Postdischarge Environment Following Heart Failure Hospitalization: Expanding the View of Hospital Readmission

eadmission after hospitalization for heart failure (HF) has received increasing attention due to the significant burden it places on patients and payers. 1,2 Among Medicare beneficiaries, readmission within 30 days following heart failure hospitalization approaches 25%. 2 Even after adjusting for case mix, significant variation in hospital readmission rates exists. This hospital-level variation suggests that many of these readmissions may be preventable. 3 HF readmission rates adjusted for risk using a claims-based model are now publicly reported as a measure of institutional quality (www. HospitalCompare.hhs.gov). As of October 2012, the Patient Protection and Affordable Care Act's (PPACA) value-based purchasing policies began reducing Medicare payments to hospitals with "excess" HF readmissions and offered new funding opportunities for innovative approaches to reduce HF readmissions. espite the obvious value of reducing unnecessary readmissions, the way forward is not as clear as these policies might suggest. An increasing segment of the medical community is voicing concern with the extent to which public reporting and financial penalties positively influence institutional HF readmissionrates. Value-basedpurchasingmayunfairlypunishhospitals that provide care to socioeconomically disadvantaged patients and incentivize the avoidance of high-risk patients 6-9 due to perceivedinadequaciesofcurrentriskstandardizationmodels. ior efforts to identify risk factors for HF readmission have put an inordinate priority on the convenience of data collection. The vast majority of existing risk models employ administrative billing and inpatient clinical data from a single episode of care that are not designed to fully elucidate the breadth of potential causes of readmission. Notably missing are factors reflecting the patient's postdischarge environment. Recent literature suggests that "social instability"-a term which reflects a relative lack of social support, education, economic stability, access to care, and safety in the patient's environment-is an important mediator of readmission risk. ithin this context, we set out to ( Doing so has the potential to improve the predictive capacity of HF readmission risk models, thereby making quality measures fairer, and to guide us in improving transitions of care, and ultimately leading toward reductions in unnecessary readmissions.