Patient Factors Linked with Return Acute Healthcare Use in Older Adults by Discharge Disposition.

Objectives: Compare patient characteristics by hospital discharge disposition (home without services, home with home healthcare (HHC) services, or post-acute care (PAC) facilities). Examine timing and rates of 30-day healthcare utilization (rehospitalization, emergency department (ED) visit, or observation (OBS) visit) and patient characteristics associated with rehospitalization by discharge location.

Design: Retrospective analysis of hospital administrative and clinical data.

Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.

Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity. We applied a random forest algorithm on readily available HHC data from the mandated Outcomes and Assessment Information Set (OASIS) with over 100 items from 59,006 HHC patients to identify factors that predict and quantify fall risks.

Meritorious Academic Partnership Designation: Recognizing Nursing Professional Development in Graduate Curricula.

Graduate nursing education programs' focus on preparation for academia results in many graduate nurses being unprepared to function as nursing professional development (NPD) practitioners in the practice environment. This article describes the development of an innovative collaborative partnership designation program and how a specialty organization, health system, and academia partnered to create an educational program to prepare NPD practitioners. The designation program provides a practical tool for use by NPD departments to advocate for the NPD specialty.

Comparison of algorithm advice for post-acute care referral to usual clinical decision-making: examination of 30-day acute healthcare utilization.

: Compare patient characteristics and acute healthcare utilization between patients identified as in need of post-acute care (PAC) by the clinical decision support (CDS) algorithm yet were discharged home without services, to those where the CDS and hospital clinicians agreed on no referral. : Retrospective analysis of hospital administrative and clinical data for 1,366 patients. : 30-day acute healthcare utilization rates are significantly higher for those patients flagged as in need of PAC referral.

Nurse Generated EHR Data Supports Post-Acute Care Referral Decision Making: Development and Validation of a Two-step Algorithm.

Build and validate a clinical decision support (CDS) algorithm for discharge decisions regarding referral for post-acute care (PAC) and to what site of care. Case studies derived from EHR data were judged by 171 interdisciplinary experts and prediction models were generated. A two-step algorithm emerged with area under the curve (AUC) in validation of 91.