Reducing Avoidable Emergency Visits and Hospitalizations With Patient Risk-Based Prescriptive Analytics: A Quality Improvement Project at an Oncology Care Model Practice.
Ajeet GajraYolaine Jeune-SmithAlexandrina BalaneanKelly A MillerDanielle BergmanJohn ShowalterRay D PagePublished in: JCO oncology practice (2023)
The AI tool has enabled nurse case managers to identify and resolve critical clinical issues and reduce avoidable ACU. Effects on outcomes can be inferred from the reduction; targeting short-term interventions toward patients most at-risk translates to better long-term care and outcomes. QI projects involving predictive modeling of patient risk, prescriptive analytics, and nurse outreach may reduce ACU.
Keyphrases
- quality improvement
- long term care
- primary care
- healthcare
- end stage renal disease
- palliative care
- big data
- case report
- newly diagnosed
- ejection fraction
- chronic kidney disease
- public health
- emergency department
- prognostic factors
- peritoneal dialysis
- type diabetes
- machine learning
- insulin resistance
- affordable care act
- emergency medical