The Patient Experience of Prior Authorization for Cancer Care

Chino, Fumiko; Baez, Alexandra; Elkins, Ivy B.; Aviki, Emeline M.; Ghazal, Lauren V.; Thom, Bridgette

doi:10.1001/jamanetworkopen.2023.38182

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…Studies in other cancers have similarly found low correspondence between FDA approvals and patient receipt of medication and high approval rates after prior authorization ( Dickens and Pollock, 2017 , Tran et al, 2019 ) Yet each prior authorization request adds 30–60 min on average to clinical staff workload ( Dickens and Pollock, 2017 , Niccolai et al, 2017 ). A 10-day delay from PARP inhibitor prescription to patient receipt after prior authorization may not have a clinical impact on cancer recurrence, but it creates anxiety and work for patients and clinicians ( Chino et al, 2023 ). Early prescription of PARP inhibitor, such as with cycle 5–6 of chemotherapy, may reduce time from chemotherapy end to PARP inhibitor start.…”

Section: Discussionmentioning

confidence: 99%

Prior authorization for FDA-approved PARP inhibitors in ovarian cancer

Smith,

Apple,

Hugo

et al. 2024

Gynecologic Oncology Reports

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Section: Discussionmentioning

confidence: 99%

Prior authorization for FDA-approved PARP inhibitors in ovarian cancer

Smith,

Apple,

Hugo

et al. 2024

Gynecologic Oncology Reports

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“…[44][45][46] National estimates of the time spent receiving health care are highest among adults newly diagnosed with cancer, although time spent related to health care remains elevated throughout survivorship. 45,46 Emerging research suggests that patients spend significant time with administrative tasks related to their health care, including addressing issues with health insurance coverage (e.g., prior authorizations for treatment) 47 and contesting medical bills, 48 which also must often take place during work hours. Time spent receiving health care has long been recognized as having an economic cost (i.e., patient time costs); more recently, this concept has been denoted as time toxicity to reflect the time burden of intensive care.…”

Section: Is Paid Sick Leave Sufficient For the Amount Of Time Require...mentioning

confidence: 99%

Cancer diagnosis and treatment in working‐age adults: Implications for employment, health insurance coverage, and financial hardship in the United States

Yabroff,

Doran,

Zhao

et al. 2024

CA A Cancer J Clinicians

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The rising costs of cancer care and subsequent medical financial hardship for cancer survivors and families are well documented in the United States. Less attention has been paid to employment disruptions and loss of household income after a cancer diagnosis and during treatment, potentially resulting in lasting financial hardship, particularly for working‐age adults not yet age‐eligible for Medicare coverage and their families. In this article, the authors use a composite patient case to illustrate the adverse consequences of cancer diagnosis and treatment for employment, health insurance coverage, household income, and other aspects of financial hardship. They summarize existing research and provide nationally representative estimates of multiple aspects of financial hardship and health insurance coverage, benefit design, and employee benefits, such as paid sick leave, among working‐age adults with a history of cancer and compare them with estimates among working‐age adults without a history of cancer from the most recently available years of the National Health Interview Survey (2019–2021). Then, the authors identify opportunities for addressing employment and health insurance coverage challenges at multiple levels, including federal, state, and local policies; employers; cancer care delivery organizations; and nonprofit organizations. These efforts, when informed by research to identify best practices, can potentially help mitigate the financial hardship associated with cancer.

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“…14,15 In a cross-sectional survey, 22% of cancer patients reported that they did not receive care as originally recommended by their oncologists. 16 At 97% of services, radiation oncology has been reported to be the medical specialty with the highest proportion of services for which insurers require authorization prior to treatment. 2 One academic radiation oncology practice estimated its annual prior authorization-related cost burden to be nearly $500,000.…”

Section: Introductionmentioning

confidence: 99%

Large language models to help appeal denied radiotherapy services

Kiser,

Waters,

Reckford

et al. 2024

Preprint

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Background Large language model (LLM) artificial intelligences have potential to perform myriad healthcare tasks but should be validated in specific clinical use cases before deployment. One use case is to help physicians appeal insurer denials of prescribed medical services, a task that delays patient care and contributes to burnout. We evaluated LLM performance at this task for denials of radiotherapy services. Methods We evaluated generative pre-trained transformer 3.5 (GPT-3.5) (OpenAI, San Francisco, CA), GPT-4, GPT-4 with internet search functionality (GPT-4web), and GPT-3.5ft. The latter was developed by fine-tuning GPT-3.5 via an OpenAI application programming interface with 53 examples of appeal letters written by radiation oncologists. Twenty test prompts with simulated patient histories were programmatically presented to the LLMs, and output appeal letters were scored by three blinded radiation oncologists for language representation, clinical detail inclusion, clinical reasoning validity, literature citations, and overall readiness for insurer submission. Results Interobserver agreement between radiation oncologists' scores was moderate or better for all domains (Cohen's kappa coefficients: 0.41 - 0.91). GPT-3.5, GPT-4, and GPT-4web wrote letters that were on average linguistically clear, summarized provided clinical histories without confabulation, reasoned appropriately, and were scored useful to expedite the insurance appeal process. GPT-4 and GPT-4web letters demonstrated superior clinical reasoning and were readier for submission than GPT-3.5 letters (p < 0.001). Fine-tuning increased GPT-3.5ft confabulation and compromised performance compared to other LLMs across all domains (p < 0.001). All LLMs, including GPT-4web, were poor at supporting clinical assertions with existing, relevant, and appropriately cited primary literature. Conclusions When prompted appropriately, three commercially available LLMs drafted letters that physicians deemed would expedite appealing insurer denials of radiotherapy services. LLMs may decrease this task's clerical workload on providers. However, LLM performance worsened when fine-tuned with a task-specific, small training dataset.

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The Patient Experience of Prior Authorization for Cancer Care

Cited by 3 publications

References 23 publications

Prior authorization for FDA-approved PARP inhibitors in ovarian cancer

Prior authorization for FDA-approved PARP inhibitors in ovarian cancer

Cancer diagnosis and treatment in working‐age adults: Implications for employment, health insurance coverage, and financial hardship in the United States

Large language models to help appeal denied radiotherapy services

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