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Abel N. Kho

Publications and source records attributed to Abel N. Kho.

2 recordsLinked to original sources

Identifying heat-related diagnoses in emergency department visits among adults in Chicago: a heat-wide association study

Extreme heat is an escalating public health concern. Although prior studies have examined heat-health associations, their reliance on restricted diagnoses and diagnostic categories misses or misclassifies heat-related illness. We conducted a heat-wide association study to identify acute-care diagnoses associated with extreme heat in Chicago, Illinois. Using 916,904 acute-care visits -- including emergency department and urgent care encounters -- among 372,140 adults across five healthcare systems from 2011-2023, we applied a two-stage analytic approach: quasi-Poisson regression to screen 1,803 diagnosis codes for heat-related risks, followed by distributed lag non-linear models in a time-stratified case-crossover design to refine the list of heat-related diagnoses and estimate same-day and short-term cumulative odds ratios of acute-care visits during extreme heat versus reference temperature. We observed same-day increases in visits for heat illness, volume depletion, hypotension, edema, acute kidney failure, and multiple injuries. By analyzing the full diagnostic spectrum of acute-care services, this study comprehensively characterizes heat-associated morbidity, reinforcing and advancing existing literature.

stat.AP↗

Learning Bundled Care Opportunities from Electronic Medical Records

Objectives: The fee-for-service approach to healthcare leads to the management of a patient's conditions in an independent manner, inducing various negative consequences. It is recognized that a bundled care approach to healthcare-one that manages a collection of health conditions together-may enable greater efficacy and cost savings. However, it is not always evident which sets of conditions should be managed in a bundled program. Study Design: Retrospective inference of clusters of health conditions from an electronic medical record (EMR) system. A survey of healthcare experts to ascertain the plausibility of the clusters for bundled care programs. Methods: We designed a data-driven framework to infer clusters of health conditions via their shared clinical workflows according to EMR utilization by healthcare employees. We evaluated the framework with approximately 16,500 inpatient stays from a large medical center. The plausibility of the clusters for bundled care was assessed through a survey of a panel of healthcare experts using an analysis of variance (ANOVA) under a 95% confidence interval. Results: The framework inferred four condition clusters: 1) fetal abnormalities, 2) late pregnancies, 3) prostate problems, and 4) chronic diseases (with congestive heart failure featuring prominently). Each cluster was deemed plausible by the experts for bundled care. Conclusions: The findings suggest that data from EMRs may provide a basis for discovering new directions in bundled care. Still, translating such findings into actual care management will require further refinement, implementation, and evaluation.

cs.CY↗