programs or to HHS beneficiaries 

and of unjust enrichment by providers. The investigative efforts of 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. 

OFFICE OF EVALUATION AND INSPECTIONS 

The OIG’S Office of Evaluation and Inspections (OEI) conducts short-term 

management and program evaluations (called inspections) that focus on issues of 

concern to the Department, the Congress, and the public. The findings and 

recommendations contained in these inspection reports generate rapid, accurate, and 

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

departmental programs. 

Amy L. Lockwood of BOTEC Analysis Corporation prepared this report with 

direction from Janet W. Knight, BOTEC Project Director, and David C. Hsia, OIG 

Project Officer. Contract information and project participants are listed in Appendix 

A to this inspection. 
Department of Health and Human Services 

OFFICE OF 

INSPECTOR GENERAL 

DRG 296 VALIDATION UPDATE: 

NUTRITIONAL AND MISCELLANEOUS 

METABOLIC DISORDERS 

OCTOBER 1992 OEI-12-89-00195 
EXECUTIVE SUMMARY


PURPOSE 

This inspection reabstracted on a blinded basis, the International Classification of 

Diseases, 9th Edition, Clinical Modification codes from a sample of Medicare 

discharges billed as diagnosis-related group (DRG) 296, nutritional and miscellaneous 

metabolic disorders. It compared the reabstracted DRG to the hospital-billed DRG 

for reimbursement changes. The sample was nationally representative and covered all 

of 1988, the most recent data available. 

This inspection updated a previous Office of Inspector General (OIG) study. For 

1985, the OIG found 19.3 percent errors among 173 reabstractions, improperly overreimbursing hospitals by a projected $19.9 million. This inspection used a parallel 

methodology to make these studies statistically comparable. 

FINDINGS 

DRG 296 errom not reduced 

Of 106 discharges reabstracted for this inspection, 10.4 percent had billing errors. This 

proportion did not differ statistically from the 19.3 percent errors for DRG 296 

discharges in 1985. It also did not differ statistically from the 14.7 percent errors for 

all discharges in 1988. 

DRG 296 erronrrandom 

Of 11 bills with DRG errors, 45.5 percent over-reimbursed the hospital. This 

proportion differed statistically from the 75.0 percent over-reimbursement in 1985. 

DRG 296 erron cause no over-reimbursement 

The DRG 296 billing errors under-reimbursed hospitals $14.7 million. While not itself 

statistically different from zero (no under-reimbursement), this result does differ 

statistically from the $19,9 million over-reimbursement in 1985. 

i 
TABLE OF CONTENTS


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


TABLE OF CONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii


INTRODU(XION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1


FINDINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4


Errorsnotreduced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4


Errors occur randomly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4


Errors cause no over-reimbursement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5


Reasons for errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5


ENDNOTES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6


APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7


A: Project participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8


B: ICD-9-CM codes in DRG 296..... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10


C: Sample representativeness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11


D: Proportion of DRG 296 billing errors, 1985 and 1988 . . . . . . . . . . . . . . . . . . . 12


E: DRG296case-mix index change, 1985 and 1988 . . . . . . . . . . . . . . . . . . . . . . 13

INTRODUCTION


Background 

Diagnosis-related group (DRG) 296 accepts 58 International Classification of Diseases, 

%hEdition, Clinical Modification (ICD-9-CM) codes asptincipal diagnoses. These 

ICD-9-CM codes identify metabolic disorders principally associated with dehydration 

and fluid-electrolyte imbalances. DRG 297 accepts the same principal diagnoses, but 

requires a complication. DRGs 296 and 297 do not include admissions for diabetes, 

the commonest metabolic order. [Appendix B]. 

DRG 296’s weight increased from 0.8886 in 1985 to 0.9259 in 1988. Beginning in FY 

1988, the HCFA altered DRG 296 to drop age over 69 as a complication code. This 

change shifted billings in one quarter of the data collection period for this inspection. 

