An AI-driven clinical care pathway to reduce 30-day readmission for chronic obstructive pulmonary disease (COPD) patients.

Healthcare regulatory agencies have mandated a reduction in 30-day hospital readmission rates and have targeted COPD as a major contributor to 30-day readmissions. We aimed to develop and validate a simple tool deploying an artificial neural network (ANN) for early identification of COPD patients with high readmission risk. Using COPD patient data from eight hospitals within a large urban hospital system, four variables were identified, weighted and validated.

A multifaceted study of hospital variables and interventions to improve inpatient satisfaction in a multi-hospital system.

Knowing the areas of service, actions, and parameters that can influence patient perception about a service provided can help hospital executives and healthcare workers to devise improvement plans, leading to higher patient satisfaction. To identify inpatient satisfaction determinants, assess their relationships with hospital variables, and improve patient satisfaction through interventions. We studied the inpatient population of an eight-hospital tertiary medical center in 2015.