RESUMEN
OBJECTIVE: To determine the surveillance impact of utilizing a discrete field in structured radiology reports in patients with incidental pancreatic findings. METHODS: We implemented a dictation template containing a discrete structured field element to auto-trigger listing of patients with incidental pancreatic findings on a pancreas clinic registry in the electronic health record. We isolated CT and MRI reports with incidental pancreatic findings over a 24-month period. We stratified patients by presence or absence of the discrete field element in reports (flagged versus unflagged) and evaluated the impact of report flagging on likelihood of clinic follow-up, follow-up imaging, endoscopic ultrasound, surgical intervention, genetics referral, obtaining pathologic diagnosis, and time interval between index imaging to various outcomes. RESULTS: Patients with flagged reports were more likely to be seen or discussed in a pancreas clinic compared with those with unflagged reports (189 of 376, 50.3% versus 79 of 474, 16.7%; P <. 001). Patients with flagged reports were more likely to get follow-up imaging than patients with unflagged reports (188 of 376, 50.0% versus 121 of 474, 25.5%; P < .001) and were more likely to undergo appropriate management of actionable findings compared with patients in the unflagged group (23 of 62, 37.1% versus 28 of 129, 21.7%; P = .036). DISCUSSION: Implementation of a structured discrete field element for reporting of patients with incidental pancreatic findings had positive impact on surveillance measures and can be applied in other organ systems with established surveillance guidelines to standardize patient care.
Asunto(s)
Hallazgos Incidentales , Tomografía Computarizada por Rayos X , Humanos , Imagen por Resonancia Magnética , Páncreas/diagnóstico por imagen , Estudios Retrospectivos , UltrasonografíaRESUMEN
PURPOSE: To provide evidence that medical education is associated with population health in order to support adaptation of medical school programs to address populations with health disparities. We explored medical education efforts, local physician supply, and life expectancy in Alabama. METHODS: County-level public data of the number of students accepted to medical schools in 2008 and 2011, primary care physicians, life expectancy, and demographic/contextual variables were analyzed to develop a model for hypothesized associations. Correlational analysis, ANCOVA modeling, and path analysis were employed to identify, reduce, and organize significant variables in this cross-sectional ecologic study. FINDINGS: The path model, which met criteria for goodness of fit, found significant relationships among medical students per 10,000 population, primary care physicians per 10,000 population, life expectancy, and contextual variables for rurality and poverty. ANCOVA models showed that geographic region was significant. CONCLUSIONS: Within limitations of the study design, these findings support the proposition that the number of medical students produced in a county is related to the number of primary care physicians, which is related to life expectancy. Recommendations are to confirm the findings in other populations and inform public health policy concerning the utility of medical education to address population health by producing local medical students.