Effect of Interactive eHealth Interventions on Improving Medication Adherence in Adults With Long-Term Medication: Systematic Review

Effectiveness of eHealth Interventions in Improving Medication Adherence Among Patients With Cardiovascular Disease: Systematic Review and Meta-Analysis

BACKGROUND

Nonadherence to medication among patients with cardiovascular diseases undermines the desired therapeutic outcomes. eHealth interventions emerge as promising strategies to effectively tackle this issue.

OBJECTIVE

The aim of this study was to conduct a network meta-analysis (NMA) to compare and rank the efficacy of various eHealth interventions in improving medication adherence among patients with cardiovascular diseases (CVDs).

METHODS

A systematic search strategy was conducted in PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure Library (CNKI), China Science and Technology Journal Database (Weipu), and WanFang databases to search for randomized controlled trials (RCTs) published from their inception on January 15, 2024. We carried out a frequentist NMA to compare the efficacy of various eHealth interventions. The quality of the literature was assessed using the risk of bias tool from the Cochrane Handbook (version 2.0), and extracted data were analyzed using Stata16.0 (StataCorp LLC) and RevMan5.4 software (Cochrane Collaboration). The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach.

RESULTS

A total of 21 RCTs involving 3904 patients were enrolled. The NMA revealed that combined interventions (standardized mean difference [SMD] 0.89, 95% CI 0.22-1.57), telephone support (SMD 0.68, 95% CI 0.02-1.33), telemonitoring interventions (SMD 0.70, 95% CI 0.02-1.39), and mobile phone app interventions (SMD 0.65, 95% CI 0.01-1.30) were statistically superior to usual care. However, SMS compared to usual care showed no statistical difference. Notably, the combined intervention, with a surface under the cumulative ranking curve of 79.3%, appeared to be the most effective option for patients with CVDs. Regarding systolic blood pressure and diastolic blood pressure outcomes, the combined intervention also had the highest probability of being the best intervention.

CONCLUSIONS

The research indicates that the combined intervention (SMS text messaging and telephone support) has the greatest likelihood of being the most effective eHealth intervention to improve medication adherence in patients with CVDs, followed by telemonitoring, telephone support, and app interventions. The results of these network meta-analyses can provide crucial evidence-based support for health care providers to enhance patients' medication adherence. Given the differences in the design and implementation of eHealth interventions, further large-scale, well-designed multicenter trials are needed.

TRIAL REGISTRATION

INPLASY 2023120063; https://inplasy.com/inplasy-2023-12-0063/.

Effectiveness of a Multifaceted Mobile Health Intervention (Multi-Aid-Package) in Medication Adherence and Treatment Outcomes Among Patients With Hypertension in a Low- to Middle-Income Country: Randomized Controlled Trial

BACKGROUND

The high prevalence of uncontrolled hypertension in Pakistan is predominantly attributed to poor medication adherence. As more than 137 million people in Pakistan use cell phones, a suitable mobile health (mHealth) intervention can be an effective tool to overcome poor medication adherence.

OBJECTIVE

We sought to determine whether a novel mHealth intervention is useful in enhancing antihypertensive therapy adherence and treatment outcomes among patients with hypertension in a low- to middle-income country.

METHODS

A 6-month parallel, single-blinded, superiority randomized controlled trial recruited 439 patients with hypertension with poor adherence to antihypertensive therapy and access to smartphones. An innovative, multifaceted mHealth intervention (Multi-Aid-Package), based on the Health Belief Model and containing reminders (written, audio, visual), infographics, video clips, educational content, and 24/7 individual support, was developed for the intervention group; the control group received standard care. The primary outcome was self-reported medication adherence measured using the Self-Efficacy for Appropriate Medication Adherence Scale (SEAMS) and pill counting; the secondary outcome was systolic blood pressure (SBP) change. Both outcomes were evaluated at baseline and 6 months. Technology acceptance feedback was also assessed at the end of the study. A generalized estimating equation was used to control the covariates associated with the probability of affecting adherence to antihypertensive medication.

RESULTS

Of 439 participants, 423 (96.4%) completed the study. At 6 months post intervention, the median SEAMS score was statistically significantly higher in the intervention group compared to the controls (median 32, IQR 11 vs median 21, IQR 6; U=10,490, P<.001). Within the intervention group, there was an increase in the median SEAMS score by 12.5 points between baseline and 6 months (median 19.5, IQR 5 vs median 32, IQR 11; P<.001). Results of the pill-counting method showed an increase in adherent patients in the intervention group compared to the controls (83/220, 37.2% vs 2/219, 0.9%; P<.001), as well as within the intervention group (difference of n=83, 37.2% of patients, baseline vs 6 months; P<.001). There was a statistically significant difference in the SBP of 7 mmHg between the intervention and control groups (P<.001) at 6 months, a 4 mmHg reduction (P<.001) within the intervention group, and a 3 mmHg increase (P=.314) within the controls. Overall, the number of patients with uncontrolled hypertension decreased by 46 in the intervention group (baseline vs 6 months), but the control group remained unchanged. The variables groups (adjusted odds ratio [AOR] 1.714, 95% CI 2.387-3.825), time (AOR 1.837, 95% CI 1.625-2.754), and age (AOR 1.618, 95% CI 0.225-1.699) significantly contributed (P<.001) to medication adherence. Multi-Aid-Package received a 94.8% acceptability score.

CONCLUSIONS

The novel Multi-Aid-Package is an effective mHealth intervention for enhancing medication adherence and treatment outcomes among patients with hypertension in a low- to middle-income country.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04577157; https://clinicaltrials.gov/study/NCT04577157.

Factors associated with poor adherence to medication in patients with diabetes and hypertension in Peru: findings from a pooled analysis of six years of population-based surveys

OBJECTIVE

To evaluate the factors associated with poor medication adherence in patients with DM and HTN in Peru.

STUDY DESIGN

A cross-sectional study.

METHODS

We analyzed data from the Peruvian Demographic and Family Health Survey from 2014 to 2019. Adjusted prevalence ratios (aPR) and their respective 95% confidence intervals (CI) were estimated to determine the factors associated with poor medication adherence.

RESULTS

We included 15,184 participants with a known diagnosis of DM and HTN. The frequency of poor medication adherence was 37.1%, with 36.7% among individuals with HTN and 29.2% among individuals with DM. Those belonging to age groups above 30 years (aPR: 0.77; 95% CI: 0.74-0.80, for the group ≥ 60 years) had a lower frequency of poor medication adherence. Meanwhile, being male (aPR: 1.03; 95% CI: 1.01-1.05), lacking health insurance (aPR: 1.08; 95% CI: 1.05-1.10), belonging to lower wealth quintiles (aPR: 1.12; 95% CI: 1.08-1.17, for the first quintile), and living in the mountain region (aPR: 1.09; 95% CI: 1.06-1.12) were associated with a higher frequency of poor medication adherence. These findings were consistent when stratifying by the type of disease.

CONCLUSION

This study showed that poor medication adherence is common in patients with HTN and DM in Peru and is associated with sociodemographic factors, highlighting the importance of public health approaches to improve adherence.

Randomized comparison of the effects of tailored text messaging versus pillbox organizers on medication adherence of heart failure patients

BACKGROUND

Heart failure (HF) is a major public health issue worldwide, affecting approximately 64.3 million people in 2017. Non-adherence to medication is a common and serious issue in the management of HF. However, new reminder systems utilizing mobile technology, such as text messaging, have shown promise in improving medication adherence. The purpose of this study was to compare the impact of tailored text messaging (TTM) and pillbox organizers on medication adherence in individuals with HF.

METHODS

A randomized controlled trial was conducted, involving 189 eligible patients with HF who were randomly assigned to either the TTM, pillbox organizer, or control group. Medication adherence was evaluated using pill counting and the Medication Adherence Rating Scale (MARS) over a period of three months and compared across the groups. The data were analyzed using Kruskal-Wallis, Analysis of Variance (ANOVA), and Repeated Measures ANOVA tests.

RESULTS

The results indicate that both the TTM and pillbox organizers groups had significantly higher medication adherence compared to the control group, as measured by pill counting (MD = 0.05, 95%CI = 0.03-0.06; p < 0.001 for TTM group, MD = 0.04, 95%CI = 0.03-0.06; p < 0.001 for pillbox organizers group) and the MARS (MD = 1.32, 95%CI = 0.93 to 1.72; p < 0.001 for TTM group, MD = 1.33, 95%CI = 0.95 to 1.72; p < 0.001 for pillbox organizers group). However, there was no statistically significant difference in medication adherence between the two intervention groups using either measurement method. The TTM group exhibited a lower hospitalization rate than the other groups in the first follow up (p = 0.016).

CONCLUSIONS

Both the TTM and pillbox organizers were shown to be effective in enhancing medication adherence among patients with HF. Therefore, healthcare providers should take into account the patient's condition and preferences when selecting one of these methods to promote medication adherence. Future research should aim to address the limitations of this study, such as controlling for confounding variables, considering long-term effects, and comparing the effectiveness of different interventions.

Developing Social Enhancements for a Web-Based, Positive Emotion Intervention for Alzheimer Disease Caregivers: Qualitative Focus Group and Interview Study

BACKGROUND

Alzheimer disease is a degenerative neurological condition that requires long-term care. The cost of these responsibilities is often borne by informal caregivers, who experience an elevated risk of negative physical and psychological outcomes. Previously, we designed a positive emotion regulation intervention that was shown to improve well-being among dementia caregivers when delivered through one-on-one videoconferencing lessons with a trained facilitator. However, the format required significant resources in terms of logistics and facilitator time. To broaden the reach of the intervention, we aimed to develop the Social Augmentation of Self-Guided Electronic Delivery of the Life Enhancing Activities for Family Caregivers (SAGE LEAF) program, an iteration of the intervention in a self-guided, web-based format with enhanced opportunities for social connection.