In a previous study, the OIG found that DRG 296 had an unusually high proportion of 

billing errors.1 Correct ICD-9-CM coding would have grouped 19.3 percent of its 173 

reabstractions to different DRGs in 1985. These billing errors over-reimbursed the 

hospitals a projected $19.9 million. 

This inspection updated the previous study using 1988 data, the most recent available. 

It used a parallel methodology to make these inspections statistically comparable. 

Methodology 

This inspection randomly selected 106 DRG 296 discharges. The study population


consisted of the 191,509 Medicare-reimbursed DRG 296 discharges during calendar


year 1988. The design excluded discharges from specialty institutions such as


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


discharges in Maryland and New Jersey, which the PPS still exempted in 1988. Finally,


it excluded bills for pediatric, obstetric, and psychiatric DRGs (principally drug and


alcohol rehabilitation performed by a general hospital).2 Unlike its 1985 predecessor,


it included hospitals established since the advent of the PPS in 1983.


The OIG requested that hospitals send complete copies of the sampled medical


records to the OIG’S contractor, Baxter-Health Data Institute (HDI) of Lexington,


MA. The OIG followed-up missing records and issued subpoenas to compel the


cooperation of four hospitals.


The OIG contracted with the American Medical Record Association (AMRA) to


reabstract the charts. The AMRA selected ICD-9-CM codes supported by the record,


determined the principle diagnosis, and grouped to select the correct DRG. To assure


that the original ICD-9-CM codes and DRGs did not effect the reabstraction, the


AMRA coders conducted their work without knowledge of the original ICD-9-CM


codes and DRGs. The coders had instructions not to treat marginal problems or


1 
honest differences injudgement about appropriate coding as DRG errors. This 

standard should have produced a conservative estimate of the proportion of discharges 

having DRG errors. A series of reliability checks verified the reproducibility and 

accuracy of the AMRA coding. The AMRA also identified the reasons why a 

hospital’s bill differed from the correct codes. 

BOTEC Analysis Corporation of Cambridge, Massachusetts (BOTEC) edited the 

AMRA database, checked the sample’s representativeness, and conducted statistical 

analyses of the correlates and financial consequences of DRG 296 miscoding. It also 

reweighted the 1985 data to improve comparability with this inspection. The t-test 

determined whether numeric differences between the 1985 results and 1988 results 

were real (statistically significant) or could be attributed to random error. 

Representativeness 

To test the sample’s representativeness, the OIG compared the distribution of sample 

bills to the distribution of the underlying population of DRG 296. The sample came 

disproportionately from small, nonteaching, and for-profit hospitals. It did not differ 

statistically from the underlying population with respect to patient characteristics. 

[Appendix C]. 

Bedsize I Teachingstatus 

lW-299 Taaching <I(M 

100-299 

@l!!5* ~<’m ,on.w.~ ~ 

Nonteachhg 

Sample Population Sample Population 

Looation Controi 

,mm@pr”Nm.(=Jm ‘“Q:_QNm.. 

Sample Population Sample Population 

2

Age Sex 

Race 

3 
FINDINGS


Errors not reduced 

Of the 106 sample discharges, 10.4


percent had billing errors that changed 20


their reimbursement from DRG 296.


The difference between this result and


the 19.3 percent error rate the OIG


previously reported for 1985 was not


statistically significant.a This trend 10


applied across most hospital and patient


characteristics. Small and large


hospitals, urban hospitals, and teaching


+ — 

Year 

•1 1985 

� 1988 

institutions showed more improvement. 0i —


Patients aged 65-74 years and 85+


years, and males also had better coding Figure 3: Coding errors, 1985 & 1988


accuracy. [Appendix D].


This nonsignificant 1985-1988 decrease in the proportion of DRG 296 billing errors


exceeded the improvement for all DRGs. However, the latter change from 20.8


percent in 1985 to 14.7 percent in 1988 comparison attained statistical significance


because of their larger sample sizes. The difference between this inspection’s 10.4


percent DRG 296 e~rors and the 14.7 percent errors for all DRGs in-1988 was not


statistically significant.3 

&Ol_S occur randomly 

Of the 11 billing errors, 45.5 percent 

over-reimbursed the hospital. The errors 

do not have any statistical directionality. 

