Does State Regulation of Quality Impose Costs on Nursing Homes?

Department of Medicine, University of California, Irvine, Health Policy Research Institute, Irvine, CA 92697-5800, USA.
Medical care (Impact Factor: 3.23). 06/2011; 49(6):529-34. DOI: 10.1097/MLR.0b013e318207ef9e
Source: PubMed


Government regulation is intended to enhance quality, safety, fairness, or competition in the regulated industry. Such regulation entails both direct and indirect costs.
To estimate the costs associated with the regulation of quality of the nursing home industry.
This study includes 11,168 free-standing nursing homes nationally, between 2004 and 2006.
Data included information from the Medicare cost reports, Minimum Data Set, Medicare Denominator file, OSCAR, and a survey of States' Certification and Licensing Offices conducted by the authors. These data were used to create variables measuring nursing homes costs, outputs, wages, competition, adjusted deficiency citations, ownership, state-fixed effects, and an index of each state's regulatory stringency. We estimated hybrid cost functions which included the regulatory stringency index.
The estimated cost functions demonstrated the typical behavior expected of nursing home cost functions. The stringency index was positively and significantly associated with costs, indicating that nursing homes located in states with more stringent regulatory requirements face higher costs, ceteris paribus. The average incremental costs of a 1 standard deviation increase in the stringency index resulted in a 1.1% increase in costs.
This study for the first time places a price tag on the regulation of quality in nursing homes. It offers an order of magnitude on the costs to the industry of complying with the current set of standards and given the current level of enforcement. Complementary studies of the benefits that these regulations entail are needed to gain a comprehensive assessment of the effect of the regulation.

13 Reads
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper examines the impact of an endogenous cost function variable on the inefficiency estimates generated by stochastic frontier analysis (SFA). The specific variable of interest in this application is endogenous quality in nursing homes. We simulate a dataset based on the characteristics of for-profit nursing homes in California, which we use to assess the impact on SFA-generated inefficiency estimates of an endogenous regressor under a variety of scenarios, including variations in the strength and direction of the endogeneity and whether the correlation is with the random noise or the inefficiency residual component of the error term. We compare each of these cases when quality is included and excluded from the cost equation. We provide evidence of the impact of endogeneity on inefficiency estimates yielded by SFA under these various scenarios and when the endogenous regressor is included and excluded from the model.
    Journal of Productivity Analysis 04/2012; 39(2). DOI:10.1007/s11123-012-0277-z · 0.87 Impact Factor
  • Medical care 06/2011; 49(6):535-7. DOI:10.1097/MLR.0b013e31821f7f56 · 3.23 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Nursing homes that are not meeting quality standards are cited for deficiencies. Before 1995, the only recourse for a nursing home was a formal appeal process, which is lengthy and costly. In 1995, the Centers for Medicare & Medicaid Services instituted the Informal Dispute Resolution (IDR) process. This study presents for the first time national statistics about the IDR process and an analysis of the factors that influence nursing homes' decisions to request an IDR. Retrospective study including descriptive statistics and multivariate logistic hierarchical models. US nursing homes from 2005 to 2008. Participants were 15,916 Medicaid- and Medicare-certified nursing homes nationally, with 94,188 surveys and 9388 IDRs. The unit of observation was an annual survey or a complaint survey that generated at least one deficiency. The dependent variable was dichotomous and indicated whether the annual or a complaint survey triggered an IDR request. Independent variables included characteristics of the nursing home, the deficiency, the market, and the state regulatory environment. Ten percent of all annual surveys and complaint surveys resulted in IDRs. There was substantial variation across states, which persisted over time. Multivariate results suggest that nursing homes' decisions to request an IDR depend on their assessment of the probability of success and assessment of the benefits of the submission. Nursing homes avail themselves of the IDR process. Their propensity to do so depends on a number of factors, including the state regulatory system and the market environment in which they operate.
    Journal of the American Medical Directors Association 03/2012; 13(6):512-6. DOI:10.1016/j.jamda.2012.01.005 · 4.94 Impact Factor
Show more