ArticleSSM. Qualitative research in health2025
A multi-site study of clinician perspectives in the lifecycle of an algorithmic risk prediction tool.
Article in SSM. Qualitative research in health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Recent advancements in the performative capacities of artificial intelligence (AI), machine learning (ML), and algorithmic-based tools open up numerous applications in modern medicine. There are, however, few studies that track the whole lifecycle of a digital healthcare tool as it evolves from conception, to design, and deployment in real world settings-especially with a focus on the social dynamics amongst the end-users of the tool: clinicians. In this paper, we present data from a multi-site, 5-year study focused on the development and deployment of an algorithmic risk calculator (HeartMate 3 Risk Score) into a validated and efficacy tested clinical decision support system (CDSS) for patients and clinicians engaging in shared decision making about left ventricular assist device (LVAD) therapy for advanced heart failure. We conducted a total of 76 interviews with 20 advanced heart failure cardiologists and 14 nurse coordinators with LVAD expertise (n=34) across different timepoints during the lifecycle of this digital healthcare tool. Results from Thematic Analysis revealed an array of social factors at play at each stage of the tool's development and implementation, from finding social consensus around risk messaging in the conception and design phases, to various social contingencies that served as facilitators and barriers to the successful integration of the tool in its later stages. Our findings confirm many previously raised issues with introducing new medical and digital healthcare tools into clinical care, and highlight new issues specific to the rapidly advancing technology in CDSS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.