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Provider Scheduling to Maximize Patient Access. | LitMetric

AI Article Synopsis

Article Abstract

Introduction: We describe and demonstrate an efficient method for assigning clinic days to urology providers in academic and large urology group practices given their numerous scheduling constraints including evaluation and management visits, office or operating room procedures/surgeries, teaching, trainee mentorship, committee work and outreach activities.

Methods: We propose an integer programming model for scheduling providers for clinic shifts in order to maximize patient access to appointments considering the aforementioned scheduling constraints. We present results for a case study with an academic urology clinic and lessons learned from implementing the model generated schedule.

Results: The integer programming model produced a feasible schedule that was implemented after pairwise and 3-way switches among attending providers to account for preferences. The optimized schedule had reduced variability in the number of providers scheduled per shift (standard deviation 1.409 vs 0.999, p=0.01). While other confounding factors are possible we noted a significant increase in the number of encounters after implementing changes from the model (1,370 vs 1,196 encounters, p=0.011).

Conclusions: Optimization models offer an efficient and transferable method of generating a clinic template for providers that takes into account other clinical and academic responsibilities, and can increase the number of appointments for patients. Optimization of schedules may be performed periodically to address changes in providers or provider constraints.

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Source
http://dx.doi.org/10.1097/UPJ.0000000000000115DOI Listing

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