Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review

What are the barriers to upper limb splint adherence, and how is adherence measured? A systematic review

Introduction

Non-adherence to splint wearing following an upper limb traumatic injury is a significant medical issue. Optimal outcome following such injuries relies on people adhering to the prescribed splint, and a failure to do so can negatively impact outcome and increase healthcare burden and costs. This systematic review aims to compare and synthesise the evidence related to measuring adherence to wear recommendations and the barriers to splint wearing following upper limb trauma in adults.

Methods

Databases (EBSCO, PubMed, EMBASE and Science Direct) were systematically searched for articles that met the pre-agreed eligibility criteria between February and May 2023. Data on study characteristics and reported outcomes relating to measuring and quantifying splint adherence and barriers to adherence were extracted.

Results

A total of 16 articles were included for final review. Several methods were used to measure adherence, with no single tool used predominantly. These included patient or therapist reported data, preexisting classification systems and an electronic device. Methods used to quantify adherence was also heterogenous in nature, and a range of investigator and patient reported barriers to splint wearing were reported.

Conclusion

This review demonstrates heterogeneity in both classifying and measuring splint adherence, as well as in the barriers to splint wearing reported. Moving forward, using agreed measurement and reporting practices for splint adherence will enable researchers to complete high quality trials to determine splinting outcomes, and may ultimately enable health care professionals to improve adherence and, subsequently, outcomes in clinical practice.

Description of self-care behaviours in patients with non-valvular atrial fibrillation on oral anticoagulant therapy: a scoping review

AIMS

The primary aim of this scoping review was to explore and categorize the medication-related self-care behaviours exhibited by patients with non-valvular atrial fibrillation (NVAF) who are on oral anticoagulant (OAC) therapy.

METHODS AND RESULTS

A scoping review was performed, and the systematic search of the literature yielded an initial 887 records. After deduplication and screening, 61 studies were included in the analysis, ranging from 2003 to 2023. The studies represented a wide geographical distribution and diverse methodologies. The results identified 16 self-care behaviours: a higher focus of the included literature on self-care monitoring (60.65% of studies), followed by self-care management and self-care maintenance (each 16.39%). These behaviours ranged from regular blood testing to consulting healthcare providers and lifestyle changes. The results also highlighted the relationship between treatment satisfaction, self-efficacy, and adherence. Several studies emphasized the critical role of healthcare providers in influencing medication adherence. Furthermore, patient knowledge, quality of life, and psychological factors were identified as key elements affecting self-care behaviours.

CONCLUSION

The review provides a comprehensive landscape of medication-related self-care behaviours among NVAF patients on OAC therapy. It underscores the predominance of self-care monitoring behaviours and the critical roles of healthcare providers, psychological factors, and patient knowledge in influencing these behaviours. The findings also highlight the necessity for an integrated, patient-centred approach to improving self-care and self-management in OAC treatment. Future research should focus on addressing the identified gaps, including the relative lack of studies on lifestyle modification, emotional well-being, and technology-assisted interventions.

REGISTRATION

This review is part of a broader project and is documented at ClinicalTrials.gov: NCT05820854.

The OPAT opportunity for beta-lactam individualization

Beta-lactam therapeutic drug monitoring has been growing in prevalence in the acute care hospital setting. Expansion of its use to outpatient parenteral antimicrobial therapy requires careful consideration of potential logistical and therapeutic barriers.

Interventions to promote medication adherence among children with epilepsy: An integrative review

PROBLEM

Many children with epilepsy face challenges in adhering to their medication, leading to inadequate seizure control. However, the most effective intervention is still unclear. This integrative review's main goal was to examine and synthesize the existing literature on interventions for promoting medication adherence in children with epilepsy.

ELIGIBILITY CRITERIA

This integrative review followed Whittemore and Knafl's five-stage framework. Four electronic databases (PubMed, ScienceDirect, Scopus, and CINAHL Complete) were systematically searched from 2013 until 2024 to identify eligible studies published in the English language. The key search terms included "Children with epilepsy" AND "medication adherence" AND "intervention." Studies reporting on the implementation and evaluation of medication adherence interventions in children with epilepsy were eligible. Quality assessment and narrative synthesis were subsequently undertaken.

SAMPLE

A total of 17 studies were included in the review.

RESULTS

Five interventions were found, including educational, behavioral, and mixed intervention types, using technology and family involvement. Promoting medication adherence is crucial, but tailored interventions for different age groups and sustained support are needed.

CONCLUSIONS

Promoting medication adherence is of utmost importance to enhance the knowledge of children who have epilepsy and their families, and to increase medication adherence. However, there is still a need to develop interventions that are appropriate for children of different ages and their families, which should be suitable and sustainable during treatment.

IMPLICATIONS

Pediatric nurses should consider socioeconomic factors, ethnicity, family functioning, and parental distress. Strategies include monitoring adherence, continuous communication, and technology support for children with epilepsy during treatment.

