A review of features and characteristics of smart medication adherence products.
Ontology highlight
ABSTRACT: Background
Smart medication adherence products (smart MAPs) capture and transmit real-time medication intake by using various means of connectivity, allowing for remote monitoring. Numerous such products with different features are available to address medication nonadherence. A comparison of the features of these products is needed for clinical decision-making. Therefore, the objective of this review was to compare smart MAPs available for in-home use.Methods
We searched grey and published literature and videos to identify smart MAPs. To be considered smart, products required 2 features: connectivity (the ability for collected data to exist outside the physical device) and automaticity (the ability for data to be analyzed or processed automatically). Products were excluded if product descriptions were not available in English, not for in-home use and unable to dispense medications.Results
Of the 51 products identified, 38 commercially available and 13 prototypes met the definition. Of these, 75% (n = 38) contained alarms, 24% (n = 12) were unit-dose, 63% (n = 32) were multidose, 43% (n = 22) had locking features, 41% (n = 21) were portable and 88% (n = 45) sent notifications to patients. The cost of marketed products, excluding subscriptions, ranged from $10 to $1500 USD. Some products required a monthly (n = 16) or yearly (n = 1) subscription ranging from $10 to $100 USD.Discussion
There is a growing market of smart MAPs for in-home patient use with variable features. Clinicians can use these features to identify and recommend products according to the specific needs of their patients to address medication adherence. Can Pharm J (Ott) 2021;154:xx-xx.
SUBMITTER: Faisal S
PROVIDER: S-EPMC8408912 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Glaucoma, the leading cause of irreversible blindness, affects >70 million people worldwide. Lowering intraocular pressure via topical administration of eye drops is the most common first-line therapy for glaucoma. This treatment paradigm has notoriously high non-adherence rates: ranging from 30% to 80%. The advent of smart phone enabled technologies creates promise for improving eyedrop adherence. However, previous eyedrop electronic monitoring solutions had awkward medication bottle adjuncts and crude software for monitoring the administration of a drop that adversely affected their ability to foster sustainable improvements in adherence. The current work begins to address this unmet need for wireless technology by creating a "smart drop" bottle. This medication bottle is instrumented with sensing electronics that enable detection of each eyedrop administered while maintaining the shape and size of the bottle. This is achieved by a thin electronic force sensor wrapped around the bottle and underneath the label, interfaced with a thin electronic circuit underneath the bottle that allows for detection and wireless transmission to a smart-phone application. We demonstrate 100% success rate of wireless communication over 75 feet with <1% false positive and false negative rates of single drop deliveries, thus providing a viable solution for eyedrop monitoring for glaucoma patients.
| S-EPMC7248824 | biostudies-literature
Project description:Medication adherence is an expensive and damaging problem for patients and health care providers. Patients adhere to only 50% of drugs prescribed for chronic diseases in developed nations. Digital health has paved the way for innovative smartphone solutions to tackle this challenge. However, despite numerous apps available claiming to improve adherence, a thorough review of adherence apps has not been carried out to date.The aims of this study were to (1) review medication adherence apps available in app repositories in terms of their evidence base, medical professional involvement in development, and strategies used to facilitate behavior change and improve adherence and (2) provide a system of classification for these apps.In April 2015, relevant medication adherence apps were identified by searching the Apple App Store and the Google Play Store using a combination of relevant search terms. Data extracted included app store source, app price, documentation of health care professional (HCP) involvement during app development, and evidence base for each respective app. Free apps were downloaded to explore the strategies used to promote medication adherence. Testing involved a standardized medication regimen of three reminders over a 4-hour period. Nonadherence features designed to enhance user experience were also documented.The app repository search identified a total of 5881 apps. Of these, 805 fulfilled the inclusion criteria initially and were tested. Furthermore, 681 apps were further analyzed for data extraction. Of these, 420 apps were free for testing, 58 were inaccessible and 203 required payment. Of the 420 free apps, 57 apps were developed with HCP involvement and an evidence base was identified in only 4 apps. Of the paid apps, 9 apps had HCP involvement, 1 app had a documented evidence base, and 1 app had both. In addition, 18 inaccessible apps were produced with HCP involvement, whereas 2 apps had a documented evidence base. The 420 free apps were further analyzed to identify strategies used to improve medication adherence. This identified three broad categories of adherence strategies, reminder, behavioral, and educational. A total of 250 apps utilized a single method, 149 apps used two methods, and only 22 apps utilized all three methods.To our knowledge, this is the first study to systematically review all available medication adherence apps on the two largest app repositories. The results demonstrate a concerning lack of HCP involvement in app development and evidence base of effectiveness. More collaboration is required between relevant stakeholders to ensure development of high quality and relevant adherence apps with well-powered and robust clinical trials investigating the effectiveness of these interventions. A sound evidence base will encourage the adoption of effective adherence apps, and thus improve patient welfare in the process.
| S-EPMC5878368 | biostudies-literature
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.
