Key Takeaways
- 56% of physicians reported prior authorization as a barrier to care in the U.S. 2019–2020 physician survey period
- 88% of physicians reported prior authorization requirements increase administrative burden
- 49% of physicians reported they regularly experience delays due to prior authorization
- 2021 average time-to-prior-authorization decision for commercial plans was 10.7 business days reported in a 2022 analysis
- 2021 44% of prior authorization decisions for drugs were completed within required plan timeframes in a 2022 measurement study
- 2021 26% of prior authorization decisions for medical services were completed within required plan timeframes in the same measurement study
- A 2014 study found prior authorization contributed to 5.5% of all physician office overhead related to administrative tasks in the U.S.
- A 2020 study estimated that clinicians spend 1.3 billion hours per year on paperwork-related administrative activities, with prior authorization among key drivers
- 6% of total health care spending growth was attributable to administrative costs, with prior authorization contributing to administrative burden in one econometric analysis
- In a 2020 survey, 69% of patients reported they experienced delays due to prior authorization
- There were 21,000+ prior authorization requests per 1,000 covered lives reported in a claims utilization dataset analysis (2019)
- A 2021 report estimated that prior authorization programs impacted an estimated 100 million covered lives in the U.S.
- The prior authorization market for software and services reached $1.6 billion in 2023 globally (estimate) in a market research report
- The prior authorization software market forecasted a CAGR of 12.4% from 2024 to 2030 (estimate) in a market research report
- $0.8 billion was the U.S. spend attributed to utilization management technology software components in 2022 (estimate) in a vendor analysis
Prior authorization delays and paperwork burden doctors and patients alike, with many decisions requiring extra documentation.
Industry Trends
Industry Trends Interpretation
Performance Metrics
Performance Metrics Interpretation
Cost Analysis
Cost Analysis Interpretation
User Adoption
User Adoption Interpretation
Market Size
Market Size Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Margot Villeneuve. (2026, February 13). Prior Authorization Statistics. Gitnux. https://gitnux.org/prior-authorization-statistics
Margot Villeneuve. "Prior Authorization Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/prior-authorization-statistics.
Margot Villeneuve. 2026. "Prior Authorization Statistics." Gitnux. https://gitnux.org/prior-authorization-statistics.
References
- 1ama-assn.org/system/files/2022-02/2019-Physician-Prior-Authorization-Survey.pdf
- 13ama-assn.org/system/files/2022-08/prior-authorization-impact-practices.pdf
- 2jamanetwork.com/journals/jamainternalmedicine/fullarticle/2736178
- 5jamanetwork.com/journals/jama-health-forum/fullarticle/2781836
- 6jamanetwork.com/journals/jama/fullarticle/2703842
- 15jamanetwork.com/journals/jamanetworkopen/fullarticle/2807072
- 16jamanetwork.com/journals/jama/fullarticle/2778335
- 30jamanetwork.com/journals/jamanetworkopen/fullarticle/2784891
- 31jamanetwork.com/journals/jamainternalmedicine/fullarticle/2529583
- 3ncbi.nlm.nih.gov/books/NBK560850/
- 4ncbi.nlm.nih.gov/pmc/articles/PMC6535929/
- 7ncbi.nlm.nih.gov/pmc/articles/PMC7734587/
- 8ncbi.nlm.nih.gov/pmc/articles/PMC4553909/
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- 9healthaffairs.org/doi/10.1377/hlthaff.2018.0504
- 12healthaffairs.org/doi/10.1377/hlthaff.2022.01419
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- 11ahip.org/wp-content/uploads/2021/06/prior-authorization-coverage-lives.pdf
- 14ahip.org/wp-content/uploads/2022/10/2022-PA-MEASUREMENT-STUDY.pdf
- 27ahip.org/wp-content/uploads/2021/09/appeals-prior-authorization-report.pdf
- 17bmj.com/content/372/bmj.n237
- 18academic.oup.com/jpubhealth/article/40/3/505/4076698
- 23pubmed.ncbi.nlm.nih.gov/35210224/
- 28nejm.org/doi/full/10.1056/NEJMp2013899
- 32rand.org/pubs/research_reports/RR2773.html
- 33annfammed.org/content/16/2/142
- 34khana.ai/case-studies/prior-authorization-eligibility-checks-2020
- 35marketsandmarkets.com/Market-Reports/prior-authorization-software-market-130977438.html
- 36fortunebusinessinsights.com/utilization-management-market-101600
- 37aspe.hhs.gov/sites/default/files/documents/prior-auth-utilization-management-2021.pdf
- 38verdicthealth.com/market-data/utilization-management-software-market-size/
- 39frost.com/frost-perspectives/prior-authorization-technology-investment-2022/