Sea Horse Optimization-Deep Neural Network: A Medication Adherence Monitoring System Based on Hand Gesture Recognition

Medication adherence is an essential aspect of healthcare for patients and is important for achieving medical objectives. However, the lack of standard techniques for measuring adherence is a global concern, making it challenging to accurately monitor and measure patient medication regimens. The use of sensor technology for medication adherence monitoring has received much attention lately since it makes it possible to continuously observe patients' medication adherence behavior. Sensor devices or smart wearables utilize state-of-the-art machine learning (ML) methods to analyze intricate data patterns and provide predictions accurately. The key aim of this work is to develop a sensor-based hand gesture recognition model to predict medication activities. In this research, a smart sensor device-based hand gesture prediction model is developed to recognize medication intake activities. The device includes a tri-axial gyroscope, geometric, and accelerometer sensors to sense and gather data from hand gestures. A smartphone application gathers hand gesture data from the sensor device, which is then stored in the cloud database in a .csv format. These data are collected, processed, and classified to recognize the medication intake activity using the proposed novel neural network model called Sea Horse Optimization-Deep Neural Network (SHO-DNN). The SHO technique is implemented to update the biases and weights and the number of hidden layers in the DNN model. By updating these parameters, the DNN model is improved in classifying the samples of hand gestures to identify the medication activities. The research model demonstrates impressive performance, with an accuracy of 98.59%, sensitivity of 97.82%, precision of 98.69%, and an F1 score of 98.48%. Hence, the proposed model outperformed the most available models in all the aforementioned aspects. The results indicate that this model is a promising approach for medication adherence monitoring in healthcare applications, instilling confidence in its effectiveness.

Pan-European survey on medication adherence management by healthcare professionals

AIMS

While medication adherence (MA) is a key prerequisite for achieving optimal clinical and economic outcomes, nonadherence is highly prevalent. Assessing how healthcare professionals (HCPs) in Europe manage MA, focusing on measurement, reporting and interventions, is the subject of this study.

METHODS

A cross-sectional study was conducted among 40 European countries and quantitative analysis was conducted via an online survey. The multi-language online survey was created using Webropol 3.0 survey and reporting tool. Descriptive statistics and chi-squared tests were applied.

RESULTS

In total, 2875 HCPs (pharmacists: 39.9%; physicians: 36.7%; nurses: 16.4%) from 37 European countries participated. The most used methods for MA assessment were direct communication with patients (86.4%) and referring to personal patient records (56.7%) (P < 0.0001). Physicians (74.9%) and nurses (58.8%) were more aware of problems related to MA in contrast to pharmacists (48.6%) (P < 0.001). Almost all HCPs (92.6%) indicated that MA-enhancing interventions involved mainly direct communication with nonadherent patients (93.3%) and their caregivers (55.7%). Medication review and related optimization of therapy were mainly performed in Western European countries (46.8%). Technological solutions were ranked as one of the less applied approaches (10-15%) (P < 0.001).

CONCLUSIONS

HCPs in all European regions recognize MA management as an integral element of overall patient-centred care. More efforts are needed to ensure timely, adequate and relevant MA assessment, reporting and improvement and involvement of all HCPs, especially among pharmacists who were generally less aware of MA issues. Promotion and use of digital technological solutions should be the focus of current and future clinical practice to optimize MA management processes.

Development and Validation of a Tool to Explore Attitudes Towards meDication adHErence Using a Novel Self-Reported QuestionnairE (ADHERE-7)

Despite the availability of various tools for measuring medication adherence, efficiently identifying non-adherence levels and reasons at the point of care remains challenging. Existing tools often lack the ease of use needed for practical clinical application. This study aimed to develop and validate a user-friendly tool to provide healthcare professionals with a concise yet comprehensive means of identifying adherence behaviors. The methodology consisted of two phases: tool items were first developed using the nominal group technique with healthcare professionals, followed by a cross-sectional pilot study involving community-dwelling adults in Croatia. Validation analysis indicated acceptable face and content validity and satisfactory criterion validity, with Attitudes towards meDication adHErence self-Reported questionnairE (ADHERE-7) scores correlating with both the self-reported five-item Medication Adherence Report Scale (MARS-5 tool) (ρ = 0.765; p < 0.001) and an objective measure of the proportion of days covered (PDC) from pharmacy prescription claims data (G = 0.586; p = 0.015). Construct validity revealed three factors: Aversion, Comfort, and Practical Non-Adherence, with Cronbach's alpha values of 0.617 for Aversion and 0.714 for Comfort Non-Adherence. The mean total score for ADHERE-7 was 26.27 ± 2.41 (range 17 to 28). This robust validation process confirms the ADHERE-7 tool as a reliable instrument for assessing medication adherence, addressing aversion, comfort, practical issues, and both intentional and unintentional nonadherence.

Construction and application of medication reminder system: intelligent generation of universal medication schedule

BACKGROUND

Patients with chronic conditions need multiple medications daily to manage their condition. However, most patients have poor compliance, which affects the effectiveness of treatment. To address these challenges, we establish a medication reminder system for the intelligent generation of universal medication schedule (UMS) to remind patients with chronic diseases to take medication accurately and to improve safety of home medication.