OBJECTIVE

The aim of this study was to gather feedback to inform the design of social features for the SAGE LEAF intervention. In the absence of a facilitator, our goal with the self-guided SAGE LEAF intervention was to integrate various social features (eg, discussion board, automated support, and profiles) to maximize engagement among participants.

METHODS

Qualitative data were collected from 26 individuals through (1) interviews with participants who completed a previous version of the intervention via videoconferencing with a facilitator, (2) focus groups with dementia caregivers who had not previously experienced the intervention, and (3) focus groups with Alzheimer disease clinical care providers. We conducted a qualitative thematic analysis to identify which social features would be the most helpful and how they could be implemented in a way that would be best received by caregivers.

RESULTS

Interview and focus group feedback indicated that participants generally liked the potential features suggested, including the discussion boards, multimedia content, and informational support. They had valuable suggestions for optimal implementation. For example, participants liked the idea of a buddy system where they would be matched up with another caregiver for the duration of the study. However, they expressed concern about differing expectations among caregivers and the possibility of matched caregivers not getting along. Participants also expressed interest in giving caregivers access to a podcast on the skills, which would allow them to review additional content when they wished.

CONCLUSIONS

Taken together, the discussions with caregivers and providers offered unique insights into the types of social features that may be integrated into the SAGE LEAF intervention, as well as implementation suggestions to improve the acceptability of the features among caregivers. These insights will allow us to design social features for the intervention that are optimally engaging and helpful for caregivers.

Quality Assessment of Smartphone Medication Management Apps in France: Systematic Search

BACKGROUND

Adherence to medication is estimated to be around 50% for chronically ill patients in high-income countries. Improving the effectiveness of adherence interventions could have a far greater impact on population health than any improvement in specific medical treatments. Mobile health (mHealth) is one of the most effective solutions for helping patients improve their medication intake, notably through the use of mobile apps with reminder systems. With more than 327,000 apps available in the mHealth field, it is difficult for health care professionals and patients alike to choose which apps to recommend and use.

OBJECTIVE

We aim to carry out a systematic search of medication management smartphone apps available in France that send reminders to patients and assess their quality using a validated scale.

METHODS

Mobile apps were identified in October and November 2022 after a systematic keyword search on the 2 main app download platforms: App Store (Apple Inc) and Google Play Store. Inclusion criteria were free availability, date of last update, and availability in French. Next, 2 health care professionals independently evaluated the included apps using the French version of the Mobile App Rating Scale (MARS-F), an objective scoring system validated for assessing the overall quality of apps in the mHealth field. An intraclass correlation coefficient was calculated to determine interrater reliability.

RESULTS

In total, 960 apps were identified and 49 were selected (25 from the App Store and 24 from the Google Play Store). Interrater reliability was excellent (intraclass correlation coefficient 0.92; 95% CI 0.87-0.95; P<.001). The average MARS-F score was 3.56 (SD 0.49) for apps on the App Store and 3.51 (SD 0.46) for those on the Google Play Store, with 10 apps scoring above 4 out of 5. Further, 2 apps were tested in at least one randomized controlled trial and showed positive results. The 2 apps with the highest ratings were Mediteo rappel de médicaments (Mediteo GmbH) and TOM rappel medicaments, pilule (Innovation6 GmbH), available on both platforms. Each app's MARS-F score was weakly correlated with user ratings on the App Store and moderately correlated on the Google Play Store.

CONCLUSIONS

To our knowledge, this is the first study that used a validated scoring system to evaluate medication management apps that send medication reminders. The quality of the apps was heterogeneous, with only 2 having been studied in a randomized controlled trial with positive results. The evaluation of apps in real-life conditions by patients is necessary to determine their acceptability and effectiveness. Certification of apps is also essential to help health care professionals and patients identify validated apps.

Digital Care Pathway for Patients With Sleep Apnea in Specialized Care: Mixed Methods Study

BACKGROUND

Sleep apnea is a significant public health disorder in Finland, with a prevalence of 3.7%. Continuous positive airway pressure (CPAP) therapy is the first-line treatment for moderate or severe sleep apnea. From November 18, 2019, all patients who started their CPAP therapy at Oulu University Hospital were attached to a sleep apnea digital care pathway (SA-DCP) and were instructed on its use. Some patients still did not use the SA-DCP although they had started their CPAP therapy.

OBJECTIVE

We aimed to study health care professionals' (HCPs') perspectives on the SA-DCP and its usefulness for their work; whether the main targets of SA-DCP can be reached: shortening the initial guiding sessions of CPAP therapy, reducing patient calls and contact with HCPs, and improving patients' adherence to CPAP therapy; and patients' perspectives on the SA-DCP and its usefulness to them.

METHODS

Overall, 6 HCPs were interviewed in May and June 2021. The survey for SA-DCP users (58/91, 64%) and SA-DCP nonusers (33/91, 36%) was conducted in 2 phases: from May to August 2021 and January to June 2022. CPAP device remote monitoring data were collected from SA-DCP users (80/170, 47.1%) and SA-DCP nonusers (90/170, 52.9%) in May 2021. The registered phone call data were collected during 2019, 2020, and 2021. Feedback on the SA-DCP was collected from 446 patients between February and March 2022.

RESULTS

According to HCPs, introducing the SA-DCP had not yet significantly improved their workload and work practices, but it had brought more flexibility in some communication situations. A larger proportion of SA-DCP users familiarized themselves with prior information about CPAP therapy before the initial guiding session than nonusers (43/58, 74% vs 16/33, 49%; P=.02). Some patients still had not received prior information about CPAP therapy; therefore, most of the sessions were carried out according to their needs. According to the patient survey and remote monitoring data of CPAP devices, adherence to CPAP therapy was high for both SA-DCP users and nonusers. The number of patients' phone calls to HCPs did not decrease during the study. SA-DCP users perceived their abilities to use information and communications technology to be better than nonusers (mean 4.2, SD 0.8 vs mean 3.2, SD 1.2; P<.001).

CONCLUSIONS

According to this study, not all the goals set for the introduction of the SA-DCP have been achieved. Despite using the SA-DCP, some patients still wanted to communicate with HCPs by phone. The most significant factors explaining the nonuse of the SA-DCP were lower digital literacy and older age of the patients. In the future, more attention should be paid to these user groups when designing and introducing upcoming digital care pathways.

Integration of e-Health Strategies for Post-COVID-19 Pandemic Pediatric Weight Management Programs

Background: The COVID-19 pandemic catalyzed a renewed urgency to address the obesity pandemic and accelerated the use of technology to treat pediatric obesity. Yet, there are significant incongruities between the existing literature on technology for obesity management and the current health care system that may lead to suboptimal outcomes and increased costs. This study reviewed the types of e-health strategies currently in use, highlighted inconsistencies and overlap in terminology, and identified future research directions in e-health for childhood obesity, including gaps in implementation science. Methods: This narrative literature review synthesized seminal articles from the literature, as well as recent articles, using PubMed and Google Scholar that focused on the use of technology in treating pediatric obesity. This inclusive strategy was intended to elucidate the heterogeneity in how different disciplines are using digital health terminology in pediatric obesity research. Results: Both the prevalence of e-health interventions and its associated terminology are increasing in the peer-reviewed literature, especially since the beginning of the COVID-19 pandemic. Yet, their definitions and usage are unstandardized, leading to a lack of cohesion in the research and between disciplines. There is a gap in implementation science outcomes, including reimbursement, that may significantly impact external validity and uptake. Conclusion: A more systematic and precise approach to researching e-health that can assess specific technologies and combinations of technologies, their short-term and long-term effect sizes, and feasibility can produce the necessary data that may lead to reimbursement policies and, ultimately, improved pediatric weight management outcomes.

Risk Factors for Non-Adherence to Pharmacist or Non-Pharmacist Explanations on Preoperative Medication Discontinuation: A Retrospective Japanese Study

Purpose

The risk factors for non-adherence to pharmacist or non-pharmacist explanations of preoperative medication discontinuation are unknown. The primary outcome of this study was to determine whether the final explainer's occupation was a risk factor for non-adherence. The secondary outcomes were to determine the risk factors for non-adherence after limiting the departments or adjusting for age.

Patients and Methods

We retrospectively examined the data (including patient age, sex, prescription medications, comorbidities, presence of roommate, and number of days between receiving explanation and surgery) of 1132 patients on medications that could affect surgery at a Japanese university hospital between April 1, 2017, and March 31, 2020. The primary endpoint was whether the occupation of the last person explaining medication discontinuation to the patient was an independent risk factor for non-adherence (age ≥65 years vs <65 years). Secondary endpoints included subgroup analyses in urological, gastrointestinal, and otolaryngological areas, as well as a sensitivity analysis (age as a continuous variable) to confirm the validity of the primary endpoint results. A multivariate binary logistic regression identified independent non-adherence risk factors.

Results

The main analysis showed that discontinuing two or more medications was a risk factor for non-adherence (adjusted odds ratio (AOR): 1.67; 95% confidence interval (CI): 1.13-2.47; p = 0.01). However, in analyses coordinated by department (urological, gastrointestinal, and otolaryngological), ≥65 (versus <65) years of age was determined as a risk factor for increased nonadherence (AOR: 2.27, 95% CI: 1.11-4.63; p=0.024). Age-adjusted analysis (continuous variables) showed similar results to the primary endpoint (AOR: 1.68, 95% CI: 1.14-2.49, p = 0.009).

