Journal Information
Vol. 15. Issue 5.
Pages 423-431 (August - October 2001)
Vol. 15. Issue 5.
Pages 423-431 (August - October 2001)
Open Access
Risk adjustment: beyond patient classification systems
Ajuste del riesgo: más allá de los sistemas de clasificación de pacientes
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F. Cotsa,
Corresponding author
Fcots@imas.imim.es

Correspondence: Dr. F. Cots. Servei d'Estudis. Hospital del Mar. Passeig Marítim, 25–29. 08003 Barcelona.
, X. Castellsa, L. Mercadéa, P. Torreb, M. Riua
a Servei d'Estudis de l'Institut Municipal d'Assistència Sanitària.
b Servei de Documentació de l'Institut Municipal d'Assistència Sanitària. Barcelona.
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Article information
Abstract

Diagnosis related groups (DRGs) are widely used in several countries. Their various versions aim to value the cost of hospital production. In Europe, the patient classification systems and standard weights used are usually the American originals.

Objectives

The objective of this study was to analyse the extent to which DRGs and DRG-weights explain patient cost variability. Different components of patient cost (severity, comorbidities, complications and socioeconomic status), which are not well explained by DRG and which can be approximated by using administrative data, were also analysed.

Methods

A total of 35,262 discharges from two public hospitals in Barcelona were analysed. The Health Care Financing Administration (HCFA)-DRGs and the All Patient Refined (APR)- DRGs were calculated. Severity was adjusted by Disease Staging, and comorbidities and complications were calculated using Elixhauser and Charlson comorbidities groupings. An ecological socioeconomic status indicator was used. Linear regressions were estimated to explain per-patient cost variability.

Results

We found that Medicare's DRG-weights explained only 19% of cost variability. Cost-based weights explained nearly 40% (38-42%, depending on the DRG classification used). Exclusion of outliers increased explanatory power to R2 = 47–48%. The remaining adjustment variables increased R2 to 49–51%.

Discussion

Medicare's DRG-weights are not well-suited to Europe. Cost-based DRG-weights and outlier trimming have significantly greater explanatory power. The remaining clinical and socioeconomic variables have considerably less explanatory power but were statistically significant and behaved as expected. Spanish and other European health authorities should adapt DRG-classification systems to their environments for use in hospital production cost valuation.

Key words:
Diagnosis related groups
Hospital cost analysis
DRG-weights
Outliers
Socioeconomic status
Severity
Risk adjustment
Resumen

Los grupos relacionados con el diagnóstico (GRD) se utilizan ampliamente en diferentes países. Sus diversas versiones tratan de estimar el coste de la producción hospitalaria. En Europa, los sistemas de clasificación de pacientes y los pesos relativos estándares utilizados habitualmente son los originales norteamericanos.

Objetivos

El objetivo del presente estudio fue analizar el grado hasta el cual los GRD y las ponderaciones GRD explican la variabilidad del coste del paciente. También se analizaron los diferentes componentes del coste del paciente (gravedad, comorbilidades, complicaciones y posición socioeconómica) que no se explican adecuadamente mediante los GRD y que pueden abordarse utilizando datos administrativos.

Métodos

Se analizaron un total de 35.262 altas de dos hospitales públicos de Barcelona. Se calcularon los GRD de la Health Care Financing Administration (HCFA) y los GRD refinados de todos los pacientes (APR). La gravedad se ajustó mediante la Disease Staging, y las comorbilidades y complicaciones se calcularon utilizando las agrupaciones de comorbilidades de Elixhauser y Charlson. Se utilizó un indicador ecológico de la posición socioeconómica. Para explicar la variabilidad del coste por paciente se estimaron regresiones lineales. Resultados: Pusimos de manifiesto que las ponderaciones GRD Medicare sólo explicaron un 19% de la variabilidad del coste. Las ponderaciones basadas en el coste explicaron casi un 40% (38–42%, dependiendo de la clasificación GRD utilizada). La exclusión de los valores extremos aumentó la potencia explicativa hasta un R2 = 47–48%. Las variables de ajuste restantes aumentaron el R2 hasta un 49–51%.

Discusión

Las ponderaciones GRD Medicare no son apropiadas para Europa. Las ponderaciones GRD basadas en el coste y la reducción de los valores extremos se caracterizaron por una potencia explicativa significativamente mayor. Para las variables clínicas y socioeconómicas restantes se identificó una potencia explicativa considerablemente menor, fueron estadísticamente significativas y se comportaron como se esperaba. Las autoridades sanitarias españolas y de otros países europeos deben adaptar los sistemas de clasificación GRD a sus ámbitos para utilizarlos en la evaluación del coste de la producción hospitalaria.