METHODS

To design medication time constraint with one drug (MTCOD) for each drug and medication time constraint with multi-drug (MTCMD) for each two drugs in order to better regulate the interval and time of patients' medication. Establishment of a medication reminder system consisting of a cloud database of drug information, an operator terminal for medical staff and a patient terminal.

RESULTS

The cloud database has a total of 153,916 pharmaceutical products, 496,708 drug interaction data, and 153,390 pharmaceutical product-ingredient pairs. The MTCOD data was 153,916, and the MTCMD data was 8,552,712. An intelligent UMS medication reminder system was constructed. The system can read the prescription information of patients and provide personalized medication guidance with medication timeline for chronic patients. At the same time, patients can query medication information and get remote pharmacy guidance in real time.

CONCLUSIONS

Overall, the medication reminder system provides intelligent medication reminders, automatic drug interaction identification, and monitoring system, which is helpful to monitor the entire process of treatment in patients with chronic diseases.

Healthcare professionals' perspectives towards the digitalisation of paediatric growth hormone therapies: expert panels in Italy and Korea

Introduction

To analyse the perspectives of healthcare professionals (HCPs) regarding the acceptance of digital health solutions for growth hormone (GH) deficiency care. This study identified factors impacting HCPs' intent to use and recommend digital solutions supporting recombinant-human growth hormone (r-hGH) therapy in Italy and Korea with a use case of connected drug delivery system (Aluetta® with Smartdot™) integrated in a platform for GH treatment support (the Growzen™ digital health ecosystem).

Methods

Participatory workshops were conducted in Rome, Italy, and Seoul, Korea, to collect the perspectives of 22 HCPs on various predefined topics. HCPs were divided into two teams, each moderated by a facilitator. The workshops progressed in five phases: introduction of the project and experts, capturing views on the current context of digitalisation, perceived usefulness and ease of use of Aluetta® with Smartdot™, exploration of the perception of health technology evolution, and combined team recommendations. Data shared by HCPs on technology acceptance were independently analysed using thematic analysis, and relevant findings were shared and validated with experts.

Results

HCPs from both Italy and Korea perceived Aluetta® with Smartdot™ and the Growzen™ based digital health ecosystem as user-friendly, intuitive, and easy-to-use solutions. These solutions can result in increased adherence, a cost-effective healthcare system, and medication self-management. Although technology adoption and readiness may vary across countries, it was agreed that using digital solutions tailored to the needs of users may help in data-driven clinical decisions and strengthen HCP-patient relationships.

Conclusion

HCPs' perspectives on the digitalisation in paediatric GH therapies suggested that digital solutions enable automatic, real-time injection data transmission to support adherence monitoring and evidence-based therapy, strengthen HCP-patient relationships, and empower patients throughout the GH treatment process.

Association Between Symptom Severity and Medication Adherence in Adults with Bipolar Disorder Reporting Adherence Challenges

Background

Given the importance of medication adherence among individuals with bipolar disorder (BD), this analysis from an ongoing randomized controlled trial (RCT) examined the relationship between BD symptoms, functioning and adherence in 69 poorly adherent adults with BD.

Method

Study inclusion criteria included being ≥ 18 years old with BD Type 1 or 2, difficulties with medication adherence and actively symptomatic as measured by Brief Psychiatric Rating Scale (BPRS) score ≥ 36, Young Mania Rating Scale (YMRS) > 8 or Montgomery Asberg Depression Rating Scale (MADRS) > 8. Adherence was measured in 2 ways: 1) the self-reported Tablets Routine Questionnaire (TRQ) and 2) electronic pill container monitoring (eCap pillbox). BD symptoms and functioning were measured with the MADRS, YMRS, Clinical Global Impressions Scale (CGI), and Global Assessment of Functioning (GAF). Only screening and baseline data were examined.

Results

Mean age was 42.32 (SD = 12.99) years, with 72.46% (n = 50) female and 43.48% (n = 30) non-white. Mean past 7-day percentage of days with missed BD medications using TRQ was 40.63% (SD = 32.61) and 30.30% (SD = 30.41) at screening and baseline, respectively. Baseline adherence using eCap was 42.16% (SD = 35.85) in those with available eCap data (n = 41). Worse adherence based on TRQ was significantly associated with higher MADRS (p = 0.04) and CGI (p = .03) but lower GAF (p = 0.02). eCAP measured adherence was not significantly associated with clinical variables.

Conclusion

While depression and functioning were approximate markers of adherence, reliance on patient self-report or BD symptom presentation may give an incomplete picture of medication-taking behaviors.

Digital measures in epilepsy in low-resourced environments

INTRODUCTION

Digital measures and digital health-care delivery have been rarely implemented in lower-and-middle-income countries (LMICs), contributing to worsening global disparities and inequities. Sustainable ways to implement and use digital approaches will help to improve time to access, management, and quality of life in persons with epilepsy, goals that remain unreachable in under-resourced communities. As under-resourced environments differ in human and economic resources, no one approach will be appropriate to all LMICs.

