Evidence map›Paper›PMID 32012090›Full record

ArticleJMIR mHealth and uHealth2020

Quality Assurance of Health Wearables Data: Participatory Workshop on Barriers, Solutions, and Expectations.

Robab Abdolkhani, Kathleen Gray, Ann Borda, Ruth DeSouza

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 20 citations in OpenAlex.

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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 at 1 institution in 1 country.

Robab AbdolkhaniHealth and Biomedical Informatics Centre, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0002-6741-7543
Kathleen GrayHealth and Biomedical Informatics Centre, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-1616-2170
Ann BordaHealth and Biomedical Informatics Centre, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-3884-2978
Ruth DeSouzaHealth and Biomedical Informatics Centre, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-3862-5375
The University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ubiquity of health wearables and the consequent production of patient-generated health data (PGHD) are rapidly escalating. However, the utilization of PGHD in routine clinical practices is still low because of data quality issues. There is no agreed approach to PGHD quality assurance; therefore, realizing the promise of PGHD requires in-depth discussion among diverse stakeholders to identify the data quality assurance challenges they face and understand their needs for PGHD quality assurance.

objectiveThis paper reports findings from a workshop aimed to explore stakeholders' data quality challenges, identify their needs and expectations, and offer practical solutions.

methodsA qualitative multi-stakeholder workshop was conducted as a half-day event on the campus of an Australian University located in a major health care precinct, namely the Melbourne Parkville Precinct. The 18 participants had experience of PGHD use in clinical care, including people who identified as health care consumers, clinical care providers, wearables suppliers, and health information specialists. Data collection was done by facilitators capturing written notes of the proceedings as attendees engaged in participatory design activities in written and oral formats, using a range of whole-group and small-group interactive methods. The collected data were analyzed thematically, using deductive and inductive coding.

resultsThe participants' discussions revealed a range of technical, behavioral, operational, and organizational challenges surrounding PGHD, from the time when data are collected by patients to the time data are used by health care providers for clinical decision making. PGHD stakeholders found consensus on training and engagement needs, continuous collaboration among stakeholders, and development of technical and policy standards to assure PGHD quality.

conclusionsAssuring PGHD quality is a complex process that requires the contribution of all PGHD stakeholders. The variety and depth of inputs in our workshop highlighted the importance of co-designing guidance for PGHD quality guidance.

Indexed as

MotivationWearable Electronic DevicesAustraliaData CollectionDelivery of Health CareHumansdata quality assuranceparticipatory researchpatient-generated health dataremote sensing technologywearable devices

Identifiers

PMID32012090
PMCPMC7003125
OpenAlexW2981319337

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.