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Digital Health for Medication Adherence in Adult Diabetes or Hypertension: An Integrative Review.

ABSTRACT: BACKGROUND:Optimal management of chronic diseases, such as type 2 diabetes and hypertension, often include prescription medications. Medication adherence (MA) is one component of self-management. Optimization through digital health-eHealth and mHealth-could enhance patient awareness and/or communication between the patient and provider. OBJECTIVE:Medication adherence is a major issue that affects 50%-60% of chronically ill adults. Digital health refers to eHealth and mHealth, collectively, and as these technologies become more accessible, remote health delivery is increasingly available as an adjunct to improve medication adherence; communicate with patients and providers; and provide education to patients, families, and communities. The objective of this integrative review was to examine the types of digital health technologies that targeted medication adherence in the adult population with diabetes or hypertension. METHODS:An integrative review was conducted using databases within EBSCOhost, PubMed, and Scopus. Eligible studies available as of September 2016 had to be written in English, had to contain digital health interventions to improve medication adherence to prescription medications in adults 18 years or older, and had to focus on diabetes or hypertension. RESULTS:Of the 337 located studies, 13 (3.9%) used a digital health intervention for medication adherence to prescribed medications for diabetes or hypertension and were assessed according to the Chronic Care Model. CONCLUSIONS:The 13 studies included in this review found no conclusive evidence of improved medication adherence using digital health interventions such as interactive voice response (IVR), short message service (SMS) text messaging, telemonitoring, and interactive software technology. Among the 13 studies were digital health interventions that foster medication adherence via one-way communication to the patient or two-way communication between the patient and health care provider for adjunct medication adherence strategies. More research is needed to determine which digital health interventions are most beneficial for individuals with diabetes or hypertension.

SUBMITTER: Conway CM

PROVIDER: S-EPMC6238839 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

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Digital Health for Medication Adherence in Adult Diabetes or Hypertension: An Integrative Review.

Conway Cheryl Moseley CM Kelechi Teresa J TJ

JMIR diabetes 20170816 2

<h4>Background</h4>Optimal management of chronic diseases, such as type 2 diabetes and hypertension, often include prescription medications. Medication adherence (MA) is one component of self-management. Optimization through digital health-eHealth and mHealth-could enhance patient awareness and/or communication between the patient and provider.<h4>Objective</h4>Medication adherence is a major issue that affects 50%-60% of chronically ill adults. Digital health refers to eHealth and mHealth, coll ...[more]

PMID: 30291093

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Project description:BackgroundDiabetes is one of the leading noncommunicable chronic diseases globally. In people with diabetes, blood glucose levels need to be monitored regularly and managed adequately through healthy lifestyles and medications. However, various factors contribute to poor medication adherence. Smartphone apps can improve medication adherence in people with diabetes, but it is not clear which app features are most beneficial.ObjectiveThis study aims to systematically review and evaluate high-quality apps for diabetes medication adherence, which are freely available to the public in Android and Apple app stores and present the technical features of the apps.MethodsWe systematically searched Apple App Store and Google Play for apps that assist in diabetes medication adherence, using predefined selection criteria. We assessed apps using the Mobile App Rating Scale (MARS) and calculated the mean app-specific score (MASS) by taking the average of app-specific scores on 6 dimensions, namely, awareness, knowledge, attitudes, intention to change, help-seeking, and behavior change rated on a 5-point scale (1=strongly disagree and 5=strongly agree). We used the mean of the app's performance on these 6 dimensions to calculate the MASS. Apps that achieved a total MASS mean quality score greater than 4 out of 5 were considered to be of high quality in our study. We formulated a task-technology fit matrix to evaluate the apps for diabetes medication adherence.ResultsWe identified 8 high-quality apps (MASS score≥4) and presented the findings under 3 main categories: characteristics of the included apps, app features, and diabetes medication adherence. Our framework to evaluate smartphone apps in promoting diabetes medication adherence considered physiological factors influencing diabetes and app features. On evaluation, we observed that 25% of the apps promoted high adherence and another 25% of the apps promoted moderate adherence. Finally, we found that 50% of the apps provided low adherence to diabetes medication.ConclusionsOur findings show that almost half of the high-quality apps publicly available for free did not achieve high to moderate medication adherence. Our framework could have positive implications for the future design and development of apps for patients with diabetes. Additionally, apps need to be evaluated using a standardized framework, and only those promoting higher medication adherence should be prescribed for better health outcomes.