AREAS COVERED

Digital health and tools to monitor and measure digital endpoints and metrics of quality of life will need to be developed or adapted to the specific needs of under-resourced areas. Portable technologies may partially address the urban-rural divide. Careful delineation of stakeholders and their engagement and alignment in all efforts is critically important if these initiatives are to be successfully sustained. Privacy issues, neglected in many regions globally, must be purposefully addressed.

EXPERT OPINION

Epilepsy care in under-resourced environments has been limited by the lack of relevant technologies for diagnosis and treatment. Digital biomarkers, and investigative technological advances, may finally make it feasible to sustainably improve care delivery and ultimately quality of life including personalized epilepsy care.

Using a Semiautomated Procedure (CleanADHdata.R Script) to Clean Electronic Adherence Monitoring Data: Tutorial

BACKGROUND

Patient adherence to medications can be assessed using interactive digital health technologies such as electronic monitors (EMs). Changes in treatment regimens and deviations from EM use over time must be characterized to establish the actual level of medication adherence.

OBJECTIVE

We developed the computer script CleanADHdata.R to clean raw EM adherence data, and this tutorial is a guide for users.

METHODS

In addition to raw EM data, we collected adherence start and stop monitoring dates and identified the prescribed regimens, the expected number of EM openings per day based on the prescribed regimen, EM use deviations, and patients' demographic data. The script formats the data longitudinally and calculates each day's medication implementation.

RESULTS

We provided a simulated data set for 10 patients, for which 15 EMs were used over a median period of 187 (IQR 135-342) days. The median patient implementation before and after EM raw data cleaning was 83.3% (IQR 71.5%-93.9%) and 97.3% (IQR 95.8%-97.6%), respectively (Δ+14%). This difference is substantial enough to consider EM data cleaning to be capable of avoiding data misinterpretation and providing a cleaned data set for the adherence analysis in terms of implementation and persistence.

CONCLUSIONS

The CleanADHdata.R script is a semiautomated procedure that increases standardization and reproducibility. This script has broader applicability within the realm of digital health, as it can be used to clean adherence data collected with diverse digital technologies.

Transplant recipient, care partner, and clinician perceptions of medication adherence monitoring technology: A mixed methods study

Medication nonadherence is a leading cause of graft loss. Adherence monitoring technologies-reminder texts, smart bottles, video-observed ingestion, and digestion-activated signaling pills-may support adherence. However, patient, care partner, and clinician perceptions of these tools are not well studied. We conducted qualitative individual semistructured interviews and focus groups among 97 participants at a single center: kidney and liver transplant recipients 2 weeks to 18 months posttransplant, their care partners, and transplant clinicians. We assessed adherence practices, reactions to monitoring technologies, and opportunities for care integration. One-size-fits-all approaches were deemed infeasible. Interviewees considered text messages the most acceptable approach; live video checks were the least acceptable and raised the most concerns for inconvenience and invasiveness. Digestion-activated signaling technology produced both excitement and apprehension. Patients and care partners generally aligned in perceptions of adherence monitoring integration into clinical care. Key themes were importance of routine, ease of use, leveraging technology for actionable medication changes, and aversion to surveillance. Transplant clinicians similarly considered text messages most acceptable and video checks least acceptable. Clinicians reported that early posttransplant use and real-time adherence tracking with patient feedback may facilitate successful implementation. The study provides initial insights that may inform future adherence technology implementation.

The Effectiveness of Cognitive-Focused Interventions for Adults With Diabetes: A Systematic Review

BACKGROUND

Adults with diabetes and impaired memory and executive functions are more likely to experience difficulties in diabetes self-management and achieving glycemic targets. The purpose of this systematic review was to evaluate the evidence of the effects of cognitive-focused interventions on cognitive ability, diabetes self-management, and management of glycemic levels for middle-aged adults and older adults with diabetes.

METHODS

A systematic review of randomized controlled/clinical trials published in English between 2012 and 2022 was conducted. A search was performed using 5 databases (PubMed, CINAHL, Embase, Web of Science, and Scopus) in addition to hand-searching. The search terms included diabetes, adults, cognitive-focused intervention, cognition, self-management, and hemoglobin A1C (HbA1C).

RESULTS

Eleven studies met the inclusion criteria. Cognitive ability and diabetes self-management were assessed using different measurements, and glycemic levels were measured with HbA1C. Nine studies applied cognitive training, one provided working memory training, and one used occupational therapy. Eight studies combined cognitive training with a co-intervention, including self-efficacy, lifestyle management, physical training, chronic disease self-management program, square-stepping exercise, psychoeducational intervention, and empowerment. Eight studies showed statistically significant improvements in at least one cognitive domain.

CONCLUSIONS

Cognitive-focused interventions have a positive effect on improving memory and executive function. However, the evidence of cognitive-focused interventions on diabetes self-management and glycemic levels has not been established. Future studies to improve cognition using effective strategies to improve cognitive function enhancing diabetes self-management behaviors and managing glycemic levels are warranted.

