Jay J Shen1, Gregory O Ginn. 1. Department of Health Care Administration and Policy, School of Community Health Sciences, University of Nevada-Las Vegas, USA. jay.shen@unlv.edu
Abstract
AIM: Financial barriers are a major factor of slow electronic health record (EHR) adoption among US hospitals. All existing literature focuses on relationships between current or short-term financial position and EHR adoption. This study examines relationship between financial position in previous years and the current level of EHR adoption. METHODS: Retrospective longitudinal data were extracted from (1) the 2009 American Hospital Association (AHA) EHR implementation survey; (2) the 2002 and 2006 Centers for Medicare & Medicaid Cost Reports; and (3) the 2002 and 2006 AHA Annual Survey containing organizational and operational data. The final sample was 2,701 acute care hospitals in the United States. General ordinal logistic regression was used for data analysis with a three-level dependent variable to measure adoption, five independent variables to measure financial position, and 11 control variables to measure structure and environment. RESULTS: For 2006, higher total margin was significantly and positively associated with EHR adoption, but higher asset turnover was significantly and negatively associated with EHR adoption. For 2002, higher total margin was significantly and positively associated with EHR adoption, but higher asset turnover and higher equity multiplier were both significantly and negatively associated with EHR adoption. In addition, lower net days revenue in accounts receivable was significantly and positively associated with EHR adoption. For both the 2002 and 2006 control variables, human resource intensity and bed size were significant and positively related to adoption, and percentage Medicare patients and investor ownership were significant and negatively related to adoption. CONCLUSIONS: Financial position does relate to EHR adoption in mid-term and long-term planning.
AIM: Financial barriers are a major factor of slow electronic health record (EHR) adoption among US hospitals. All existing literature focuses on relationships between current or short-term financial position and EHR adoption. This study examines relationship between financial position in previous years and the current level of EHR adoption. METHODS: Retrospective longitudinal data were extracted from (1) the 2009 American Hospital Association (AHA) EHR implementation survey; (2) the 2002 and 2006 Centers for Medicare & Medicaid Cost Reports; and (3) the 2002 and 2006 AHA Annual Survey containing organizational and operational data. The final sample was 2,701 acute care hospitals in the United States. General ordinal logistic regression was used for data analysis with a three-level dependent variable to measure adoption, five independent variables to measure financial position, and 11 control variables to measure structure and environment. RESULTS: For 2006, higher total margin was significantly and positively associated with EHR adoption, but higher asset turnover was significantly and negatively associated with EHR adoption. For 2002, higher total margin was significantly and positively associated with EHR adoption, but higher asset turnover and higher equity multiplier were both significantly and negatively associated with EHR adoption. In addition, lower net days revenue in accounts receivable was significantly and positively associated with EHR adoption. For both the 2002 and 2006 control variables, human resource intensity and bed size were significant and positively related to adoption, and percentage Medicare patients and investor ownership were significant and negatively related to adoption. CONCLUSIONS: Financial position does relate to EHR adoption in mid-term and long-term planning.
Authors: Jay J Shen; Christopher R Cochran; Olena Mazurenko; Charles B Moseley; Guogen Shan; Robin Mukalian; Scott Neishi Journal: Ethn Dis Date: 2016-07-21 Impact factor: 1.847
Authors: Cheng-Hsun Ho; Hsyien-Chia Wene; Chi-Ming Chu; Yi-Syuan Wu; Jen-Leng Wang Journal: Int J Environ Res Public Health Date: 2014-06-06 Impact factor: 3.390
Authors: Bisundev Mahato; Tiffany M N Otero; Carrie A Holland; Patrick T Giguere; Ednan K Bajwa; Carlos A Camargo; Sadeq A Quraishi Journal: J Intensive Care Date: 2016-06-17