Impact of Behavioral Health Screening on Proactive Identification of Patients at Risk for Hospital Readmission.

Improving the ability to predict which patients are at increased risk for readmission can lead to more effective interventions and greater compliance with CMS Hospital Readmissions Reduction Program (HRRP) requirements. This study evaluated the performance of a risk model that used data from a health system's electronic medical record (EMR) to predict all-cause readmission among adult inpatients with acute medical conditions, with a specific focus on the impact of including behavioral health screening data. The study included 39,155 unique adult patients admitted during 2015 to 4 acute care inpatient facilities within a nonprofit community-based health care system. The risk model integrated a comprehensive set of data elements including demographics, psychosocial characteristics, medical history, assessment results, and clinical events. Predictive models were constructed using a multivariable logistic regression with a stepwise selection approach. Among study participants, the mean age was 62.9 years, 48.0% were male, 31.2% had comorbid psychiatric conditions, and 6986 had medical conditions/procedures subject to HRRP penalties. Results from exploratory predictive analyses demonstrated that any patients with a Serious Mental Illness (SMI) diagnosis were 28% more likely to be readmitted within 30 days, and the likelihood of readmission associated with SMI increased to 56% for patients with medical conditions subject to HRRP penalties. As health care systems face increasing pressures to reduce readmissions and avoid CMS HRRP financial penalties, study results indicate the importance of including behavioral health data from EMRs and screening assessments for all inpatients to improve discharge planning and patient outcomes.

Feasibility and Acute Care Utilization Outcomes of a Post-Acute Transitional Telemonitoring Program for Underserved Chronic Disease Patients.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) are chronic diseases that impart significant health and care costs to the patient and health system. Limited access to health services affects disease severity and functional status. Telemonitoring has shown promise in reducing acute care utilization for chronic disease patients, but the benefit for the underserved has not been determined. We evaluated acute care utilization outcomes following an acute event of a 90-day transitional care program integrating telemonitoring technology and home visits for underserved COPD and HF patients. MATERIALS AND METHODS: Patients were enrolled into the program between October 2010 and August 2012. Primary outcomes included rates of emergency department (ED) visits and all-cause re-admission at 30, 90, and 180 days postdischarge. Program and functional status at enrollment and discharge and satisfaction with telemonitoring at discharge were measured. Telemonitoring included daily symptomatology recording and was removed at 90 days. A control cohort was identified through electronic health records and propensity-matched via 15 variables to achieve a sample size with balanced baseline characteristics. RESULTS: Program patients showed 50% reduction in 30-day re-admission and 13-19% reduction in 180-day re-admission compared with control patients. There was no significant difference in ED utilization. Patients were satisfied with telemonitoring services, and functional status improved by program end. CONCLUSIONS: This feasibility study suggests telemonitoring in the context of a transitional care model following an acute event may reduce all-cause 30-day re-admissions by up to 50% and has the potential to reduce long-term acute care utilization and thus care costs. More rigorous and long-term investigation is warranted.