September 08, 2023
Prior authorizations (PAs) have been used as a primary utilization management tool for many years. Employers see PA as one of the most important mechanisms at their disposal to promote safety and prevent inappropriate utilization of a medication or medical service. From initially being used as a simple diagnosis validation tool, PA has changed greatly over time, becoming a process involving a far more complex set of criteria. Not only has the number of procedures and therapies subject to PA increased, but the onerous nature of manual processing coupled with increasingly complex clinical criteria has also added to the increased cost and resource burden associated with the process.
These challenges have sparked the industry and legislators to call for change and a reassessment of the value of PAs. Therefore, key stakeholders need to carefully consider the overall impact of their PA decisions on the system and on patients. This increased scrutiny has the potential to improve the efficiency of the PA process and how it is utilized, emphasizing how PAs should continue to evolve in tandem with overall changes in treatment protocols and care delivery.
In recent years, PAs have become a target for provider groups due to the excessive administrative burden they cause. Employers do not always have clear visibility to what services and medications require a PA, and an absence of reporting on the volume and outcomes of the process from their partners makes it challenging for many employers to assess the effectiveness of PAs and their role in achieving desired health outcomes as well as cost savings. Employers can work with their health plans and pharmacy benefit managers (PBMs) to make decisions on what services have a PA requirement and regularly monitor and evaluate whether this tool is doing what it is intended to do.
Some strategies to improve efficiency in the PA process, such as gold carding and automation, have gained traction, but these strategies must be implemented in combination with an evaluation of medically necessary, appropriate and safe health care services personalized to each patient. An ideal PA process would be able to help physicians and plans drive patients to the most cost-effective and clinically appropriate treatment without putting a disproportionate administrative or patient burden on providers, which could lead to delays in appropriate treatment and possibly adverse outcomes.
Stakeholder Perspectives
See Table 1 below outlining some of the benefits and challenges different stakeholders face regarding the PA process.
Table 1: Benefits and Challenges of the PA Process
Benefits | Challenges | |
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Employers |
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Patients |
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Providers |
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Health Plans & PBMs |
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Emerging Solutions and Relevant Changes within Prior Authorization
- Vendor Carve-outs: Employers may explore carving out the PA process to achieve more transparency on PA decisions and to apply a higher level of scrutiny for protocol administration and outcomes.
- Gold Carding: Physician practices that consistently remain in line with evidence-based guidelines for treating their patients are rewarded with an exemption from PA requirements for certain services. This may only reward physicians who consistently achieve approval due to their mastery of navigating the current PA process, but multiple states are experimenting with the idea.
- Automation: An end-to-end automation approach may be able to reduce administrative burden and optimize the PA process through a streamlined workflow for patients, providers and health plans and PBMs.
Key Recommendations
- 1 | Collaborate with your health plan and PBM to achieve PA goal alignment and further transparency of the benefits, limitations and overall impacts of the PA process. This can be achieved by asking for regular reporting on the monitoring of PAs and the evaluation of their effectiveness.
- 2 | Promote discussions among health plans/PBMs and providers within your network about the clinical evidence behind certain common treatments and medications to see where PAs may not be necessary and where more stringent PA processes may be required. Motivate partners to use the PA process as a tool to inform providers on evolving evidence-based treatment protocols, not as a barrier to treating patients. Such discussions can help identify where PAs are successfully achieving their quality and cost goals while determining their incremental value to services that have become standards of practice.
- 3 | Galvanize the health plans in your network to work with providers to improve efficiency and consistency of the PA process, reduce the need for manual intervention and align on recommendations about how the process can be designed to help providers comply while seeking the most effective, covered treatment.
More Topics
Resource Plan Design & Administration Cost Management Pharmacy- 1 | Hu K. ChatGPT sets record for fastest-growing user base - analyst notes. Reuters. February 1, 2023. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/ . Accessed July 24, 2023.
- 2 | Nundy S, Cooper LA, Mate KS. The Quintuple Aim for Health Care Improvement: A New Imperative to Advance Health Equity. JAMA. 2022;327(6):521–522. doi:10.1001/jama.2021.25181
- 3 | Nundy S, Cooper L, Kelsay E. Employers Can Do More to Advance Health Equity. January 1, 2023. https://hbr.org/2023/01/employers-can-do-more-to-advance-health-equity. Accessed August 4, 2023.
- 4 | McKinsey & Company. What is generative AI? January 19, 2023. https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai. Accessed July 24, 2023.
- 5 | Furlong A. AI improves breast cancer detection rate by 20 percent. August 2, 2023. https://www.politico.eu/article/ai-improves-breast-cancer-detection-rate-20-percent-swedish-study/. Accessed July 24, 2023.
- 6 | Grandview Research. Artificial Intelligence in Health Care. July 24, 2023. https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-healthcare-market#:~:text=The%20global%20artificial%20intelligence%20in,37.5%25%20from%202023%20to%202030. Accessed August 4, 2023.
- 7 | Furlong A. AI improves breast cancer detection rate by 20 percent. August 2, 2023. https://www.politico.eu/article/ai-improves-breast-cancer-detection-rate-20-percent-swedish-study/. Accessed July 24, 2023.
