Strategic Operational Redesign for Successfully Navigating Prior Authorization Barriers at a Large-Volume Proton Therapy Center

Bringing proton therapy to India: The recent article from Gupta et al. on revolutionizing cancer treatment in India

Gupta et al. have outlined a rational approach for bringing the promising emerging technology of proton therapy to India. Their roadmap is based on consensus‐driven prioritization systems (American Society for Radiation Oncology guidelines), careful assessment of population needs, and careful consideration of economics.

The Impact of Pandemic-Driven Care Redesign on Hospital Efficiency

Purpose

This study aims to identify medical care transformations during the COVID-19 pandemic and to assess the economic efficiency of these care transformations.

Methods

A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviewing and Meta-Analysis (PRISMA) guidelines. The databases used in the search protocol included PubMed, RSCI, and Google Scholar.

Results

Ten eligible studies in English and one publication in Russian were identified. In general, the following changes in organization of health care processes since 2020 are observed: hospital at home, telemedicine (physician-to-patient), and the adoption of new information communication technologies within physician-to-physician and physician-to-nurse communication. Earlier trends, such as (a) wider use of electronic devices, (b) adoption of Lean techniques, (c) the incorporation of patient and other customer experience feedback, and (d) the implementation of clinical decision support systems and automation of workflow, tend to be preserved.

Conclusion

The most common changes in hospital care organization and the respective impacts of workflow changes (ie, workflow interventions, redesign, and transformations) on the efficiency of hospital care were summarized and avenues for future research and policy implications were discussed. The pandemic demonstrated a need for building more resilient and adaptive healthcare systems, enhancing crisis preparedness along with rapid and effective responses.

The impact of prior authorization review on orthopaedic subspecialty care: a prospective multicenter analysis

BACKGROUND

Prior authorization review (PAR), in the United States, is a process that was initially intended to focus on hospital admissions and costly high-acuity care. Over time, payors have broadened the scope of PAR to include imaging studies, prescriptions, and routine treatment. The potential detrimental effect of PAR on health care has recently been brought into the limelight, but its impact on orthopedic subspecialty care remains unclear. This study investigated the denial rate, the duration of care delay, and the administrative burden of PAR on orthopedic subspecialty care.

METHODS

A prospective, multicenter study was performed analyzing the PAR process. Orthopedic shoulder and/or sports subspecialty practices from 6 states monitored payor-mandated PAR during the course of providing routine patient care. The insurance carrier (traditional Medicare, managed Medicare, Medicaid, commercial, worker's compensation, or government payor [ie, Tricare, Veterans Affairs]), location of service, rate of approval or denial, time to approval or denial, and administrative time required to complete process were all recorded and evaluated.

RESULTS

Of 1065 total PAR requests, we found a 1.5% (16/1065) overall denial rate for advanced imaging or surgery when recommended by an orthopedic subspecialist. Commercial and Medicaid insurance resulted in a small but statistically significantly higher rate of denial compared to traditional Medicare, managed Medicare, worker's compensation, or governmental insurance (P < .001). The average administrative time spent on a single PAR was 19.5 minutes, and patients waited an average of 2.2 days to receive initial approval. Managed Medicare, commercial insurance, worker's compensation, and Medicaid required approximately 3-4 times more administrative time to process a PAR than to traditional Medicare or other governmental insurance (P < .001). After controlling for the payor, we identified a significant difference in approval or denial based on geographic location (P < .001). An appeal resulted in a relatively low rate of subsequent denial (20%). However, approximately a third of all appeals remained in limbo for 30 days or more after the initial request.

CONCLUSIONS

This is the largest prospective analysis to date of the impact of PAR on orthopedic subspecialty care in the United States. Nearly all PAR requests are eventually approved when recommended by orthopedic subspecialists, despite requiring significant resource use and delaying care. Current PAR practices constitute an unnecessary process that increases administrative burden and negatively impacts access to orthopedic subspecialty care. As health care shifts to value-based care, PAR should be called into question, as it does not seem to add value but potentially negatively impacts cost and timeliness of care.

Improvements for the Prior Authorization Process for Elective Surgical Procedures at an Academic Medical Center

Prior authorization is an approval process to ensure that services provided by healthcare organizations will be reimbursed by insurance carriers. Prior authorization denials can result in revenue loss. Due to multiple prior authorization issues, over $21 million in charges was denied, and $291,217.63 was ultimately written off as uncollectible in a one-year period at the Department of Surgery at Hospital X. This paper aimed to design an improved process to reduce, or eliminate, the issues causing charges to be written off. Three divisions with the most prior authorization denials within the department were identified. A comprehensive review of the current prior authorization process was conducted. Each division was found to have a unique prior authorization issue that was causing charges to be written off. Barriers were identified, educational training was provided accordingly, and process changes were implemented thereafter. When comparing the results pre- and post-interventions, these interventions resulted in these charges no longer being denied or written off. The processes utilized here can be easily replicated for organizations with similar barriers.