Project description:Adherence to prescribed medication is suboptimal in 50% of the chronic population, resulting in negative medical and economic outcomes. With the widespread use of mobile phones worldwide, medication adherence apps for mobile phones become promising medication adherence aids thanks to simplicity, user-friendliness, and accessibility for the public. Yet, until today, there is insufficient evidence in favor of using mobile health (mHealth) apps to increase medication adherence. This study aims to develop a methodology for scientific and end-user (patient) mHealth evaluation (a) to identify medication adherence apps search terms, (b) to evaluate identified apps based on scientific criteria, and (c) to report best smartphone apps evaluated by patients. Search terms were identified via literature review and expertise. Firstly, an online questionnaire was developed to identify frequently used search terms by recruited patients. Related medication adherence apps were identified and selected using predefined inclusion criteria. Secondly, identified apps were evaluated thanks to a scientific evaluation method and a created online questionnaire for patient feedback. Recruited patients were invited to test and evaluate the selected apps. Out of 1,833 free-of-charge and 307 paid apps identified, only four free-of-charge and three paid apps remained included in the study after eligibility criteria. None of the selected app reached a high score. Looking at the overall scores, Medisafe (59%), MyTherapy (56%), and Meds on time (44%) received the highest scores in the scientific app evaluation. In the patient evaluation, Dosecast (3.83 out of five points), Medisafe (3.62), and SwissMeds (3.50) received the highest scores. None of the apps in this research has undergone a process for certification, for example, CE marking, through a notified body. Security and data protection aspects of existing apps highly contribute to these low evaluation scores through little information on patient's data processing and storage. This might be corrected through the introduction of General Data Protection Regulation (GDPR) in the European Economic Area (EEA) and more scrutiny through regulatory bodies in the EU/EEA and the USA. None of the applications should be recommended by healthcare providers. In addition, clinical studies with chronic patients are necessary to measure long-term app impacts.

Project description:BackgroundMedication adherence is critical to the effectiveness of psychopharmacologic therapy. Psychiatric disorders present special adherence considerations, notably an altered capacity for decision making and the increased street value of controlled substances. A wide range of interventions designed to improve adherence in mental health and substance use disorders have been studied; recently, many have incorporated information technology (eg, mobile phone apps, electronic pill dispensers, and telehealth). Many intervention components have been studied across different disorders. Furthermore, many interventions incorporate multiple components, making it difficult to evaluate the effect of individual components in isolation.ObjectiveThe aim of this study was to conduct a systematic scoping review to develop a literature-driven, transdiagnostic taxonomic framework of technology-based medication adherence intervention and measurement components used in mental health and substance use disorders.MethodsThis review was conducted based on a published protocol (PROSPERO: CRD42018067902) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review guidelines. We searched 7 electronic databases: MEDLINE, EMBASE, PsycINFO, the Cochrane Central Register of Controlled Trials, Web of Science, Engineering Village, and ClinicalTrials.gov from January 2000 to September 2018. Overall, 2 reviewers independently conducted title and abstract screens, full-text screens, and data extraction. We included all studies that evaluate populations or individuals with a mental health or substance use disorder and contain at least 1 technology-delivered component (eg, website, mobile phone app, biosensor, or algorithm) designed to improve medication adherence or the measurement thereof. Given the wide variety of studied interventions, populations, and outcomes, we did not conduct a risk of bias assessment or quantitative meta-analysis. We developed a taxonomic framework for intervention classification and applied it to multicomponent interventions across mental health disorders.ResultsThe initial search identified 21,749 results; after screening, 127 included studies remained (Cohen kappa: 0.8, 95% CI 0.72-0.87). Major intervention component categories include reminders, support messages, social support engagement, care team contact capabilities, data feedback, psychoeducation, adherence-based psychotherapy, remote care delivery, secure medication storage, and contingency management. Adherence measurement components include self-reports, remote direct visualization, fully automated computer vision algorithms, biosensors, smart pill bottles, ingestible sensors, pill counts, and utilization measures. Intervention modalities include short messaging service, mobile phone apps, websites, and interactive voice response. We provide graphical representations of intervention component categories and an element-wise breakdown of multicomponent interventions.ConclusionsMany technology-based medication adherence and monitoring interventions have been studied across psychiatric disease contexts. Interventions that are useful in one psychiatric disorder may be useful in other disorders, and further research is necessary to elucidate the specific effects of individual intervention components. Our framework is directly developed from the substance use disorder and mental health treatment literature and allows for transdiagnostic comparisons and an organized conceptual mapping of interventions.