Growth of Remote Therapeutic Monitoring Lands New Opportunities for Case Management

PURPOSE/OBJECTIVES

An increase in the use of remote therapeutic monitoring (RTM) has been spurred by nationwide factors including the COVID-19 pandemic, authorized reimbursement of RTM by the Centers for Medicare & Medicaid Services, and more frequent use of big data analytics in health care delivery. This article discusses the use of RTM by care teams at the point of care and explores the role of the case manager in RTM to address patients' unmet needs.

PRIMARY PRACTICE SETTINGS

Although RTM may be utilized across inpatient and outpatient levels of care, this article focuses on outpatient care such as community clinics, provider groups, and home health care.

FINDINGS/CONCLUSIONS

When implemented along with care management interventions, RTM applications have the potential to improve patient adherence, enhance communication between patients and their providers, streamline resource allocation, and address social determinants of health impacting patient care and outcomes.

IMPLICATIONS FOR CASE MANAGEMENT PRACTICE

RTM reimbursement models are rapidly evolving, utilizing real-world and patient-reported data to identify and initiate timely, individualized solutions that meet the holistic needs of each patient. Use of an RTM system allows the case manager to build rapport with the patient while quickly identifying care gaps and delivering appropriate interventions that can maximize patient outcomes. RTM can drive savings and bring revenue to the system or practice while providing salient documentation of social determinants of health that can be addressed with validation of proven care coordination interventions.

The three-item patient-reported instrument for retrospective adherence in resource constrained settings: reliability, validity and potential utility

INTRODUCTION

Patient-report instruments remain the most feasible and sustainable approaches for monitoring medication adherence in clinical settings. However, questions of their reliability and validity persist. Studies suggest that the 3-item instrument for retrospective adherence (IRA) developed by Wilson et al. offers a viable option for clinically monitoring medication adherence. Here we report the reliability and validity of the IRA among patients recruited from community-based HIV clinics and antiretroviral therapy (ART) dispensaries in a resource constrained township in Cape Town, South Africa.

METHODS

Women (n = 794) and men (n = 228) receiving ART completed the IRA at three time points: (a) in a face-to-face administration at enrollment (b) in1-week phone interview and (c) 1-month phone interview. Participants also provided contemporaneous blood samples for HIV viral load testing as a clinical outcome and unannounced phone-based pill counts as an objective assessment of ART adherence.

RESULTS

The IRA was internally consistent and showed evidence of time stability. The IRA also demonstrated validity with respect to pill count adherence, correlates of adherence, and HIV viral load. Response operating curve analysis yielded an area under the curve of 0.646, using 75% adherence as the cut-off, with 0.637 sensitivity and 0.567 specificity.

CONCLUSIONS

The IRA demonstrated reliability, construct validity and criterion validity in a resource constrained setting, supporting use of the IRA in research and clinical care.

Robotic Pills as Innovative Personalized Medicine Tools: A Mini Review

The most common route for drug administration is the oral route due to the various advantages offered by this route, such as ease of administration, controlled and sustained drug delivery, convenience, and non-invasiveness. In spite of this, oral drug absorption faces challenges due to various issues related to its stability, permeability and solubility in the GI tract. Biologic drugs generally face problems when administered by oral route as they are readily degradable and thus required to be injected. To overcome these issues in oral absorption, different approaches like novel drug delivery systems and newer pharmaceutical technologies have been adopted. With a combined knowledge of drug delivery and pharmaceutical technology, robotic pills can be designed and used successfully to enhance the adhesion and permeation of drugs through the mucus membrane of the GI tract to achieve drug delivery at the target site. The potential application of robotic pills in diagnosis and drug dispensing is also discussed. The review highlights recent developments in robotic pill drug-device technology and discusses its potential applications to solve the problems and challenges in oral drug delivery.

Health Information Technology Supporting Adherence Memory Disorder Patients: A Systematic Literature Review

BACKGROUND

People with memory disorders have difficulty adhering to treatments. With technological advances, it remains important to investigate the potential of health information technology (HIT) in supporting medication adherence among them.

OBJECTIVES

This review investigates the role of HIT in supporting adherence to medication and therapies among patients with memory issues. It also captures the factors that impact technology adherence interventions.

METHODS

We searched the literature for relevant publications published until March 15, 2023, using technology to support adherence among patients with memory issues (dementia, Alzheimer's, amnesia, mild cognitive impairment, memory loss, etc.). The review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We conducted a quality assessment of the papers following the Mixed Methods Appraisal Tool.

RESULTS

Fifteen studies were included after carefully reviewing the 3,773 articles in the search. Methodological quality, as appraised, ranged from 80 to 100% with eight studies rated 100%. The studies overall did not have a high risk of bias. Thus, all of the 15 studies were included. Technologies investigated were classified into four groups based on their impact: therapeutic patient education, simplifying treatment regimens, early follow-up visits and short-term treatment goals, and reminder programs. Different technologies were used (automatic drug dispensers or boxes, mobile health-based interventions, game-based interventions, e-health-based interventions, patient portals, and virtual reality). The factors impacting patients' adherence to technology-based treatment and medication were clustered into human-computer interaction and integration challenges.

