The Healthcare Innovation Lab is helping support BJC and WashU’s Tele Critical Care (TCC) team in the transition from a vendor-provided platform for patient monitoring and analytics into Epic Monitor. The transition to Epic Monitor is starting with three BJC ICU units in Q4 2024 and will be rolled out to all monitored units in a phased approach going into 2025.
Within the Epic Predictive Analytics Program, work is being done to analyze and assess four Epic-based predictive models to be used for quality assurance and clinical decision support within Epic Monitor. The Epic models are assessed for accuracy and their performance in comparison to the counterpart vendor-provided models. These Epic-based models include:
- ICU In-Hospital Mortality Risk – — Calculates a patient’s expected mortality risk for retrospective risk-adjusted benchmarking of ICU mortality rates, enabling the clinical team to see outcomes and quality of care in their ICUs.
- ICU Length of Stay – — Calculates a patient’s expected length of stay in the ICU for retrospective risk-adjusted benchmarking, enabling the clinical team to see outcomes and quality of care in their ICUs.
- Risk of ICU Readmission or Mortality – — Identifies patients who are at risk of being readmitted to the ICU or dying, helping ICU clinicians make better better-informed decisions during rounding and discharge planning workflows.
- Deterioration Index – — Provides a trending risk score to identify patients who are clinically deteriorating, allowing for the stratification of patient populations to better monitor the progression of individual patients.
The Lab is also assisting the Epic Monitor implementation with updating some classical (non-predictive) scoring systems. This work involves separating a prioritization score developed by Epic into two separate prioritization scores: one for clinical risk and one for incomplete daily review/documentation.
