Reducing Patient Care Delays in Radiation Oncology Via Optimization of Insurance Preauthorization

Maxwell Tran; Bhisham Chera; Kevin Shrake; Bradley Depaoli; Edward Duffy 3rd; Michael Hall; Justin Steinman; Stephanie Myers; Osagie Igiebor; Jay Callahan; Daniel McDonald; Jennifer Harper; Samuel Lewis Cooper

doi:10.1016/j.prro.2024.10.002

Reducing Patient Care Delays in Radiation Oncology Via Optimization of Insurance Preauthorization

Pract Radiat Oncol. 2024 Oct 26:S1879-8500(24)00283-2. doi: 10.1016/j.prro.2024.10.002. Online ahead of print.

Affiliations

¹ Department of Radiation Oncology, Medical University of South Carolina, Charleston, South Carolina.
² Department of Radiation Oncology, Medical University of South Carolina, Charleston, South Carolina. Electronic address: [email protected].
³ Department of Radiation Oncology, Roper St. Francis Cancer Center, Charleston, South Carolina.
⁴ Radiation Oncology, Alabama Cancer Care, Fort Payne, Alabama.

PMID: 39490921
DOI: 10.1016/j.prro.2024.10.002

Abstract

Purpose: Difficulties and delays in insurance preauthorization (preauth) can negatively impact patient care, resulting in postponing, modifying, or even canceling radiation therapy for patients. We aimed to perform a root cause analysis for preauth delays in our department and implement solutions to optimize our workflow. Our primary objectives were to decrease the mean time for clinical treatment plan (CTP) completion and the number of cases delayed/denied by 50% each.

Methods and materials: We performed a root cause analysis for preauth delays and used the Plan, Do, Study, Act, and A3 quality improvement methods. We sampled ∼2 cases per disease site (19 cases from July to August 2022) to determine the baseline. Countermeasures included (1) optimizing our CTP templates per disease site to contain the specific clinical information required for preauth, (2) formalizing earlier completion of CTPs in our Care Path, and (3) formalizing the preauth workflow in our Care Path. We tracked various metrics, including the mean time for CTP completion, the percentage usage of our Care Path, the percentage usage of revised CTP templates, the mean time until preauth was initiated and completed, and the percentage of cases delayed/denied. Two-tailed t tests and χ² tests were used to generate P values comparing mean values and percentages, respectively.

Results: A total of 495 patients completed computed tomography simulation in our department between October 2022 and February 2023. The mean time for CTP completion (day 0 = day of computed tomography simulation scheduling) improved from 16 days at baseline to 4 days (P < .001). Care Path usage improved from 16% to 97% (P < .001), as did the usage of our revised CTP templates, from 0% to 97% (P < .001). The mean time from insurance preauth initiation to completion improved from 5 days to 1 day. The percentage of cases that were delayed/denied was reduced significantly from 32% to 8% (P < .001).

Conclusions: Improving timeliness and details of CTP documentation and preauth by using our Care Path and optimizing CTP templates improved the efficiency of insurance preauth completion and reduced the number of cases delayed/denied.