Conclusion

Two or more medications, and not the final explainer's occupation, were associated with pre-surgery medication non-adherence. To prevent non-adherence, pharmacists and non-pharmacists should educate patients about preoperative medication discontinuation. These findings could help identify high-risk non-adherence patients.

Digital Solutions Available to Be Used by Informal Caregivers, Contributing to Medication Adherence: A Scoping Review

Medication adherence is essential for managing chronic diseases and achieving optimal health outcomes. However, this process is often challenging, particularly for patients with complex care needs. Informal caregivers play a pivotal role in supporting medication management, but they may face resource limitations and a lack of necessary support. Digital health tools offer a promising avenue to enhance medication adherence by providing reminders, education, and remote monitoring capabilities. This scoping review aimed to identify and evaluate digital solutions available to informal caregivers for improving medication adherence. A systematic search of PubMed and Web of Science was conducted using relevant keywords. Four studies were included in the review, examining a variety of digital tools including mobile apps, SMS messaging, and wearable devices. These tools demonstrated efficacy in improving medication adherence, managing disease symptoms, and enhancing quality of life for patients and caregivers. Digital health interventions hold the potential to revolutionize medication adherence among chronic disease patients. By empowering informal caregivers, these tools can bridge the gaps in medication management and contribute to better health outcomes. Further research is warranted to optimize the design, implementation, and evaluation of digital interventions for medication adherence.

Efficacy of eHealth Technologies on Medication Adherence in Patients With Acute Coronary Syndrome: Systematic Review and Meta-Analysis

BACKGROUND

Suboptimal adherence to cardiac pharmacotherapy, recommended by the guidelines after acute coronary syndrome (ACS) has been recognized and is associated with adverse outcomes. Several randomized controlled trials (RCTs) have shown that eHealth technologies are useful in reducing cardiovascular risk factors. However, little is known about the effect of eHealth interventions on medication adherence in patients following ACS.

OBJECTIVE

The aim of this study is to examine the efficacy of the eHealth interventions on medication adherence to selected 5 cardioprotective medication classes in patients with ACS.

METHODS

A systematic literature search of PubMed, Embase, Scopus, and Web of Science was conducted between May and October 2022, with an update in October 2023 to identify RCTs that evaluated the effectiveness of eHealth technologies, including texting, smartphone apps, or web-based apps, to improve medication adherence in patients after ACS. The risk of bias was evaluated using the modified Cochrane risk-of-bias tool for RCTs. A pooled meta-analysis was performed using a fixed-effect Mantel-Haenszel model and assessed the medication adherence to the medications of statins, aspirin, P2Y12 inhibitors, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and β-blockers.

RESULTS

We identified 5 RCTs, applicable to 4100 participants (2093 intervention vs 2007 control), for inclusion in the meta-analysis. In patients who recently had an ACS, compared to the control group, the use of eHealth intervention was not associated with improved adherence to statins at different time points (risk difference [RD] -0.01, 95% CI -0.03 to 0.03 at 6 months and RD -0.02, 95% CI -0.05 to 0.02 at 12 months), P2Y12 inhibitors (RD -0.01, 95% CI -0.04 to 0.02 and RD -0.01, 95% CI -0.03 to 0.02), aspirin (RD 0.00, 95% CI -0.06 to 0.07 and RD -0.00, 95% CI -0.07 to 0.06), angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (RD -0.01, 95% CI -0.04 to 0.02 and RD 0.01, 95% CI -0.04 to 0.05), and β-blockers (RD 0.00, 95% CI -0.03 to 0.03 and RD -0.01, 95% CI -0.05 to 0.03). The intervention was also not associated with improved adherence irrespective of the adherence assessment method used (self-report or objective).

CONCLUSIONS

This review identified limited evidence on the effectiveness of eHealth interventions on adherence to guideline-recommended medications after ACS. While the pooled analyses suggested a lack of effectiveness of such interventions on adherence improvement, further studies are warranted to better understand the role of different eHealth approaches in the post-ACS context.

The Use of eHealth for Pharmacotherapy Management With Patients With Respiratory Disease, Cardiovascular Disease, or Diabetes: Scoping Review

BACKGROUND

eHealth is increasingly considered an important tool for supporting pharmacotherapy management.

OBJECTIVE

We aimed to assess the (1) use of eHealth in pharmacotherapy management with patients with asthma or chronic obstructive pulmonary disease (COPD), diabetes, or cardiovascular disease (CVD); (2) effectiveness of these interventions on pharmacotherapy management and clinical outcomes; and (3) key factors contributing to the success of eHealth interventions for pharmacotherapy management.

METHODS

We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review) statement. Databases searched included Embase, MEDLINE (PubMed), and Cochrane Library. Screening was conducted by 2 independent researchers. Eligible articles were randomized controlled trials and cohort studies assessing the effect of an eHealth intervention for pharmacotherapy management compared with usual care on pharmacotherapy management or clinical outcomes in patients with asthma or COPD, CVD, or diabetes. The interventions were categorized by the type of device, pharmacotherapy management, mode of delivery, features, and domains described in the conceptual model for eHealth by Shaw at al (Health in our Hands, Interacting for Health, Data Enabling Health). The effectiveness on pharmacotherapy management outcomes and patient- and clinician-reported clinical outcomes was analyzed per type of intervention categorized by number of domains and features to identify trends.

RESULTS

Of 63 studies, 16 (25%), 31 (49%), 13 (21%), and 3 (5%) included patients with asthma or COPD, CVD, diabetes, or CVD and diabetes, respectively. Most (38/63, 60%) interventions targeted improving medication adherence, often combined for treatment plan optimization. Of the 16 asthma or COPD interventions, 6 aimed to improve inhaled medication use. The majority (48/63, 76%) of the studies provided an option for patient feedback. Most (20/63, 32%) eHealth interventions combined all 3 domains by Shaw et al, while 25% (16/63) combined Interacting for Health with Data Enabling Health. Two-thirds (42/63, 67%) of the studies showed a positive overall effect. Respectively, 48% (23/48), 57% (28/49), and 39% (12/31) reported a positive effect on pharmacotherapy management and clinician- and patient-reported clinical outcomes. Pharmacotherapy management and patient-reported clinical outcomes, but not clinician-reported clinical outcomes, were more often positive in interventions with ≥3 features. There was a trend toward more studies reporting a positive effect on all 3 outcomes with more domains by Shaw et al. Of the studies with interventions providing patient feedback, more showed a positive clinical outcome, compared with studies with interventions without feedback. This effect was not seen for pharmacotherapy management outcomes.

CONCLUSIONS

There is a wide variety of eHealth interventions combining various domains and features to target pharmacotherapy management in asthma or COPD, CVD, and diabetes. Results suggest feedback is key for a positive effect on clinician-reported clinical outcomes. eHealth interventions become more impactful when combining domains.

Effective Behavior Change Techniques in Digital Health Interventions for the Prevention or Management of Noncommunicable Diseases: An Umbrella Review

BACKGROUND

Despite an abundance of digital health interventions (DHIs) targeting the prevention and management of noncommunicable diseases (NCDs), it is unclear what specific components make a DHI effective.

PURPOSE

This narrative umbrella review aimed to identify the most effective behavior change techniques (BCTs) in DHIs that address the prevention or management of NCDs.

METHODS

Five electronic databases were searched for articles published in English between January 2007 and December 2022. Studies were included if they were systematic reviews or meta-analyses of DHIs targeting the modification of one or more NCD-related risk factors in adults. BCTs were coded using the Behavior Change Technique Taxonomy v1. Study quality was assessed using AMSTAR 2.

RESULTS

Eighty-five articles, spanning 12 health domains and comprising over 865,000 individual participants, were included in the review. We found evidence that DHIs are effective in improving health outcomes for patients with cardiovascular disease, cancer, type 2 diabetes, and asthma, and health-related behaviors including physical activity, sedentary behavior, diet, weight management, medication adherence, and abstinence from substance use. There was strong evidence to suggest that credible source, social support, prompts and cues, graded tasks, goals and planning, feedback and monitoring, human coaching and personalization components increase the effectiveness of DHIs targeting the prevention and management of NCDs.

CONCLUSIONS

This review identifies the most common and effective BCTs used in DHIs, which warrant prioritization for integration into future interventions. These findings are critical for the future development and upscaling of DHIs and should inform best practice guidelines.

Apremilast Adherence and Persistence in Patients with Psoriasis and Psoriatic Arthritis in the Telehealth Setting Versus the In-person Setting During the COVID-19 Pandemic

INTRODUCTION

Limited access to healthcare during the COVID-19 pandemic prompted patients to seek care using telehealth. In this study, we assessed whether treatment patterns differed for patients with psoriasis (PsO) or psoriatic arthritis (PsA) initiating apremilast by either a telehealth or an in-person visit.

METHODS

We estimated adherence and persistence among US patients in the Merative© MarketScan© Commercial and Supplemental Medicare Databases who newly initiated apremilast between April and June 2020, categorized by the type of visit (telehealth or in-person) when apremilast was first prescribed. Adherence was defined as the proportion of days covered (PDC), with PDC ≥ 0.80 considered to indicate high adherence. Persistence was defined as having apremilast available to take without a 60-day gap during follow-up. Factors associated with high adherence and persistence were estimated with logistic and Cox regression.