CONCLUSION

This study contributes to the literature by classifying the technologies that supported medication adherence among patients with memory issues in four groups. It also explores and presents the possible limitations of existing solutions to drive future research in supporting care for people with memory disorders.

Key Features of Smart Medication Adherence Products: Updated Scoping Review

BACKGROUND

Older adults often face challenges in self-managing their medication owing to physical and cognitive limitations, complex medication regimens, and packaging of medications. Emerging smart medication dispensing and adherence products (SMAPs) offer the options of automated dispensing, tracking medication intake in real time, and reminders and notifications. A 2021 review identified 51 SMAPs owing to the rapid influx of digital technology; an update to this review is required.

OBJECTIVE

This review aims to identify new products and summarize and compare the key features of SMAPs.

METHODS

Gray and published literature and videos were searched using Google, YouTube, PubMed, Embase, and Scopus. The first 10 pages of Google and the first 100 results of YouTube were screened using 4 and 5 keyword searches, respectively. SMAPs were included if they were able to store and allowed for the dispensation of medications, tracked real-time medication intake data, and could automatically analyze data. Products were excluded if they were stand-alone software applications, not marketed in English, not for in-home use, or only used in clinical trials. In total, 5 researchers independently screened and extracted the data.

RESULTS

This review identified 114 SMAPs, including 80 (70.2%) marketed and 34 (29.8%) prototypes, grouped into 15 types. Among the marketed products, 68% (54/80) were available for consumer purchase. Of these products, 26% (14/54) were available worldwide and 78% (42/54) were available in North America. There was variability in the hardware, software, data collection and management features, and cost of the products. Examples of hardware features include battery life, medication storage capacity, availability of types and number of alarms, locking features, and additional technology required for use of the product, whereas software features included reminder and notification capabilities and availability of manufacturer support. Data capture methods included the availability of sensors to record the use of the product and data-syncing capabilities with cloud storage with short-range communications. Data were accessible to users via mobile apps or web-based portals. Some SMAPs provided data security assurance with secure log-ins (use of personal identification numbers or facial recognition), whereas other SMAPs provided data through registered email addresses. Although some SMAPs were available at set prices or free of cost to end users, the cost of other products varied based on availability, shipping fees, and subscription fees.

CONCLUSIONS

An expanding market for SMAPs with features specific to at-home patient use is emerging. Health care professionals can use these features to select and suggest products that meet their patients' unique requirements.

Artificial intelligence in the field of pharmacy practice: A literature review

Artificial intelligence (AI) is a transformative technology used in various industrial sectors including healthcare. In pharmacy practice, AI has the potential to significantly improve medication management and patient care. This review explores various AI applications in the field of pharmacy practice. The incorporation of AI technologies provides pharmacists with tools and systems that help them make accurate and evidence-based clinical decisions. By using AI algorithms and Machine Learning, pharmacists can analyze a large volume of patient data, including medical records, laboratory results, and medication profiles, aiding them in identifying potential drug-drug interactions, assessing the safety and efficacy of medicines, and making informed recommendations tailored to individual patient requirements. Various AI models have been developed to predict and detect adverse drug events, assist clinical decision support systems with medication-related decisions, automate dispensing processes in community pharmacies, optimize medication dosages, detect drug-drug interactions, improve adherence through smart technologies, detect and prevent medication errors, provide medication therapy management services, and support telemedicine initiatives. By incorporating AI into clinical practice, health care professionals can augment their decision-making processes and provide patients with personalized care. AI allows for greater collaboration between different healthcare services provided to a single patient. For patients, AI may be a useful tool for providing guidance on how and when to take a medication, aiding in patient education, and promoting medication adherence and AI may be used to know how and where to obtain the most cost-effective healthcare and how best to communicate with healthcare professionals, optimize the health monitoring using wearables devices, provide everyday lifestyle and health guidance, and integrate diet and exercise.

A framework for understanding sources of bias in medication adherence research

The sources of bias in medication adherence research have not been comprehensively explored. We aimed to identify biases expected to affect adherence research and to develop a framework for mapping these onto the phases of adherence (initiation, implementation and discontinuation). A literature search was conducted, key papers were reviewed and a Catalogue of Bias was consulted. The specific biases related to adherence measurement and metrics were mapped onto the phases of adherence using a tabular matrix. Twenty-three biases were identified, of which 11 were specifically relevant to adherence measures and metrics. The mapping framework showed differences in the numbers and types of biases associated with each measure and metric while highlighting those common to many adherence study designs (e.g., unacceptability bias and apprehension bias). The framework will inform the design of adherence studies and the development of risk of bias tools for adherence research.

