Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study
BackgroundDigitalization is currently revolutionizing health care worldwide. A promising technology in this context is artificial intelligence (AI). The application of AI can support health care providers in their daily work in various ways. The integration of AI is particula...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-02-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e63377 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832542852120313856 |
|---|---|
| author | Godwin Denk Giebel Pascal Raszke Hartmuth Nowak Lars Palmowski Michael Adamzik Philipp Heinz Marianne Tokic Nina Timmesfeld Frank Brunkhorst Jürgen Wasem Nikola Blase |
| author_facet | Godwin Denk Giebel Pascal Raszke Hartmuth Nowak Lars Palmowski Michael Adamzik Philipp Heinz Marianne Tokic Nina Timmesfeld Frank Brunkhorst Jürgen Wasem Nikola Blase |
| author_sort | Godwin Denk Giebel |
| collection | DOAJ |
| description |
BackgroundDigitalization is currently revolutionizing health care worldwide. A promising technology in this context is artificial intelligence (AI). The application of AI can support health care providers in their daily work in various ways. The integration of AI is particularly promising in clinical decision support systems (CDSSs). While the opportunities of this technology are numerous, the problems should not be overlooked.
ObjectiveThis study aimed to identify challenges and barriers in the context of AI-based CDSSs from the perspectives of experts across various disciplines.
MethodsSemistructured expert interviews were conducted with different stakeholders. These included representatives of patients, physicians and caregivers, developers of AI-based CDSSs, researchers (studying AI in health care and social and health law), quality management and quality assurance representatives, a representative of an ethics committee, a representative of a health insurance fund, and medical product consultants. The interviews took place on the web and were recorded, transcribed, and subsequently subjected to a qualitative content analysis based on the method by Kuckartz. The analysis was conducted using MAXQDA software. Initially, the problems were separated into “general,” “development,” and “clinical use.” Finally, a workshop within the project consortium served to systematize the identified problems.
ResultsA total of 15 expert interviews were conducted, and 309 expert statements with reference to problems and barriers in the context of AI-based CDSSs were identified. These emerged in 7 problem categories: technology (46/309, 14.9%), data (59/309, 19.1%), user (102/309, 33%), studies (17/309, 5.5%), ethics (20/309, 6.5%), law (33/309, 10.7%), and general (32/309, 10.4%). The problem categories were further divided into problem areas, which in turn comprised the respective problems.
ConclusionsA large number of problems and barriers were identified in the context of AI-based CDSSs. These can be systematized according to the point at which they occur (“general,” “development,” and “clinical use”) or according to the problem category (“technology,” “data,” “user,” “studies,” “ethics,” “law,” and “general”). The problems identified in this work should be further investigated. They can be used as a basis for deriving solutions to optimize development, acceptance, and use of AI-based CDSSs.
International Registered Report Identifier (IRRID)RR2-10.2196/preprints.62704 |
| format | Article |
| id | doaj-art-c448072d39114a079624477af43939eb |
| institution | Kabale University |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-c448072d39114a079624477af43939eb2025-02-03T15:00:34ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-02-0127e6337710.2196/63377Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview StudyGodwin Denk Giebelhttps://orcid.org/0000-0002-4182-1927Pascal Raszkehttps://orcid.org/0009-0008-6538-0733Hartmuth Nowakhttps://orcid.org/0000-0002-6509-1463Lars Palmowskihttps://orcid.org/0009-0008-9553-6575Michael Adamzikhttps://orcid.org/0000-0002-7188-4873Philipp Heinzhttps://orcid.org/0009-0007-5331-5785Marianne Tokichttps://orcid.org/0000-0001-9789-575XNina Timmesfeldhttps://orcid.org/0000-0002-5175-4326Frank Brunkhorsthttps://orcid.org/0000-0002-8132-8651Jürgen Wasemhttps://orcid.org/0000-0001-9653-168XNikola Blasehttps://orcid.org/0000-0003-3774-5009 BackgroundDigitalization is currently revolutionizing health care worldwide. A promising technology in this context is artificial intelligence (AI). The application of AI can support health care providers in their daily work in various ways. The integration of AI is particularly promising in clinical decision support systems (CDSSs). While the opportunities of this technology are numerous, the problems should not be overlooked. ObjectiveThis study aimed to identify challenges and barriers in the context of AI-based CDSSs from the perspectives of experts across various disciplines. MethodsSemistructured expert interviews were conducted with different stakeholders. These included representatives of patients, physicians and caregivers, developers of AI-based CDSSs, researchers (studying AI in health care and social and health law), quality management and quality assurance representatives, a representative of an ethics committee, a representative of a health insurance fund, and medical product consultants. The interviews took place on the web and were recorded, transcribed, and subsequently subjected to a qualitative content analysis based on the method by Kuckartz. The analysis was conducted using MAXQDA software. Initially, the problems were separated into “general,” “development,” and “clinical use.” Finally, a workshop within the project consortium served to systematize the identified problems. ResultsA total of 15 expert interviews were conducted, and 309 expert statements with reference to problems and barriers in the context of AI-based CDSSs were identified. These emerged in 7 problem categories: technology (46/309, 14.9%), data (59/309, 19.1%), user (102/309, 33%), studies (17/309, 5.5%), ethics (20/309, 6.5%), law (33/309, 10.7%), and general (32/309, 10.4%). The problem categories were further divided into problem areas, which in turn comprised the respective problems. ConclusionsA large number of problems and barriers were identified in the context of AI-based CDSSs. These can be systematized according to the point at which they occur (“general,” “development,” and “clinical use”) or according to the problem category (“technology,” “data,” “user,” “studies,” “ethics,” “law,” and “general”). The problems identified in this work should be further investigated. They can be used as a basis for deriving solutions to optimize development, acceptance, and use of AI-based CDSSs. International Registered Report Identifier (IRRID)RR2-10.2196/preprints.62704https://www.jmir.org/2025/1/e63377 |
| spellingShingle | Godwin Denk Giebel Pascal Raszke Hartmuth Nowak Lars Palmowski Michael Adamzik Philipp Heinz Marianne Tokic Nina Timmesfeld Frank Brunkhorst Jürgen Wasem Nikola Blase Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study Journal of Medical Internet Research |
| title | Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study |
| title_full | Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study |
| title_fullStr | Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study |
| title_full_unstemmed | Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study |
| title_short | Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study |
| title_sort | problems and barriers related to the use of ai based clinical decision support systems interview study |
| url | https://www.jmir.org/2025/1/e63377 |
| work_keys_str_mv | AT godwindenkgiebel problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT pascalraszke problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT hartmuthnowak problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT larspalmowski problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT michaeladamzik problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT philippheinz problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT mariannetokic problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT ninatimmesfeld problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT frankbrunkhorst problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT jurgenwasem problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy AT nikolablase problemsandbarriersrelatedtotheuseofaibasedclinicaldecisionsupportsystemsinterviewstudy |