Evidence map›Paper›PMID 35266873›Full record

ReviewJMIR mHealth and uHealth2022

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

Madilyn Mason, Youmin Cho, Jessica Rayo, Yang Gong, Marcelline Harris, Yun Jiang

Abstract readReview
In one paragraph

Review in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

77 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  12. Cardiac event-induced PTSD symptoms and continuous heart rate in coronary artery disease patients.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2026
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17 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Madilyn MasonSchool of Nursing, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0002-6775-147X
Youmin ChoSchool of Nursing, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-1381-652X
Jessica RayoSchool of Nursing, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0002-7954-8663
Yang GongSchool of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID 0000-0002-0864-8368
Marcelline HarrisSchool of Nursing, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0002-3957-6643
Yun JiangSchool of Nursing, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-6737-5016

Funding

Patient Engagement in Reporting Medication Events during Transitions of CareR01HS027846 · AHRQ · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GONG, YANG, JIANG, YUN · 2021 to 2025
$2.0M
Learning from patient safety events: A case base tool kitR01HS022895 · AHRQ · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI GONG, YANG · 2014 to 2018
$1.2M
AHRQ HHS R01 HS022895AHRQ HHS R01 HS027846
6 · The paper itself

Abstract

backgroundAccurate measurement and monitoring of patient medication adherence is a global challenge because of the absence of gold standard methods for adherence measurement. Recent attention has been directed toward the adoption of technologies for medication adherence monitoring, as they provide the opportunity for continuous tracking of individual medication adherence behavior. However, current medication adherence monitoring technologies vary according to their technical features and data capture methods, leading to differences in their respective advantages and limitations. Overall, appropriate criteria to guide the assessment of medication adherence monitoring technologies for optimal adoption and use are lacking.

objectiveThis study aims to provide a narrative review of current medication adherence monitoring technologies and propose a set of technology assessment criteria to support technology development and adoption.

methodsA literature search was conducted on PubMed, Scopus, CINAHL, and ProQuest Technology Collection (2010-present) using the combination of keywords medication adherence, measurement technology, and monitoring technology. The selection focused on studies related to medication adherence monitoring technology and its development and use. The technological features, data capture methods, and potential advantages and limitations of the identified technology applications were extracted. Methods for using data for adherence monitoring were also identified. Common recurring elements were synthesized as potential technology assessment criteria.

resultsOf the 3865 articles retrieved, 98 (2.54%) were included in the final review, which reported a variety of technology applications for monitoring medication adherence, including electronic pill bottles or boxes, ingestible sensors, electronic medication management systems, blister pack technology, patient self-report technology, video-based technology, and motion sensor technology. Technical features varied by technology type, with common expectations for using these technologies to accurately monitor medication adherence and increase adoption in patients' daily lives owing to their unobtrusiveness and convenience of use. Most technologies were able to provide real-time monitoring of medication-taking behaviors but relied on proxy measures of medication adherence. Successful implementation of these technologies in clinical settings has rarely been reported. In all, 28 technology assessment criteria were identified and organized into the following five categories: development information, technology features, adherence to data collection and management, feasibility and implementation, and acceptability and usability.

conclusionsThis narrative review summarizes the technical features, data capture methods, and various advantages and limitations of medication adherence monitoring technology reported in the literature and the proposed criteria for assessing medication adherence monitoring technologies. This collection of assessment criteria can be a useful tool to guide the development and selection of relevant technologies, facilitating the optimal adoption and effective use of technology to improve medication adherence outcomes. Future studies are needed to further validate the medication adherence monitoring technology assessment criteria and construct an appropriate technology assessment framework.

Indexed as

Technology Assessment, BiomedicalTelemedicineHumansMedication AdherenceTechnologymedication adherenceremote sensing technologytechnology assessmenttelemedicine

Identifiers

PMID35266873
PMCPMC8949687

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.