Reducing Patient Care Delays in Radiation Oncology Via Optimization of Insurance Pre-Authorization: Reducing Delays via Optimization of Pre-Auth

Maxwell Tran; Bhisham Chera; Kevin Shrake; Bradley Depaoli; Edward Duffy Iii; 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 Pre-Authorization: Reducing Delays via Optimization of Pre-Auth

Pract Radiat Oncol. 2024 Oct 25:S1879-8500(24)00283-2. doi: 10.1016/j.prro.2024.10.002. Online ahead of print.

Affiliations

¹ Medical University of South Carolina, Department of Radiation Oncology, Charleston, SC.
² Medical University of South Carolina, Department of Radiation Oncology, Charleston, SC. Electronic address: cherabs@musc.edu.
³ Medical University of South Carolina, Charleston, SC.
⁴ Roper St. Francis Cancer Center, Department of Radiation Oncology, Charleston, SC.
⁵ Alabama Cancer Care, Radiation Oncology, Fort Payne, AL.

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

Abstract

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

Materials/methods: We performed a root cause analysis for pre-auth delays, and used the PDSA & A3 quality improvement methods. We sampled ∼2 cases per disease site (19 cases from July - Aug 2022) to determine the baseline. Countermeasures included: 1) optimizing our CTP templates per disease site to contain the specific clinical information required for pre-auth, 2) formalizing earlier completion of CTPs in our Care Path®, and 3) formalizing the pre auth workflow in our Care Path®. We tracked various metrics, including mean time for CTP completion, % usage of our Care Path®, % usage of revised CTP templates, mean time until pre-auth initiated & completed, and % of cases delayed/denied. Two-tailed T-tests and Chi-squared tests were used to generate p-values comparing mean values and percentages, respectively.

Results: 495 patients completed CT simulation in our department between October 2022 and February 2023. Mean time for CTP completion (Day 0 = day of CT simulation scheduling) improved from 16 days at baseline to 4 days (p<0.001). Care Path® usage improved from 16% to 97% (p<0.001), as did usage of our revised CTP templates, from 0% to 97% (p<0.001). The mean time from insurance pre-auth initiation to completion improved from 5 days to 1 day. The percent of cases that were delayed/denied was reduced significantly from 32% to 8% (p<0.001).

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