Search: onr:"swepub:oai:DiVA.org:hh-52291" >
A Framework to Guid...
A Framework to Guide Implementation of AI in Health Care : Protocol for a Cocreation Research Project
-
- Nilsen, Per, 1960- (author)
- Linköpings universitet,Högskolan i Halmstad,Akademin för hälsa och välfärd,Linköping University, Linköping, Sweden,Avdelningen för samhälle och hälsa,Medicinska fakulteten,Halmstad Univ, Sweden
-
- Svedberg, Petra, 1973- (author)
- Högskolan i Halmstad,Akademin för hälsa och välfärd,Halmstad Univ, Sweden
-
- Neher, Margit, 1959- (author)
- Högskolan i Halmstad,Akademin för hälsa och välfärd,Halmstad Univ, Sweden
-
show more...
-
- Nair, Monika, 1985- (author)
- Högskolan i Halmstad,Akademin för hälsa och välfärd,Halmstad Univ, Sweden
-
- Larsson, Ingrid, 1968- (author)
- Högskolan i Halmstad,Akademin för hälsa och välfärd,Halmstad Univ, Sweden
-
- Petersson, Lena, 1968- (author)
- Högskolan i Halmstad,Akademin för hälsa och välfärd,Halmstad Univ, Sweden
-
- Nygren, Jens M., 1976- (author)
- Högskolan i Halmstad,Akademin för hälsa och välfärd,Halmstad Univ, Sweden
-
show less...
-
(creator_code:org_t)
- Toronto : JMIR Publications, 2023
- 2023
- English.
-
In: JMIR Research Protocols. - Toronto : JMIR Publications. - 1929-0748. ; 12
- Related links:
-
https://doi.org/10.2...
-
show more...
-
https://urn.kb.se/re...
-
https://doi.org/10.2...
-
https://urn.kb.se/re...
-
show less...
Abstract
Subject headings
Close
- Background: Artificial intelligence (AI) has the potential in health care to transform patient care and administrative processes, yet health care has been slow to adopt AI due to many types of barriers. Implementation science has shown the importance of structured implementation processes to overcome implementation barriers. However, there is a lack of knowledge and tools to guide such processes when implementing AI-based applications in health care.Objective: The aim of this protocol is to describe the development, testing, and evaluation of a framework, “Artificial Intelligence-Quality Implementation Framework” (AI-QIF), intended to guide decisions and activities related to the implementation of various AI-based applications in health care.Methods: The paper outlines the development of an AI implementation framework for broad use in health care based on the Quality Implementation Framework (QIF). QIF is a process model developed in implementation science. The model guides the user to consider implementation-related issues in a step-by-step design and plan and perform activities that support implementation. This framework was chosen for its adaptability, usability, broad scope, and detailed guidance concerning important activities and considerations for successful implementation. The development will proceed in 5 phases with primarily qualitative methods being used. The process starts with phase I, in which an AI-adapted version of QIF is created (AI-QIF). Phase II will produce a digital mockup of the AI-QIF. Phase III will involve the development of a prototype of the AI-QIF with an intuitive user interface. Phase IV is dedicated to usability testing of the prototype in health care environments. Phase V will focus on evaluating the usability and effectiveness of the AI-QIF. Cocreation is a guiding principle for the project and is an important aspect in 4 of the 5 development phases. The cocreation process will enable the use of both on research-based and practice-based knowledge.Results: The project is being conducted within the frame of a larger research program, with the overall objective of developing theoretically and empirically informed frameworks to support AI implementation in routine health care. The program was launched in 2021 and has carried out numerous research activities. The development of AI-QIF as a tool to guide the implementation of AI-based applications in health care will draw on knowledge and experience acquired from these activities. The framework is being developed over 2 years, from January 2023 to December 2024. It is under continuous development and refinement.Conclusions: The development of the AI implementation framework, AI-QIF, described in this study protocol aims to facilitate the implementation of AI-based applications in health care based on the premise that implementation processes benefit from being well-prepared and structured. The framework will be coproduced to enhance its relevance, validity, usefulness, and potential value for application in practice. © 2023 The Author(s).
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Health Care Service and Management, Health Policy and Services and Health Economy (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)
Keyword
- artificial intelligence
- AI
- health care
- implementation
- process models
- frameworks
- framework
- process model
- IDC
- IDC
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
To the university's database
- By the author/editor
-
Nilsen, Per, 196 ...
-
Svedberg, Petra, ...
-
Neher, Margit, 1 ...
-
Nair, Monika, 19 ...
-
Larsson, Ingrid, ...
-
Petersson, Lena, ...
-
show more...
-
Nygren, Jens M., ...
-
show less...
- About the subject
-
- MEDICAL AND HEALTH SCIENCES
-
MEDICAL AND HEAL ...
-
and Health Sciences
-
and Health Care Serv ...
-
- MEDICAL AND HEALTH SCIENCES
-
MEDICAL AND HEAL ...
-
and Health Sciences
-
and Public Health Gl ...
- Articles in the publication
-
JMIR Research Pr ...
- By the university
-
Halmstad University
-
Linköping University