Formulary Restrictions and Stroke Risk in Patients With Atrial Fibrillation

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Limiting access to non–vitamin K antagonist oral anticoagulants through step therapy and prior authorization may exacerbate current underuse of anticoagulants and increase the risk of stroke in patients with newly diagnosed atrial fibrillation.


Objectives: To determine the use of formulary restrictions (prior authorization and step therapy) on the use of non–vitamin K antagonist oral anticoagulants (NOACs) and their effect on health outcomes.

Study Design: Longitudinal cohort study. We identified a sample of Medicare beneficiaries with an incident diagnosis of atrial fibrillation (AF) in 2011 to 2015 and followed them until the end of 2016 or death. We compared anticoagulant use and health outcomes associated with Medicare Part D plan coverage of NOACs.

Methods: The primary outcomes were composite rates of death, stroke, transient ischemic attack, and systemic embolism. We used Cox proportional hazards models to estimate the association between formulary restrictions and adverse health outcomes.

Results: Beneficiaries enrolled in Part D plans that restricted access to NOACs had a lower probability of NOAC use (30.2% vs 32.2%), worse adherence conditional on NOAC use (32.1% vs 34.3% adherent), and longer delays in filling an initial prescription (46% vs 55% filled within 30 days of AF diagnosis). Beneficiaries in restricted plans had higher aggregate risk of mortality/stroke/transient ischemic attack (adjusted HR, 1.098; 95% CI, 1.079-1.118).

Conclusions: Limiting access to NOACs may exacerbate current underuse of anticoagulants and increase the risk of stroke among patients with newly diagnosed AF. Pharmacy benefit managers and Part D plans need to continuously review the appropriateness of formulary policies to ensure patient access to effective medications.

Am J Manag Care. 2022;28(10):In Press


Takeaway Points

Non–vitamin K antagonist oral anticoagulants (NOACs) were documented to be equivalent or superior to warfarin at reducing stroke risk in patients with atrial fibrillation. Mixed findings have been reported on the impact of step therapy and prior authorization on patients’ medication use and health outcomes across various drug classes.

  • Step therapy and prior authorization policies were associated with reduced NOAC use and higher stroke rates among patients with new atrial fibrillation in Medicare.
  • Pharmacy benefit managers and Medicare Part D plans need to continuously review the appropriateness of formulary policies to ensure patients’ access to effective medications.


Historically, stroke risk in patients with atrial fibrillation (AF) has been lowered by treatment with warfarin sodium. First approved for use in humans in 1954, warfarin is both efficacious—it has been shown to reduce the risk of stroke by up to 70% in patients with AF—and inexpensive.1,2 However, its use can be burdensome to patients because of numerous food and drug interactions requiring dietary and treatment restrictions and the need for ongoing laboratory testing and dose adjustment to achieve anticoagulant control. Consequently, patients taking warfarin are in the target therapeutic international normalized ratio range only about half of the time.3,4

Recently introduced non–vitamin K antagonist oral anticoagulants (NOACs)—including dabigatran, rivaroxaban, and apixaban—provide more convenient therapeutic options and have demonstrated equivalent or superior efficacy compared with warfarin.5-9 However, NOACs are considerably more expensive and, until recently, lacked a reversal agent to mitigate the risk of life-threatening bleeding. Some health plans initially excluded NOACs from coverage or chose to restrict access to them through the use of prior authorization (PA) and step therapy (ST) requirements. Under PA, the health plan or pharmacy benefit manager must authorize a particular prescription before it can be covered. Under ST, also called “fail first,” patients must try and fail to reach therapeutic target on a lower-cost alternative, in this case warfarin, before receiving authorization for the originally requested medication. Both PA and ST are designed to promote formulary compliance, reduce unnecessary prescription drug use, and lower costs, but if not used judiciously, they can induce patients to delay treatment, switch to less effective medications, or become nonadherent and, as a result, experience adverse health effects.10-20

Herein we examine the effect of the use of PA and ST on the utilization of NOACs among patients with newly diagnosed AF enrolled in Medicare Part D. We linked detailed, plan-level information on the coverage of NOACs in Part D plans to beneficiaries’ medical and prescription drug claims. We tested the association between coverage restrictions and NOAC use, including initiation and adherence, and whether coverage restrictions were associated with elevated risk of stroke and bleeding.



