Sahni Nikhil R, Istvan Brooke, Stafford Celia, Cutler David
Department of Economics, Harvard University, Cambridge, MA, 02138, United States.
Center for US Healthcare Improvement, McKinsey & Company, Boston, MA 02110, United States.
Health Aff Sch. 2024 Aug 6;2(9):qxae096. doi: 10.1093/haschl/qxae096. eCollection 2024 Sep.
The prior authorization (PA) process consumes time and money on the part of patients, providers, and payers. While some research shows substantial possible savings in the PA process, identifying what different groups can do is not as well known. Thus, organizations have struggled to capture this opportunity. To understand different perspectives on PA burden and receptivity to possible changes in the PA process, we surveyed 1005 patients, 1010 provider employees, and 115 private payer employees. Patients reported the longest perceived wait times but indicated the highest perceived approval rates and lowest perceived burden. The relatively low burden for patients is because most do not have to engage in PA directly. Provider respondents reported spending time equivalent of more than 100 000 full-time registered nurses per year on prior authorization. Artificial intelligence (AI) represents a possible solution: 65% of private payer respondents reported that their organizations planned to incorporate AI into the process in the next 3 to 5 years. Intended adoption by provider respondents is much smaller (11%). Private payer respondents cited cybersecurity concerns and a lack of technical infrastructure as barriers; provider respondents cited lack of budget and limited trust in the technology.
预先授权(PA)流程耗费了患者、医疗服务提供者和支付方的时间与金钱。虽然一些研究表明PA流程有可能大幅节省开支,但不同群体能采取什么措施却鲜为人知。因此,各机构一直在努力抓住这一机遇。为了解对PA负担的不同看法以及对PA流程可能变化的接受程度,我们对1005名患者、1010名医疗服务提供者员工和115名私人支付方员工进行了调查。患者报告的感知等待时间最长,但表示感知批准率最高且感知负担最低。患者负担相对较低是因为大多数患者无需直接参与PA。医疗服务提供者受访者报告称,他们每年在预先授权方面花费的时间相当于超过10万名全职注册护士的工作时间。人工智能(AI)可能是一种解决方案:65%的私人支付方受访者表示,他们的机构计划在未来3至5年内将AI纳入该流程。医疗服务提供者受访者的预期采用率则低得多(11%)。私人支付方受访者认为网络安全问题和缺乏技术基础设施是障碍;医疗服务提供者受访者则提到缺乏预算和对该技术的信任有限。