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BMJ Qual Saf. 2018 Nov;27(11):878-891. doi: 10.1136/bmjqs-2017-007416. Epub 2018 Mar 15.

Effect of copayment policies on initial medication non-adherence according to income: a population-based study.

Author information

1
Research and Development Unit, Institut de Recerca Sant Joan de Déu, Barcelona, Catalonia, Spain.
2
Centro de Investigacion Biomedica en Red de Epidemiologia y Salud Publica, Barcelona, Catalunya, Spain.
3
Department of Clinical Pharmacology, University of Southern Denmark, Odense, Denmark.
4
Service of Community Health, Public Health Agency of Barcelona, Barcelona, Catalonia, Spain.
5
Institut Català de la Salut, Barcelona, Catalunya, Spain.
6
Research and Development Unit, Parc Sanitari Sant Joan de Déu, Barcelona, Catalonia, Spain.
7
Faculty of Economics and Business Science, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.
8
Primary Care Prevention and Health Promotion Research Network, Barcelona, Catalonia, Spain.
9
Faculty of Health and Sport Sciences, University of Zaragoza, Huesca, Spain.
10
Distrito de Atención Primaria Málaga-Guadalhorce, Málaga, Spain.
11
IBIMA, Málaga, Spain.
12
School of Pharmacy, University of Barcelona, Barcelona, Catalonia, Spain.

Abstract

OBJECTIVE:

Copayment policies aim to reduce the burden of medication expenditure but may affect adherence and generate inequities in access to healthcare. The objective was to evaluate the impact of two copayment measures on initial medication non-adherence (IMNA) in several medication groups and by income level.

DESIGN:

A population-based study was conducted using real-world evidence.

SETTING:

Primary care in Catalonia (Spain) where two separate copayment measures (fixed copayment and coinsurance) were introduced between 2011 and 2013.

PARTICIPANT:

Every patient with a new prescription issued between 2011 and 2014 (3 million patients and 10 million prescriptions).

OUTCOMES:

IMNA was estimated throughout dispensing and invoicing information. Changes in IMNA prevalence after the introduction of copayment policies (immediate level change and trend changes) were estimated through segmented logistic regression. The regression models were stratified by economic status and medication groups.

RESULTS:

Before changes to copayment policies, IMNA prevalence remained stable. The introduction of a fixed copayment was followed by a statistically significant increase in IMNA in poor population, low/middle-income pensioners and low-income non-pensioners (OR from 1.047 to 1.370). In high-income populations, there was a large statistically non-significant increase. IMNA decreased in the low-income population after suspension of the fixed copayment and the introduction of a coinsurance policy that granted this population free access to medications (OR=0.676). Penicillins were least affected while analgesics were affected to the greatest extent. IMNA to medications for chronic conditions increased in low/middle-income pensioners.

CONCLUSION:

Even nominal charge fixed copayment may generate inequities in access to health services. An anticipation effect and expenses associated with IMNA may have generated short-term costs. A reduction in copayment can protect from non-adherence and have positive, long-term effects. Copayment scenarios could have considerable long-term consequences for health and costs due to increased IMNA in medication for chronic physical conditions.

KEYWORDS:

health policy; pharmacoepidemiology; primary care

PMID:
29545326
DOI:
10.1136/bmjqs-2017-007416

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