RESULTS

Among apremilast initiators (n = 505), the mean age was 47.6 years, 57.8% were female, and the majority had PsO (79.6%). Telehealth index visits were more likely among patients residing in Northeast USA (odds ratio [OR] 3.31, 95% confidence interval [CI] 1.63-6.71) and Western USA (OR 2.52, 95% CI 1.07-5.93]), those with a prescribing rheumatologist (OR 2.27, 95% CI 1.10-4.68), and those with any baseline telehealth visit (OR 1.91, 85% CI 1.20-3.04). Those initiating apremilast with a telehealth visit (n = 141) had similar mean PDC to those initiating apremilast with an in-person visit (n = 364) (0.695 vs. 0.728; p = 0.272). At the end of the 6-month follow-up, 54.3% of the overall population had high adherence (PDC ≥ 0.80) and 65.1% were persistent. After adjusting for potential confounders, patients initiating apremilast via telehealth had similar full adherence (OR 0.80, 95% CI 0.52-1.21) and persistence as those initiating apremilast in-person.

CONCLUSION

Patients with PsO and patients with PsA initiating apremilast via telehealth or in-person during the COVID-19 pandemic had similar medication adherence and persistence during the 6-month follow-up period. These data suggest that patients initiating apremilast can be as effectively managed with telehealth visits as with in-person visits.

eHealth profile of patients with diabetes

Background

Digital health technology can be useful to improve the health of patients with diabetes and to support patient-centered care and self-management. In this cross-sectional study, we described the eHealth profile of patients with diabetes, based on their use of digital health technology, and its association with sociodemographic characteristics.

Methods

We used data from the "Qualité Diabète Valais" cohort study, conducted in one region of Switzerland (Canton Valais) since 2019. Participants with type 1 or type 2 diabetes completed questionnaires on sociodemographic characteristics and on the use of digital health technology. We defined eHealth profiles based on three features, i.e., ownership or use of (1) internet-connected devices (smartphone, tablet, or computer), (2) mHealth applications, and (3) connected health tools (activity sensor, smart weight scale, or connected blood glucose meter). We assessed the association between sociodemographic characteristics and participants' eHealth profiles using stratified analyses and logistic regression models.

Results

Some 398 participants (38% women) with a mean age of 65 years (min: 25, max: 92) were included. The vast majority (94%) were Swiss citizens or bi-national and 68% were economically inactive; 14% had a primary level education, 51% a secondary level, and 32% a tertiary level. Some 75% of participants had type 2 diabetes. Some 90% of the participants owned internet-connected devices, 43% used mHealth applications, and 44% owned a connected health tool. Older age and a lower educational level were associated with lower odds of all features of the eHealth profile. To a lesser extent, having type 2 diabetes or not being a Swiss citizen were also associated with a lower use of digital health technology. There was no association with sex.

Conclusion

While most participants owned internet-connected devices, only about half of them used mHealth applications or owned connected health tools. Older participants and those with a lower educational level were less likely to use digital health technology. eHealth implementation strategies need to consider these sociodemographic patterns among patients with diabetes.

Effectiveness of eHealth Smoking Cessation Interventions: Systematic Review and Meta-Analysis

BACKGROUND

Rapid advancements in eHealth and mobile health (mHealth) technologies have driven researchers to design and evaluate numerous technology-based interventions to promote smoking cessation. The evolving nature of cessation interventions emphasizes a strong need for knowledge synthesis.

OBJECTIVE

This systematic review and meta-analysis aimed to summarize recent evidence from randomized controlled trials regarding the effectiveness of eHealth-based smoking cessation interventions in promoting abstinence and assess nonabstinence outcome indicators, such as cigarette consumption and user satisfaction, via narrative synthesis.

METHODS

We searched for studies published in English between 2017 and June 30, 2022, in 4 databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. We pooled comparable studies based on the population, follow-up time, intervention, and control characteristics. Two researchers performed an independent meta-analysis on smoking abstinence using the Sidik-Jonkman random-effects model and log risk ratio (RR) as the effect measurement. For studies not included in the meta-analysis, the outcomes were narratively synthesized.

RESULTS

A total of 464 studies were identified through an initial database search after removing duplicates. Following screening and full-text assessments, we deemed 39 studies (n=37,341 participants) eligible for this review. Of these, 28 studies were shortlisted for meta-analysis. According to the meta-analysis, SMS or app text messaging can significantly increase both short-term (3 months) abstinence (log RR=0.50, 95% CI 0.25-0.75; I2=0.72%) and long-term (6 months) abstinence (log RR=0.77, 95% CI 0.49-1.04; I2=8.65%), relative to minimal cessation support. The frequency of texting did not significantly influence treatment outcomes. mHealth apps may significantly increase abstinence in the short term (log RR=0.76, 95% CI 0.09-1.42; I2=88.02%) but not in the long term (log RR=0.15, 95% CI -0.18 to 0.48; I2=80.06%), in contrast to less intensive cessation support. In addition, personalized or interactive interventions showed a moderate increase in cessation for both the short term (log RR=0.62, 95% CI 0.30-0.94; I2=66.50%) and long term (log RR=0.28, 95% CI 0.04-0.53; I2=73.42%). In contrast, studies without any personalized or interactive features had no significant impact. Finally, the treatment effect was similar between trials that used biochemically verified or self-reported abstinence. Among studies reporting outcomes besides abstinence (n=20), a total of 11 studies reported significantly improved nonabstinence outcomes in cigarette consumption (3/14, 21%) or user satisfaction (8/19, 42%).

CONCLUSIONS

Our review of 39 randomized controlled trials found that recent eHealth interventions might promote smoking cessation, with mHealth being the dominant approach. Despite their success, the effectiveness of such interventions may diminish with time. The design of more personalized interventions could potentially benefit future studies.

TRIAL REGISTRATION

PROSPERO CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104.

Rationale and development of an e-health application to deliver patient-centered care during treatment for recently diagnosed multiple myeloma patients: pilot study of the MM E-coach

BACKGROUND

Patients with multiple myeloma (MM) increasingly face complicated treatment regimens. E-health may support patients and healthcare providers in enhancing a patient-centered healthcare approach. Therefore, we aimed to develop a patient-centered multi-modality e-health application, to assess the application for usability and end-user experiences.

METHODS

The application was developed following an iterative "action-based" methodology using the design thinking approach. Key end users participated, and relevant stakeholders were consulted in the development process. First, the care pathway was evaluated, the focus of development was determined, and a solution ideated during recurring multidisciplinary meetings. Second, a prototype was tested and improved. Third, a subsequent prototype was evaluated during a pilot study with patients and healthcare professionals on usability, usage, and experiences.

RESULTS

The multi-modality application, named the "MM E-coach," consisted of a newly developed medication module, patient-reported outcome (PRO) questionnaire assessments, a messaging service, alerts, information provision, and a personal care plan. The median system usability score was 60 on a scale of 0-100. Patients appreciated the medication overview, healthcare professionals appreciated the outpatient clinic preparation module, and both appreciated the messaging service. Additional recommendations for improvement mostly revolved around the flexibility of functionalities and look and feel of the application.

CONCLUSIONS

The MM E-coach has the potential to provide patient-centered care by supporting patients and caregivers during MM treatment and is a promising application to be implemented in the MM care pathway. A randomized clinical trial was initiated to study its clinical effectiveness.

A mixed methods approach to obtaining health care provider feedback for the development of a Canadian pediatric dental caries risk assessment tool for children <6 years

Introduction

Early childhood caries (ECC) is a chronic but preventable disease affecting young children worldwide. Many young children face access to care barriers to early preventive dental visits for a variety of reasons, which can increase their risk for ECC. Non-dental primary health care providers are well positioned to assist in assessing a child's risk for ECC by performing caries risk assessment (CRA). The purpose of this project was to report on primary health care provider and stakeholder feedback in order to refine a drafted CRA tool for Canadian children &lt;6 years of age intended for use by non-dental primary health care providers.

Methods

In this mixed methods project, we conducted six focus groups with primarily non-dental primary health care providers followed by a short paper-based survey to quantify preferences and feedback. Data were thematically and descriptively analyzed.

Results

Participants’ feedback on the drafted CRA tool included the need for it to be relatively quick to complete, easy and practical to score, easy to implement into practitioners’ clinic schedules, and to include anticipatory guidance information to share with parents and caregivers. All participants (100%) welcomed a CRA tool. Many (85.4%) liked a layout that could be added to tools they already utilize. Most (73.2%) wanted the tool to be in colour, and many (90.2%) wanted the tool to include pictures.

Conclusion

Non-dental primary health care providers informed the final development and layout of the newly released Canadian CRA tool. Their feedback resulted in a user-friendly CRA tool with provider-patient dynamics and preferences.

Healthcare Workers' Perspectives of mHealth Adoption Factors in the Developing World: Scoping Review

BACKGROUND

mHealth applications provide health practitioners with platforms that enable disease management, facilitate drug adherence, facilitate drug adherence, speed up diagnosis, monitor outbreaks, take and transfer medical images, and provide advice. Many developing economies are investing more in mobile telecommunication infrastructure than in road transport and electric power generation. Despite this, mHealth has not seen widespread adoption by healthcare workers in the developing world. This study reports a scoping review of factors that impact the adoption of mHealth by healthcare workers in the developing world, and based on these findings, a framework is developed for enhancing mHealth adoption by healthcare workers in the developing world.

