Huiwen Xu1,2, John R Bowblis3,4, Thomas V Caprio2,5,6, Yue Li2, Orna Intrator2,6. 1. Departments of Surgery, Cancer Control. 2. Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY. 3. Department of Economics, Farmer School of Business. 4. Scripps Gerontology Center, Miami University, Oxford, OH. 5. Department of Medicine, Division of Geriatrics, University of Rochester School of Medicine and Dentistry, Rochester. 6. Geriatrics & Extended Care Data Analysis Center (GECDAC), Canandaigua VA Medical Center, Canandaigua, NY.
Abstract
BACKGROUND: Higher risk-adjusted rate of emergency department (ED) visits might reflect poor quality of nursing home (NH) care; however, existing evidence is limited regarding rural-urban differences in ED rates of NHs, especially for long-stay residents. OBJECTIVES: To determine and quantify sources of rural-urban differences in NH risk-adjusted rates of any ED visit, ED without hospitalization or observation stay (outpatient ED), and potentially avoidable ED visits (PAED) of long-stay residents. RESEARCH DESIGN: We calculated quarterly NH risk-adjusted rates using 2011-2013 national Medicare claims and Minimum Data Set 3.0, and then implemented Generalized Estimating Equation models to examine rural-urban differences in ED rates and Blinder-Oaxaca decomposition to quantify the contributions of NH and market factors. SUBJECTS: Privately owned, free-standing NHs in the United States (N=13,260). RESULTS: Over the study period, risk-adjusted rates averaged 9.8% for any ED, 3.3% for outpatient ED, and 3.2% for PAED. Compared with urban NHs, rural NHs were associated with significantly lower rates of any ED, outpatient ED, and PAED (β=-1.67%, -0.44%, and -0.28%; all P<0.01). Observable differences in market factors (nursing home bed concentration, hospital beds, and the existence of a critical access hospital) explained about half of the rural-urban differences in rates of any ED and PAED, but not outpatient ED. CONCLUSIONS: Decomposition analyses suggested that lower ED rates in rural NHs appear to be related to market availability of hospital resources. Policymakers may focus on not only reducing unnecessary ED visits but also ensuring equitable hospital access in rural areas.
BACKGROUND: Higher risk-adjusted rate of emergency department (ED) visits might reflect poor quality of nursing home (NH) care; however, existing evidence is limited regarding rural-urban differences in ED rates of NHs, especially for long-stay residents. OBJECTIVES: To determine and quantify sources of rural-urban differences in NH risk-adjusted rates of any ED visit, ED without hospitalization or observation stay (outpatient ED), and potentially avoidable ED visits (PAED) of long-stay residents. RESEARCH DESIGN: We calculated quarterly NH risk-adjusted rates using 2011-2013 national Medicare claims and Minimum Data Set 3.0, and then implemented Generalized Estimating Equation models to examine rural-urban differences in ED rates and Blinder-Oaxaca decomposition to quantify the contributions of NH and market factors. SUBJECTS: Privately owned, free-standing NHs in the United States (N=13,260). RESULTS: Over the study period, risk-adjusted rates averaged 9.8% for any ED, 3.3% for outpatient ED, and 3.2% for PAED. Compared with urban NHs, rural NHs were associated with significantly lower rates of any ED, outpatient ED, and PAED (β=-1.67%, -0.44%, and -0.28%; all P<0.01). Observable differences in market factors (nursing home bed concentration, hospital beds, and the existence of a critical access hospital) explained about half of the rural-urban differences in rates of any ED and PAED, but not outpatient ED. CONCLUSIONS: Decomposition analyses suggested that lower ED rates in rural NHs appear to be related to market availability of hospital resources. Policymakers may focus on not only reducing unnecessary ED visits but also ensuring equitable hospital access in rural areas.
Authors: Mingyang Li; Yibin Ao; Shulin Deng; Panyu Peng; Shuangzhou Chen; Tong Wang; Igor Martek; Homa Bahmani Journal: Int J Environ Res Public Health Date: 2022-08-19 Impact factor: 4.614