The Seventh Vital Sign: Predicting Expenditures with a Global Health Status Measure
Location(s): United States
Predicting health care expenditures is important for health care research, policy, and practice. In health care delivery settings, interest often focuses on identifying potential high-cost patients, who could be enrolled in case-management or disease-management programs. Moreover, when used as a means of risk adjustment to improve comparability of different groups, predictions of high-cost cases are useful for evaluating clinical interventions or the effects of policy changes.
Health care measurement generally tells the administration, physician, and patient where the system is and has been. These measures provide little information about where the system is going. Health status evaluations can fill this void, as they are predictive of outcomes and resource use. Yet, these parameters are not routinely measured, monitored, and evaluated by most health care systems. Research has demonstrated that a single global health status question can predict subsequent expenditures in Medicare and private-sector populations. The purpose of this project is to repeat this evaluation in the New Orleans Veterans Affairs Medical Center (VANO) primary care clinic system. Using the VANO electronic medical record, patients' health status will be routinely measured as part of their vital signs intake during routine visits to the general medicine clinics. Health care costs and utilization for these patients will be measured one year from enrollment in the study. Secondary objectives will examine whether SF-1 predictability varies by demographic groups such as race and disease subsets. They also will evaluate whether the SF-1 predicts certain categories of expenditures better than others such as expected versus unexpected utilization. They will sample a subgroup of patients with a more detailed health status evaluation, the VA SF-12, to look at the relationship between the subscales and subsequent expenditures. Finally, they will evaluate whether annual trends in the SF-1 and the SF-12 are better predictors of future expenditures than a single measure.