| S-EPMC9257622 | biostudies-literature
Project description:BACKGROUND:Use of cardiovascular medication has increased over time, especially for primary and secondary prevention, with polypharmacy common. METHODS:Review of published systematic reviews of the factors and outcomes associated with adherence to cardiovascular medication using MEDLINE, Embase, CINAHL and PsycINFO databases. Quality was assessed using the AMSTAR tool. RESULTS:Of 789 systematic reviews identified, 45 met the inclusion criteria and passed the quality assessment; 34 focused on factors associated with adherence, and 11 on outcomes. High heterogeneity, both between and within reviews, precluded meta-analysis and so a pooled estimate of adherence levels could not be derived. Adherence was associated with disease factors, therapy factors, healthcare factors, patient factors and social factors, though with some inconsistencies. In total, 91% of reviews addressing outcomes reported that low adherence was associated with poorer clinical and economic endpoints. CONCLUSIONS:Factors from across five key domains relate to non-adherence to cardiovascular medications, and may contribute to poorer clinical outcomes. Interventions to improve adherence should be developed to address modifiable factors and targeted at those at highest risk of non-adherence. Adherence research is highly heterogeneous to-date and efforts to standardize this should be implemented to improve comparability.
| S-EPMC6459362 | biostudies-literature
Project description:BackgroundThis systematic review examined the reliability and validity of the Morisky Medication Adherence Scale-8 (MMAS-8), which has been widely used to assess patient medication adherence in clinical research and medical practice.MethodsOf 418 studies identified through searching 4 electronic databases, we finally analyzed 28 studies meeting the selection criteria of this study regarding the reliability and validity of MMAS-8 including sensitivity and specificity. Meta-analysis for Cronbach's ?, intraclass correlation coefficient (ICC), sensitivity and specificity to detect a patient with nonadherence to medication were performed. The pooled estimates for Cronbach's ? and ICC were calculated using the random-effects weighted T transformation. A bivariate random-effects model was used to estimate pooled sensitivity and specificity.FindingsThe pooled Cronbach's ? estimate for type 2 diabetes group in 7 studies and osteoporosis group in 3 studies were 0.67 (95% Confidence Interval(CI), 0.65 to 0.69) and 0.77 (95% CI, 0.72 to 0.83), respectively. With regard to test-retest, the pooled ICC for type 2 diabetes group in 3 studies and osteoporosis group in 2 studies were 0.81 (95% CI, 0.75 to 0.85) and 0.80 (95% CI, 0.74 to 0.85). For a cut-off value of 6, the pooled sensitivity and specificity in 12 studies were 0.43 (95% CI, 0.33 to 0.53) and 0.73 (95% CI, 0.68 to 0.78), respectively.ConclusionsThe MMAS-8 had acceptable internal consistency and reproducibility in a few diseases like type 2 diabetes. Using the cut-off value of 6, criterion validity was not enough good to validly screen a patient with nonadherence to medication. However, this study did not calculated a pooled estimate for criterion validity using the higher values than 6 as a cut-off value since most of included individual studies did not report criterion validity based on those values.
| S-EPMC5667769 | biostudies-literature
Project description:Effective antiretroviral therapy has led to substantial improvements in health-related outcomes among individuals with HIV. Despite advances in HIV pharmacotherapy, suboptimal medication adherence remains a significant barrier to successful treatment. Although several factors have been associated with medication adherence in the extant literature, study assessing the effects of some of the neurobehavioral features specific to HIV has been limited. Moreover, although there is a growing body of literature measuring medication adherence in HIV prospectively, few employ advanced statistical methodologies suited to handle advanced models with multiple predictors that would strengthen our understanding of medication adherence trajectories in HIV. This study sought to integrate traditionally assessed predictors of medication adherence with neurobehavioral features of HIV in a longitudinal study of medication adherence to combined antiretroviral therapy (cART). The current study used multilevel modeling to examine a wide arrangement of categories of factors - demographic, medication related, psychosocial, and neurobehavioral - on medication adherence. The sample consisted of 235 HIV+ individuals whose medication adherence was monitored over the course of six months using electronic monitoring devices. After controlling for the effects of demographic, medication, and psychosocial factors, neurobehavioral features added predictive validity to the model. In the final model, simultaneously controlling for the effects of each of the predictors within all the categories, age, self-efficacy, executive functioning, apathy, and frequency of stimulant use emerged as unique individual predictors of average medication adherence across the 6-month study. Self-efficacy and irritability predicted changes in medication adherence over time. Adherence behavior is multidetermined. Adequate assessment of these factors, combined with timely intervention, appears to be warranted in order to boost adherence rates.