METHODS

A structured literature search was performed using PubMed and Scopus, supplemented by hand searching. The searches were restricted to articles in English during the period January 2009 to December 2019 and relevant to the developing world that addressed: mobile phone use by healthcare workers and identified factors impacting the adoption of mHealth implementations. All authors reviewed selected papers, with final inclusion by consensus. Data abstraction was performed by all authors. The results were used to develop the conceptual framework using inductive iterative content analysis.

RESULTS AND DISCUSSION

Of 919 articles, 181 met the inclusion criteria and, following a review of full papers, 85 reported factors that impact (promote or impede) healthcare worker adoption of mHealth applications. These factors were categorised into 18 themes and, after continued iterative review and discussion were reduced to 7 primary categories (engagement/funding, infrastructure, training/technical support, healthcare workers' mobile-cost/ownership, system utility, motivation/staffing, patients' mobile-cost/ownership), with 17 sub-categories. These were used to design the proposed framework.

CONCLUSIONS

Successful adoption of mHealth by healthcare workers in the developing world will depend on addressing the factors identified in the proposed framework. They must be assessed in each specific setting prior to mHealth implementation. Application of the proposed framework will help shape future policy and practice of mHealth implementation in the developing world and increase adoption by health workers.

Gaming for Adherence to Medication using Ehealth in Rheumatoid arthritis (GAMER) study: a randomised controlled trial

Objective

To examine the effect on adherence to disease modifying anti-rheumatic drugs (DMARDs) in participants with rheumatoid arthritis (RA) of a serious game that targeted implicit attitudes toward medication.

Methods

A multicentre randomised controlled trial (RCT) was performed with adults with RA that used DMARDs and possessed a smartphone/tablet. Control and intervention groups received care as usual. The intervention group played the serious game at will during 3 months. Game play data and online questionnaires Compliance Questionnaire on Rheumatology (CQR), Beliefs about Medicine Questionnaire (BMQ), Health Assessment Questionnaire (HAQ) and Rheumatoid Arthritis Disease Activity Index (RADAI) were collected. Primary outcome was DMARD implementation adherence operationalised as the difference in proportion of non-adherent participants (<80% taking adherence) between intervention and control group after 3 months using a Chi-squared test. Two sample t-tests and Wilcoxon rank-sum test were performed to test for differences on secondary outcomes.

Results

Of the 110 intervention participants that started the study, 87 participants (79%) installed the game and had a median playtime of 9.7 hours at 3 months. Overall, 186 participants completed the study. Adherence in intervention group (63%) and control group (54%) did not differ significantly (p=0.13) at 3 months. Neither were there differences oberved in CQR continuous score, beliefs about medication (BMQ) or clinical outcomes (HAQ and RADAI).

Conclusion

A serious game aimed at reinterpreting attitudes toward medication failed to show an effect on adherence to DMARDs or clinical outcomes in patients with RA. The game was played frequently indicating that it can be an effective channel for reaching patients.

Trial registration number

NL7217.

Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study

BACKGROUND

Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.

OBJECTIVE

With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.

METHODS

The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.

RESULTS

The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.

CONCLUSIONS

Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population.

Analysing breast cancer survivors’ acceptance profiles for using an electronic pillbox connected to a smartphone application using Seintinelles, a French community-based research tool

Introduction: Up to 50% of breast cancer (BC) survivors discontinue their adjuvant endocrine therapy (AET) before the recommended 5 years, raising the issue of medication non-adherence. eHealth technologies have the potential to support patients to enhance their medication adherence and may offer an effective way to complement the healthcare. In order for eHealth technologies to be successfully implemented into the healthcare system, end-users need to be willing and accepting to use these eHealth technologies.

Aim: This study aims to evaluate the current usability of eHealth technologiesin and to identify differences in BC SURVIVORS BC survivors accepting a medication adherence enhancing eHealth technology to support their AET to BC survivors that do not accept such a medication adherence enhancing eHealth technology.

Methods: This study was conducted in 2020 including volunteering BC survivors belonging to the Seintinelles Association. Eligible participants were women, diagnosed with BC within the last 10 years, and been exposed to, an AET. Univariable and multivariable logistic regression analyses were performed to investigate medication adherence enhancing eHealth technology acceptance profiles among BC survivors. The dependent variable was defined as acceptance of an electronic pillbox connected to a smartphone application (hereafter: medication adherence enhancing eHealth technology).

Results: Overall, 23% of the participants already use a connected device or health application on a regular basis. The mean age of the participants was 52.7 (SD 10.4) years. In total, 67% of 1268 BC survivors who participated in the survey declared that they would accept a medication adherence enhancing eHealth technology to improve their AET. BC survivors accepting a medication adherence enhancing eHealth technology for their AET, are younger (OR = 0.97, 95% CI [0.95; 0.98]), do take medication for other diseases (OR = 0.31, 95% CI [0.13; 0.68]), already use a medication adherence enhancing eHealth technology or technique (OR = 1.74, 95% CI [1.06; 2.94]) and are willing to possess or currently possess one or more connected devices or health applications (OR = 2.89, 95% CI [2.01; 4.19]).

Conclusion: Understanding acceptance profiles of BC survivors is fundamental for conceiving an effective eHealth technology enhancing AET among BC survivors. Hence, such profiling will foster the development of personalized medication adherence enhancing eHealth technology.

E-health as a sine qua non for modern healthcare

In each era we need to balance between being able to provide care with our “technical skill, scientific knowledge, and human understanding” (Harrison's Principles of Internal Medicine, 1950) to the individual patient and simultaneously ensure that our healthcare serves all. With the increasing demand of healthcare by an aging population and the lack of specialists, accessible healthcare within a reasonable time frame is not always guaranteed. E-health provides solutions for current situations where we do not meet our own aims of good healthcare, such as restrictions in access to care and a reduction in care availability by a reducing workforce. In addition, telemedicine offers opportunities to improve our healthcare beyond what is possible by in person visits. However, e-health is often viewed as an deficient version of healthcare of low quality. We disagree with this view. In this article we will discuss how to position e-health in the current situation of healthcare, given the continuing rapid development of digital technologies and the changing needs of healthcare professionals and patients. We will address the evolution of e-health towards connected and intelligent systems and the stakeholders perspective, aiming to open up the discussion on e-Health.

The Impact of eHealth Interventions on the Improvement of Self-Care in Chronic Patients: An Overview of Systematic Reviews

Promoting self-care is one of the most promising strategies for managing chronic conditions. This overview aimed to investigate the effectiveness of eHealth interventions at improving self-care in patients with type-2 diabetes mellitus, cardiovascular disease, and chronic obstructive pulmonary disease when compared to standard care. We carried out a review of systematic reviews on PubMed, Scopus, Cochrane, PsychInfo, and CINAHL. AMSTAR-2 was used for quality appraisal. Eight systematic reviews (six with meta-analysis) were included, involving a total of 41,579 participants. eHealth interventions were categorized into three subgroups: (i) reminders via messaging apps, emails, and apps; (ii) telemonitoring and online operator support; (iii) internet and web-based educational programs. Six systematic reviews showed an improvement in self-care measurements through eHealth interventions, which also led to a better quality of life and clinical outcomes (HbA1C, blood pressure, hospitalization, cholesterol, body weight). This overview provided some implications for practice and research: eHealth is effective in increasing self-care in chronic patients; however, it is required to designate the type of eHealth intervention based on the needed outcome (e.g., implementing telemonitoring to increase self-monitoring of blood pressure). In addition, there is a need to standardize self-care measures through increased use of validated assessment tools.

The Interplay of Work, Digital Health Usage, and the Perceived Effects of Digitalization on Physicians' Work: Network Analysis Approach

Background

In health care, the benefits of digitalization need to outweigh the risks, but there is limited knowledge about the factors affecting this balance in the work environment of physicians. To achieve the benefits of digitalization, a more comprehensive understanding of this complex phenomenon related to the digitalization of physicians’ work is needed.

Objective

The aim of this study was to examine physicians’ perceptions of the effects of health care digitalization on their work and to analyze how these perceptions are associated with multiple factors related to work and digital health usage.

Methods

A representative sample of 4630 (response rate 24.46%) Finnish physicians (2960/4617, 64.11% women) was used. Statements measuring the perceived effects of digitalization on work included the patients’ active role, preventive work, interprofessional cooperation, decision support, access to patient information, and faster consultations. Network analysis of the perceived effects of digitalization and factors related to work and digital health usage was conducted using mixed graphical modeling. Adjusted and standardized regression coefficients are denoted by b. Centrality statistics were examined to evaluate the relative influence of each variable in terms of node strength.

Results

Nearly half of physicians considered that digitalization has promoted an active role for patients in their own care (2104/4537, 46.37%) and easier access to patient information (1986/4551, 43.64%), but only 1 in 10 (445/4529, 9.82%) felt that the impact has been positive on consultation times with patients. Almost half of the respondents estimated that digitalization has neither increased nor decreased the possibilities for preventive work (2036/4506, 45.18%) and supportiveness of clinical decision support systems (1941/4458, 43.54%). When all variables were integrated into the network, the most influential variables were purpose of using health information systems, employment sector, and specialization status. However, the grade given to the electronic health record (EHR) system that was primarily used had the strongest direct links to faster consultations (b=0.32) and facilitated access to patient information (b=0.28). At least 6 months of use of the main EHR was associated with facilitated access to patient information (b=0.18).

Conclusions

The results highlight the complex interdependence of multiple factors associated with the perceived effects of digitalization on physicians’ work. It seems that a high-quality EHR system is critical for promoting smooth clinical practice. In addition, work-related factors may influence other factors that affect digital health success. These factors should be considered when developing and implementing new digital health technologies or services for physicians’ work. The adoption of digital health is not just a technological project but a project that changes existing work practices.

