OBJECTIVE: Medications frequently require prior authorization from payers before filling is authorized. Obtaining prior authorization can create delays in filling prescriptions and ultimately reduce patient adherence to medication. Electronic prior authorization (ePA), embedded in the electronic health record (EHR), could remove some barriers but has not been rigorously evaluated. We sought to evaluate the impact of implementing an ePA system on prescription filling. MATERIALS AND METHODS: ePA was implemented in 2 phases in September and November 2018 in a large US healthcare system. This staggered implementation enabled the later-implementing sites to be controls. Using EHR data from all prescriptions written and linked information on whether prescriptions were filled at pharmacies, we 1:1 matched ePA prescriptions with non-ePA prescriptions for the same insurance plan, medication, and site, before and after ePA implementation, to evaluate primary adherence, or the proportion of prescriptions filled within 30 days, using generalized estimating equations. We also conducted concurrent analyses across sites during the peri-implementation period (Sept-Oct 2018). RESULTS: Of 74 546 eligible ePA prescriptions, 38 851 were matched with preimplementation controls. In total, 24 930 (64.2%) ePA prescriptions were filled compared with 26 731 (68.8%) control prescriptions (Adjusted Relative Risk [aRR]: 0.92, 95%CI: 0.91-0.93). Concurrent analyses revealed similar findings (64.7% for ePA vs 62.3% control prescriptions, aRR: 1.03, 95%CI: 0.98-1.09). DISCUSSION: Challenges with implementation, such as misfiring and insurance fragmentation, could have undermined its effectiveness, providing implications for other health informatics interventions deployed in outpatient care. CONCLUSION: Despite increasing interest in implementing ePA to improve prescription filling, adoption did not change medication adherence.
OBJECTIVE: Medications frequently require prior authorization from payers before filling is authorized. Obtaining prior authorization can create delays in filling prescriptions and ultimately reduce patient adherence to medication. Electronic prior authorization (ePA), embedded in the electronic health record (EHR), could remove some barriers but has not been rigorously evaluated. We sought to evaluate the impact of implementing an ePA system on prescription filling. MATERIALS AND METHODS: ePA was implemented in 2 phases in September and November 2018 in a large US healthcare system. This staggered implementation enabled the later-implementing sites to be controls. Using EHR data from all prescriptions written and linked information on whether prescriptions were filled at pharmacies, we 1:1 matched ePA prescriptions with non-ePA prescriptions for the same insurance plan, medication, and site, before and after ePA implementation, to evaluate primary adherence, or the proportion of prescriptions filled within 30 days, using generalized estimating equations. We also conducted concurrent analyses across sites during the peri-implementation period (Sept-Oct 2018). RESULTS: Of 74 546 eligible ePA prescriptions, 38 851 were matched with preimplementation controls. In total, 24 930 (64.2%) ePA prescriptions were filled compared with 26 731 (68.8%) control prescriptions (Adjusted Relative Risk [aRR]: 0.92, 95%CI: 0.91-0.93). Concurrent analyses revealed similar findings (64.7% for ePA vs 62.3% control prescriptions, aRR: 1.03, 95%CI: 0.98-1.09). DISCUSSION: Challenges with implementation, such as misfiring and insurance fragmentation, could have undermined its effectiveness, providing implications for other health informatics interventions deployed in outpatient care. CONCLUSION: Despite increasing interest in implementing ePA to improve prescription filling, adoption did not change medication adherence.
Authors: William H Shrank; Niteesh K Choudhry; Michael A Fischer; Jerry Avorn; Mark Powell; Sebastian Schneeweiss; Joshua N Liberman; Timothy Dollear; Troyen A Brennan; M Alan Brookhart Journal: Ann Intern Med Date: 2010-11-16 Impact factor: 25.391
Authors: Sameer Malhotra; Adam D Cheriff; J Travis Gossey; Curtis L Cole; Rainu Kaushal; Jessica S Ancker Journal: J Am Med Inform Assoc Date: 2016-02-17 Impact factor: 4.497
Authors: Katherine H Schiavoni; Lisa Soleymani Lehmann; Wendy Guan; Meredith Rosenthal; Thomas D Sequist; Alyna T Chien Journal: J Gen Intern Med Date: 2016-08-25 Impact factor: 5.128
Authors: Julie A Schmittdiel; Gregory A Nichols; Wendy Dyer; John F Steiner; Andrew J Karter; Marsha A Raebel Journal: Med Care Date: 2015-04 Impact factor: 2.983