Evidence map›Paper›PMID 36786028›Full record

SynthesisInternational journal of technology assessment in health care2023

Stakeholder preferences for attributes of digital health technologies to consider in health service funding.

Amy von Huben, Martin Howell, Sarah Norris, Kam Cheong Wong, James Tang, Samia Kazi, Liliana Laranjo, Clara K Chow, Kirsten Howard

Open access · hybridAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in International journal of technology assessment in health care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
5.2field-weighted citation impact, top 5% 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

6 citing papers in PubMed, 12 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

9 authors at 2 institutions in 1 country.

Amy von HubenSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.ORCID https://orcid.org/0000-0001-6168-9719
Martin HowellSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.
Sarah NorrisSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.
Kam Cheong WongSchool of Rural Health, The University of Sydney, Orange, NSW, Australia.
James TangSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.
Samia KaziWestmead Applied Research Centre (WARC), The University of Sydney, Westmead, NSW, Australia.
Liliana LaranjoWestmead Applied Research Centre (WARC), The University of Sydney, Westmead, NSW, Australia.
Clara K ChowWestmead Applied Research Centre (WARC), The University of Sydney, Westmead, NSW, Australia.
Kirsten HowardSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.
The University of Sydney · AUCamden and Campbelltown Hospitals · AU

Funding

Australian Government Australian Government Research ScholarshipNational Health and Medical Research Council MRFF Grant (APP1199902)University of Sydney Postgraduate Scholarship in Health Economics (Pati
6 · The paper itself

Abstract

objectivesHealth service providers are currently making decisions on the public funding of digital health technologies (DHTs) for managing chronic diseases with limited understanding of stakeholder preferences for DHT attributes. This study aims to understand the community, patient/carer, and health professionals' preferences to help inform a prioritized list of evaluation criteria.

methodsAn online best-worst scaling survey was conducted in Australia, New Zealand, Canada, and the United Kingdom to ascertain the relative importance of twenty-four DHT attributes among stakeholder groups using an efficient incomplete block design. The attributes were identified from a systematic review of DHT evaluation frameworks for consideration in a health technology assessment. Results were analyzed with multinomial models by stakeholder group and latent class.

resultsA total of 1,251 participants completed the survey (576 general community members, 543 patients/carers, and 132 health professionals). Twelve attributes achieved a preference score above 50 percent in the stakeholder group model, predominantly related to safety but also covering technical features, effectiveness, ethics, and economics. Results from the latent class model supported this prioritization. Overall, connectedness with the patient's healthcare team seemed the most important; with "

conclusionsIt is proposed that these prioritized twelve attributes be considered in all evaluations of DHTs that manage chronic disease, supplemented with a limited number of attributes that reflect the specific perspective of funders, such as equity of access, cost, and system-level implementation considerations.

Indexed as

Decision MakingHealth PersonnelAustraliaCaregiversHealth ServicesHumansbest-worst scalingchronic disease self-managementdigital health technologyhealth technology assessmentremote monitoring

Identifiers

PMID36786028
PMCPMC11574528
OpenAlexW4320709258

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.