Determinants of performance failure in the nursing home industry

Abstract

This study investigates the determinants of performance failure in U.S. nursing homes. The sample consisted of 91,168 surveys from 10,901 facilities included in the Online Survey Certification and Reporting system from 1996 to 2005. Failed performance was defined as termination from the Medicare and Medicaid programs. Determinants of performance failure were identified as core structural change (ownership change), peripheral change (related diversification), prior financial and quality of care performance, size and environmental shock (Medicaid case mix reimbursement and prospective payment system introduction). Additional control variables that could contribute to the likelihood of performance failure were included in a cross-sectional time series generalized estimating equation logistic regression model. Our results support the contention, derived from structural inertia theory, that where in an organization’s structure change occurs determines whether it is adaptive or disruptive. In addition, while poor prior financial and quality performance and the introduction of case mix reimbursement increases the risk of failure, larger size is protective, decreasing the likelihood of performance failure.

Geographic Concentration and Correlates of Nursing Home Closures: 1999-2008

“…Perhaps this is a desired outcome, since closure is the ultimate indicator of performance failure. 4 However, the operation of regulatory efforts and market forces are not likely to result in random distribution of closures. Rather, some facility types will be affected more than others.…”

Hospital-skilled nursing facility referral linkage reduces readmission rates among Medicare patients receiving major surgery

“…SNF attributes from the OSCAR data included the full-time equivalents (FTEs) of different types of nursing staff [registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs)] 10-13 , the proportion of Medicaid paid residents 14-17 , the weighted deficiency score based on state’s inspection of the SNF 13,18,19 , occupancy rate, chain membership, corporate ownership (for profit or not), and the presence of any physician extenders (e.g. nurse practitioners, physician assistants, etc) 20 .…”

“…Given the large number of observations and the inclusion of a numerous covariates, we estimated a linear probability model even though the outcome was dichotomous. Based on prior research, age, gender, race, Elixhauser and Deyo-modified Charlson co-morbidity scores 2,3,5,6 , hospital length-of-stay and ICU use 3,6 , RN, LPN and CNA FTEs 10-13 , the proportion of Medicaid paid residents 14-17 , the weighted deficiency score based on state’s inspection of the SNF 13,18,19 , occupancy rate, chain membership, corporate ownership, and the presence of any physician extenders were included as co-variates in the multivariable regression model.…”

Medicaid Reimbursement and the Quality of Nursing Home Care: A Case Study of Medi-Cal Long-Term Care Reimbursement Act of 2004 in California

“…The level of resources available has substantial influence on quality of care. Studies have found that nursing homes with high concentrations of Medicaid patients were more like to have quality of care problems due to very limited resources compared to nursing homes with low concentrations of Medicaid patients [39,[188][189]. In addition, public reporting may increase the divide between providers that are more or less able to improve quality [190].…”