The Associations Between United States Medical Licensing Examination Performance and Outcomes of Patient Care.

PURPOSE: The United States Medical Licensing Examination (USMLE) comprises a series of assessments required for the licensure of U.S. MD-trained graduates as well as those who are trained internationally. Demonstration of a relationship between these examinations and outcomes of care is desirable for a process seeking to provide patients with safe and effective health care. METHOD: This was a retrospective cohort study of 196,881 hospitalizations in Pennsylvania over a 3-year period (January 1, 2017 to December 31, 2019) for 5 primary diagnoses: heart failure, acute myocardial infarction, stroke, pneumonia, or chronic obstructive pulmonary disease. The 1,765 attending physicians for these hospitalizations self-identified as family physicians or general internists. A converted score based on USMLE Step 1, Step 2 Clinical Knowledge, and Step 3 scores was available, and the outcome measures were in-hospital mortality and log length of stay (LOS). The research team controlled for characteristics of patients, hospitals, and physicians. RESULTS: For in-hospital mortality, the adjusted odds ratio was 0.94 (95% confidence interval [CI] = 0.90, 0.99; P < .02). Each standard deviation increase in the converted score was associated with a 5.51% reduction in the odds of in-hospital mortality. For log LOS, the adjusted estimate was 0.99 (95% CI = 0.98, 0.99; P < .001). Each standard deviation increase in the converted score was associated with a 1.34% reduction in log LOS. CONCLUSIONS: Better provider USMLE performance was associated with lower in-hospital mortality and shorter log LOS for patients, although the magnitude of the latter is unlikely to be of practical significance. These findings add to the body of evidence that examines the validity of the USMLE licensure program.

Using inpatient hospital discharge data to monitor patient safety events.

The development of systematic and sustainable surveillance systems is necessary for the creation of patient safety prevention programs and the evaluation of improvement resulting from innovations. To that end, inpatient hospital discharges collected by the Pennsylvania Health Care Cost Containment Council were used to investigate patient safety events (PSEs) in Pennsylvania in 2006. PSEs were identified using external cause of injury codes (E-codes) in combination with the Agency for Healthcare Research and Quality's patient safety indicators (PSIs). Encounters with and without PSEs were compared with regard to patient age, sex, race, length of stay, and cost. Approximately 9% of all Pennsylvania inpatient discharges had a PSE in 2006. Patients with a PSE were on average older, male, and white. The average length of stay for a PSE was 3 days longer and $35 000 more expensive than a non-PSE encounter. It was concluded that E-codes and PSIs were useful tools for the surveillance of PSEs in Pennsylvania, and that administrative data from healthcare organizations provide a consistent source of standardized data related to patient encounters, creating an opportunity to describe PSEs at the population level.

What U.S. data should be used to measure the price elasticity of demand for alcohol?

This paper examines how estimates of the price elasticity of demand for beer vary with the choice of alcohol price series examined. Our most important finding is that the commonly used ACCRA price data are unlikely to reliably indicate alcohol demand elasticities-estimates obtained from this source vary drastically and unpredictably. As an alternative, researchers often use beer taxes to proxy for alcohol prices. While the estimated beer taxes elasticities are more stable, there are several problems with using taxes, including difficulties in accounting for cross-price effects. We believe that the most useful estimates reported in this paper are obtained using annual Uniform Product Code (UPC) "barcode" scanner data on grocery store alcohol prices. These estimates suggest relatively low demand elasticity, probably around -0.3, with evidence that the elasticities are considerably overstated in models that control for beer but not wine or spirits prices.