Through a reuse agreement with the National Bureau of Economic Research, we used data for a 20% random sample of fee-for-service Medicare beneficiaries. We linked data on enrollment, demographics, and parts A (inpatient), B (outpatient), and D (pharmacy) claims for patients with newly diagnosed AF from 2010 to 2016. Inpatient and outpatient medical claims provided information on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes (International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] codes were included beginning October 2015) and Current Procedural Terminology procedure codes, dates of service, and spending. Part D claims provided information related to prescription drug claims, including National Drug Code, fill dates, and days supplied. Enrollment and claims data were supplemented with claim histories from the Chronic Conditions Data Warehouse, which identifies incident dates of diagnosed chronic health conditions and cardiovascular risk factors.

We linked the Part D claims to the plan characteristics file, which provided detailed information on each plan’s formulary, benefit design, and utilization management policies, including PA and ST. We used this information to identify the formulary restrictions and cost-sharing requirements for each NOAC in the plan-year. To adjust for other aspects of plan quality, we linked the plan characteristic file with the annual Part D star performance rating provided by CMS.21 Star ratings, which range from 1 to 5, were designed to provide summary measures of how well Part D plans perform in terms of customer service, member experience, drug pricing, and patient safety.

Study Sample

The study sample consisted of beneficiaries with an incident diagnosis of AF (ICD-9-CM diagnosis code 427.31 or ICD-10-CM codes I48.0-I48.2, I48.91) between 2010 and 2015, based on at least 1 inpatient or 2 outpatient or carrier claims (eAppendix Table 1 [eAppendix available at]). We excluded patients who died or had a stroke within 30 days of the index AF diagnosis and defined the index date as the date of the first AF medical claim (inpatient or outpatient). We required at least 1 year of follow-up data unless the patient died within 364 days of the index AF diagnosis. We also required enrollment in a fee-for-service Medicare plan for at least 1 year before the incidence date to capture the health history. We excluded beneficiaries enrolled in Medicare Advantage plans due to incomplete capture of medical claims and those enrolled in a Part D plan through an employer because CMS waives Part D formulary submission requirements for these plans. Finally, we excluded patients with valvular heart disease, end-stage chronic kidney disease, kidney transplant, dialysis, or hip or knee replacement surgery with a diagnosis of deep vein thrombosis or pulmonary embolism at any point during the study sample (eAppendix Table 2).

We categorized Part D plans into 2 groups based on their coverage of NOACs. Plans were defined as unrestricted if 1 or more NOACs were available without PA/ST and as restricted if all NOACs were subject to PA/ST or not covered by the plan (by 2013, all prescription drug plans covered at least 1 NOAC). We excluded a small number of beneficiaries who switched from an unrestricted to a restricted plan or vice versa after their AF diagnosis. The final study sample included 139,041 patients with incident AF, 36% of whom (n = 50,596) were enrolled in restricted plans.

Statistical Analyses

To estimate the direct impact of PA/ST on medication use, we counted the number of anticoagulant prescription fills (30-day equivalent) 1 year before the index date and after diagnosis for patients in restricted and nonrestricted plans. To control for differences in beneficiaries’ cardiovascular risk and other characteristics that may influence anticoagulant use, we compared the medication adherence of patients in restricted plans vs those in unrestricted plans using multivariate logistic regression. The key independent variable was a binary indicator for a restricted plan as defined earlier. Other independent variables included beneficiary demographics (age, sex, race/ethnicity) and binary indicators for AF incidence year to control for time trends. Race/ethnicity was determined using the beneficiary race code in enrollment data from CMS and by applying an algorithm developed by the Research Triangle Institute that improves identification of Hispanic and Asian individuals based on name. To adjust for patients’ socioeconomic status, we linked enrollment and claims data from their AF incidence year to zip code–level data on household income and education from the American Community Survey. We also controlled for 27 comorbid conditions identified in the Chronic Conditions Data Warehouse (eAppendix Table 3). These included binary indicators for previous diagnosis of stroke, acute myocardial infarction, congestive heart failure, hypertension, and diabetes (full model results are available from the corresponding author). To control for plan quality, we calculated the beneficiary-level mean star rating since incident diagnosis and created a binary variable indicating mean star rating above the median.

