Abstract
Interventional pharmacoepidemiology applies quantitative analysis of patterns of medication use and outcomes to help design, guide and then evaluate programs to improve prescription drug use and outcomes. Surveillance of prescribing and drug-taking in large populations is increasingly practical because of the proliferation of detailed data on medication use decisions, often based on paid claims billing data. At the same time, increasingly granular clinical information is available on patient characteristics and outcomes. This can offer important opportunities to identify problematic use, focus interventions to address them, and measure their impact. Alexander et al (Am J Epidemiol. 0000;000(00):0000-0000) review the need for such research and provide methodological guidance for its performance. While randomized controlled trials of such interventions are ideal, real-world considerations often require other evaluation strategies, including stepped-wedge designs and interrupted time-series analysis. As drug therapy becomes more powerful and more costly, and the risks of poor medication choices as well as under-use of effective treatments become even better understood, the health care system will increasingly rely on such approaches to assess current patterns of prescribing and patient adherence, target programs to address problem areas, and measure the effectiveness of such interventions.
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