The performance of administrative and self-reported measures for risk adjustment of veterans affairs expenditures

Health Services Research, June, 2005 by Matthew L. Maciejewski, Chuan-Fen Liu, Ann Derleth, Mary McDonell, Steve Anderson, Stephan D. Fihn

Various approaches have been taken in observational and experimental studies to reduce differences among patient samples that may inherently be at differential risk. Risk adjustment has also been used in an attempt to reduce biases in prospective payments because of systematic differences in patient risk (Pope et al. 1998). Risk adjustment measures have been developed from various data sources including: diagnoses from medical records or health insurance claims (e.g., Adjusted Clinical Group [ACG] and Diagnostic Cost Group [DCG]), self-reported demographic and health status (e.g., SF-36) data from patient surveys, and pharmaceutical indicators of clinical conditions (e.g., RxRisk).

Medicare uses the DCG diagnosis-based measure in setting the Average Adjusted Per Capita Cost capitation paid to Medicare+Choice health plans. The Chronic Illness and Disability Payment System (CDPS) diagnosis-based measure is currently being used in eight states to adjust payments for Medicaid patients (personal communication with Todd Gilmer). Heretofore, the nation's largest integrated health care system, the Veterans Health Administration of the Department of Veterans Affairs (VA) has not used any of these risk adjusters in allocating its Congressionally determined global budget to each of its 21 component networks, even though there are known to be substantial regional differences in health and utilization (Kazis et al. 1998; Au et al. 2001). VA provides an ideal setting to assess the performance of differing strategies to adjust for patient risk differences in observational or experimental studies because of the availability of extensive demographic, clinical, pharmacy, and economic data on several million veterans who use VA services. In addition, many studies conducted within VA collect patient-reported survey data that can be coupled with administrative data.

Studies of risk adjustment in VA have examined the correlation between self-reported health status and claims-based risk adjusters (Wang et al. 2001); risk adjustment of ambulatory encounters and the combination of inpatient length of stay and outpatient visit days (Rosen et al. 2001; Rosen et al. 2002); and risk adjustment of total costs (Sales et al. 2003). No study to date has compared the full array of administrative-, pharmacy-based, and self-reported risk adjustors on the same patient data set, partly because it is rarely possible to compile self-report, pharmacy and diagnosis data on a large sample of patients from multiple sites.

This study employs administrative, clinical, and survey data on 14,449 veterans that were collected as part of a randomized trial of a quality improvement intervention (Fihn et al. 2004). The purpose of this analysis was to compare the predictive accuracy of eight risk adjustment measures derived from routinely collected administrative data or from self-reported health status questionnaires in prospective models of outpatient, inpatient, and total expenditures of VA care. In addition, this study examined the performance of models incorporating more than one measure of risk.

This comparison of risk adjustment measures may assist researchers in choosing which measures are most suitable for inclusion in future prospective experimental and observational studies. In addition, use of the most predictive risk adjuster in experimental studies could generate more precise cost predictions for cost-effectiveness analysis. Finally, VA medical center directors could use risk adjustment to determine which types of patients to attract, based on prospective risk adjustment models that accurately predict expenditures of low cost patients.

METHODS

Sample

Data for our analysis came from the Ambulatory Care Quality Improvement Project (ACQUIP), which was a multicenter, randomized trial conducted in the General Internal Medicine (primary care) Clinics at seven VA medical centers (VAMCs) in six states during 1997-2000. The objective of the trial was to determine whether providing regular reports to providers about their patients' self-reported health status, combined with routine clinical data and information about clinical guidelines would enhance patient care outcomes. Eligible patients included those who were assigned a primary care provider and had had a least one primary care visit in the year prior to the study intervention. The study examined whether quality of care and guideline-concordant care would change as a result of these provider-based assessments of patient health.

Patients in the intervention group were sent an initial screening questionnaire 6 months prior to the study start about their chronic medical conditions. All patients were sent the same questionnaire every 6 months thereafter until the end of the study. Those who completed the initial health-screening questionnaire were then sent SF-36 and other condition specific surveys at 6 and 3 months prior to baseline, at baseline, and at 6-month intervals after baseline for 2 years. Control group patients who responded to the initial screening questionnaire were sent the same surveys at baseline, 1 and 2 years (Fihn et al. 2004).