In 1985, a statistically significant 75.0 

percent of the 37 coding errors overreimbursed the hospital. Curiously, the 

randomness of this inspection’s error 

direction does not differ statistically from 

the previous inspection’s definite 

Percent 

30- Errordkectlon 

� Over-reimbursed 

20 � Under-reimbursed 

lo0-

-1oYear 1~ 1988 

directionality, presumably because of Figure 4: Direction of DRG 296 coding 

their relatively small sample sizes. errors, 1985 & 1988 

a. Because of the smaller sample size used in this DRG-specific analysis, estimates are 

less precise than the OIGS national estimate. Statistical testing determined whether 

apparent differences were real (statistically significant) or could be attributed to 

random error. 

4 
Errors cause no over-reimbursement 

The 106 sample discharges originally 

carried Relative Weights of 0.9259 

equivalent to an average payment of 

$2,829. The AMRA reabstraction 

increased the case-mix index (CMI) to 

0.9499, a nonstatistically significant 

difference of 0.0240. This trend 

persisted across all hospital and patient 

demographic categories. However, the 

net CMI change in 1988 did differ 

statistically from the net CMI change for 

DRG 296 in 1985. [Appendix E]. 

Extrapolation of the CMI change in 

1988 to all 191,509 DRG 296 discharges 

$million 2 

. 

Fim.we 5: Financial imnact. 1. 1985 & 1988

“ 

from the hospital categories included in this 

sample projected that billing errors under-reimbursed hospitals a nonstatistically 

significant $14.7 million. However, this under-reimbursement did differ statistically 

from the $19.9 million over-reimbursement the OIG previously reported for 1985. 

Reasons for errors 

The AMRA identified only two types of errors in the sample, mis-specification and 

“resequencing” in 1988. Mis-specification caused 36.4 percent of the 11 billing errors, 

not statistkafiy different from its 37.2 percent for 1985; Resequencing cause~ the 

balance of 1988 coding errors (63.4 percent), compared to 50.7 percent for 1985. 

Miscoding and “other” errors caused the remainder of errors for 1985. 

5


— 
ENDNOTES


1. Stone D, Kleiman M, Meyers M, Schutte J, Lee F, Hsia D, & Krushat M. DRG 

296: Nutritional and metabolic disorders. Washington, DC: HHS Office of Inspector 

General, 1989. Publication no. 0AI-12-88-01150. 

2. Knight J W & Hsia D C, eds. National DRG Validation Study Update: Technical 

Report. Washington, DC: HHSOffice of Inspector General, 1992. Inspection no. 

OEI-12-90-00191. 

3. Knight J W & Hsia D C, eds. National DRG Validation Study Update: Summary 

Report. Washington, DC HHS Ofilce of Inspector General, 1992. Inspection no. 

OEI-12-90-00190. 

6

APPENDICES 

7 
Appendix #k Project participants 

~ 

Cathaleen A. Ahern, B.A.


Evan J. Buckingham, B.A.


David C. Hsia, J.D., M.D., M.P.H.


Thomas F. Komaniecki, M.P.A.


W. Mark Krushat, M.P.H.


Linda M. Moscoe, B.A.


Brian P. Ritchie, B.A.


Barry L. Steeleyb


John M. Traczyk, B.A.


HCFA


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


Stephen F. Jencks, M.D.


Michael R. McMullan, M.B.A.


Harry L. Savitt, Ph.D.


Jeanette M. Smith, M.D., M.P.H.’


Malcolm A. Sneen, B.S.


RAND Cor~oration


Haya P. Rubin, M.D., Ph.Dd


Baxter-Health Data Institutee


Patricia J. Baxter, R.N.


Patricia Cassidy-Tsnosas, R.N.


Annette M. Delaney, R.N., M.A.


Ellen B. Inghilleri, R.N.


Janet Mathews, A.R.T.


Laurie H. Moore, R.R.A.


Claire Shannon, A.R.T.


Michele A. Wiese, B.A.


