Helena Temkin-Greener1, Yunjiao Mao2, Susan Ladwig3, Xueya Cai4, Sheryl Zimmerman5, Yue Li2. 1. Department of Public Health Sciences, University of Rochester School of Medicine & Dentistry, Rochester, NY, USA. Electronic address: Helena_Temkin-Greener@urmc.rochester.edu. 2. Department of Public Health Sciences, University of Rochester School of Medicine & Dentistry, Rochester, NY, USA. 3. Department of Medicine, University of Rochester School of Medicine & Dentistry, Rochester, NY, USA. 4. Department of Biostatistics and Computational Biology, University of Rochester School of Medicine & Dentistry, Rochester, NY, USA. 5. School of Social Work, University of North Carolina, Chapel Hill, NC, USA.
Abstract
OBJECTIVES: We examined state variations in assisted living (AL) regulatory policies for admission/retention, staffing/training, medication management, and dementia care. Factors associated with domain-specific and overall regulatory stringency were identified. DESIGN: This observational study used the following data sources: 2019 review of state AL regulations; 2019 national inventory of AL communities; 2014 Government Accountability Office survey of Medicaid agencies; 2016 Genworth Cost of Care Survey; and the 2018 Nursing Home Compare. SETTING AND PARTICIPANTS: Final analyses included 46 states (excluding Alaska, Kentucky, Louisiana, and West Virginia) and the District of Columbia. METHODS: For each regulatory domain of interest (dependent variables), we generated policy scores by conducting content analysis of state regulatory databases. States were assigned points for presence of each policy (eg, staff training). The number of points assigned to each policy was divided by the total possible number of policy-related points, producing state stringency scores (between 0% and 100%) for each policy domain. Independent variables included market-level characteristics (eg, AL monthly cost), state generosity (eg, proportion of Medicaid aged using AL services), quality of care (eg, percent of nursing homes with few deficiencies), and others. Descriptive analyses and multivariable logistic regression models with stepwise selection were used. RESULTS: We found significant variations in all policy domains across states. No single policy appeared to clearly dominate a state's rank. AL bed supply, monthly AL cost, proportion of Medicaid beneficiaries receiving AL services, and other variables were significantly associated with regulatory stringency of the domains examined. CONCLUSIONS AND IMPLICATIONS: There were substantial variations in regulatory stringency across states. Several market and state generosity measures were identified as potential determinants of stringency, but the direction of these associations appeared to depend on what was being regulated. Future studies should examine how regulatory stringency affects access to and care quality in ALs.
OBJECTIVES: We examined state variations in assisted living (AL) regulatory policies for admission/retention, staffing/training, medication management, and dementia care. Factors associated with domain-specific and overall regulatory stringency were identified. DESIGN: This observational study used the following data sources: 2019 review of state AL regulations; 2019 national inventory of AL communities; 2014 Government Accountability Office survey of Medicaid agencies; 2016 Genworth Cost of Care Survey; and the 2018 Nursing Home Compare. SETTING AND PARTICIPANTS: Final analyses included 46 states (excluding Alaska, Kentucky, Louisiana, and West Virginia) and the District of Columbia. METHODS: For each regulatory domain of interest (dependent variables), we generated policy scores by conducting content analysis of state regulatory databases. States were assigned points for presence of each policy (eg, staff training). The number of points assigned to each policy was divided by the total possible number of policy-related points, producing state stringency scores (between 0% and 100%) for each policy domain. Independent variables included market-level characteristics (eg, AL monthly cost), state generosity (eg, proportion of Medicaid aged using AL services), quality of care (eg, percent of nursing homes with few deficiencies), and others. Descriptive analyses and multivariable logistic regression models with stepwise selection were used. RESULTS: We found significant variations in all policy domains across states. No single policy appeared to clearly dominate a state's rank. AL bed supply, monthly AL cost, proportion of Medicaid beneficiaries receiving AL services, and other variables were significantly associated with regulatory stringency of the domains examined. CONCLUSIONS AND IMPLICATIONS: There were substantial variations in regulatory stringency across states. Several market and state generosity measures were identified as potential determinants of stringency, but the direction of these associations appeared to depend on what was being regulated. Future studies should examine how regulatory stringency affects access to and care quality in ALs.
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