Elsevier

Contemporary Clinical Trials

Volume 33, Issue 5, September 2012, Pages 1023-1032
Contemporary Clinical Trials

An EMR-based tool to support collaborative planning for medication use among adults with diabetes: Design of a multi-site randomized control trial

https://doi.org/10.1016/j.cct.2012.05.010Get rights and content

Abstract

Patients with type II diabetes often struggle with self-care, including adhering to complex medication regimens and managing their blood glucose levels. Medication nonadherence in this population reflects many factors, including a gap between the demands of taking medication and the limited literacy and cognitive resources that many patients bring to this task. This gap is exacerbated by a lack of health system support, such as inadequate patient–provider collaboration. The goal of our project is to improve self-management of medications and related health outcomes by providing system support. The Medtable™ is an Electronic Medical Record (EMR)-integrated tool designed to support patient–provider collaboration needed for medication management. It helps providers and patients work together to create effective medication schedules that are easy to implement. We describe the development and initial evaluation of the tool, as well as the process of integrating it with an EMR system in general internal medicine clinics. A planned evaluation study will investigate whether an intervention centered on the Medtable™ improves medication knowledge, adherence, and health outcomes relative to a usual care control condition among type II diabetic patients struggling to manage multiple medications.

Introduction

Type II diabetes is a prevalent chronic illness in the US that tends to increase with age [1]. Along with managing blood glucose levels, medication is central to treating and managing diabetes in ambulatory care. Nonadherence is a common barrier to effective treatment—as many as half of patients do not take their medications as prescribed [2], [3]. The problem is linked to many patient, medication-, and system-related factors [4]. One important reason for nonadherence involves a gap between the demands of adherence and the limited resources that patients bring to this complex task. This gap is exacerbated by inadequate support from the health care system. Adherence demands depend on factors such as medication regimen complexity. Complex regimens require patients to create plans for taking multiple medications that meet many constraints, such as medication interactions and auxiliary instructions. Nonadherence increases with complexity [5], in part because of inadequate planning [6]. Planning requires health literacy skills [6], [7], [8] and broader cognitive resources such as processing capacity (e.g., working memory) and health knowledge [9]. Adherence especially challenges older adults, who are more likely to have a chronic illness requiring complex regimens, yet experience declines in literacy and cognitive resources needed for self-care [4], [5].

Patient–provider collaboration and other system support are crucial for adherence [10], [11]. For example, patient education can increase knowledge and literacy skills, and simplifying regimens and coordinating treatment across providers reduces demands on adherence. Unfortunately, system support is often inadequate, especially for adults with lower health literacy [2]. Collaboration requires partners to work together to ensure information is mutually understood [12]. However, providers do not always collaborate with patients effectively. For example, they may not present key information [13], use patient-centered language [14], or check patients’ comprehension of information [15], [16]. More generally, system support for medication management in primary care is inadequate for supporting adequate adherence. Medication review is sporadic and fragmented [17] and reconciliation, the process of ensuring comprehensive and current patient medication lists, is lacking [2].

The consequences of inadequate system support are especially acute for adults with low health literacy because, although they may be most likely to benefit from it, they are also less likely to develop shared adherence plans with their providers, leading to nonadherence [2], [18], [19]. Adults with diabetes and lower health literacy report worse communication with providers [20] and have worse health outcomes than do patients with adequate literacy [21], [22].

Poor patient–provider collaboration reflects system barriers such as limited patient contact time, inadequate communication training, and lack of support for consistent use of patient-centered strategies [2]. Health information technology (IT) can provide system support for patient-centered communication [23], [24]. For example, comprehensive medication lists printed on cards are recommended for medication review and reconciliation with patients, but studies evaluating such cards in pharmacy [25], hospital discharge [26], and specialized clinic [18] environments produce inconsistent evidence. This may reflect the fact that the cards were not designed to support patient–provider collaboration nor linked with health IT and thus not integrated with clinical practice. There is a need for robust support for collaborative medication management [2]. This paper details the development of a tool to support the patient/provider collaboration that is important to medication use among older adults with diabetes, and describes a study that will evaluate the impact of the tool on patient outcomes.

Section snippets

Study overview

We are evaluating the effects of an IT-based intervention designed to improve patient–provider collaboration in primary care clinics on medication use and health-related outcomes among patients with type II diabetes. The intervention involves nurses using the interactive, EMR-integrated tool (the Medtable™) to support patients’ medication planning. Nurses were chosen to deliver the intervention because their education and training focuses on patient-centered care, they indicate a need for

Design

The study is a multi-site longitudinal randomized controlled trial, and is registered on clinicaltrials.gov. A simple 1:1 random assignment is made at each site, placing patients in either the Medtable™ intervention study arm (see Section III) or to a usual care condition. Patients in the usual care condition at both research sites receive the medication counseling and communication that is standard of care at these sites. This includes a medication reconciliation process supported by patient

Procedure

For their first study appointment, patients schedule a time to come in within a week after their next regularly scheduled appointment. A research assistant administers the baseline individual differences battery, the medication knowledge, and adherence measures (about 45 min). Then patients in the intervention condition work with intervention nurses using the Medtable™. Immediately following the intervention with the nurse, patients meet with a research assistant during which medication

Planned analyses

The primary analyses evaluate whether the Medtable™ intervention improves patient outcomes relative to the usual care group by using multivariable generalized linear models that include patient education, medication regimen complexity, patient health status (time since diabetes diagnosis, number of co-morbid conditions), self-reported frequency of diabetes self-care activities, and provider experience as co-variates. Group (Intervention vs. Control), Time and Group × Time interaction terms, will

Discussion

Patients with type II diabetes often struggle with self-care, especially the ability to take complex medication regimens as prescribed. Medication nonadherence in this population relates to many factors, including a gap between the demands of taking medication, limited literacy, and cognitive resources that patients bring to this task, which is exacerbated by inadequate patient–provider collaboration and other aspects of the health care system. The Medtable™ intervention is designed to support

Acknowledgments

This material is based upon work supported by the National Institutes of Health grant # 1R01NR01130. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the NIH. We thank Sameem Samad and Imadhulah Syed for Medtable development and support.

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