Program Evaluation of an Early Nurse Intervention Team.

BACKGROUND: Many hospitals have implemented early rapid response teams to improve detection of patients at risk for decline. However, formal evaluation of these programs is rare. OBJECTIVE: To evaluate the Early Nurse Intervention Team program at a large community hospital in the southeastern United States. METHODS: A retrospective evaluation was performed of unplanned intensive care unit transfers, hospital length of stay, length of stay index, ventilator days, and mortality in 2 patient groups: those with and those without an Early Nurse Intervention Team nurse present. RESULTS: There was a marked decline in unplanned intensive care unit transfers as the Early Nurse Intervention Team nurse staffing increased. There were no significant interaction or main effects for length of stay, length of stay index, ventilator days, or mortality between the 2 groups. CONCLUSIONS: This study showed a positive impact of implementation of an Early Nurse Intervention Team program, with significant savings given the cost of unplanned intensive care unit transfers.

Safe Interorganizational Health Information Exchange During the COVID-19 Pandemic.

Accurate and timely transmission of medical records between skilled nursing facilities and acute care settings has been logistically problematic. Often people are sent to the hospital with a packet of paper records, which is easily misplaced. The COVID-19 pandemic has further magnified this problem by the possibility of viral transmission via fomites. To protect themselves, staff and providers were donning personal protective equipment to review paper records, which was time-consuming and wasteful. We describe an innovative process developed by a team of hospital leadership, members of a local collaborative of skilled nursing facilities, and leadership of this collaborative group, to address this problem. Many possible solutions were suggested and reviewed. We describe the reasons for selecting our final document transfer process and how it was implemented. The critical success factors are also delineated. Other health systems and collaborative groups of skilled nursing facilities may benefit from implementing similar processes.

Implementation and Continuous Monitoring of an Electronic Health Record Embedded Readmissions Clinical Decision Support Tool.

Unplanned hospital readmissions represent a significant health care value problem with high costs and poor quality of care. A significant percentage of readmissions could be prevented if clinical inpatient teams were better able to predict which patients were at higher risk for readmission. Many of the current clinical decision support models that predict readmissions are not configured to integrate closely with the electronic health record or alert providers in real-time prior to discharge about a patient's risk for readmission. We report on the implementation and monitoring of the Epic electronic health record-"Unplanned readmission model version 1"-over 2 years from 1/1/2018-12/31/2019. For patients discharged during this time, the predictive capability to discern high risk discharges was reflected in an AUC/C-statistic at our three hospitals of 0.716-0.760 for all patients and 0.676-0.695 for general medicine patients. The model had a positive predictive value ranging from 0.217-0.248 for all patients. We also present our methods in monitoring the model over time for trend changes, as well as common readmissions reduction strategies triggered by the score.