hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Artificial Intelligence Applications in Health Care Practice: Scoping Review
Karolinska Institutet, Medical Management Centre, Stockholm, Sweden. (Healthcare improvement research group)ORCID iD: 0000-0003-4334-9977
Halmstad University, School of Health and Welfare. Karolinska Institutet, Medical Management Centre, Stockholm, Sweden. (Healthcare improvement research group)ORCID iD: 0000-0003-2836-903X
Halmstad University, School of Health and Welfare. (Healthcare improvement research group)ORCID iD: 0000-0001-7610-0954
Halmstad University, School of Health and Welfare. (Healthcare improvement research group)ORCID iD: 0000-0002-4341-660X
Show others and affiliations
2022 (English)In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 24, no 10, article id e40238Article in journal (Refereed) Published
Abstract [en]

Background: Artificial intelligence (AI) is often heralded as a potential disruptor that will transform the practice of medicine. The amount of data collected and available in health care, coupled with advances in computational power, has contributed to advances in AI and an exponential growth of publications. However, the development of AI applications does not guarantee their adoption into routine practice. There is a risk that despite the resources invested, benefits for patients, staff, and society will not be realized if AI implementation is not better understood.

Objective: The aim of this study was to explore how the implementation of AI in health care practice has been described and researched in the literature by answering 3 questions: What are the characteristics of research on implementation of AI in practice? What types and applications of AI systems are described? What characteristics of the implementation process for AI systems are discernible?

Methods: A scoping review was conducted of MEDLINE (PubMed), Scopus, Web of Science, CINAHL, and PsycINFO databases to identify empirical studies of AI implementation in health care since 2011, in addition to snowball sampling of selected reference lists. Using Rayyan software, we screened titles and abstracts and selected full-text articles. Data from the included articles were charted and summarized.

Results: Of the 9218 records retrieved, 45 (0.49%) articles were included. The articles cover diverse clinical settings and disciplines; most (32/45, 71%) were published recently, were from high-income countries (33/45, 73%), and were intended for care providers (25/45, 56%). AI systems are predominantly intended for clinical care, particularly clinical care pertaining to patient-provider encounters. More than half (24/45, 53%) possess no action autonomy but rather support human decision-making. The focus of most research was on establishing the effectiveness of interventions (16/45, 35%) or related to technical and computational aspects of AI systems (11/45, 24%). Focus on the specifics of implementation processes does not yet seem to be a priority in research, and the use of frameworks to guide implementation is rare.

Conclusions: Our current empirical knowledge derives from implementations of AI systems with low action autonomy and approaches common to implementations of other types of information systems. To develop a specific and empirically based implementation framework, further research is needed on the more disruptive types of AI systems being implemented in routine care and on aspects unique to AI implementation in health care, such as building trust, addressing transparency issues, developing explainable and interpretable solutions, and addressing ethical concerns around privacy and data protection.Keywords: artificial intelligence; health care; implementation; scoping review; technology adoption.©Malvika Sharma, Carl Savage, Monika Nair, Ingrid Larsson, Petra Svedberg, Jens M Nygren. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 05.10.2022.

Place, publisher, year, edition, pages
Toronto: JMIR Publications , 2022. Vol. 24, no 10, article id e40238
Keywords [en]
artificial intelligence, health care, implementation, scoping review, technology adoption
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Research subject
Health Innovation, IDC; Health Innovation, IDC
Identifiers
URN: urn:nbn:se:hh:diva-48294DOI: 10.2196/40238ISI: 000869463700001PubMedID: 36197712Scopus ID: 2-s2.0-85139313999OAI: oai:DiVA.org:hh-48294DiVA, id: diva2:1701903
Note

This research is included in the CAISR Health research profile.

Available from: 2022-10-07 Created: 2022-10-07 Last updated: 2024-12-03Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records

Savage, CarlNair, MonicaLarsson, IngridSvedberg, PetraNygren, Jens M.

Search in DiVA

By author/editor
Sharma, MalvikaSavage, CarlNair, MonicaLarsson, IngridSvedberg, PetraNygren, Jens M.
By organisation
School of Health and Welfare
In the same journal
Journal of Medical Internet Research
Health Care Service and Management, Health Policy and Services and Health Economy

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 93 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf