Evidence map›Paper›PMID 31367650›Full record

ArticleEGEMS (Washington, DC)2019

Willingness to Participate in Health Information Networks with Diverse Data Use: Evaluating Public Perspectives.

Jodyn Platt, Minakshi Raj, Ayşe G Büyüktür, M Grace Trinidad, Olufunmilayo Olopade, Mark S Ackerman, Sharon Kardia

Abstract read
In one paragraph

Article in EGEMS (Washington, DC), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Public comfort with the use of ChatGPT and expectations for healthcare.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  5. Article
  6. Review
  7. Article
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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

7 authors.

Jodyn PlattUniversity of Michigan Medical School, Department of Learning Health Sciences, US.ORCID 0000-0003-4902-4903
Minakshi RajUniversity of Michigan School of Public Health, Department of Health Management and Policy, US.
Ayşe G BüyüktürUniversity of Michigan School of Information and Michigan Institute for Clinical and Health Research, US.
M Grace TrinidadUniversity of Michigan Medical School, Department of Learning Health Sciences, US.
Olufunmilayo OlopadeUniversity of Chicago Medicine, US.
Mark S AckermanUniversity of Michigan School of Information, College of Engineering, EECS, and Medical School, Department of Learning Health Systems, US.
Sharon KardiaUniversity of Michigan School of Public Health, Department of Epidemiology, US.

Funding

Michigan Institute for Clinical and Health Research (MICHR)UL1TR002240 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUMENG, JULIE C, MASHOUR, GEORGE ALEXANDER · 2017 to 2022
$54.9M
The Lifecycle of Health Data: Polices and PracticesR01CA214829 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KARDIA, SHARON L, PLATT, JODYN ELIZABETH · 2018 to 2021
$2.4M
NCATS NIH HHS UL1 TR002240NCI NIH HHS R01 CA214829
6 · The paper itself

Abstract

introductionHealth information generated by health care encounters, research enterprises, and public health is increasingly interoperable and shareable across uses and users. This paper examines the US public's willingness to be a part of multi-user health information networks and identifies factors associated with that willingness.

methodsUsing a probability-based sample (n = 890), we examined the univariable and multivariable relationships between willingness to participate in health information networks and demographic factors, trust, altruism, beliefs about the public's ethical obligation to participate in research, privacy, medical deception, and policy and governance using linear regression modeling.

resultsWillingness to be a part of a multi-user network that includes health care providers, mental health, social services, research, or quality improvement is low (26 percent-7.4 percent, depending on the user). Using stepwise regression, we identified a model that explained 42.6 percent of the variability in willingness to participate and included nine statistically significant factors associated with the outcome: Trust in the health system, confidence in policy, the belief that people have an obligation to participate in research, the belief that health researchers are accountable for conducting ethical research, the desire to give permission, education, concerns about insurance, privacy, and preference for notification. DISCUSSION: Our results suggest willingness to be a part of multi-user data networks is low, but that attention to governance may increase willingness. Building trust to enable acceptance of multi-use data networks will require a commitment to aligning data access practices with the expectations of the people whose data is being used.

Indexed as

health data networkslearning health systemspublic opiniontrust

Identifiers

PMID31367650
PMCPMC6659576

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.