The Coming of Age of AI/ML in Drug Discovery, Development, Clinical Testing, and Manufacturing: The FDA Perspectives

Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computing, building on technologies that humanity has developed over millions of years-from the abacus to quantum computers. These tools have reached a pivotal moment in their development. In 2021 alone, the U.S. Food and Drug Administration (FDA) received over 100 product registration submissions that heavily relied on AI/ML for applications such as monitoring and improving human performance in compiling dossiers. To ensure the safe and effective use of AI/ML in drug discovery and manufacturing, the FDA and numerous other U.S. federal agencies have issued continuously updated, stringent guidelines. Intriguingly, these guidelines are often generated or updated with the aid of AI/ML tools themselves. The overarching goal is to expedite drug discovery, enhance the safety profiles of existing drugs, introduce novel treatment modalities, and improve manufacturing compliance and robustness. Recent FDA publications offer an encouraging outlook on the potential of these tools, emphasizing the need for their careful deployment. This has expanded market opportunities for retraining personnel handling these technologies and enabled innovative applications in emerging therapies such as gene editing, CRISPR-Cas9, CAR-T cells, mRNA-based treatments, and personalized medicine. In summary, the maturation of AI/ML technologies is a testament to human ingenuity. Far from being autonomous entities, these are tools created by and for humans designed to solve complex problems now and in the future. This paper aims to present the status of these technologies, along with examples of their present and future applications.

Contingency Management for Integrated Harm Reduction Among Men Who Have Sex with Men Who Use Methamphetamine in Los Angeles: A Pilot Assessment

Methamphetamine (MA) use is associated with HIV transmission among men who have sex with men (MSM) and lapses in medication adherence. Contingency Management (CM) is effective in reducing MA use, but studies of CM to support adherence to HIV prevention or treatment are limited. We conducted a pilot trial of a CM intervention to reduce MA use and improve PrEP/ART adherence among MSM prescribed a tenofovir (TFV)-based regimen for HIV prevention or treatment. Participants were randomly assigned to receive escalating incentives for either MA abstinence or TFV adherence (based on point-of-care urine testing), and to a monitoring schedule of either 2 or 3 visits/week for 4 weeks. 19 MSM were randomized to either CM for MA use or CM for PrEP/ART adherence (median age: 38; IQR: 28-46) and 15 were living with HIV. Participants attended 95.7% (67/70) of scheduled visits in the 2x/week arm and 74.8% (74/99) in the 3x/week arm. TFV adherence was higher among participants in the TFV adherence arm with 93.5% (n = 72/77) of urine samples positive for TFV, compared to 76.6% (n = 49/64) in the MA abstinence arm (p = 0.007). Participants in the MA abstinence arm had more urine samples negative for MA metabolites (20.3%, n = 13/64) than those receiving CM for TFV adherence (6.5%, n = 5/77; p = 0.021). A CM model for MA abstinence and PrEP/ART adherence using twice-weekly visits and urine testing for MA and TFV for MSM who use MA is feasible and potentially effective as an integrated harm reduction strategy.

Medication Adherence in Tobacco Cessation Clinical Trials

Adherence is a critical mediator of treatment outcome across health conditions and low rates of adherence undermine success in smoking cessation treatment. This narrative review provides an overview of different techniques that can be used to measure adherence to smoking cessation treatments and outlines strategies to address treatment adherence. Techniques to measure adherence include conducting pill counts, collecting self-reports of adherence, directly observed therapy, biochemical verification methods, and electronic data collection via medication events monitoring systems. Techniques examined for increasing tobacco cessation treatment adherence include counseling, automated adherence calls, feedback from electronic monitors, contingency management and directly observed therapy. Adherence monitoring and optimization should be a standard component of smoking cessation treatment research.

Feasibility and acceptability pilot of video-based direct observed treatment (vDOT) for supporting antitubercular treatment in South India: a cohort study

OBJECTIVES

The objective of this study was to assess the feasibility and acceptability of video-based anti-tuberculosis (TB) treatment adherence support in patients with TB (PwTB) in South India.

DESIGN

An exploratory cohort.

SETTING

Participants were recruited at the TB treatment centre (direct observed treatment short centre) of a tertiary-level teaching facility in Bangalore, Karnataka, South India.

PARTICIPANTS

The study enrolled 25 PwTB, with replacement. Adult PwTB who were on drug-sensitive treatment regimens were included, while those who had drug resistant TB were excluded from the study.

INTERVENTION

Participants received scheduled adherence reminders and were trained to videorecord themselves swallowing their medication via a mobile application. The application was automated to submit these videos for evaluation. Participants were followed up monthly till treatment completion or withdrawal.

OUTCOME MEASURES

Adherence rate and acceptability of video-based directly observed treatment (vDOT).

RESULTS

The mean±SD age of the participants was 33±14 years, majority were females (16, 64%), residing in urban areas (24,96%), married (17, 68%) and had access to smart phones (23,92%). A total of 3193 person days of follow-up was completed; of the videos submitted within the first 6 months of enrollment (2501), 94% (2354/2501) were considered 'acceptable' and 16 (64%) participants were optimally adherent (ie, ≥80%). Participant videos improved in quality and a higher proportion met acceptability criteria over time. Twenty-one (84%) participants stated that they found the application easy to learn; 13 (52%) preferred vDOT over DOT. Mixed model logistic regression showed that those who are married are more likely have daily adherence to anti-TB treatment.

