ReviewInteractive journal of medical research2024
Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.
Review in Interactive journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.
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
17 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Real-World Performance Measurement of Patient-Centered Clinical Decision Support Tools: Qualitative Study.JMIR formative research · 2026Pooled it
- Digital patient safety interventions in primary care: a systematic review and meta-analysis.BMC medicine · 2026Pooled it
- Factors Influencing the Implementation and Adoption of Digital Nursing Technologies: Systematic Umbrella Review.Journal of medical Internet research · 2025Pooled it
- C8 Health, a Platform for the Implementation of Best Practices: Survey-Based Usability Study.JMIR human factors · 2026Article
- Learning From the Adoption of a Readmission Clinical Decision Support Tool: Group Model Building Approach.JMIR human factors · 2026Article
- Workflow-embedded automation improves hepatitis B screening and safety in b/tsDMARD users.BMC infectious diseases · 2026Article
- Engaging Hospital Staff to Identify Levers for Adoption of Clinical Decision Support: Protocol for a Single-Site Case Study Using System Dynamics Group Model Building.JMIR research protocols · 2026Article
- Nexus between policy and practice in institutionalization of clinical information systems and knowledge management in developing health systems: Context of tertiary hospitals in Malawi.PLOS digital health · 2026Article
- Strengthening digital competencies in India's health workforce: development and feasibility evaluation of a digital health competency framework for frontline healthcare workers in Uttar Pradesh.Oxford open digital health · 2026Article
- Developing Attributes and Levels for a Discrete Choice Experiment on Internet Hospital Service Preferences Among Chinese Patients with Chronic Diseases: A Mixed-Methods Study.Patient preference and adherence · 2026Article
- Knowledge-based clinical decision support system for the automated classification of anemia in hemodialysis patientsBiomedica : revista del Instituto Nacional de Salud · 2025Observational
- Clinical Decision Support Systems in Indian Healthcare Settings: Benefits, Barriers, and Future Implications.Healthcare (Basel, Switzerland) · 2025Review
- Integrating PRISM with User-centered Design (PRISM+UCD): Designing clinical decision support for safe opioid prescribing.Research square · 2025Article
- Leveraging Dual Usability Methods to Evaluate Clinical Decision Support Among Patients With Traumatic Brain Injury: Mixed Methods Study.JMIR human factors · 2025Article
- Analytical validation of Exandra: a clinical decision support system for promoting guideline-directed therapy of type-2 diabetes in primary care - a collaborative study with experts from Diabetes Canada.BMC medical informatics and decision making · 2025Article
- Orthopaedic training for non-orthopaedic providers: A review.Bioinformation · 2025Article
- Implementation and Evaluation of a Real-Time Prescription Alert System to Optimize Antiretroviral Therapy and Medication Adherence in People Living with HIV. SANPAT PROJECT.Patient preference and adherence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinical decision support systems (CDSSs) are designed to assist in health care delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts of health care technologies assisting in disease management, including diagnosis, treatment, and monitoring. While electronic medical records (EMRs) serve as data repositories, CDSSs are used to assist clinicians in providing personalized, context-specific recommendations derived by comparing individual patient data to evidence-based guidelines.
objectiveThis targeted literature review (TLR) aimed to identify characteristics and features of both stand-alone and EMR-integrated CDSSs that influence their outcomes and benefits based on published scientific literature.
methodsA TLR was conducted using the Embase, MEDLINE, and Cochrane databases to identify data on CDSSs published in a 10-year frame (2012-2022). Studies on computerized, guideline-based CDSSs used by health care practitioners with a focus on chronic disease areas and reporting outcomes for CDSS utilization were eligible for inclusion.
resultsA total of 49 publications were included in the TLR. Studies predominantly reported on EMR-integrated CDSSs (ie, connected to an EMR database; n=32, 65%). The implementation of CDSSs varied globally, with substantial utilization in the United States and within the domain of cardio-renal-metabolic diseases. CDSSs were found to positively impact "quality assurance" (n=35, 69%) and provide "clinical benefits" (n=20, 41%), compared to usual care. Among CDSS features, treatment guidance and flagging were consistently reported as the most frequent elements for enhancing health care, followed by risk level estimation, diagnosis, education, and data export. The effectiveness of a CDSS was evaluated most frequently in primary care settings (n=34, 69%) across cardio-renal-metabolic disease areas (n=32, 65%), especially in diabetes (n=13, 26%). Studies reported CDSSs to be commonly used by a mixed group (n=27, 55%) of users including physicians, specialists, nurses or nurse practitioners, and allied health care professionals.
conclusionsOverall, both EMR-integrated and stand-alone CDSSs showed positive results, suggesting their benefits to health care providers and potential for successful adoption. Flagging and treatment recommendation features were commonly used in CDSSs to improve patient care; other features such as risk level estimation, diagnosis, education, and data export were tailored to specific requirements and collectively contributed to the effectiveness of health care delivery. While this TLR demonstrated that both stand-alone and EMR-integrated CDSSs were successful in achieving clinical outcomes, the heterogeneity of included studies reflects the evolving nature of this research area, underscoring the need for further longitudinal studies to elucidate aspects that may impact their adoption in real-world scenarios.
Indexed as
Identifiers
What Socratic 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 Socratic graph.