BACKGROUND: Government regulation is intended to enhance quality, safety, fairness, or competition in the regulated industry. Such regulation entails both direct and indirect costs. OBJECTIVES: To estimate the costs associated with the regulation of quality of the nursing home industry. SAMPLE: This study includes 11,168 free-standing nursing homes nationally, between 2004 and 2006. RESEARCH DESIGN: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: Government regulation is intended to enhance quality, safety, fairness, or competition in the regulated industry. Such regulation entails both direct and indirect costs. OBJECTIVES: To estimate the costs associated with the regulation of quality of the nursing home industry. SAMPLE: This study includes 11,168 free-standing nursing homes nationally, between 2004 and 2006. RESEARCH DESIGN: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Dana B Mukamel; David L Weimer; Yue Li; Lauren Bailey; William D Spector; Charlene Harrington Journal: J Am Med Dir Assoc Date: 2012-03-07 Impact factor: 4.669
Authors: Dana B Mukamel; Yue Li; David L Weimer; William D Spector; Lauren Bailey; Charlene Harrington Journal: J Am Med Dir Assoc Date: 2012-11-07 Impact factor: 4.669
Authors: Dana B Mukamel; David L Weimer; Charlene Harrington; William D Spector; Heather Ladd; Yue Li Journal: Health Serv Res Date: 2012-09-04 Impact factor: 3.402
Authors: Sundar S Shrestha; Amanda A Honeycutt; Wenya Yang; Ping Zhang; Olga A Khavjou; Diana C Poehler; Simon J Neuwahl; Thomas J Hoerger Journal: Diabetes Care Date: 2018-10-10 Impact factor: 19.112