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Clinical Decision Support Systems for Palliative Care Management: A Scoping Review
Fabiana Cristina Dos Santos1, Urszula A Snigurska1, Gail M Keenan1
1Department of Family, Community, and Health Systems Science (F.C.D.S, U.A.S., G.M.K.), College of Nursing, University of Florida, Gainesville, Florida, USA.
Clinical decision support systems (CDSSs) aid nurses in palliative care. While improving patient outcomes, adherence to CDSS recommendations varies, highlighting a need for better usability and trust in these systems.
Area of Science:
- Palliative Care
- Health Informatics
- Clinical Decision Support
Background:
- Palliative care services are expanding in clinical settings.
- Clinical decision support systems (CDSSs) are vital for enhancing care quality for patients with life-limiting conditions.
- Nurses and clinicians require effective tools to support complex patient care decisions.
Purpose of the Study:
- To characterize palliative care CDSSs.
- To explore end-users' actions, adherence to recommendations, and clinical decision time.
- To identify factors influencing the effectiveness and usability of palliative care CDSSs.
Main Methods:
- Systematic scoping review of CINAHL, Embase, and PubMed databases (inception–September 2022).
- Adherence to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines.
- Analysis of 12 selected studies from 284 screened abstracts, assessing evidence levels.
Main Results:
- Palliative care CDSSs focus on patient identification, referrals, medication, and symptom management.
- All studies indicated CDSSs improved clinician knowledge, leading to better decisions and patient outcomes.
- Adherence to CDSS recommendations varied (3 high, 4 low), with usability issues like lack of customization and trust cited as limitations.
Conclusions:
- Palliative care CDSSs can improve care quality for patients.
- Variability in CDSSs and study methods complicates direct comparisons of effectiveness.
- Further research with rigorous methods is recommended to evaluate CDSS features, adherence, and efficiency.
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