Project description:IntroductionThe exact pathway linking health literacy, self-efficacy, medication adherence, and glycemic control for type 2 diabetes remains unclear. Understanding the relationship between patient factors, medication adherence, and lower glycated hemoglobin (HbA1c) may help patients better manage their disease. This study examined the association of health literacy and medication self-efficacy with self-reported diabetes medication adherence, and the association of health literacy, medication self-efficacy, and self-reported diabetes medication adherence with HbA1c of patients with type 2 diabetes.MethodsThis cross-sectional study utilized a face-to-face questionnaire at two family medicine clinics in a Midwestern state among 174 patients; subjects enrolled were at least 20 years old with diagnosed type 2 diabetes, prescribed at least one oral diabetes medicine, and understood English. Questionnaires were administered to assess the participants': health literacy, using the Newest Vital Sign six-item questionnaire (NVS); self-efficacy for medication use, using the 13-item Self-Efficacy for Appropriate Medication Use Scale; and self-report medication adherence, using the eight-item Morisky Medication Adherence Scale. HbA1c values were obtained from participants' electronic medical records. Multiple linear regressions were used to explore the association of health literacy and medication self-efficacy with both medication adherence and HbA1c level after controlling for all other covariates.ResultsSelf-reported health status (β = 0.17, p = 0.015) and medication self-efficacy (β = 0.53, p < 0.001) were positively associated with diabetes medication adherence. Health literacy was neither associated with diabetes medication adherence (β = -0.04, p = 0.586) nor HbA1c (β = -0.06, p = 0.542). Lower diabetes medication adherence (β = -0.26, p = 0.008) and higher number of prescribed medications (β = 0.28, p = 0.009) were correlated with higher HbA1c.ConclusionHealth literacy, as measured by the NVS, does not correlate with medication adherence or glycemic control among patients with type 2 diabetes. Interventions to improve patients' self-efficacy of medication use may improve diabetes medication adherence.

Project description:ObjectiveTo design and investigate a pharmacist-run intervention using low health literacy flashcards and a smartphone-activated quick response (QR) barcoded educational flashcard video to increase medication adherence and disease state understanding.DesignProspective, matched, quasi-experimental design.SettingCounty health system in Dallas, Texas.ParticipantsSixty-eight primary care patients prescribed targeted heart failure, hypertension, and diabetes medications INTERVENTION: Low health literacy medication and disease specific flashcards, which were also available as QR-coded online videos, were designed for the intervention patients. The following validated health literacy tools were conducted: Newest Vital Sign (NVS), Rapid Estimate of Adult Literacy Medicine-Short Form, and Short Assessment of Health Literacy-50.Main outcome measuresThe primary outcome was the difference in medication adherence at 180 days after pharmacist intervention compared with the control group, who were matched on the basis of comorbid conditions, targeted medications, and medication class. Medication adherence was measured using a modified Pharmacy Quality Alliance proportion of days covered (PDC) calculation. Secondary outcomes included 90-day PDC, improvement of greater than 25% in baseline PDC, and final PDC greater than 80%. Linear regression was performed to evaluate the effect of potential confounders on the primary outcome.ResultsOf the 34 patients receiving the intervention, a majority of patients scored a high possibility of limited health literacy on the NVS tool (91.2%). The medication with the least adherence at baseline was metformin, followed by angiotensin-converting enzyme inhibitors and beta blockers. At 180 days after intervention, patients in the intervention group had higher PDCs compared with their matched controls (71% vs. 44%; P = 0.0069).ConclusionThe use of flashcards and QR-coded prescription bottles for medication and disease state education is an innovative way of improving adherence to diabetes, hypertension, and heart failure medications in a low-health literacy patient population.

Dataset Information

Digital Health for Medication Adherence in Adult Diabetes or Hypertension: An Integrative Review.

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Digital Health for Medication Adherence in Adult Diabetes or Hypertension: An Integrative Review.

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