Statistical Applications in Population, Health and Geography: At Home in the Twilight Zone

This dissertation presents four distinct applications in Population and Health Geography. While varied, in each of these applications I center geographic constructs (space, time, exposure and scale), and implement a specific study design (often with novel methods and/or measures) to elucidate these themes in context. In particular, I trace the challenges of measuring exposure, effects, and uncertainty through each application. In the first application I use historical wildfire evacuation zones to identify wildfire exposed populations and investigate the relationship between wildfire exposure and cardiovascular events. For the second application, I describe and test a new time use data collection method in the context of existing tools and simulation models. In the third application I introduce a statistical model into wildfire vulnerability index construction and discuss implications for spatial variability. For the final application I construct a novel indirect measure of school climate and combine multiple data sources to explore mental health variation across school districts in New York City. Together these applications demonstrate the natural partnership of Geography and Statistics in social science

Culture: The Unexpected Key to Exemplary Primary Care

Health care organizations achieve better outcomes at lower cost where known advances in primary care have been implemented. With few exceptions, primary care in the US has been unsuccessful inimplementing these advances. We conducted eight case studies of exemplar primary care organizations to theorize best systems design in adverse conditions; we offer a cross-case analysis. Every study site had culture characterized by 1) trusting, long-term relationships; and 2) power, responsibility, and authority redistribution. Organizational culture may drive exemplary primary care; building cultures with identified traits may improve primary care outcomes and is actionable

How does work environment relate to diagnostic quality? A prospective, mixed methods study in primary care

Objectives The quest to measure and improve diagnosis has proven challenging; new approaches are needed to better understand and measure key elements of the diagnostic process in clinical encounters. The aim of this study was to develop a tool assessing key elements of the diagnostic assessment process and apply it to a series of diagnostic encounters examining clinical notes and encounters’ recorded transcripts. Additionally, we aimed to correlate and contextualise these findings with measures of encounter time and physician burnout.Design We audio-recorded encounters, reviewed their transcripts and associated them with their clinical notes and findings were correlated with concurrent Mini Z Worklife measures and physician burnout.Setting Three primary urgent-care settings.Participants We conducted in-depth evaluations of 28 clinical encounters delivered by seven physicians.Results Comparing encounter transcripts with clinical notes, in 24 of 28 (86%) there was high note/transcript concordance for the diagnostic elements on our tool. Reliably included elements were red flags (92% of notes/encounters), aetiologies (88%), likelihood/uncertainties (71%) and follow-up contingencies (71%), whereas psychosocial/contextual information (35%) and mentioning common pitfalls (7%) were often missing. In 22% of encounters, follow-up contingencies were in the note, but absent from the recorded encounter. There was a trend for higher burnout scores being associated with physicians less likely to address key diagnosis items, such as psychosocial history/context.Conclusions A new tool shows promise as a means of assessing key elements of diagnostic quality in clinical encounters. Work conditions and physician reactions appear to correlate with diagnostic behaviours. Future research should continue to assess relationships between time pressure and diagnostic quality