We also examined the association between formulary restrictions and clinical outcomes. The primary outcome was the composite risk of death or stroke, including ischemic stroke, hemorrhagic stroke, and transient ischemic attack (TIA). The secondary outcome was major bleeding, including gastrointestinal bleeding, intracranial bleeding, and bleeding from other sites. To focus on acute events, outcomes were identified using only inpatient or emergency department medical claims (see eAppendix Table 1 for associated ICD-9-CM and ICD-10-CM codes). We plotted unadjusted Kaplan-Meier curves of unadjusted rates of all-cause mortality, stroke, or TIA for patients in restricted vs unrestricted plans. We grouped patients into 3 subgroups based on their CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes, stroke, vascular disease, age 65-74 years, sex category) scores at AF incidence date (≤ 3, 4-5, or ≥ 6), and we used Cox proportional hazards models to test the association between PA/ST and all-cause mortality, stroke, and bleeding for each subgroup. Cox regressions included the same set of covariates as the logistic regression models for medication use.

We ran several additional analyses to assess whether patients at higher cardiovascular risk differentially enrolled in less restrictive plans and whether the magnitude of effects we observed were consistent with clinical trial data. First, we predicted rates of NOAC use and stroke by plan type (eAppendix Table 4). Second, we estimated the association between anticoagulant use and adverse health outcomes for a subsample of patients without a history of anticoagulant use before their incident AF date (eAppendix Table 5). Finally, we compared predicted stroke rates using observed differences in NOAC use in the present sample with the effect sizes reported from clinical trial data (eAppendix Table 6).


Coverage of NOACs

Figure 1 reports the prevalence of formulary restrictions in our sample of Part D plans. Warfarin accounted for 94% of anticoagulant prescriptions for patients with AF in 2011 and remained the most frequently prescribed anticoagulant throughout the study period, although its share of use fell to 62% by 2016 (eAppendix Figure 1). The steady increase in NOAC prescriptions coincided with a decline in formulary restrictions. In 2011, 44% of plans covered NOACs without restrictions, 41% imposed PA or ST, and the remaining 15% excluded NOACs from the formulary altogether. However, by 2013 all the plans in the sample covered at least 1 NOAC, and the percentage of Part D plans imposing PA or ST decreased to 31% in 2013 and to 26% by 2016.

Importantly, unrestricted plans were similar to restricted plans in their coverage of all other medications (Table 1). The number of unique medications included in the formulary of restricted plans was similar to that in unrestricted plans (1234 and 1139, respectively), as was the fraction of formulary drugs subject to PA or ST (21% in both plan types). Unrestricted plans had slightly higher mean star ratings (3.34 vs 3.26, respectively) and were more likely to receive a star rating of 4 or higher (20.7% vs 13.3%, respectively) than restricted plans.

Anticoagulant Use

A primary concern when using observational claims data to assess health outcomes is that plan choice may be correlated with unobserved factors that affect medication use and outcomes, including health status. Given the similarities in restricted and unrestricted plans aside from their coverage of NOACs, it is not surprising that we found little evidence that beneficiaries differentially enrolled in the 2 plan types (Table 2). Beneficiaries in restricted plans were slightly older (1 year) at the time of their incident AF diagnosis and were less likely to be male and non-White, but they had similar rates of acute myocardial infarction, heart failure, heart disease, stroke, and TIA before their AF diagnosis.

Beneficiaries enrolled in unrestricted plans had modestly higher rates of NOAC use (32.2% vs 30.2% in restricted plans) and lower, but not statistically significantly different, use of warfarin (32.9% vs 33.3%, respectively). Conditional on NOAC use, beneficiaries in unrestricted plans had higher adherence rates (34.3% vs 32.1%) and shorter delays in filling an initial prescription. More than 55% of those in unrestricted plans filled their first NOAC within 30 days of AF diagnosis compared with 46% in restricted plans.