Effects of eHealth Interventions on Quality of Life and Psychological Outcomes in Cardiac Surgery Patients: Systematic Review and Meta-analysis

BACKGROUND

Patients undergoing heart surgery may experience a range of physiological changes, and the postoperative recovery time is long. Patients and their families often have concerns about quality of life (QoL) after discharge. eHealth interventions may improve patient participation, ensure positive and effective health management, improve the quality of at-home care and the patient's quality of life, and reduce rates of depression.

OBJECTIVE

The purpose of this study was to evaluate the effects of eHealth interventions on the physiology, psychology, and compliance of adult patients after cardiac surgery to provide a theoretical basis for clinical practice.

METHODS

We conducted systematic searches of the following 4 electronic databases: PubMed, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials. Mean (SD) values were used to calculate the pooled effect sizes for all consecutive data, including QoL, anxiety, and depression. Where the same results were obtained using different instruments, we chose the standardized mean difference with a 95% CI to represent the combined effect size; otherwise, the mean difference (MD) with a 95% CI was used. Odds ratios were used to calculate the combined effect size for all dichotomous data. The Cohen Q test for chi-square distribution and an inconsistency index (I²) were used to test for heterogeneity among the studies. We chose a fixed-effects model to estimate the effect size if there was no significant heterogeneity in the data (I²≤50%); otherwise, a random-effects model was used. The quality of the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2).

RESULTS

The search identified 3632 papers, of which 19 met the inclusion criteria. In terms of physical outcomes, the score of the control group was lower than that of the intervention group (MD 0.15, 95% CI 0.03-0.27, I²=0%, P=.02). There was no significant difference in the mental outcomes between the intervention and control groups (MD 0.10, 95% CI -0.03 to 0.24, I²=46.4%, P=.14). The control group's score was lower than that of the intervention group for the depression outcomes (MD -0.53, 95% CI -0.89 to -0.17, I²=57.1%, P=.004). Compliance outcomes improved in most intervention groups. The results of the sensitivity analysis were robust. Nearly half of the included studies (9/19, 47%) had a moderate to high risk of bias. The quality of the evidence was medium to low.

CONCLUSIONS

eHealth improved the physical component of quality of life and depression after cardiac surgery; however, there was no statistical difference in the mental component of quality of life. The effectiveness of eHealth on patient compliance has been debated. Further high-quality studies on digital health are required.

TRIAL REGISTRATION

PROSPERO CRD42022327305; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=327305.

A randomized controlled trial of customized adherence enhancement (CAE-E): study protocol for a hybrid effectiveness-implementation project

BACKGROUND

Mood-stabilizing medications are a cornerstone of treatment for people with bipolar disorder, though approximately half of these individuals are poorly adherent with their medication, leading to negative and even severe health consequences. While a variety of approaches can lead to some improvement in medication adherence, there is no single approach that has superior adherence enhancement and limited data on how these approaches can be implemented in clinical settings. Existing data have shown an increasing need for virtual delivery of care and interactive telemedicine interventions may be effective in improving adherence to long-term medication.

METHODS

Customized adherence enhancement (CAE) is a brief, practical bipolar-specific approach that identifies and targets individual patient adherence barriers for intervention using a flexibly administered modular format that can be delivered via telehealth communications. CAE is comprised of up to four standard treatment modules including Psychoeducation, Communication with Providers, Medication Routines, and Modified Motivational Interviewing. Participants will attend assigned module sessions with an interventionist based on their reasons for non-adherence and will be assessed for adherence, functioning, bipolar symptoms, and health resource use across a 12-month period. Qualitative and quantitative data will also be collected to assess barriers and facilitators to CAE implementation and reach and adoption of CAE among clinicians in the community.

DISCUSSION

The proposed study addresses the need for practical adherence interventions that are effective, flexible, and designed to adapt to different settings and patients. By focusing on a high-risk, vulnerable group of people with bipolar disorder, and refining an evidence-based approach that will integrate into workflow of public-sector care and community mental health clinics, there is substantial potential for improving bipolar medication adherence and overall health outcomes on a broad level.

TRIAL REGISTRATION

The study was registered on ClinicalTrials.gov NCT04622150 on November 9, 2020.

Reimbursed Medication Adherence Enhancing Interventions in European Countries: Results of the EUREcA Study

Introduction: Current literature lacks detailed understanding of the reimbursement framework of medication adherence enhancing interventions (MAEIs). As part of the ENABLE COST Action, the EUREcA (“EUropen REimbursement strategies for interventions targeting medication Adherence”) study aimed to provide an in-depth overview of reimbursed MAEIs currently available in European countries at national and regional levels and to pave the way for further MAEIs to be implemented in the future.

Methods: A web-based, cross-sectional survey was performed across 38 European countries and Israel. The survey questionnaire was developed as a result of an iterative process of discussion informed by a desk review. The survey was performed among invited ENABLE collaborators from June to July 2021. Besides descriptive analysis, association between country income and health care expenditure, and the availability of reimbursed MAEIs were also assessed.

Results: The survey identified 13 reimbursed MAEIs in nine countries: multi-dose drug dispensing (n = 5), medication review (n = 4), smart device (n = 2), mobile application (n = 1), and patient education (n = 1). The median GDP per capita of countries having ≥1 reimbursed MAEI was significantly higher compared to countries having no reimbursed adherence intervention (33,888 EUR vs 16,620 EUR, respectively; p = 0.05).

Conclusions: Our findings highlight that to date only a small number of MAEIs have been reimbursed in European countries. Comprehensive health technology assessment recommendations and multi-stakeholder collaboration could help removing barriers related to the implementation and reimbursement of MAEIs.

Poison control centres and alternative forms of communication: comparison of response rates between text message and telephone follow-up

INTRODUCTION

In recent years, the number of patients managed by poison control centres (PCCs) has increased without a proportional increase in the number of physicians. To improve efficiency without neglecting patient follow-up, some PCCs have begun using text messages. We evaluated the difference in response rates between text messaging and traditional telephone follow-up.

MATERIALS AND METHODS

This retrospective, monocentric, non-randomised cohort study was conducted using data from calls made by the New Aquitaine PCC between February 27, 2019, and March 31, 2019. Patients were contacted up to three times by a phone call or short message service (SMS).

RESULTS

For the analysis, 823 patients were included. At the end of follow-up, the response rates were similar in the phone call and SMS group (94 vs. 94%; p = 0.76) with median [interquartile range] response times of 0 min [0; 27 min] and 29 min [6; 120 min], respectively. The response rates did not differ in subgroups stratified according to sex, self-poisoning vs. relative response, age class, and solicitation during working hours vs. outside of working hours (all p > 0.5). Moreover, health practitioners required 2.4-fold more time to call than to send text messages (p < 0.001), and all practitioners were satisfied or very satisfied with text messaging implementation.

CONCLUSION

Patients had good adherence to text messages. Text messages are easy to use, rapid, and allow the physician to easily prioritise follow-up without occupying the emergency line. Additionally, the costs of installation and maintenance are low for text message systems; these low costs facilitate the implementation of such services in various medical situations.

Improving the Safety of Medicines via Digital Technology: An Assessment of the Scope and Quality of Risk Minimization Websites in the United States and United Kingdom

INTRODUCTION

EHealth holds tremendous promise for enhancing drug safety initiatives known as risk minimization programs. Little is known, however, regarding the scope and quality of existing risk minimization websites.

METHODS

Two publicly accessible repositories, REMS@FDA [1] and Electronic Medicines Compendium [2], were reviewed to identify all regulatorily approved risk minimization programs in the United States (US) and United Kingdom (UK) with websites. Website quality was evaluated using the Enlight Quality Assessment tool, a psychometrically validated instrument that addresses seven quality domains.

RESULTS

Ninety-three websites were identified: 59 for healthcare professionals (7 UK/52 US), and 34 for patients (5 UK/29 US). The websites functioned chiefly as archives for electronic copies of educational materials; a subset (31/93) had additional features. Mean quality ratings for Usability (mean 4.70, SD 0.59), Visual Design (mean 4.03, SD 0.87) and Content (mean 4.31, SD 0.82) were good. General Subjective Evaluation was fair (mean 3.15, SD 1.21). Mean scores for Therapeutic Alliance and Therapeutic Persuasiveness were poor (mean 2.62, SD 1.47; and mean 2.50, SD 1.48, respectively); those for User Engagement were very poor (mean 2.25, SD 1.03). No differences were found by target audience but several were identified based on region.

CONCLUSIONS

Risk minimization websites are easy to navigate and well organized. Few, however, incorporate eHealth design elements that facilitate user engagement, build therapeutic alliance and exert therapeutic persuasiveness. Such elements can enhance program uptake and effectiveness. Results highlight opportunities for improving the quality of risk minimization websites and their ability to bridge pharmaceutical and healthcare systems.

Patient and practitioner views on a combined face-to-face and digital intervention to support medication adherence in hypertension: a qualitative study within primary care

OBJECTIVES

To explore patients' and healthcare practitioners' (HCPs) views about non-adherence to hypertension medication and potential content of a combined very brief face-to-face discussion (VBI) and digital intervention (DI).

METHODS

A qualitative study (N=31): interviews with patients with hypertension (n=6) and HCPs (n=11) and four focus groups with patients with hypertension (n=14). Participants were recruited through general practices in Eastern England and London. Topic guides explored reasons for medication non-adherence and attitudes towards a potential intervention to support adherence. Stimuli to facilitate discussion included example SMS messages and smartphone app features, including mobile sensing. Analysis was informed methodologically by the constant comparative approach and theoretically by perceptions and practicalities approach.