AMRA 

Margret K. Amatayakul, M.B.A., R.R.A.


Mary Converse, R.R.A.


Nicholas J. Cotsonas, M.D.f


Linda Ertl, R.R.A.


b. Now at Health Audit Services, Ellicott City, MD. 

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

d. Now at Johns Hopkins Medical Institutions. 

e. Ceased operations February 16, 1990. 

f. Outside contractor. 

8 
Rita M. Finnegan, R.R.A.


Desla Mantilla, A.R.T.


Barbara Manny, R.R.A.


Sonia Martyniuk, R.R.A.


Toula Nicholas, A.R.T.


Charlotte Razor, R.R.A.


LouAnn Schraffenberger, R.R.A.


Lynn Smetko, R.R.A.


Dawn Smith, A.R.T.


Joan Zacharias, A.R.T.


BOTEC Analvsis Corporation


Geraldine M. Berenhol~ R.R.A.


Andrew H. Chalsma, B.A.


David P. Cavanagh, M.A., Ph.D.


Janet W. Knight, R.N., Ph.D.


Amy L. Lockwood, B.A.


Contract information 

Contractor


BOTEC Analysis Corporation


1698 Massachusetts Avenue


Cambridge, MA 02138


Proiect Officer


David Hsia, J.D., M.D., M.P.H.


Office of Inspector General


330 Independence Avenue


Washington, D.C. 20201


Contract


HHS-1OO-9O-OO23


Firm-fixed price contract


$203,257


9

Appendix B: ICD-9-CM codes in DRG 2% 

251 hypoglycemia 

260 kwashiorkor 

261 marasmus 

262 other severe malnutrition 

263 other malnutrition 

264 vitamin A deficiency 

265 beriberi 

266 vitamin B deficiencies 

267 vitamin C deficiency 

268 vitamin D deficiency 

269 vitamin Kand other nutritional deficiencies 

275 magnesium-calcium metabolism diseases 

276 fluid and electrolyte disorders 

277 cystic fibrosis 

278 obesity 

781.7 tetany 

783 weight change 

790.2 abnormal glucose tolerance test 

791.6 acetonuria 

10

Appendix C Sample representativeness 

Number [percent] Population Sample 

Hos~ital demoma~hv 

1-99 beds 32,071 [16.7] 25 [23.6] 

100-299 beds 70,929 [37.0] 48 [45.3] 

300+ beds 88,474 [46.2] 33 [31.1] 

Metropolitan 143,417 [74.9] 72 [67.9] 

Nonmetropolitan 48,092 [25.1] 34 [32.1] 

Teaching 76,999 [40.2] 29 [27.4] 

Nonteaching 114,510 [59.8] 77 [72.6] 

Profit 20,273 [10.8] 18 [17.1] 

Nonprofit 166,626 [89.2] 87 [82.9] 

Patient demoma~hy 

c 65 years 16,914 [8.8] 6 [5.7] 

65-74 years 55,985 [29.2] 36 [34.0] 

75-84 years 70,772 [37.0] 34 [32.1] 

85+ years 47,838 [25.0] 30 [28.3] 

Male 70,471 [36.8] 34 [32.1] 

Female 121,038 [63.2] 72 [67.9] 

White 155,215 [81.0] 88 [83.0] 

Black 28,005 [14.6] 14 [13.2] 

Other 3,104 [1.6] 1 [0.9] 

Unknown 5,185 [2.7] 3 [2.8] 

Total 191.509 ., [100.01 ~—.- 106 [100.0] ‘J 

Chi-square 

9.54, 2 df, P= O.991 

2.58, 1 df, P= O.888 

6.87, 1 df, P= O.991 

4.10, 1 df, P= O.955 

2.99, 3 df, P= O.606 

0.96, 1 df, P=0.668 

0.47, 3 df, P= O.076 

11

Appendix D: Proportion of DRG 2% billingerrors, 1985 & 1988 

Number [percent] 1988 

HosRital demo~ra~hy 

1-99 beds 

100-299 beds 

300+ beds 

Metropolitan 

Nonmetropolitan 

Teaching 

Nonteaching 

Profit 

Nonprofit 

Patient demo~raphv 

<65 years 

65-74 years 

75-84 years 

85+ years 

Male 

Female 

White 

Black 

Other 

Unknown 

Total 

3 [12.0 t 6.6] 