Regression results shown in Table 3 indicate that patients in restricted plans had lower use of NOACs. They had lower odds of receiving a NOAC (odds ratio [OR], 0.961; 95% CI, 0.937-0.986) after an initial AF diagnosis but no statistically significant difference in warfarin use. Plan-level differences in NOAC use varied markedly by race/ethnicity, with lower use among Black (OR, 0.786; 95% CI, 0.695-0.890), Hispanic (OR, 0.864; 95% CI, 0.753-0.993), and Asian (OR, 0.772; 95% CI, 0.625-0.955) individuals in restricted plans compared with White individuals. The association between formulary restrictions and NOAC use was more pronounced for those at higher risk of stroke, with lower use of NOACs among those at intermediate (CHA2DS2-VASc score of 4 or 5: OR, 0.942; 95% CI, 0.907-0.978) and high (CHA2DS2-VASc score ≥6: OR, 0.926; 95% CI, 0.879-0.977) stroke risk.

Health Outcomes

Figure 2 plots the cumulative incidence of mortality/stroke/TIA by plan type. Kaplan-Meier estimates of the composite risk of death, stroke, and TIA within 500, 1000, 1500, and 2000 days after the index date (defined as 30 days after the AF incidence date) were 21.9%, 37.7%, 51.0%, and 62.4%, respectively, for beneficiaries in restricted plans compared with 20.2%, 34.9%, 46.4%, and 55.4%, respectively, for beneficiaries in unrestricted plans. In multivariate Cox regression analyses, patients in restricted plans also had higher risk of mortality/stroke/TIA (adjusted HR, 1.098; 95% CI, 1.079-1.118) (Table 3). Bleed rates were also higher, with an adjusted HR of 1.046 (95% CI, 1.014-1.079).

Table 3 reports adjusted HRs of adverse outcomes by sex, race, and CHA2DS2-VASc subgroups over a range of clinical end points (ischemic and hemorrhagic strokes, TIAs, and bleeding). The association between formulary restrictions and composite risk of death, stroke, and TIA was slightly stronger for women (OR, 1.102; 95% CI, 1.078-1.128) compared with men (OR, 1.091; 95% CI, 1.060-1.122) and for Black patients (OR, 1.139; 95% CI, 1.062-1.222) compared with White patients (OR, 1.091; 95% CI, 1.071-1.112). We also found that the impact of PA/ST was greater for hemorrhagic stroke (OR, 1.109; 95% CI, 1.020-1.206) relative to ischemic stroke (OR, 1.082; 95% CI, 1.026-1.142) and for intracranial bleeds (OR, 1.103; 95% CI, 1.011-1.203) relative to gastrointestinal bleeding (OR, 1.030; 95% CI, 0.994-1.068) in the full sample.


We studied the association between formulary restrictions on the use of NOACs and associated clinical outcomes among Medicare beneficiaries with an incident diagnosis of AF. Although formulary restrictions have been shown to reduce use of the targeted drug or medical service, there is some concern that substitution to an alternative therapy is often incomplete.11-16 The present results seem to validate this concern in the case of AF, as we found that restricting access to NOACs by either requiring PA/ST or not covering them at all reduced the likelihood of using these medications by approximately 2 percentage points (PP) and lowered overall anticoagulant use by 1.3 PP among Medicare beneficiaries with incident AF. In addition, formulary restrictions reduced mean adherence rates by 2.2 PP among NOAC users and reduced the probability of filling a first prescription within 30 days of AF incidence by 9.1 PP among new NOAC users. Lower use and delayed initiation of NOACs were associated with elevated risks of stroke and bleeding, consistent with data from clinical trials and other observational studies.

