Correlation of Risk Adjustment Measures Based on Diagnoses and Patient Self-Reported Health Status
Tóm tắt
Case-mix adjustments have traditionally used diagnosis-based models such as Diagnostic Cost Groups (DCGs). The recent development and availability of reliable and valid patient self-reported health status measures such as the Veterans SF-36 (Short Form Health Survey) may be useful in complementing existing diagnostic information in describing patients' health status for purposes of risk adjustment. However, the correlation between these two approaches has not been explored. We collected SF-36 data from 31,419 veterans nationwide based on a national probability sample of veterans receiving ambulatory care to assess the physical (PCS) and mental (MCS) component of patient self-reported health status. In addition, we used inpatient and outpatient diagnoses from one year (1/1/97 to 1/1/98) to calculate DCG relative risk scores, with the 1991 Medicare beneficiary population as the benchmark. We found that higher DCG relative risk scores were associated with worse PCS (r=−0.223, p<0.05) and MCS (r=−0.174, p<0.05) scores. Further examination of the distribution of MCS categories (MCS≤40) across the five psychiatric hierarchical condition categories (HCCs) in the DCG/HCC model showed a small association between MCS category and disease severity level. These results suggest that risk adjustment approaches based on patient self-reported health status and diagnoses convey different case-mix information, specifically for patients with psychiatric conditions. These two approaches can be used as the basis for the development of a more comprehensive risk adjustment model which incorporates both the providers' and the patients' perspectives in predicting resource utilization.
Tài liệu tham khảo
A. Ash, F. Porell, L. Gruenberg, E. Sawitz and A. Beiser. An analysis of alternative AAPCC models using data from the continuous medical history sample, Brandeis/Boston University, Boston, 1986.
A. Ash, F. Porell, L. Gruenberg, E. Sawitz and A. Beiser. “Adjusting Medicare capitation payments using prior hospitalization data,” Health Care Financing Review, 10, pp. 17-29, 1989.
M. C. Beattie, R. W. Swindle and L. A. Tomko. Department of Veterans Affairs Databases Resource Guide, HSR&D Center for Health Care Evaluation, Palo Alto, 1993.
A. C. Brewster, B. G. Karlin, L. A. Hyde, C. M. Jacobs, R. C. Bradbury and Y. M. Chae. “MEDISGRPS: A clinically based approach to classifying hospital patients at admission,” Inquiry, 22, pp. 377-387, 1985.
R. H. Brook, J. E. Ware, Jr., A. Davies-Avery, A. L. Stewart, C. A. Donald, W. H. Rogerss, K. Williams and S. A. Johnson. “Overview of adult health status measures fielded in Rand health insurance study,” Medical Care, 17S, pp. 1-131, 1979.
D. A. Dillman. Mail and telephone surveys: The total design method, John Wiley and Sons, New York, 1978.
R. P. Ellis and A. Ash. “Refinements to the diagnostic cost group model.” Inquiry, 32, pp. 418-429, 1995.
R. P. Ellis, G. C. Pope, L. I. Iezzoni, J. Z. Ayanian, D. W. Bates, H. Burstin and A. S. Ash. “Diagnosis-based risk adjustment for Medicare capitation payments,” Health Care Financing Review, 17, pp. 101-128, 1996.
R. B. Fetter, Y. Shin, R. F. Freeman, R. F. Averill and J. D. Thompson. “Case mix definition by diagnosis-related groups,” Medical Care, 18(Suppl. 2), pp. 1-53, 1980.
J. B. Fowles, J. P. Weiner, D. Knutson, E. Fowler, A. M. Tucker and M Ireland. “Taking health status into account when setting capitation rates,” JAMA, 276, pp. 1316-1321, 1996.
M. C. Hornbrook and M. J. Goodman. “Assessing relative health plan risk with the RAND-36 health survey.” Inquiry, 32, pp. 56-74, 1995.
M. C. Hornbrook and M. J. Goodman. “Chronic disease, functional health status, and demographics: a multidimensional approach to risk adjustment,” Health Services Research, 31, pp. 283-307, 1996.
L. I. Iezzoni. Risk adjustment for measuring healthcare outcomes, 2nd Edition, Health Administration Press, Chicago, p. 95, 1997.
L. I. Iezzoni. Risk adjustment for measuring healthcare outcomes, 2nd Edition, Health Administration Press, Chicago, p. 3, 1997.
L. I. Iezzoni. “Risk adjustment for medical effectiveness research: an overview of conceptual and methodological considerations,” Journal of Investigative Medicine, 43, pp. 136-150, 1995.
R. M. Kaplan and J. P. Anderson. “The quality of well-being scale: rationale for a single quality of life index.” In Quality of life: assessment and application, (S. R. Walker and R. M. Rosser, eds) pp. 51-78, MTP Press: Lancaster, 1988.
L. E. Kazis, D. R. Miller, J. Clark, K. Skinner, A. Lee, W. Rogers, A. Spiro, III., S. Payne, G. Fincke, A. Selim and M. Linzer. “Health-related quality of life in patients served by the department of veterans affairs: results from the veterans health study.” Archives of Internal Medicine 158: pp. 626-632, 1998.
L. E. Kazis and N. Wilson. Health status and outcomes of veterans: physical and mental component summary scores (Veterans SF-36V): 1998 National Survey of Ambulatory Care Patients, Mid-Year Executive Report. Office of Performance and Quality, and Health Assessment Project, Health Services Research and Development Service. Washington DC and Bedford, Massachusetts, July 1998.