RESULTS

Participants' overarching explanations for non-adherence were non-intentional (forgetting) and intentional (concerns about side effects, reluctance to medicate). These underpinned their views on intervention components: messages that targeted forgetting medication or obtaining prescriptions were considered more useful than messages providing information on consequences of non-adherence. Tailoring the DI to the individuals' needs, regarding timing and number of messages, was considered important for user engagement. Patients wanted control over the DI and information about data use associated with any location sensing. While the DI was considered limited in its potential to address intentional non-adherence, HCPs saw the potential for a VBI in addressing this gap, if conducted in a non-judgemental manner. Incorporating a VBI into routine primary care was considered feasible, provided it complemented existing GP practice software and HCPs received sufficient training.

CONCLUSIONS

A combined VBI-DI can potentially address intentional and non-intentional reasons for non-adherence to hypertension medication. For optimal engagement, recommendations from this work include a VBI conducted in a non-judgmental manner and focusing on non-intentional factors, followed by a DI that is easy-to-use, highly tailored and with provision of data privacy details about any sensing technology used.

Adherence to Growth Hormone Treatment Using a Connected Device in Latin America: Real-World Exploratory Descriptive Analysis Study

BACKGROUND

Recombinant human growth hormone (rhGH) therapy is an effective treatment for children with growth disorders. However, poor outcomes are often associated with suboptimal adherence to treatment.

OBJECTIVE

The easypod connected injection device records and transmits injection settings and dose data from patients receiving rhGH. In this study, we evaluated adherence to rhGH treatment, and associated growth outcomes, in Latin American patients.

METHODS

Adherence and growth data from patients aged 2-18 years from 12 Latin American countries were analyzed. Adherence data were available for 6207 patients with 2,449,879 injections, and growth data were available for 497 patients with 2232 measurements. Adherence was categorized, based on milligrams of rhGH injected versus milligrams of rhGH prescribed, as high (≥85%), intermediate (>56%-<85%), or low (≤56%). Transmission frequency was categorized as high (≥1 per 3 months) or low (<1 per 3 months). Chi-square tests were applied to study the effect of pubertal status at treatment start and sex on high adherence, and to test differences in frequency transmission between the three adherence levels. Multilevel linear regression techniques were applied to study the effect of adherence on observed change in height standard deviation score (∆HSDS).

RESULTS

Overall, 68% (4213/6207), 25% (n=1574), and 7% (n=420) of patients had high, intermediate, and low adherence, respectively. Pubertal status at treatment start and sex did not have a significant effect on high adherence. Significant differences were found in the proportion of patients with high transmission frequency between high (2018/3404, 59%), intermediate (608/1331, 46%), and low (123/351, 35%) adherence groups (P<.001). Adherence level had a significant effect on ∆HSDS (P=.006). Mean catch-up growth between 0-24 months was +0.65 SD overall (+0.52 SD in patients with low/intermediate monthly adherence and +0.69 SD in patients with high monthly adherence). This difference translated into 1.1 cm greater catch-up growth with high adherence.

CONCLUSIONS

The data extracted from the easypod Connect ecosystem showed high adherence to rhGH treatment in Latin American patients, with positive growth outcomes, indicating the importance of connected device solutions for rhGH treatment in patients with growth disorders.

Healthcare professionals’ perceptions on barriers and facilitators to DMARD use in rheumatoid arthritis

Background

Disease-modifying anti-rheumatic drugs (DMARDs) are the cornerstone of rheumatoid arthritis (RA) treatment. However, the full benefits of DMARDs are often not realized because many patients are sub-optimally adherent to their medication. In order to optimize adherence, it is essential that healthcare professionals (HCPs) understand patients’ barriers and facilitators for medication use. Insight in these barriers and facilitators may foster the dialogue about adequate medication use between HCPs and patients. What HCPs perceive as barriers and facilitators has, so far, scarcely been investigated. This study aimed to identify the perceptions of HCPs on patients’ barriers and facilitators that might influence their adherence.

Methods

This qualitative study was performed using semi structured in-depth interviews with HCPs. An interview guide was used, based on an adjusted version of the Theoretical Domains Framework (TDF). Thematic analysis was conducted to identify factors that influence barriers and facilitators to DMARD use according to HCPs.

Results

Fifteen HCPs (5 rheumatologists, 5 nurses and 5 pharmacists) were interviewed. They mentioned a variety of factors that, according to their perceptions, influence DMARD adherence in patients with RA. Besides therapy-related factors, such as (onset of) medication effectiveness and side-effects, most variation was found within patient-related factors and reflected patients’ beliefs, ways of coping, and (self-management) skills toward medication and their condition. In addition, factors related to the condition (e.g., level of disease activity), healthcare team and system (e.g., trust in HCP), and social and economic context (e.g. support, work shifts) were reported.

Conclusions

This study provided insights in HCPs’ perceptions of the barriers and facilitators to DMARD use patients with RA. Most factors that were mentioned were patient-related and potentially modifiable. When physicians understand patients’ perceptions on medication use, adherence to DMARDs can probably be optimized in patients with RA leading to more effectiveness of treatment outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07459-0.

Effectiveness of Digital Counseling Environments on Anxiety, Depression, and Adherence to Treatment Among Patients Who Are Chronically Ill: Systematic Review

Background

Patients who are chronically ill need novel patient counseling methods to support their self-care at different stages of the disease. At present, knowledge of how effective digital counseling is at managing patients’ anxiety, depression, and adherence to treatment seems to be fragmented, and the development of digital counseling will require a more comprehensive view of this subset of interventions.

Objective

This study aims to identify and synthesize the best available evidence on the effectiveness of digital counseling environments at improving anxiety, depression, and adherence to treatment among patients who are chronically ill.

Methods

Systematic searches of the EBSCO (CINAHL), PubMed, Scopus, and Web of Science databases were conducted in May 2019 and complemented in October 2020. The review considered studies that included adult patients aged ≥18 years with chronic diseases; interventions evaluating digital (mobile, web-based, and ubiquitous) counseling interventions; and anxiety, depression, and adherence to treatment, including clinical indicators related to adherence to treatment, as outcomes. Methodological quality was assessed using the standardized Joanna Briggs Institute critical appraisal tool for randomized controlled trials or quasi-experimental studies. As a meta-analysis could not be conducted because of considerable heterogeneity in the reported outcomes, narrative synthesis was used to synthesize the results.

Results

Of the 2056 records screened, 20 (0.97%) randomized controlled trials, 4 (0.19%) pilot randomized controlled trials, and 2 (0.09%) quasi-experimental studies were included. Among the 26 included studies, 10 (38%) digital, web-based interventions yielded significantly positive effects on anxiety, depression, adherence to treatment, and the clinical indicators related to adherence to treatment, and another 18 (69%) studies reported positive, albeit statistically nonsignificant, changes among patients who were chronically ill. The results indicate that an effective digital counseling environment comprises high-quality educational materials that are enriched with multimedia elements and activities that engage the participant in self-care. Because of the methodological heterogeneity of the included studies, it is impossible to determine which type of digital intervention is the most effective for managing anxiety, depression, and adherence to treatment.

Conclusions

This study provides compelling evidence that digital, web-based counseling environments for patients who are chronically ill are more effective than, or at least comparable to, standard counseling methods; this suggests that digital environments could complement standard counseling.

Risk Factors for Non-Adherence to Medications That Affect Surgery: A Retrospective Study in Japan

PURPOSE

Data on risk factors for non-adherence to doctors' and pharmacists' instructions to discontinue medications prior to surgery are lacking. This study aimed to identify characteristics and risk factors for such non-adherent patients.

PATIENTS AND METHODS

Data (including patient age, sex, prescription medications, comorbidities, presence of roommate at home, and number of days between receiving instruction and surgery) of 887 patients who used medications affecting surgery at a university hospital from April 2017 to March 2020 were retrospectively evaluated. The primary endpoint was to investigate the rate of non-adherence and to explore independent risk factors for non-adherence (with age categorized as ≥65 [versus <65] years). Secondary endpoints included analysis of limited number of departments subgroup and a sensitivity analysis (with age categorized as ≥75 [versus <75] years) to confirm the robustness of the primary endpoint results. Independent risk factors for non-adherence were identified using logistic regression analysis.

RESULTS

The non-adherence rate was 11.4% (n=101/887), median age (interquartile range) at admission was 73 (70-79) years, and proportion of male patients was 81.2% (n=82). The main analysis adjusted for age ≥65 (versus <65) years showed age as a risk factor for increased non-adherence (adjusted odds ratio: 2.1, 95% confidence interval: 1.09-4.05; p=0.027). However, analyses adjusted for departments (other than urology, gynecology, and breast surgery, with a large sex bias in hospitalized patients) and for age ≥75 (versus <75) years showed no such risk.

CONCLUSION

Age ≥65 years was associated with a higher risk of non-adherence to medications that should be discontinued before surgery. It is important for doctors and pharmacists to ensure that patients at high risk for non-adherence are aware of the importance of adherence. Our findings may help identify patients at high risk for non-adherence to such medications.

Electronic Smart Blister Packages to Monitor and Support Medication Adherence: A Usability Study

PURPOSE

An electronic version of the Dosepak^® (EDP) which records date and time of dosing events has been developed to monitor adherence to medication packaged in blisters. This study aimed to evaluate its usability and acceptance and to monitor dose-taking adherence for optimal implementation in future clinical trials and practice.