These findings are particularly concerning given that anticoagulants are substantially underused in community practice.22 A recent initiative to improve outpatient cardiac care in the United States found that only 60% of patients at high thromboembolic risk (CHADS2 [congestive heart failure, hypertension, age ≥ 75 years, diabetes, stroke] score ≥ 2) were treated with warfarin or NOACs.23 A retrospective analysis of more than 94,000 patients with an acute ischemic stroke who had a known history of AF found that 84% did not receive guideline-recommended therapeutic anticoagulation preceding the stroke or had anticoagulation levels that were not in the therapeutic range.4 Our results suggest that limiting access to NOACs may exacerbate the underuse of anticoagulants and increase the risk of stroke and bleeding for those at high thromboembolic risk. These findings are particularly germane to women with AF, who are at greater risk when taking warfarin, and minority groups, for whom NOACs are relatively underprescribed.24-26

Although common, the use of PA, ST, and other utilization management strategies is controversial. Health plans and pharmacy benefit managers contend that the PA process reduces waste and unnecessary use. However, physicians often object that these policies are overused, impose administrative burden, and undermine their clinical decision-making.27 In addition, physicians, pharmaceutical manufacturers, and patient advocates argue that these policies can induce patients to delay treatment, switch to less effective medications, or become nonadherent in some cases and, as a result, experience adverse health effects. The evidence on this is mixed; some studies find that PA, ST, and other restrictions lead to nonadherence and worse health outcomes,9-14 whereas others find no effects.15-17 Although encouraging the use of less expensive alternatives in a therapeutic class may be warranted in many contexts, our study highlights a particular class in which PA/ST may be harmful to patients.

A recent economic analysis comparing apixaban with warfarin found that apixaban was clinically superior for patients with AF and was cost-effective by current US norms but not cost-saving.28 This exemplifies the near-universal trade-off between cost and quality resulting from medical innovation. Medicare and most commercial health insurance plans typically base coverage decisions of new medical technologies on evidence of effectiveness rather than on cost-effectiveness or any other direct measure of value.29 Yet the continued growth in health care spending heightens pressure on manufacturers to demonstrate the clinical and economic value of their products. Broad and increasing use of formulary restrictions raises concern that there are other therapies besides NOACs for which restricting access may be clinically and/or economically counterproductive.


This study has several limitations. Because Part D is a voluntary program, these results may be biased if beneficiaries at higher cardiovascular risk are more likely to enroll in plans that restrict access to potentially more effective, higher-cost therapies. We found no evidence that Medicare beneficiaries differentially enrolled in Part D plans based on the coverage of NOACs. Furthermore, the goal of this study was not to evaluate the efficacy of the medications, which has been well established in clinical trials, but rather to assess how plan-level policies designed to restrict access to these drugs affected medication use and clinical outcomes in real-world populations. These questions can be answered only by observational studies.

Because we relied on medical claims, we lacked clinical detail such as the type of AF, ejection fraction, and smoking histories. Observational studies using registries and single-center electronic medical records typically provide more clinical detail than those relying on administrative data. In addition, we restricted the analyses to stand-alone Part D prescription drug plans due to the lack of medical claims for Medicare Advantage and Part D plans. The latter may have stronger financial incentives to provide generous drug coverage if keeping enrollees healthy leads to savings in medical costs.


PA and ST policies are most effective when there is clear evidence that a service is being overused or misused and when patient safety and cost implications indicate that it is helpful or appropriate. Nonetheless, their use can be costly for payers, manufacturers, physicians, and patients. A recent study estimated that drug utilization management costs $93.3 billion annually in the United States.30 Given the administrative and economic burden on providers and the risk to patients, it may be more effective to identify and educate outlier physicians rather than impose these policies on all providers and their patients. All payers, not just Part D sponsors, need to continuously review the use and appropriateness of formulary policies to ensure that beneficiaries have access to clinically beneficial medications.

Author Affiliations: University of Southern California (USC) Schaeffer Center for Health Policy and Economics (BZ, SS, DG, GJ), Los Angeles, CA; USC School of Pharmacy (BZ, SS, GJ), Los Angeles, CA; USC Price School of Public Policy (DG), Los Angeles, CA.

Source of Funding: The research was supported by a grant from the American Medical Association and by the National Institute on Aging of the National Institutes of Health (NIH) under Award No. R01AG055401. Research reported in this publication was supported by the National Institute on Aging of the NIH under Award No. P30AG024968. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Author Disclosures: Dr Goldman reports personal fees from Biogen and GRAIL as a scientific advisor during the past 12 months. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (BZ, SS, DG, GJ); acquisition of data (DG, GJ); analysis and interpretation of data (BZ, SS, GJ); drafting of the manuscript (BZ, SS, GJ); critical revision of the manuscript for important intellectual content (BZ, GJ); statistical analysis (BZ, GJ); provision of patients or study materials (GJ); obtaining funding (DG, JG); and administrative, technical, or logistic support (GJ).

