ArticleApplied clinical informatics2020
Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.
Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of Artificial Intelligence-Based Nursing Interventions for Chronic Illness Care: Umbrella Review.JMIR nursing · 2026Pooled it
- Real-World Barriers to and Facilitators of Implementing AI-Based Clinical Decision Support Systems: Scoping Review.JMIR medical informatics · 2026Article
- The Designated Institutional Official: An Essential GME Role, But What Do They Actually Do?Journal of general internal medicine · 2026Article
- Machine learning prediction of discharge destination in patients with Parkinson's disease; a nationwide cohort study.NPJ Parkinson's disease · 2026Article
- Machine Learning Prediction of Discharge Destination in Patients with Parkinson's Disease; A Nationwide Cohort Study.Research square · 2026Article
- Smart aging: integrating AI into elderly healthcare.BMC geriatrics · 2025Review
- Opportunities and Challenges Associated with the Pilot Implementation of Clinical Decision Support Systems in a Rural Hospital: A Qualitative Study.Applied clinical informatics · 2025Article
- Generative Artificial Intelligence Use in Healthcare: Opportunities for Clinical Excellence and Administrative Efficiency.Journal of medical systems · 2025Article
- Artificial intelligence in transitional care: practice, promise, and pitfalls-a scoping review.Frontiers in digital health · 2025Review
- Critical activities for successful implementation and adoption of AI in healthcare: towards a process framework for healthcare organizations.Frontiers in digital health · 2025Article
- Advancing precision oncology with AI-powered genomic analysis.Frontiers in pharmacology · 2025Review
- Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
- Artificial intelligence in healthcare: a scoping review of perceived threats to patient rights and safety.Archives of public health = Archives belges de sante publique · 2024Article
- Applying the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability Framework Across Implementation Stages to Identify Key Strategies to Facilitate Clinical Decision Support System Integration Within a Large Metropolitan Health Service: Interview and Focus Group Study.JMIR medical informatics · 2024Article
- Recommendations to promote fairness and inclusion in biomedical AI research and clinical use.Journal of biomedical informatics · 2024Article
- Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions.PLOS digital health · 2024Article
- Health Equity and Ethical Considerations in Using Artificial Intelligence in Public Health and Medicine.Preventing chronic disease · 2024Article
- A Neurosurgical Readmissions Reduction Program in an Academic Hospital Leveraging Machine Learning, Workflow Analysis, and Simulation.Applied clinical informatics · 2024Article
- Evaluating Algorithmic Bias in 30-Day Hospital Readmission Models: Retrospective Analysis.Journal of medical Internet research · 2024Article
- A comprehensive overview of barriers and strategies for AI implementation in healthcare: Mixed-method design.PloS one · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictive model coupled with effective, patient-centered interventions.
objectiveThe aim of this study was to reduce unplanned hospital readmissions through the use of artificial intelligence-based clinical decision support.
methodsA commercially vended artificial intelligence tool was implemented at a regional hospital in La Crosse, Wisconsin between November 2018 and April 2019. The tool assessed all patients admitted to general care units for risk of readmission and generated recommendations for interventions intended to decrease readmission risk. Similar hospitals were used as controls. Change in readmission rate was assessed by comparing the 6-month intervention period to the same months of the previous calendar year in exposure and control hospitals.
resultsAmong 2,460 hospitalizations assessed using the tool, 611 were designated by the tool as high risk. Sensitivity and specificity for risk assignment were 65% and 89%, respectively. Over 6 months following implementation, readmission rates decreased from 11.4% during the comparison period to 8.1% (
conclusionWe observed a decrease in hospital readmission after implementing artificial intelligence-based clinical decision support. Our experience suggests that use of artificial intelligence to identify patients at the highest risk for readmission can reduce quality gaps when coupled with patient-centered interventions.
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