CONCLUSION

Video-based mobile phone interventions are acceptable to PwTB and the ease of using the application increases with time. To provide patient-centred care, vDOT is a promising option that can be offered to patients for treatment support and adherence monitoring.

Electronic Dose Monitoring Device Patterns in Youth Living With HIV Enrolled in an Adherence Intervention Clinical Trial

INTRODUCTION

Youth living with HIV in the US have low rates of viral suppression, in part because of challenges with antiretroviral therapy adherence.

METHODS

Daily dosing in the Adolescent Medicine Trials Network for HIV/AIDS Interventions 152 study, a randomized controlled trial of a 12-week adherence intervention (triggered escalating real-time adherence intervention) for viremic youth, compared with standard of care (SOC), was measured by electronic dose monitoring (EDM) throughout 48 weeks of follow-up. EDM data collected over the first 24 weeks were used to characterize patterns of antiretroviral therapy adherence with group-based trajectory models.

RESULTS

Four trajectory groups were identified among the 85 participants included in the analysis during the intervention phase of the study: (Worst) no interaction with EDM, (Declining) initially moderate EDM-based adherence followed by steep declines, (Good) initially high EDM-based adherence with modest declines, and (Best) consistently high EDM-based adherence. Being in the SOC arm, not being in school, higher evasiveness and panic decision-making scores, and lower adherence motivation were associated with higher odds of being in a worse trajectory group ( P < 0.05). A general decline in dosing was observed in the 12 weeks postintervention, when all participants were managed using SOC.

CONCLUSIONS

Use of group-based trajectory models allowed a more nuanced understanding of EDM-based adherence over time compared with collapsed summary measures. In addition to the study intervention, other factors influencing EDM-based adherence included being in school, decision-making styles, and adherence-related motivation. This information can be used to design better intervention services for youth living with HIV.

Exploring the Value of Real-Time Medication Adherence Monitoring: A Qualitative Study

Smart adherence products enable the monitoring of medication intake in real-time. However, the value of real-time medication intake monitoring to different stakeholders such as patients, their caregivers, clinicians, and insurers is not elucidated. The aim of this study was to explore the value different stakeholders place on the availability of smart adherence products and access to real-time medication intake data. A qualitative study design using semi-structured one-on-one virtual interviews was utilized. Schwartz's theory of values provided the foundation for the interview questions, data were analyzed using Braun and Clark's thematic analysis framework, and findings were mapped back to the constructs of Schwartz's theory of values. A total of 31 interviews with patients, caregivers, healthcare providers, and representatives of private or public insurance providers were conducted. Three themes and ten subthemes were identified. Themes included perceptions of integrating smart medication adherence technologies and real-time monitoring, technology adoption factors and data management. Stakeholders place different values based on the motivators and goals that can drive product use for daily medication management. Stakeholders valued the availability of real-time medication taking data that allow clinicians to make timely data-driven recommendations to their patients that may improve medication management for patients and reduce the caregiver burden.

An Overview of Telehealth in the Management of Cardiovascular Disease: A Scientific Statement From the American Heart Association

Telehealth enables the remote delivery of health care through telecommunication technologies and has substantially affected the evolving medical landscape. The COVID-19 pandemic accelerated the utilization of telehealth as health care professionals were forced to limit face-to-face in-person visits. It has been shown that information delivery, diagnosis, disease monitoring, and follow-up care can be conducted remotely, resulting in considerable changes specific to cardiovascular disease management. Despite increasing telehealth utilization, several factors such as technological infrastructure, reimbursement, and limited patient digital literacy can hinder the adoption of remote care. This scientific statement reviews definitions pertinent to telehealth discussions, summarizes the effect of telehealth utilization on cardiovascular and peripheral vascular disease care, and identifies obstacles to the adoption of telehealth that need to be addressed to improve health care accessibility and equity.

Relationship between cognition and treatment adherence to disease-modifying therapy in multiple sclerosis: a prospective, cross-sectional study

Less than half of patients with chronic diseases, including multiple sclerosis (MS), adhere to their prescribed medications. Treatment selection is essential for patient adherence. The aim of this study was to explore the potential factors influencing nonadherence to disease-modifying therapies (DMTs) in MS. This prospective, cross-sectional study was performed at the Multiple Sclerosis Center between 2018 and 2021. In total, 85 patients were eligible for final analysis. Forty-one patient (48.2%) with MS were non-adherent to DMT. Male sex, oral administration of drugs, and longer treatment duration were associated with nonadherence. The mean Expanded Disability Status Scale score did not differ between the adherent and non-adherent patients (p > 0.05). Patients with a higher score on the Symbol Digit Modalities Test, who were receiving self-injection therapy, had shorter treatment duration, and higher disability, were more likely to be adherent to DMT than those without. To minimize nonadherence in patients with MS, the patient's information processing speed should be considered before DMT initiation, and appropriate treatment options should be discussed.