METHODS

Healthy volunteers aged over 18 years were asked to dispense placebo tablets twice daily from EDPs equipped with a re-usable electronic module for a total duration of four weeks. Afterwards, subjects were asked to complete an online questionnaire and partake in a short one-on-one interview. The usability of the EDP was assessed using the System Usability Scale (SUS), while dose-taking adherence was monitored by EDP records, pill counting, and self-report. The short interview explored user experiences in more detail.

RESULTS

Twenty subjects with median [IQR] age 41.5 [32-49.8] years, 55% female, 45% healthcare professionals, and 20% chronic medication users completed the study and found the EDP easy to use, with a mean [SD] SUS score of 78.0 [11.2]. Median [IQR] dose-taking adherence was 89% [82-95%] based on EDP records, 96.5% [89-100%] based on pill counting, 92% [91-96%] based on self-report, and the levels differed significantly (p < 0.05). Four themes emerged from the interviews: user preference, experience, patient burden, and ideas for improvement. Most participants preferred smaller sized blisters. They found the EDP simple to use and did not see any patient burden for its use in trials or clinical practice. Some reported forgetfulness and suggested reminders built into the blister or sent to their mobile phones. Adequate information or instruction should also be provided for older people and polypharmacy patients.

CONCLUSION

EDP had good perceived usability, was well accepted, and differed significantly from other adherence measurement methods. This study provides input to further guide scale-up of the blister packages.

Interventions for improving medication adherence in community-dwelling older people with multimorbidity: A systematic review and meta-analysis

BACKGROUND

Multimorbidity is highly prevalent amongst older people. Compared with those with a single disease, older people with multimorbidity are more susceptible to medication nonadherence, which causes adverse health outcomes and increased health care costs. The effectiveness of interventions for improving medication adherence in this population is still unclear.

OBJECTIVE

To evaluate the effectiveness of interventions to improve medication adherence for community-dwelling older people with multimorbidity.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Ten databases: Airiti Library, China National Knowledge Infrastructure, Cochrane CENTRAL, EBSCO CINAHL, OVID EMBASE, OVID MEDLINE, Proquest Central, PsycINFO, Wanfang Database and Web of Science Core Collection.

REVIEW METHODS

Studies evaluating the effects of interventions on medication adherence in community-dwelling older people with multimorbidity were included. Two researchers independently performed the study selection, data extraction and risk assessment. Intervention effects were pooled by random-effects meta-analysis.

RESULTS

A total of nine studies with 3,292 participants were included. Studies on self-management interventions revealed a significant and modest improvement in medication adherence (n = 3 studies; SMD 0.52; 95% CI 0.04 to 0.99; p = 0.03, I² = 43%). Studies using electronic health interventions demonstrated a small yet significant benefit for medication adherence (n = 2 studies; SMD 0.22; 95% CI 0.02 to 0.42; p = 0.03, I² = 0%). There was no pooled significant effect of medication review on medication adherence (n = 4 studies; SMD -0.03; 95% CI -0.21 to 0.15; p = 0.74, I² = 68%). Most of the studies failed to yield a significant improvement in patients' health outcomes.

CONCLUSIONS

Self-management interventions and electronic health interventions might be effective in improving medication adherence for older people with multimorbidity. Future adherence interventions are needed to demonstrate improvements in medication adherence and health outcomes.

PROSPERO REGISTRATION NUMBER

CRD42020150500.

Evaluating a Strengths-Based mHealth Tool (MyStrengths): Explorative Feasibility Trial

BACKGROUND

As the number of people living with chronic illnesses increases, providing wide-reaching and easy-to-use support tools is becoming increasingly important. Supporting people in this group to recognize and use more of their personal strengths has the potential to improve their quality of life. With this in mind, we have developed the MyStrengths app prototype, a gamefully designed app aimed at aiding users in both identifying their strengths and using these strengths more actively in their daily life.

OBJECTIVE

The goal of this study was to evaluate the user-reported feasibility and usefulness of the MyStrengths app. The study additionally aimed to explore whether the use of MyStrengths could be associated with selected psychosocial outcomes.

METHODS

A 31-day explorative feasibility trial with a pretest-posttest design and an optional end of study interview was conducted. Data collection included system-use log data, demographic information, pre- and post-psychosocial measures (ie, strengths use, self-efficacy, health-related quality of life, depression), user experience measures (ie, usability, engagement, flow), and interview data.

RESULTS

In total, 34 people with at least 1 chronic condition were enrolled in the study, with 26 participants (mean age 48 years, range 29-62 years; 1 male) completing the trial. Among these individuals, 18 were also interviewed posttrial. Participants used the MyStrengths app an average of 6 days during the trial period, with 54% (14/26) using the app over a period of at least 19 days. In total, 8738 unique app actions were registered. Of the psychosocial outcome measures, only 1 subscale, general health in the RAND 36-Item Health Survey, yielded significant pre- and posttest changes. Posttrial interviews showed that the number of participants who considered the MyStrengths app to be useful, somewhat useful, or not useful was evenly distributed across 3 groups. However, every participant did voice support for the strengths approach. All participants were able to identify a multitude of personal strengths using the MyStrengths app. Most participants that reported it to be useful had little or no previous experience with the personal strengths approach. A multitude of users welcomed the gameful design choices, particularly the rolling die feature, suggesting strengths exercises, activities that use a specific strength, were well received.

CONCLUSIONS

Although the reported usefulness and feedback from use varied, most participants were favorable to the strengths-focused approach to care and support. Consequently, low-threshold and wide-reaching mobile health tools that use a strengths-focused approach, such as MyStrengths, hold the potential to support people living with chronic illness in performing self-management and achieving mastery of their life.

Effectiveness of eHealth Interventions in Improving Medication Adherence for Patients With Chronic Obstructive Pulmonary Disease or Asthma: Systematic Review

Background

Poor treatment adherence in patients with chronic obstructive pulmonary disease (COPD) or asthma is a global public health concern with severe consequences in terms of patient health and societal costs. A potentially promising tool for addressing poor compliance is eHealth.

Objective

This review investigates the effects of eHealth interventions on medication adherence in patients with COPD or asthma.

Methods

A systematic literature search was conducted in the databases of Cochrane Library, PsycINFO, PubMed, and Embase for studies with publication dates between January 1, 2000, and October 29, 2020. We selected randomized controlled trials targeting adult patients with COPD or asthma, which evaluated the effectiveness of an eHealth intervention on medication adherence. The risk of bias in the included studies was examined using the Cochrane Collaboration’s risk of bias tool. The results were narratively reviewed.

Results

In total, six studies focusing on COPD and seven focusing on asthma were analyzed. Interventions were mostly internet-based or telephone-based, and could entail telemonitoring of symptoms and medication adherence, education, counseling, consultations, and self-support modules. Control groups mostly comprised usual care conditions, whereas a small number of studies used a face-to-face intervention or waiting list as the control condition. For COPD, the majority of eHealth interventions were investigated as an add-on to usual care (5/6 studies), whereas for asthma the majority of interventions were investigated as a standalone intervention (5/7 studies). Regarding eHealth interventions targeting medication adherence for COPD, two studies reported nonsignificant effects, one study found a significant effect in comparison to usual care, and three reported mixed results. Of the seven studies that investigated eHealth interventions targeting medication adherence in asthma, three studies found significant effects, two reported nonsignificant effects, and two reported mixed effects.

Conclusions

The mixed results on the effectiveness of eHealth interventions in improving treatment adherence for asthma and COPD are presumably related to the type, context, and intensity of the interventions, as well as to differences in the operationalization and measurement of adherence outcomes. Much remains to be learned about the potential of eHealth to optimize treatment adherence in COPD and asthma.

From Precision Metapharmacology to Patient Empowerment: Delivery of Self-Care Practices for Epilepsy, Pain, Depression and Cancer Using Digital Health Technologies

To improve long-term outcomes of therapies for chronic diseases, health promotion and lifestyle modifications are the most promising and sustainable strategies. In addition, advances in digital technologies provide new opportunities to address limitations of drug-based treatments, such as medication non-adherence, adverse effects, toxicity, drug resistance, drug shortages, affordability, and accessibility. Pharmaceutical drugs and biologics can be combined with digital health technologies, including mobile medical apps (digital therapeutics), which offer additional clinical benefits and cost-effectiveness. Promises of drug+digital combination therapies are recognized by pharmaceutical and digital health companies, opening opportunities for integrating pharmacotherapies with non-pharmacological interventions (metapharmacology). Herein we present unique features of digital health technologies which can deliver personalized self-care modalities such as breathing exercises, mindfulness meditation, yoga, physical activity, adequate sleep, listening to preferred music, forgiveness and gratitude. Clinical studies reveal how aforementioned complimentary practices may support treatments of epilepsy, chronic pain, depression, cancer, and other chronic diseases. This article also describes how digital therapies delivering “medicinal” self-care and other non-pharmacological interventions can also be personalized by accounting for: 1) genetic risks for comorbidities, 2) adverse childhood experiences, 3) increased risks for viral infections such as seasonal influenza, or COVID-19, and 4) just-in-time stressful and traumatic circumstances. Development and implementation of personalized pharmacological-behavioral combination therapies (precision metapharmacology) require aligning priorities of key stakeholders including patients, research communities, healthcare industry, regulatory and funding agencies. In conclusion, digital technologies enable integration of pharmacotherapies with self-care, lifestyle interventions and patient empowerment, while concurrently advancing patient-centered care, integrative medicine and digital health ecosystems.