L. E. Kazis, X. S. Ren, A. Lee, K. Skinner, W. Rogers, J. Clark and D. R. Miller. “Health status in VA patients: results from the Veterans Health Study,” Am J Med Quality, 14, pp. 28-38, 1999.
L. E. Kazis, D. Miller, J. Clark, K. Skinner, A. Lee, X. S. Ren, A. Spiro, III, W. Rogers and J. E. Ware. “Improving the response choices on the SF-36 role functioning scales: results from the veterans health study” (Medical Care Supplement, forthcoming).
L. E. Kazis, A. Lee, X. S. Ren, K. Skinner and W. Roger. Health status and outcomes of veterans: physical and mental component summary scores (Veterans SF-12): 1998 National Survey of Hospitalized Patients. Office of Performance and Quality, and Health Assessment Project, Health Services Research and Development Service. Washington DC, and Bedford, Massachusetts, March 1999.
L. M. Lamers and R. C. J. A. Van Vliet. “Multiyear diagnostic information from prior hospitalizations as risk-adjuster for capitation payments,” Medical Care, 34, pp. 549-561, 1996.
L. M. Lamers. “Risk-adjusted capitation based on the diagnostic cost group model: an empirical evaluation with health survey information,” HSR: Health Services Research, 33, pp. 1727-1744, 1999.
L. A. Lillard and M. M. Farmer. “Linking Medicare and national survey data,” Annals of Internal Medicine 127, pp. 691-695, 1997.
K. Liu, T. McBride and T. Coughlin. “Risk of entering nursing homes for long vs. short stays,” Medical Care, 32, pp. 315-327, 1994.
C. McHorney, J. E. Ware Jr., J. Rachel and C. Sherbourne. “The MOS 36-Item short form health survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups,” Medical Care, 32, pp. 40-66, 1994.
N. Muhajarine, C. Mustard, L. L. Roos, T. K. Young and D. E. Gelskey. “Comparison of survey and physician claims data for detecting hypertension,” Journal of Clinical Epidemiology, 50, pp. 711-718, 1997.
J. P. Newhouse, W. G. Manning, E. B. Keeler and E. M. Sloss. “Adjusting capitation rates using objective health measures and prior utilization,” Health Care Financing Review, 10, pp. 41-54, 1989.
D. L. Patrick, J. W. Bush and M. M. Chen. “Methods for measuring levels of well-being for a health status index,” HSR: Health Services Research, 8, pp. 228-245, 1973.
Personal communication with Arlene Ash. 1999.
S. J. Reiser. “The era of the patient: using the experience of illness in shaping the missions of health care,” JAMA, 269, pp. 1012-1017, 1993.
S. Salem-Schatz, G. Moore, M. Rucker and S. D. Pearson. “The case for case-mix adjustment in practice profiling: when good apples look bad,” JAMA, 272, pp. 871-874, 1994.
W. O. Spitzer, A. J. Dobson, J. Hall, E. Chesterman, J. Levi, R. Shepherd, R. N. Battista, B. R. Catchlove. “Measuring the quality of life of cancer patients. A concise QL-index for use by physicians,” Journal of Chronic Disease, 34, pp. 585-597, 1981.
B. H. Starfield, J. Weiner, L. Mumford and D. Steinwachs. “Ambulatory care groups: a categorization of diagnoses for research and management,” HSR: Health Services Research, 26, pp. 53-74, 1991.
J. W. Thomas and R. Lichtenstein. “Including health status in Medicare's adjusted average per capita cost capitation formula,” Medical Care, 24, pp. 259-275, 1986.
R. C. J. A. Van Vliet and W. P. M. M. Van de Ven. “Towards a capitation formula for competing health insurers,” Social Science and Medicine, 34, pp. 1035-1048, 1992.
B. C. Vladeck. “Medicare hospital payment by diagnosis-related groups,” Annals of Internal Medicine, 100, pp. 576-591, 1984.
J. E. Ware Jr., A. Davies-Avery and R. H. Brook. Conceptualization and measurement of health for adults in the health insurance study: Vol. 1. Model of Health and Methodology, Rand Corporation, Santa Monica, 1980.
J. E. Ware Jr. and C. D. Sherbourne. “The MOS 36-Item short-form health survey (SF-36). I. Conceptual framework and item selection,” Medical Care, 30, pp. 473-483, 1992.
J. E. Ware Jr., K. K. Snow, M. Kosinski and B. Gandek. SF-36 Health survey manual and interpretation guide, New England Medical Center Health Institute, Boston, 1993.
J. E. Ware Jr., M. Kosinski and S. D. Keller. SF-36 Physical and mental health summary scales: a users manual. New England Medical Center Health Institute, Boston, 1994.
J. P. Weiner, B. H. Starfield, D. M. Steinwachs and L. M. Mumford. “Development and application of a population-oriented measure of ambulatory care case-mix,” Medical Care, 29, pp. 452-472, 1991.
J. P. Weiner, B. H. Starfield, N. R. Powe, M. E. Stuart and D. M. Steinwachs. “Ambulatory care practice variation within a Medicaid program,” HSR: Health Services Research, 30, pp. 751-770, 1996.
B. William. “Comparison of services among different types of home health agencies,” Medical Care, 32, pp. 1134-1152, 1994.
S. Wood-Dauphinee and J. I. Williams. “Reintegration to normal living as a proxy to quality of life,” Journal of Chronic Disease, 40, pp. 491-499, 1987.