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Identifying Complex Scheduling Patterns Amongst Cancer Patients with Transportation and Housing Needs
ABSTRACT
Background:
Cancer patients frequently encounter complex treatment pathways, often characterized by challenges with coordinating and scheduling appointments at various specialty services and locations. Identifying patients who might benefit from scheduling and social support from community health workers (CHW) or patient navigators is largely determined on a case-by-case basis and is resource intensive.
Objective:
Our study proposes a novel algorithm to use scheduling data to identify complex scheduling patterns amongst patients with transportation and housing needs.
Methods:
We present a novel algorithm to calculate scheduling complexity from patient scheduling data. We define patient scheduling complexity as an aggregation of sequence, resolution, and facility components. We apply the scheduling complexity algorithm to 38 breast cancer patients’ scheduling data and compare this metric with common count-based metrics.
Results:
Five patients exhibited high scheduling complexity with low count-based adjustments. Two patients exhibited high count-based adjustments with low scheduling complexity. Of the 15 patients that indicated transportation or housing insecurity issues in conversations with CHWs, 86.7% (13 of 15) patients were identified as medium or high scheduling complexity while 60% (9 of 15) were identified as medium or high count-based adjustments.
Conclusions:
Scheduling complexity identifies patients with complex, but non-chronical scheduling behaviors who would be missed by traditional count-based metrics. This study shows a potential link between transportation and housing needs with schedule complexity. Scheduling complexity can complement count-based metrics when identifying patients who might need additional care coordination support especially as it relates to transportation and housing needs. Clinical Trial: NA
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.