Longitudinal clinical decision support for assessing decisions over time: State-of-the-art and future directions

• Published in: Digital health 2024-01, Vol.10, p.20552076241249925-20552076241249925
• Main Authors: Loftus, Tyler J, Balch, Jeremy A, Marquard, Jenna L, Ray, Jessica M, Alper, Brian S, Ojha, Neeraj, Bihorac, Azra, Melton-Meaux, Genevieve, Khanna, Gopal, Tignanelli, Christopher J
• Format: Article
• Language: English
• Subjects: Automation; Clinical decision making; Longitudinal studies
• ISSN: 2055-2076; 2055-2076
• DOI: 10.1177/20552076241249925

Objective Patients and clinicians rarely experience healthcare decisions as snapshots in time, but clinical decision support (CDS) systems often represent decisions as snapshots. This scoping review systematically maps challenges and facilitators to longitudinal CDS that are applied at two or more timepoints for the same decision made by the same patient or clinician. Methods We searched Embase, PubMed, and Medline databases for articles describing development, validation, or implementation of patient- or clinician-facing longitudinal CDS. Validated quality assessment tools were used for article selection. Challenges and facilitators to longitudinal CDS are reported according to PRISMA-ScR guidelines. Results Eight articles met inclusion criteria; each article described a unique CDS. None used entirely automated data entry, none used living guidelines for updating the evidence base or knowledge engine as new evidence emerged during the longitudinal study, and one included formal readiness for change assessments. Seven of eight CDS were implemented and evaluated prospectively. Challenges were primarily related to suboptimal study design (with unique challenges for each study) or user interface. Facilitators included use of randomized trial designs for prospective enrollment, increased CDS uptake during longitudinal exposure, and machine-learning applications that are tailored to the CDS use case. Conclusions Despite the intuitive advantages of representing healthcare decisions longitudinally, peer-reviewed literature on longitudinal CDS is sparse. Existing reports suggest opportunities to incorporate longitudinal CDS frameworks, automated data entry, living guidelines, and user readiness assessments. Generating best practice guidelines for longitudinal CDS would require a greater depth and breadth of published work and expert opinion.