Insurance Approval for Definitive Proton Therapy for Prostate Cancer

Purpose

To determine factors that influence insurance approval for definitive proton therapy (PT) for prostate cancer.

Materials and Methods

Between 2014 and 2018, 1592 insured patients with localized prostate cancer were evaluated and recommended to undergo definitive PT; 547 patients (34.4%) had commercial insurance, whereas 1045 patients (65.6%) had Medicare/Medicaid. Of those with Medicare, 164 patients (15.7%) had Medicare alone; 677 (64.8%) had supplemental plans; and 204 (19.5%) had secondary commercial insurance. Insurance that “covered” PT for prostate cancer implied that it was an indication designated in the coverage policy. “Not covered” means that the insurance policy did not list prostate cancer as an indication for PT. Of all 1592 patients, 1263 (79.3%) belonged to plans that covered PT per policy. However, approval for PT was still required via medical review for 619 patients (38.9%), comparative dosimetry for 56 patients (3.5%), peer-to-peer discussion for 234 patients (14.7%), and administrative law judge hearings for 3 patients (<0.1%). Multivariate analyses of factors affecting approval were conducted, including risk group (low/intermediate versus high), insurance type (commercial versus Medicare/Medicaid), whether PT was included as a covered benefit under the plan (covered versus not covered), and time period (2014-16 versus 2017 versus 2018).

Results

On multivariate analysis, factors affecting PT approval for prostate treatment included coverage of PT per policy (97.1% had approval with insurance that covered PT versus 48.6% whose insurance did not cover PT; P < .001); insurance type (32.5% had approval with commercial insurance versus 97.4% with Medicare; P < .001); and time, with 877/987 patients (88.9%) approved between 2014 and 2016, 255/312 patients (81.7%) approved during 2017, and 255/293 patients (87.0%) approved thereafter (P = .02). Clinical factors, including risk group, had no bearing on insurance approval (P = .44).

Conclusion

Proton insurance approval for prostate cancer has decreased, is most influenced by the type of insurance a patient belongs to, and is unrelated to clinical factors (risk group) in this study. More work is needed to help navigate appropriate access to care and to assist patients seeking definitive PT for prostate cancer treatment.

Cost-Effectiveness Models of Proton Therapy for Head and Neck: Evaluating Quality and Methods to Date

PURPOSE

Proton beam therapy (PBT) is associated with less toxicity relative to conventional photon radiotherapy for head-and-neck cancer (HNC). Upfront delivery costs are greater, but PBT can provide superior long-term value by minimizing treatment-related complications. Cost-effectiveness models (CEMs) estimate the relative value of novel technologies (such as PBT) as compared with the established standard of care. However, the uncertainties of CEMs can limit interpretation and applicability. This review serves to (1) assess the methodology and quality of pertinent CEMs in the existing literature, (2) evaluate their suitability for guiding clinical and economic strategies, and (3) discuss areas for improvement among future analyses.

MATERIALS AND METHODS

PubMed was queried for CEMs specific to PBT for HNC. General characteristics, modeling information, and methodological approaches were extracted for each identified study. Reporting quality was assessed via the Consolidated Health Economic Evaluation Reporting Standards 24-item checklist, whereas methodologic quality was evaluated via the Philips checklist. The Cooper evidence hierarchy scale was employed to analyze parameter inputs referenced within each model.

RESULTS

At the time of study, only 4 formal CEMs specific to PBT for HNC had been published (2005, 2013, 2018, 2020). The parameter inputs among these various Markov cohort models generally referenced older literature, excluding many clinically relevant complications and applying numerous hypothetical assumptions for toxicity states, incorporating inputs from theoretical complication-probability models because of limited availability of direct clinical evidence. Case numbers among study cohorts were low, and the structural design of some models inadequately reflected the natural history of HNC. Furthermore, cost inputs were incomplete and referenced historic figures.

CONCLUSION

Contemporary CEMs are needed to incorporate modern estimates for toxicity risks and costs associated with PBT delivery, to provide a more accurate estimate of value, and to improve their clinical applicability with respect to PBT for HNC.