- 8 | Rudy M. AI tool gives doctors personalized Alzheimer’s treatment plans for dementia patients. New York Post. May 8, 2023. https://nypost.com/2023/05/08/ai-tool-gives-doctors-personalized-alzheimers-treatment-plans/. Accessed July 24, 2023.
- 9 | Whitestone, Noelle, et al. "Feasibility and acceptance of artificial intelligence-based diabetic retinopathy screening in Rwanda." British Journal of Ophthalmology (2023). doi: 10.1136/bjo-2022-322683
- 10 | Yang YC, Islam SU, Noor A, Khan S, Afsar W, Nazir S. Influential usage of big data and artificial intelligence in healthcare. Comput Math Methods Med. 2021 Sep 6;2021:5812499. doi: 10.1155/2021/5812499. PMID: 34527076; PMCID: PMC8437645.
- 11 | U.S. Government Accountability Office. Machine Learning’s Potential to Improve Medical Diagnosis. https://www.gao.gov/blog/machine-learnings-potential-improve-medical-diagnosis. Accessed July 24, 2023.
- 12 | Dileep G, Gianchandani Gyani SG. Artificial intelligence in breast cancer screening and diagnosis. Cureus. Oct 2022;14(10):e30318. doi:10.7759/cureus.30318.
- 13 | Talaga R. AI tool can predict a brain tumor’s profile instantly: Study. Becker’s Health IT. July 7, 2023. https://www.beckershospitalreview.com/innovation/ai-tool-can-predict-a-brain-tumors-profile-instantly-study.html.. Accessed July 24, 2023.
- 14 | Ayers JW, Poliak A, Dredze M, et al. Comparing physician and artificial intelligence Chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med. Jun 1, 2023;183(6):589-596. Doi:10.1001/jamainternmed.2023.1838.
- 15 | Sharma AD. Transformative AI to revamp prior authorizations. Sagility., 2023. https://www.healthcaredive.com/spons/transformative-ai-to-revamp-prior-authorizations/646831/ Accessed August 4, 2023
- 16 | Management SHRM. Using artificial intelligence for employment purposes. https://www.shrm.org/resourcesandtools/tools-and-samples/toolkits/pages/artificial-intelligence-employment-purposes.aspx . Accessed August 4, 2023, 2023.
- 17 | PYMNTS. Artificial Intelligence is ‘Shining Star’ in Fight Against Healthcare Payments Fraud. October 12, 2021. https://www.pymnts.com/healthcare/2021/artificial-intelligence-shining-star-fight-against-fraud/. Accessed July 24, 2023.
- 18 | Johnson KB, Wei WQ, Weeraratne D, et al. Precision medicine, AI, and the future of personalized health care. Clin Transl Sci. Jan 2021;14(1):86-93. doi:10.1111/cts.12884.
- 19 | Business Wire. Value-based healthcare platform identifies individuals at risk for diabetes with over 80% accuracy. April 18, 2023. https://www.businesswire.com/news/home/20230418005451/en/Value-Based-Healthcare-Platform-Identifies-Individuals-at-Risk-for-Diabetes-With-Over-80-Accuracy. Accessed July 24, 2023.
- 20 | Hartnett K. How Northwell closes maternal health disparities with an AI chatbot. Modern Healthcare. June 23, 2023. https://www.modernhealthcare.com/digital-health/northwell-closes-maternal-health-disparities-ai-chatbot. Accessed July 24, 2023.
- 21 | Baum S. An AI-enabled approach to improve access to physical therapy for self-insured employers. MedCity News. July 18, 2023. https://medcitynews.com/2023/07/an-ai-enabled-approach-to-improve-access-to-physical-therapy-for-self-insured-employers/. Accessed July 24, 2023.
- 22 | Business Wire. Hello Heart adds breakthrough artificial intelligence (AI) capabilities to empower users to make better choices. https://www.businesswire.com/news/home/20221114005754/en/Hello-Heart-Adds-Breakthrough-Artificial-Intelligence-AI-Capabilities-to-Empower-Users-to-Make-Better-Choices. Accessed July 24, 2023.
- 23 | Business Group on Health. Artificial intelligence in health care: Its perils (bias) and potential. https://www.businessgrouphealth.org/en/resources/artificial-intelligence-in-health-care-its-perils-and-potential. Accessed July 24, 2023.
- 24 | Israni ST. Humanizing artificial intelligence. Viewpoint. JAMA. 2019;doi:10.1001/jama.2018.19398.
- 25 | Chen A, Chen DO. Accuracy of chatbots in citing journal articles. JAMA Network Open. 2023;6(8):e2327647. doi:10.1001/jamanetworkopen.2023.27647.
- 26 | Dash D, Horvitz E, Shah N. How well do large language models support clinician information needs? Stanford University Human-Centered Artificial Intelligence. March 31, 2023. https://hai.stanford.edu/news/how-well-do-large-language-models-support-clinician-information-needs. Accessed July 24, 2023.
- 27 | World Health Organization. WHO calls for safe and ethical AI for health. May 16, 2023. https://www.who.int/news/item/16-05-2023-who-calls-for-safe-and-ethical-ai-for-health . Accessed July 24, 2023.