Skip to main content
Journal cover image

Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.

Journal articles  - Pragmatic Clinical Trial, Journal Article
Sideris, K; Weir, CR; Schmalfuss, C; Hanson, H; Pipke, M; Tseng, P-H; Lewis, N; Sallam, K; Bozkurt, B; Hanff, T; Schofield, R; Larimer, K ...
Published in: Journal of the American Medical Informatics Association : JAMIA
April 2024

We conducted an implementation planning process during the pilot phase of a pragmatic trial, which tests an intervention guided by artificial intelligence (AI) analytics sourced from noninvasive monitoring data in heart failure patients (LINK-HF2).A mixed-method analysis was conducted at 2 pilot sites. Interviews were conducted with 12 of 27 enrolled patients and with 13 participating clinicians. iPARIHS constructs were used for interview construction to identify workflow, communication patterns, and clinician's beliefs. Interviews were transcribed and analyzed using inductive coding protocols to identify key themes. Behavioral response data from the AI-generated notifications were collected.Clinicians responded to notifications within 24 hours in 95% of instances, with 26.7% resulting in clinical action. Four implementation themes emerged: (1) High anticipatory expectations for reliable patient communications, reduced patient burden, and less proactive provider monitoring. (2) The AI notifications required a differential and tailored balance of trust and action advice related to role. (3) Clinic experience with other home-based programs influenced utilization. (4) Responding to notifications involved significant effort, including electronic health record (EHR) review, patient contact, and consultation with other clinicians.Clinician's use of AI data is a function of beliefs regarding the trustworthiness and usefulness of the data, the degree of autonomy in professional roles, and the cognitive effort involved.The implementation planning analysis guided development of strategies that addressed communication technology, patient education, and EHR integration to reduce clinician and patient burden in the subsequent main randomized phase of the trial. Our results provide important insights into the unique implications of implementing AI analytics into clinical workflow.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Journal of the American Medical Informatics Association : JAMIA

DOI

EISSN

1527-974X

ISSN

1067-5027

Publication Date

April 2024

Volume

31

Issue

4

Start / End Page

919 / 928

Related Subject Headings

  • Medical Informatics
  • Information Technology
  • Humans
  • Heart Failure
  • Communication
  • Artificial Intelligence
  • Ambulatory Care Facilities
  • 46 Information and computing sciences
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Sideris, K., Weir, C. R., Schmalfuss, C., Hanson, H., Pipke, M., Tseng, P.-H., … Stehlik, J. (2024). Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial. Journal of the American Medical Informatics Association : JAMIA, 31(4), 919–928. https://doi.org/10.1093/jamia/ocae017
Sideris, Konstantinos, Charlene R. Weir, Carsten Schmalfuss, Heather Hanson, Matt Pipke, Po-He Tseng, Neil Lewis, et al. “Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.” Journal of the American Medical Informatics Association : JAMIA 31, no. 4 (April 2024): 919–28. https://doi.org/10.1093/jamia/ocae017.
Sideris K, Weir CR, Schmalfuss C, Hanson H, Pipke M, Tseng P-H, et al. Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial. Journal of the American Medical Informatics Association : JAMIA. 2024 Apr;31(4):919–28.
Sideris, Konstantinos, et al. “Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.” Journal of the American Medical Informatics Association : JAMIA, vol. 31, no. 4, Apr. 2024, pp. 919–28. Epmc, doi:10.1093/jamia/ocae017.
Sideris K, Weir CR, Schmalfuss C, Hanson H, Pipke M, Tseng P-H, Lewis N, Sallam K, Bozkurt B, Hanff T, Schofield R, Larimer K, Kyriakopoulos CP, Taleb I, Brinker L, Curry T, Knecht C, Butler JM, Stehlik J. Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial. Journal of the American Medical Informatics Association : JAMIA. 2024 Apr;31(4):919–928.
Journal cover image

Published In

Journal of the American Medical Informatics Association : JAMIA

DOI

EISSN

1527-974X

ISSN

1067-5027

Publication Date

April 2024

Volume

31

Issue

4

Start / End Page

919 / 928

Related Subject Headings

  • Medical Informatics
  • Information Technology
  • Humans
  • Heart Failure
  • Communication
  • Artificial Intelligence
  • Ambulatory Care Facilities
  • 46 Information and computing sciences
  • 42 Health sciences
  • 32 Biomedical and clinical sciences