Using county-level public health data to prioritize medical education topics

Abstract

Patient behavior and poor health care access contribute to PHR but do not fully explain variation in PHR. If county-level unexplained PHR values identify high priority medical education topics, then other measures of importance, notably disease prevalence and PHR, are poor identifiers of high value topics. Although available predictor and outcome variables constrain the current analysis, unexplained variation in health outcome measures might identify educational opportunities. These observations suggest strategies for balancing and evaluating controlled trials of knowledge dissemination efforts and eventually for deploying educational activities.

Variation Over Time in Preventable Hospitalization Rates Across Counties

“…Variation in preventable hospitalization rates between Missouri counties was documented for asthma, chronic obstructive pulmonary disease, congestive heart failure, diabetes, and hypertension between 1998 and 2002. 23 In the current study, we again found 10-fold variation between the top and bottom deciles of Kentucky counties in four of five measures designed to assess the quality of primary care services received by adults. The variation is clinically and statistically significant.…”

“…In a study of Missouri counties, county level income, health care access, disease prevalence, and behavioral variables explained a moderately large fraction of variation. 23 Poverty also explained a significant fraction of variation reported in Tennessee. 22 The Kentucky dataset is distinctive in demonstrating that variation persists after correcting for the comorbidity of individual patients.…”