6 [12.5 ~ 4.8] 

2 [6.1 f 4.2] 

5 [6.9 f 3.0] 

6 [17.6 ~ 6.6] 

2 [6.9 ~ 4.8] 

9 [11.7 t 3.7] 

3 [9.2 ~ 3.1] 

8 [16.7 t 9.0] 

2 [33.3 f 21.1] 

3 [8.3 ~ 4.7] 

3 [8.8* 4.9] 

3 [10.0 ~ 5.6] 

4 [11.8 ? 5.6] 

7 [9.7 * 3.5] 

10 [11.4 * 3.4] 

o [0.0 * 0.0] 

o [0.0 * 0.0] 

1 [33.3 t 33.3] 

11 [10.4 * 3.0] 

1985” t-test 

21 [28.8 ~ 5.3] 3.18 

9 [16.1 ~ 5.0] 0.82 

7 [15.9 ~ 5.6] 2.48 

14 [20.0 t 5.0] 2.82 

23 [28.6 ~ 7.5] 1.39 

5 [15.1 A 6.3] 2.02 

32 [22.0 f 

2 [15.1 f 

35 [18.3 f 

5 [5.0 f 

13 [28.2 f 

10 [18.9 ~ 

9 [18.0 f 

17 [24.2 ~ 

20 [13.5 * 

37 [18.0 f 

5.2] 1.61 

11.0] 1.57 

3.4] 0.31 

2.8] 8.85 

7.6] 3.92 

6.1] 1.83 

5.0] 2.08 

6.4] 2.31 

3.4] 0.90 

3.3] 1.59 

*. Reweighted for comparability to 1988. 

12 
Appendix E DRG 2% case-mix index change, 1985 & 1988 

Relative weight ~ 1988 1985 Difference 

standard error 

Hospital demoma~hv 

1-99 beds -0.0123 ~ 0.0121 -0.0429 f 0.0153 0.0306 

100-299 beds 0.0654 * 0.0500 -0.0172 ~ 0.0129 0.0826 

300+ beds -0.0084 ~ 0.0118 -0.0237 f 0.0135 0.0153 

Metropolitan 0.0412 & 0.0331 -0.0207 ~ 0.0142 0.0619 

Nonmetropolitan -0.0123 ~ 0.0171 -0.0557 ~ 0.0214 0.0434 

Teaching -0.0096 t 0.0135 -0.0226 ~ 0.0134 0.0130 

Nonteaching 0.0367 ~ 0.0315 -0.0267 & 0.0137 0.0634 

Profit 0.0046 ~ 0.0114 0.0209 i 0.0443 -0.0163 

Nonprofit 0.1190 t 0.1259 -0.0284 ~ 0.0080 0.1474 

patient demomaphy 

<65 years 0.0445 t 0.1345 -0.0066 ~ 0.0060 0.0511 

65-74 years 0.0667 * 0.0634 -0.0621 k 0.0189 0.1288 

75-84 years -0.0110 t 0.0102 -0.0349 f 0.0178 0.0239 

85+ years 0.0084 t 0.0143 -0.0065 * 0.0144 0.0149 

Male 0.0597 t 0.0684 -0.0295 k 0.0152 0.0892 

Female 0.0072 ~ 0.0117 -0.0204 f 0.0093 0.0276 

White 0.0313 ~ 0.0279 

Black O.0000 * O.0000 

Other O.0000 * O.0000 

Unknown -0.0678 f 0.0678 

Total 0.0240 ~ 0.0232 -0.0243 k 0.0083 0.0483 

t-test 

2.12 

2.73 

1.53 

2.35 

1.94 

1.36 

2.46 

1.16 

6.23 

2.72 

3.84 

1.52 

1.41 

2.80 

2.25 

2.30 

13