Palabras clave:
Grupos relacionados con el diagnóstico
Análisis del coste hospitalario
Pesos relativos GRD
Valores extremos
Nivel socioeconómico
Severidad
Ajuste del riesgo
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References
[1.]
J. Hadley, S. Zuckerman, L. Iezzoni.
Financial Pressure and Competition. Changes in Hospital Efficiency and Cost-Shifting Behavior.
Med Care, 34 (1996), pp. 205-219
[2.]
L.I. Iezzoni.
The risks of risk adjustment.
JAMA, 278 (1997), pp. 1600-1607
[3.]
M.M. Wiley.
Hospital financing reform and casemix measurement: an international review.
Health Care Financing Review, 14 (1992), pp. 119-133
[4.]
R.B. Fetter, J.L. Freeman.
Grupos relacionados con el diagnóstico: gestión por líneas de productos en los hospitales.
Los grupos relacionados por el diagnóstico: experiencia y perspectivas de utilización,
[5.]
R.P. Ellis, T.G. McGuire.
Hospital response to prospective payment: Moral Hazard, selection, and practice-style effects.
J Health Econom, 15 (1996), pp. 257-277
[6.]
K.A. Calore, L. Iezzoni.
Disease staging and PMCs. Can they improve DRGs?.
Med Care, 25 (1987), pp. 724-737
[7.]
N. Söderlund, A. Gray, R. Milne, J. Raftery.
The Construction of resource-weights for healthcare resource groups: a comparison of alternative data sources and methodological approaches.
[8.]
N. Söderlund, A. Gray, R. Milne, J. Raftery.
Case mix measurement in english hospitals: an evaluation of five methods for predicting resource use.
J Health Serv Res Pol, 1 (1996), pp. 10-19
[9.]
J.W. Thomas, M.L.F. Ashcraft.
Measuring severity of illness: six severity systems and their ability to explain cost variations.
Inquiry, 28 (1991), pp. 39-55
[10.]
C. Beaver, Y. Zhao, S. McDermid, D. Hindle.
Casemix-based funding of northern territory public hospitals: adjusting for severity and socio-economic variations.
Health Econom, 7 (1998), pp. 53-61
[11.]
S. Peiró.
Comparación de resultados en la asistencia sanitaria.
Evaluación de la calidad de la asistencia sanitaria, pp. 119-138
[12.]
S. Peiró.
Limitaciones en la medición de los resultados de la atención hospitalaria: implicaciones para la gestión.
Instrumentos para la gestión en sanidad, pp. 57-101
[13.]
M.E. Charlson, P. Pompei, K.L. Ales, C.R. MacKenzie.
A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
J Chron Dis, 40 (1987), pp. 373-383
[14.]
A. Elixhauser, C. Steiner, R. Harris, R.M. Coffey.
Comorbidity measures for use with administrative data.
Med Care, 36 (1998), pp. 8-27
[15.]
N. Söderlund.
Do managers pay their way? The impact of management input on hospital productivity in the NHS internal market.
J Health Serv Res Pol, 4 (1999), pp. 6-15
[16.]
B. Gutiérrez, S.D. Culler, D.A. Freund.
Does hospital procedurespecific volume affect treatment costs? A national study of knee replacement surgery.
Health Serv Res, 33 (1998), pp. 489-513
[17.]
A.M. Epstein, R.S. Stern, J. Tognetti, C.B. Begg, R.M. Hartley, E. Cumella, et al.
The Association of Patients' Socioeconomic Characteristics with the Length of Hospital Stay and Hospital Charges Within Diagnosis-Related Groups.
N Engl J Med, 318 (1988), pp. 1579-1585
[18.]
A.M. Epstein, R.S. Stern, J.S. Weissman.
Do the Poor Cost More? A Multihospital study of Patients' Socioeconomic Status and Use of Hospital Resources.
N Engl J Med, 322 (1990), pp. 1122-1128
[19.]
J.S. Weissman, R.S. Stern, A.M. Epstein.
The impact of patient socioeconomic status and other social factors on readmission: a prospective study in four massachusetts hospitals.
Inquiry, 31 (1994), pp. 163-172
[20.]
J. Magnussen, K. Solstad.
Case-based hospital financing: the case of Norway.
Health Policy, 28 (1994), pp. 23-36
[21.]
P. Ibern.
