Hospital-physician integration and risk-coding intensity

Abstract

Hospital-physician integration has surged in recent years. Integration may allow hospitals to share resources and management practices with their integrated physicians that increase the reported diagnostic severity of their patients. Greater diagnostic severity will increase practices' payment under risk-based arrangements. We offer the first analysis of whether hospital-physician integration affects providers' coding of patient severity. Using a two-way fixed effects model, an event study, and a stacked difference-in-differences analysis of 5 million patient-year observations from 2010 to 2015, we find that the integration of a patient's primary care doctor is associated with a robust 2%-4% increase in coded severity, the risk-score equivalent of aging a physician's patients by 4-8 months. This effect was not driven by physicians treating different patients nor by physicians seeing patients more often. Our evidence is consistent with the hypothesis that hospitals share organizational resources with acquired physician practices to increase the measured clinical severity of patients. Increases in the intensity of coding will improve vertically-integrated practices' performance in alternative payment models and pay-for-performance programs while raising overall health care spending.

Keywords: healthcare spending; hospitals; medicare; physicians; professional labor markets; vertical integration.

FIGURE 1

Variation in coded severity within patients. Coded severity defined as Hierarchical Condition Category (HCC) score. Graph to illustrate variation in dependent variable. The average patient HCC score was 1.047. The average within-panel range in a patient’s HCC score from 2010 to 2015 was 0.987; the 95^th percentile of this within-panel range was 2.894

FIGURE 2

Event study of coded severity. This figure displays the event study specification of the effect of integration on the coded severity of an integrated physician’s patients. The point estimates are the regression coefficients from Equation (2). The y-axis displays the dependent variable (natural log of HCC scores). The x-axis displays the time relative to when the physician became hospital-integrated ($t=0$ represents the first year of integration). These estimates imply that patients’ risk scores increased between 2% and 4% after their primary care physician vertically integrated with a hospital

FIGURE 3

Event study of standard deviation in coded severity. This figure displays the event study specification of the effect of integration on the variability in risk scores within a physician’s panel of patients. For each physician in each year, we calculated the standard deviation of his or her patient’s Hierarchical Condition Category (HCC) scores. We then estimated a physician-year level event study model to determine whether integration exerted an influence on the variability of HCC scores. The sample mean of standard deviation in the last pre-period was 0.664. The point estimates are the regression coefficients from Equation (3). The y-axis displays the dependent variable (natural log of HCC scores). The x-axis displays the time relative to when the physician became hospital-integrated ($t=0$ represents the first year of integration). These estimates demonstrate that the variability of HCC scores within a physician’s panel of patients (even holding the panel of patients constant) decreased modestly after the physician vertically integrated with a hospital