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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
12 X users
facebook
1 Facebook page

Readers on

mendeley
161 Mendeley
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Article details
Title
The Gap Between AI and Bedside: Participatory Workshop on the Barriers to the Integration, Translation, and Adoption of Digital Health Care and AI Startup Technology Into Clinical Practice
Published in
Journal of Medical Internet Research, May 2023
DOI 10.2196/32962
Pubmed ID
Authors
Abstract

Artificial intelligence (AI) and digital health technological innovations from startup companies used in clinical practice can yield better health outcomes, reduce health care costs, and improve patients' experience. However, the integration, translation, and adoption of these technologies into clinical practice are plagued with many challenges and are lagging. Furthermore, explanations of the impediments to clinical translation are largely unknown and have not been systematically studied from the perspective of AI and digital health care startup founders and executives. The aim of this paper is to describe the barriers to integrating early-stage technologies in clinical practice and health care systems from the perspectives of digital health and health care AI founders and executives. A stakeholder focus group workshop was conducted with a sample of 10 early-stage digital health and health care AI founders and executives. Digital health, health care AI, digital health-focused venture capitalists, and physician executives were represented. Using an inductive thematic analysis approach, transcripts were organized, queried, and analyzed for thematic convergence. We identified the following four categories of barriers in the integration of early-stage digital health innovations into clinical practice and health care systems: (1) lack of knowledge of health system technology procurement protocols and best practices, (2) demanding regulatory and validation requirements, (3) challenges within the health system technology procurement process, and (4) disadvantages of early-stage digital health companies compared to large technology conglomerates. Recommendations from the study participants were also synthesized to create a road map to mitigate the barriers to integrating early-stage or novel digital health technologies in clinical practice. Early-stage digital health and health care AI entrepreneurs identified numerous barriers to integrating digital health solutions into clinical practice. Mitigation initiatives should create opportunities for early-stage digital health technology companies and health care providers to interact, develop relationships, and use evidence-based research and best practices during health care technology procurement and evaluation processes.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 161 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 12 7%
Lecturer 7 4%
Researcher 7 4%
Student > Postgraduate 6 4%
Student > Master 5 3%
Other 15 9%
Unknown 109 68%
Readers by discipline
Readers by discipline Count As %
Business, Management and Accounting 12 7%
Medicine and Dentistry 7 4%
Economics, Econometrics and Finance 5 3%
Computer Science 4 2%
Social Sciences 4 2%
Other 15 9%
Unknown 114 71%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 July 2023.
All research outputs
#1,923,172
of 28,695,121 outputs
Outputs from Journal of Medical Internet Research
#1,455
of 9,188 outputs
Outputs of similar age
#36,607
of 422,592 outputs
Outputs of similar age from Journal of Medical Internet Research
#18
of 286 outputs
Altmetric has tracked 28,695,121 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,188 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.1. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 422,592 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 286 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.