Competencia entre hospitales. Los hospitales compiten para atraer más pacientes en lugar de competir en precios.
Economía y Salud, 8 (1998), pp. 8
[22.]
I.H. Monrad Aas.
Incentives and financing methods.
Health Policy, 34 (1995), pp. 205-220
[23.]
P. Ibern, J. Bisbel, M. Casas.
The development of cost information by DRG -Experience ina a Barcelona hospital.
Health Policy, 17 (1991), pp. 179-194
[24.]
J.L. Temes, J.L. Díaz, B. Parra.
El coste por proceso hospitalario.
[25.]
F. Cots, X. Castells, A. García, M. Sáez.
Relación de los costes directos de hospitalización con la duración de la estancia.
Gac Sanit, 11 (1997), pp. 287-295
[26.]
S. Udpa.
Activity-based costing for hospitals.
Health Care Manag Rev, 21 (1996), pp. 83-96
[27.]
D.W. Young, L.K. Pearlman.
Managing the stages of hospital cost accounting.
Healthcare Financial Management, 47 (1993), pp. 58-80
[28.]
F. Cots, M.G. Carasusan, X. Castells.
Asignación de tiempo médico a tareas no asistenciales. Libro de actas de X Jornadas de salud pública y administración sanitaria.
[29.]
F. Cots, X. Castells.
Cómo pagamos a nuestros hospitales. La referencia de Cataluña y el contrapunto desde Andalucía.
Gac Sanit, (2001),
[30.]
J. Raftery.
Benchmarking costs in health services.
J Health Serv Res Policy, 4 (1999), pp. 63-64
[31.]
F. Cots, D. Elvira, X. Castells, E. Dalmau.
Medicare's DRG-Weights in a European environment: the Spanish experience.
Health Policy, 51 (2000), pp. 31-47
[32.]
All patient refined diagnosis related groups (APR-DRGs).
Definitions manual. Version 15.0.
3M health information systems, (1999),
[33.]
G.M. Carter, J.D. Rumpel.
Payment rates for unusual Medicare hospital cases.
RAND, (1992),
[34.]
E.B. Keeler, G.M. Carter, S. Trude.
Insurance aspects of DRG outlier payments.
J Health Econom, 7 (1988), pp. 193-214
[35.]
F. Cots, X. Castells, D. Elvira, M. Sáez.
Relevance of outlier cases in case mix systems and evaluation of trimming methods for use in Europe.
Mimeo, (2000),
[36.]
J.S. Gonnella, D.Z. Louis, M.E. Gozum.
Disease staging clinical criteria. Version 17.
Medstat group, (1999),
[37.]
M.M. Wiley, R. Tomas, M. Casas.
A cross-national, casemix analysis of hospital length of stay for selected pathologies.
Eur J Pub Health, 9 (1999), pp. 86-92
[38.]
W. D'Hoore, C. Sicotte, C. Tilquin.
Risk adjustment in outcome assessment: the Charlson comorbidity index.
Meth Inform Med, 32 (1993), pp. 382-387
[39.]
R.A. Deyo, D.C. Cherkin, M.A. Ciol.
Adapting a clinical comorbidity index for use with icd-9-cn administrative databases.
J Clin Epidemiol, 45 (1992), pp. 613-619
[40.]
J. Librero, S. Peiró.
Efectividad hospitalaria: exploración de los factores asociados al reingreso hospitalario urgente. Libro de actas de XV Jornadas de economía de la salud.
[41.]
P. Ibern, J.C. Vertrees, K.G. Manton, M.A. Woodbury.
Hospital groups and case-mix measurement for resource allocation and payment.
Diagnosis Related Groups in Europe, Springer-Verlag, (1993),
[42.]
H.E. Flamer, N. Chirstophidis, C. Margetts, A. Ugoni, A.J. McLean.
Extended hospital stays with increasing age: the impact of an acute geriatric unit.
MJA, 164 (1996), pp. 10-13
[43.]
T.P. Hofer, R.A. Wolfe, P.J. Tedeschi, L.F. McMahon, J.R. Griffith.
Use of community versus individual socioeconomic data in predicting variation in hospital use.
Health Serv Res, 33 (1998), pp. 243-259
[44.]
Índex de capacitat econòmica familiar a la ciutat de Barcelona II.
Departament d'estadística. Ajuntament de Barcelona.
Barcelona, (1999),
[45.]
A. Briggs, A. Gray.
The distribution of health care costs and their statistical analysis for economic evaluation.
J Health Serv Res Policy, 3 (1998), pp. 233-245
[46.]
J.R.G. Butler.
Hospital cost analysis.
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