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BACKGROUND Electronic health records (EHR) have become commonplace in medicine. A disconnect between developers and users while creating the interface often fails to create a product that captures clinical workflow, and issues become apparent with implementation. Optimization allows collaboration of clinicians and informaticists after implementation, but documentation of success has only been at the institutional level. METHODS A 4-month, department-wide EHR optimization was conducted with information technology (IT). Optimizations were developed from an intensive quality improvement process involving all levels of clinicians and clinical staff. The optimizations were then categorized as accommodations (department adjusted workflow to EHR), creations (IT developed new workflows within EHR), discoveries (department found workflows within EHR), and modifications (IT changed workflows within EHR). Departmental productivity, defined as number of visits, charges, and payments, was standardized to ratios prior to the COVID-19 pandemic and evaluated by Taylor’s change point analysis. Significant improvements were defined as shifts (change points), trends (5 or more consecutive values above/below the mean), and values outside 95% CIs. RESULTS The 124 optimizations were categorized as 43 accommodations, 13 creations, 54 discoveries, and 14 modifications. Productivity ratios of monthly charges (0.74 to 1.28) and payments (0.83 to 1.58) significantly improved with the optimization efforts. Monthly visit ratios increased (0.65 to 0.98) but did not change significantly. CONCLUSION Departmental collaboration with organizational IT for EHR optimization focused on detailed analysis of how workflows can impact productivity. Discovery optimization predominance indicates many solutions to EHR usability problems were already in the system. A large proportion of accommodation optimizations reinforced the need for better developer-user collaboration before implementation. [ABSTRACT FROM AUTHOR]

Objective: To determine factors indicating testing frequency and positive test results in a Division I sports department intrapandemic. Design: Retrospective analysis. Setting: A single Division I collegiate sports department. Patients: All studentathlete (n = 437), student staff (n = 89), and adult staff (n = 202) members of the sports department. Total cohort (n = 728). Interventions: The authors analyzed the independent variables of local positive rates, sport characteristics, and campus events for impact on the volume of the departmental testing and positive rates. Main Outcome Measures: Measured dependent variables of the volume of departmental testing and positive rates were analyzed. Results: Positive predictive rates (PPRs) largely differed from local, off-campus rates in timing and duration (59.52%: P < 0.05). Overall, 20633 tests were administered with 201 positive results (0.97% PPR). Student-athlete numbers were highest in all categories, followed by adult then student staff. Greater proportions of contact sports became positive (53.03%: P < 0.001) and all-male sports (47.69%: P < 0.001). No comparative difference was seen for teams using fomites (19.15%: P = 0.403). Spring sports teams had the lowest percentage of the team positive (22.22%: P < 0.001). Winter sports had the highest PPR (1.15%), all occurring during team-controlled activities. Playing sports indoors did not increase inside team-controlled activity positive rates (P = 0.066). Conclusions: Longitudinal changes in local, off-campus infection rates partially affected sports departmental positive results while testing rates were more influenced by sport and university schedule. Testing resources should be directed toward high-risk sports, which included contact sports (football, basketball, and soccer), all-male teams, both Winter and indoor sports inside team-controlled activities, and sports with long periods of time outside team-controlled activities. [ABSTRACT FROM AUTHOR]