Address Correspondence to: Geoffrey Joyce, PhD, USC Schaeffer Center for Health Policy and Economics, 635 Downey Way, VPD 412D, Los Angeles, CA 90089-3333. Email:


1. Ezekowitz MD, Bridgers SL, James KE, et al; Veterans Affairs Stroke Prevention in Nonrheumatic Atrial Fibrillation Investigators. Warfarin in the prevention of stroke associated with nonrheumatic atrial fibrillation. N Engl J Med. 1992;327(20):1406-1412. doi:10.1056/NEJM199211123272002

2. Stroke Prevention in Atrial Fibrillation Investigators. Adjusted-dose warfarin versus low-intensity, fixed-dose warfarin plus aspirin for high-risk patients with atrial fibrillation: Stroke Prevention in Atrial Fibrillation III randomised clinical trial. Lancet. 1996;348(9028):633-638. doi:10.1016/S0140-6736(96)03487-3

3. Baker WL, Cios DA, Sander SD, Coleman CI. Meta-analysis to assess the quality of warfarin control in atrial fibrillation patients in the United States. J Manag Care Pharm. 2009;15(3):244-252. doi:10.18553/jmcp.2009.15.3.244

4. Xian Y, O’Brien EC, Liang L, et al. Association of preceding antithrombotic treatment with acute ischemic stroke severity and in-hospital outcomes among patients with atrial fibrillation. JAMA. 2017;317(10):1057-1067. doi:10.1001/jama.2017.1371

5. Granger CB, Alexander JH, McMurray JJV, et al; ARISTOTLE Committees and Investigators. Apixaban versus warfarin in patients with atrial fibrillation. N Engl J Med. 2011;365(11):981-992. doi:10.1056/NEJMoa1107039

6. Patel MR, Mahaffey KW, Garg J, et al; ROCKET AF Investigators. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med. 2011;365(10):883-891. doi:10.1056/NEJMoa1009638

7. Giugliano RP, Ruff CT, Braunwald E, et al; ENGAGE AF-TIMI 48 Investigators. Edoxaban versus warfarin in patients with atrial fibrillation. N Engl J Med. 2013;369(22):2093-2104. doi:10.1056/NEJMoa1310907

8. Yao X, Abraham NS, Sangaralingham LR, et al. Effectiveness and safety of dabigatran, rivaroxaban, and apixaban versus warfarin in nonvalvular atrial fibrillation. J Am Heart Assoc. 2016;5(6):e003725. doi:10.1161/JAHA.116.003725

9. Hernandez I, Zhang Y, Saba S. Comparison of the effectiveness and safety of apixaban, dabigatran, rivaroxaban, and warfarin in newly diagnosed atrial fibrillation. Am J Cardiol. 2017;120(10):1813-1819. doi:10.1016/j.amjcard.2017.07.092

10. Abouzaid S, Jutkowitz E, Foley KA, Pizzi LT, Kim E, Bates J. Economic impact of prior authorization policies for atypical antipsychotics in the treatment of schizophrenia. Popul Health Manag. 2010;13(5):247-254. doi:10.1089/pop.2009.0063

11. Crystal S, Olfson M, Huang C, Pincus H, Gerhard T. Broadened use of atypical antipsychotics: safety, effectiveness, and policy challenges. Health Aff (Millwood). 2009;28(5):w770-w781. doi:10.1377/hlthaff.28.5.w770

12. Goldman DP, Dirani R, Fastenau J, Conrad RM. Do strict formularies replicate failure for patients with schizophrenia? Am J Manag Care. 2014;20(3):219-228.

