Evidence map›Paper›PMID 36826986›Full record

ArticleJMIR mHealth and uHealth2023

Recommendations for the Quality Management of Patient-Generated Health Data in Remote Patient Monitoring: Mixed Methods Study.

Robab Abdolkhani, Kathleen Gray, Ann Borda, Ruth DeSouza

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Article in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

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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

4 authors.

Robab AbdolkhaniCentre for Digital Transformation of Health, The University of Melbourne, Melbourne, Australia.ORCID 0000-0002-6741-7543
Kathleen GrayCentre for Digital Transformation of Health, The University of Melbourne, Melbourne, Australia.ORCID 0000-0003-1616-2170
Ann BordaFaculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia.ORCID 0000-0003-3884-2978
Ruth DeSouzaSchool of Art, Royal Melbourne Institue of Technology University, Melbourne, Australia.ORCID 0000-0003-3862-5375

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient-generated health data (PGHD) collected from innovative wearables are enabling health care to shift to outside clinical settings through remote patient monitoring (RPM) initiatives. However, PGHD are collected continuously under the patient's responsibility in rapidly changing circumstances during the patient's daily life. This poses risks to the quality of PGHD and, in turn, reduces their trustworthiness and fitness for use in clinical practice.

objectiveUsing a sociotechnical health informatics lens, we developed a data quality management (DQM) guideline for PGHD captured from wearable devices used in RPM with the objective of investigating how DQM principles can be applied to ensure that PGHD can reliably inform clinical decision-making in RPM.

methodsFirst, clinicians, health information specialists, and MedTech industry representatives with experience in RPM were interviewed to identify DQM challenges. Second, these stakeholder groups were joined by patient representatives in a workshop to co-design potential solutions to meet the expectations of all the stakeholders. Third, the findings, along with the literature and policy review results, were interpreted to construct a guideline. Finally, we validated the guideline through a Delphi survey of international health informatics and health information management experts.

resultsThe guideline constructed in this study comprised 19 recommendations across 7 aspects of DQM. It explicitly addressed the needs of patients and clinicians but implied that there must be collaboration among all stakeholders to meet these needs.

conclusionsThe increasing proliferation of PGHD from wearables in RPM requires a systematic approach to DQM so that these data can be reliably used in clinical care. The developed guideline is an important next step toward safe RPM.

Indexed as

Medical InformaticsWearable Electronic DevicesDelivery of Health CareHumansMonitoring, Physiologicbig datadata quality managementpatient-generated health dataremote patient monitoringremote sensing technologytelemedicinewearable electronic devices

Identifiers

PMID36826986
PMCPMC10007009

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LicenceCC BY
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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.