Out-of-Pocket Costs and Prescription Filling Behavior of Commercially Insured Individuals With Chronic Obstructive Pulmonary Disease.

This cohort study uses a longitudinal access and adjudication data set to evaluate prescription out-of-pocket costs and filling behaviors of commercially insured individuals with chronic obstructive pulmonary disease (COPD). Copyright 2022 Patel B et al. JAMA Health Forum.

Introduction

Insurance plans in the US incentivize patients to make cost-effective health care choices by incorporating cost sharing into their benefit designs.[1] These costs may contribute to patients abandoning or disrupting medically necessary treatment. With a focus on chronic obstructive pulmonary disease (COPD), we evaluated how out-of-pocket (OOP) costs are associated with prescription filling behavior among commercially insured patients.

Methods

This cohort study used IQVIA Longitudinal Access and Adjudication Data[2,3,4] for claims limited to patients filling COPD prescriptions between July 2017 and December 2019 through commercial insurance. Patient benefit design assignments were based on the highest cost-benefit design observed for all filled claims for that patient (COPD and non-COPD) in a calendar year, exclusive of any supplementary payment (eg, manufacturer copayment cards). Deductible claims were defined as costing patients more than 50% of total reimbursement and more than $250 per claim or more than $500. Coinsurance claims were defined as costing $75 to $250 with the patient paying 5% to 25% of costs, or the patient paid a defined percentage up to 50% of costs, or 25% to 50% of total cost as well as more than $75. All other claims in which the patient paid less than $75 were classified as copay. This study is a secondary analysis of deidentified claims data; thus, institutional review board approval was not sought. This study followed the STROBE reporting guidelines.

Branded COPD product OOP costs after any secondary support were used to analyze patient behavior in conjunction with benefit design. Abandonment was the observed rate of patients who did not fill their initial prescription within 30 days of approval. Treatment disruption was defined as a failure to refill a prescription within 30 days of the end of the previous fill. After patients abandoned treatment, their subsequent behavior was used to identify when they switched to a different treatment and how patient costs differed after switching. We set the 2-sided significance threshold at 5%. The statistical analysis was conducted using R, version 4.1.3 (R Foundation). Additional detail is available in the eMethods in the Supplement.

Results

Of the 550 712 patients who filled branded COPD prescriptions, copay was the most prevalent benefit design (72.9%), followed by deductible (15.3%) and coinsurance (11.9%) (Table). Patients with deductibles faced average monthly OOP costs for COPD medications of $97, more than double that of coinsurance ($46) or copay ($31). Abandonment was highest among patients with a deductible (17.7%; 95% CI, 17.5%-18.0%) compared with coinsurance (11.9%; 95% CI, 11.7%-12.2%) and copay (10.1%; 95% CI, 10.0%-10.2%). At 1 year after the initial fill, the percentage of patients remaining on their initial therapy was lower for deductible (40.7%; 95% CI, 40.3%-41.0%) and coinsurance (44.7%; 95% CI, 44.3%-45.0%) relative to copay (47.7%; 95% CI, 475%-47.8%). Among patients who abandoned treatment, 39% did not fill any COPD prescriptions.

Table.

Patient Out-of-Pocket (OOP) Costs and Behaviors by Maximum Annual Benefit Design

Metric	Overall	Benefit design
		Copay	Coinsurance	Deductible
No. of patients (%)	550 712 (100)	401 204 (72.9)	65 507 (11.9)	84 001 (15.3)
Target COPD brand total OOP, $a
Mean (SD)	43 (157)	31 (139)	46 (88)	97 (247)
Median (IQR)	18 (0-40)	15 (0-30)	15 (0-52)	20 (0-60)
Abandonment rate, % (95% CI)	11.5 (11.4-11.6)	10.1 (10.0-10.2)	11.9 (11.7-12.2)	17.7 (17.5-18.0)
Switch rate after abandonment, % (95% CI)	60.7 (60.3-61.1)	59.4 (58.9-59.9)	62.2 (61.1-63.3)	63.3 (62.5-64.2)
Continuation rate, % (95% CI)b	46.3 (46.2-46.5)	47.7 (47.5-47.8)	44.7 (44.3-45.0)	40.7 (40.3-41.0)

Abbreviation: COPD, chronic obstructive pulmonary disease.

Target brands included in analysis: Advair (GlaxoSmithKline [GSK]), Anoro (GSK), Arcapta (Novartis Pharmaceuticals Corporation [Novartis]), Bevespi (AstraZeneca), Breo (GSK), Brovana (Sunovion Pharmaceuticals), Daliresp (AstraZeneca), Duaklir (Almirall), Incruse (GSK), Lonhala (Sunovion Pharmaceuticals), Perforomist (Mylan Specialty), Seebri (Novartis), Serevent (GSK), Spiriva (Boehringer Ingelheim), Stiolto (Boehringer Ingelheim), Striverdi (Boehringer Ingelheim), Symbicort (AstraZeneca), Trelegy (GSK), Tudorza (Almirall), Utibron (Novartis), Wixela (Mylan Specialty), and Yupelri (Mylan Specialty).

At 1 year after the first fill.

Of the 61% of patients who filled a subsequent branded or generic COPD prescription, 48% filled a prescription that resulted in lower OOP costs, 40% filled one that resulted in no change in OOP cost, and 12% were exposed to higher costs (Figure).

Figure.

Change in Cost After Patient Switch Following Abandonment of Initial Therapy, by Maximum Annual Benefit Design

Discussion

This analysis adds to evidence suggesting that exposure to high patient cost sharing influences the use of prescribed medicines.[5,6] In high-deductible plans, patients had the highest OOP costs and abandoned and discontinued therapy at greater rates relative to other benefit designs. Although utility exists in ensuring that patients use the most clinically appropriate and cost-effective options, these findings illustrate how cost can intervene in clinical decision-making. Drug coverage benefit designs must account for unintended clinical implications of placing cost responsibilities on patients.

Limitations of this study are common to retrospective database analyses, including data set capture, patient selection, and methodological considerations. This study is limited to commercially insured patients who filled prescriptions, and generalizability is limited to this population. Furthermore, socioeconomic factors, demographic factors, and health status, which play a critical role in drug cost affordability, were not included in this analysis and warrant further evaluation.