13. Ridley DB, Axelsen KJ. Impact of Medicaid preferred drug lists on therapeutic adherence. Pharmacoeconomics. 2006;24(suppl 3):65-78. doi:10.2165/00019053-200624003-00006

14. Vogt WB, Joyce G, Xia J, Dirani R, Wan G, Goldman DP. Medicaid cost control measures aimed at second-generation antipsychotics led to less use of all antipsychotics. Health Aff (Millwood). 2011;30(12):2346-2354. doi:10.1377/hlthaff.2010.1296

15. Wilson J, Axelsen K, Tang S. Medicaid prescription drug access restrictions: exploring the effect on patient persistence with hypertension medications. Am J Manag Care. 2005;11(Spec No. 1):SP27-SP34.

16. Smalley WE, Griffin MR, Fought RL, Sullivan L, Ray WA. Effect of a prior-authorization requirement on the use of nonsteroidal antiinflammatory drugs by Medicaid patients. N Engl J Med. 1995;332(24):1612-1617. doi:10.1056/NEJM199506153322406

17. Kotzan JA, McMillan J, Jankel C, Foster A. Initial impact of a Medicaid prior authorization program for NSAID prescriptions. J Res Pharm Econ. 1993;5(1):25-41.

18. Kotzan JA, Jankel CA, McMillan JA, Foster AL, Myers S. Initial impact of a Medicaid maintenance dose program for H2 antagonist prescriptions. J Res Pharm Econ. 1993;5(1):43-58.

19. Delate T, Mager DE, Sheth J, Motheral BR. Clinical and financial outcomes associated with a proton pump inhibitor prior-authorization program in a Medicaid population. Am J Manag Care. 2005;11(1):29-36.

20. Gleason PP, Williams C, Hrdy S, Hartwig SC, Lassen D. Medical and pharmacy expenditures after implementation of a cyclooxygenase-2 inhibitor prior authorization program. Pharmacotherapy. 2005;25(7):924-934. doi:10.1592/phco.2005.25.7.924

21. Five-Star Quality Rating System. CMS. Updated May 26, 2022. Accessed December 5, 2021.

22. Ogilvie IM, Newton N, Welner SA, Cowell W, Lip GY. Underuse of oral anticoagulants in atrial fibrillation: a systematic review. Am J Med. 2010;123(7):638-645.e4. doi:10.1016/j.amjmed.2009.11.025

23. Hsu JC, Maddox TM, Kennedy K, et al. Aspirin instead of oral anticoagulant prescription in atrial fibrillation patients at risk for stroke. J Am Coll Cardiol. 2016;67(25):2913-2923. doi:10.1016/j.jacc.2016.03.581

24. Pancholy SB, Sharma PS, Pancholy DS, Patel TM, Callans DJ, Marchlinski FE. Meta-analysis of gender differences in residual stroke risk and major bleeding in patients with nonvalvular atrial fibrillation treated with oral anticoagulants. Am J Cardiol. 2014;113(3):485-490. doi:10.1016/j.amjcard.2013.10.035

25. Thompson LE, Maddox TM, Lei L, et al. Sex differences in the use of oral anticoagulants for atrial fibrillation: a report from the National Cardiovascular Data Registry (NCDR) PINNACLE Registry. J Am Heart Assoc. 2017;6(7):e005801. doi:10.1161/JAHA.117.005801

26. Essien UR, Holmes DN, Jackson LR II, et al. Association of race/ethnicity with oral anticoagulant use in patients with atrial fibrillation: findings from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation II. JAMA Cardiol. 2018;3(12):1174-1182. doi:10.1001/jamacardio.2018.3945

27. 2021 AMA prior authorization (PA) physician survey. American Medical Association. Accessed December 5, 2021.

28. Cowper PA, Sheng S, Lopes RD, et al. Economic analysis of apixaban therapy for patients with atrial fibrillation from a US perspective: results from the ARISTOTLE randomized clinical trial. JAMA Cardiol. 2017;2(5):525-534. doi:10.1001/jamacardio.2017.0065

29. Garber AM. Cost-effectiveness and evidence evaluation as criteria for coverage policy. Health Aff (Millwood). 2004;23(suppl 1):W4-284-W4-296. doi:10.1377/hlthaff.w4.284

30. Howell S, Yin PT, Robinson JC. Quantifying the economic burden of drug utilization management on payers, manufacturers, physicians, and patients. Health Aff (Millwood). 2021;40(8):1206-1214. doi:10.1377/hlthaff.2021.00036