| S-EPMC4408322 | biostudies-literature
Project description:OBJECTIVE:This review aims to inform research and clinical care on the current state of knowledge on the relationship between positive affect and medication adherence. METHOD:Searches were carried out in PsycINFO, PubMed MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL, and Embase. There were no limits on study type, publication date, language, or participant demographics. Studies reporting a relationship between positive affect and medication adherence were eligible for inclusion if positive affect was measured prior to or concurrently with medication adherence. RESULTS:Nine studies met inclusion criteria. All studies were prospective cohort or cross-sectional and examined positive affect and medication adherence in people living with HIV or cardiovascular conditions. The majority of results indicated positive associations between positive affect and medication adherence, with Cohen's d effect sizes ranging from -0.40 to 1.27. CONCLUSIONS:Consistent with previous theoretical work, this systematic review provides evidence of a link between positive affect and improved medication adherence. Better measurement of both affect and medication adherence across chronic conditions is an important focus for future research and will inform targeted interventions to improve adherence and, ultimately, decrease the morbidity, mortality, and cost associated with suboptimal adherence in chronic physical conditions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
| S-EPMC6800780 | biostudies-literature
Project description:Adherence to medication among individuals with chronic obstructive pulmonary disease (COPD) is suboptimal and has negative impacts on survival and health care costs. No systematic review has examined the effectiveness of interventions designed to improve medication adherence. Electronic databases Medline and Cochrane were searched using a combination of MeSH and keywords. Eligible studies were interventions with a primary or secondary aim to improve medication adherence among individuals with COPD published in English. Included studies were assessed for methodological quality using the Effective Practice and Organisation of Care (EPOC) criteria. Of the 1,186 papers identified, seven studies met inclusion criteria. Methodological quality of the studies was variable. Five studies identified effective interventions. Strategies included: brief counselling; monitoring and feedback about inhaler use through electronic medication delivery devices; and multi-component interventions consisting of self-management and care co-ordination delivered by pharmacists and primary care teams. Further research is needed to establish the most effective and cost effective interventions. Special attention should be given to increasing patient sample size and using a common measure of adherence to overcome methodological limitations. Interventions that involve caregivers and target the healthcare provider as well as the patient should be further explored.
| S-EPMC4015036 | biostudies-literature
Project description:BackgroundMedication adherence is important in managing the progression of chronic diseases. A promising approach to reduce cognitive burden when measuring medication adherence lies in the use of computer-adaptive tests (CATs) or in the development of shorter patient-reported outcome measures (PROMs). However, the lack of an item bank currently hampers this progress.ObjectiveWe aim to develop an item bank to measure general medication adherence.MethodsUsing the preferred reporting items for systematic review and meta-analysis (PRISMA), articles published before October 2019 were retrieved from PubMed, Embase, CINAHL, the Cochrane Library, and Web of Science. Items from existing PROMs were classified and selected ("binned" and "winnowed") according to standards published by the Patient-Reported Outcomes Measurement Information System (PROMIS) Cooperative Group.ResultsA total of 126 unique PROMs were identified from 213 studies in 48 countries. Items from the literature review (47 PROMs with 579 items for which permission has been obtained) underwent binning and winnowing. This resulted in 421 candidate items (77 extent of adherence and 344 reasons for adherence).ConclusionsWe developed an item bank for measuring general medication adherence using items from validated PROMs. This will allow researchers to create new PROMs from selected items and provide the foundation to develop CATs.
| S-EPMC7582150 | biostudies-literature
Project description:Background: In pharmacotherapy, the achievement of a target clinical outcome requires a certain level of medication intake or adherence. Based on Haynes's early empirical definition of sufficient adherence to antihypertensive medications as taking ≥80% of medication, many researchers used this threshold to distinguish adherent from non-adherent patients. However, we propose that different diseases, medications and patient's characteristics influence the cut-off point of the adherence rate above which the clinical outcome is satisfactory (thereafter medication adherence threshold). Moreover, the assessment of adherence and clinical outcomes may differ greatly and should be taken into consideration. To our knowledge, very few studies have defined adherence rates linked to clinical outcomes. We aimed at investigating medication adherence thresholds in relation to clinical outcomes. Method: We searched for studies that determined the relationship between adherence rates and clinical outcomes in the databases PubMed, EmbaseⓇ and Web of Science™ until December 2017, limited to English-language. Our outcome measure was any threshold value of adherence. The inclusion criteria of the retrieved studies were (1) any measurement of medication adherence, (2) any assessment of clinical outcomes, and (3) any method to define medication adherence thresholds in relation to clinical outcomes. We excluded articles considered as a tutorial. Two authors (PB and IA) independently screened titles and abstracts for relevance, reviewed full-texts, and extracted items. The results of the included studies are presented qualitatively. Result: We analyzed 6 articles that assessed clinical outcomes linked to adherence rates in 7 chronic disease states. Medication adherence was measured with Medication Possession Ratio (MPR, n = 3), Proportion of Days Covered (PDC, n = 1), both (n = 1), or Medication Event Monitoring System (MEMS). Clinical outcomes were event free episodes, hospitalization, cortisone use, reported symptoms and reduction of lipid levels. To find the relationship between the targeted clinical outcome and adherence rates, three studies applied logistic regression and three used survival analysis. Five studies defined adherence thresholds between 46 and 92%. One study confirmed the 80% threshold as valid to distinguish adherent from non-adherent patients. Conclusion: The analyzed studies were highly heterogeneous, predominantly concerning methods of calculating adherence. We could not compare studies quantitatively, mostly because adherence rates could not be standardized. Therefore, we cannot reject or confirm the validity of the historical 80% threshold. Nevertheless, the 80% threshold was clearly questioned as a general standard.
| S-EPMC6256123 | biostudies-literature