Despite advances in pharrnacotherapy for hypertension, as many as 75% of hypertensive patients' blood pressure is poorly controlled. Uncontrolled hypertension is associated with increased morbidity and mortality and is largely attributed to failure to adhere with antihypertensive medications. Nonadherence to medication regimens is a long-standing phenomenon that increases health care utilization and costs. Existing research demonstrates that a theoretical framework is needed to advance our ability to design effective interventions. Preliminary research on the application of the Transtheoretical Model (TTM) to medication adherence suggests that the model has strong explanatory power in this area and has the potential to guide intervention development. Phase l of this Fast-Track proposal involves the development and feasibility test of a stage-matched, individualized, interactive intervention based on the TTM. Feasibility includes proactively recruiting 70% of eligible participants (n=300) to participate in a randomized trial of an adherence expert system intervention and evaluating acceptability of the intervention materials. Computerized expert system interventions and stage-matched manuals delivered proactively to entire populations can have unprecedented impacts on adherence, offering far greater availability at a low cost. Applying the TTM to intervention development will provide the theoretical and individualized framework that experts in the area have indicated is necessary.
Up to 75% (37.5 million) of the 50 million Americans afflicted with hypertension fail to adhere to their medication regimen. Nonadherence with antihypertensives, which increases utilization of outpatient, inpatient, and emergency services, contributes a large proportion of drug-related morbidity and mortality the annual costs of which exceed $76 billion. Effective and cost-effective population-based adherence expert systems can reduce morbidity, mortality, health care utilization, and related costs, resulting in tremendous commercial potential.
