Effect of electronic adherence monitoring on adherence and outcomes in chronic conditions: A systematic review and meta-analysis
Open accessAbstract
Introduction: Electronic adherence monitoring (EAM) is increasingly used to improve adherence. However, there is limited evidence on the effect of EAM in across chronic conditions and on patient acceptability. We aimed to assess the effect of EAM on adherence and clinical outcomes, across all ages and all chronic conditions, and examine acceptability in this systematic review and meta-analysis. Methods: A systematic search of Ovid MEDLINE, EMBASE, Social Work Abstracts, PsycINFO, International Pharmaceutical Abstracts and CINAHL databases was performed from database inception to December 31, 2020. Randomised controlled trials (RCTs) that evaluated the effect of EAM on medication adherence as part of an adherence intervention in chronic conditions were included. Study characteristics, differences in adherence and clinical outcomes between intervention and control were extracted from each study. Estimates were pooled using random-effects meta-analysis, and presented as mean differences, standardised mean differences (SMD) or risk ratios depending on the data. Differences by study-level characteristics were estimated using subgroup meta-analysis to identify intervention characteristics associated with improved adherence. Effects on adherence and clinical outcomes which could not be meta-analysed, and patient acceptability, were synthesised narratively. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed, and Risk of bias (RoB) assessed using the Cochrane Collaboration’s RoB tool for RCTs. The review is registered with PROSPERO CRD42017084231. Findings: Our search identified 365 studies, of which 47 studies involving 6194 patients were included. Data from 27 studies (n = 2584) were extracted for the adherence outcome. The intervention group (n = 1267) had significantly better adherence compared to control (n = 1317), (SMD = 0.93, CI:0.69 to 1.17, p<0.0001) with high heterogeneity across studies (I 2= 86%). There was a significant difference in effect according to intervention complexity (p = 0.01); EAM only improved adherence when used with a reminder and/or health provider support. Clinical outcomes were measured in 38/47 (81%) of studies; of these data from 14 studies were included in a meta-analysis of clinical outcomes for HIV, hypertension and asthma. In total, 13/47 (28%) studies assessed acceptability; patient perceptions were mixed. Interpretation: Patients receiving an EAM intervention had significantly better adherence than those who did not, but improved adherence did not consistently translate into clinical benefits. Acceptability data were mixed. Further research measuring effects on clinical outcomes and patient acceptability are needed.
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Implementing personalized care strategies-such as tailored feedback, reminders, and incentives-can significantly boost patient engagement.
“Studies have shown that implementing personalized care strategies—such as tailored feedback, reminders, and incentives—can significantly boost patient engagement.30,33,34”
From Program cost and return on investment analysis of remote patient monitoring for hypertension management in the cardiology department of a large healthcare system (2026) · cites this paper as [34]
The Results (Effect of EAM on medication adherence; page not available) report significantly better medication adherence with electronic-monitoring interventions, and the patient-acceptability Results report positive responses to feedback and adherence discussions. The paper also describes customizable reminders and an incentive-based intervention, but it does not establish that these strategies significantly boost patient engagement; its measured outcome is chiefly medication adherence. (LLM, conf=0.86)
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- Authors
- Chan, A. H. Y., Foot, H., Pearce, C. J., Horne, R., Foster, J. M., & Harrison, J.
- Affiliations
- University of Auckland (NZ)
- UCL School of Pharmacy (GB)
- The University of Sydney (AU)
- Corresponding author
- Chan, Amy Hai Yan
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2022-03-21
- Volume
- 17
- Issue
- 3
- Pages
- e0265715
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC8936478
- OpenAlex
- W4220896664
- Cited by
- 47
- References
- 79
- Citations by year
- 2026: 10 · 2025: 10 · 2024: 16 · 2023: 5 · 2022: 6
- FWCI
- 2.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- ResearchSpace (University of Auckland) (submittedVersion, cc-by)
- Funders
- Amgen
- Pfizer
- GlaxoSmithKline
- Gilead Sciences
- Biogen
- Auckland District Health Board
- National Institute for Health and Care Research
- Asthma and Lung UK
- British Psychological Society
- Maurice and Phyllis Paykel Trust
- Cilag
- Topics
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacy and Medical Practices
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Keywords
- electronic adherence monitoring, medication adherence, chronic disease, patient acceptability, adherence interventions, reminders, HIV, hypertension, asthma, clinical outcomes, intervention complexity, patient empowerment, patient satisfaction, patient education, patient engagement
- MeSH terms
- Asthma, Chronic Disease, Electronics, Humans, Bias, Medication Adherence
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