Impact of electronic medical records (EMRs) on hospital productivity in Japan

INTRODUCTION Consistent with the global trend, Japanese hospitals have increasingly adopted electronic medical record (EMR) systems in the last 20 years. Although improved productivity is emphasized as one of the benefits of information technology (IT), there is a paucity of data regarding how the use of EMR systems influences the productivity of Japanese hospitals. METHODS This retrospective study focused on 658 municipal hospitals. The study period was from 2006 to 2015. We analyzed the labor productivity and multi-factor productivity (MFP) of the hospitals and their average rate of change during the study period. Logistic regression models were used to assess how EMR implementation influenced labor productivity and MFP growth. We considered the duration of EMR operation, and hospitals using EMRs were divided into three groups based on tertiles of time elapsed since the implementation of the EMR system: "early adopters", "followers", and "late adopters". RESULTS We found that the implementation of an EMR system had a significantly negative impact on MFP growth for the 'late adopters' (OR 0.51; 95%CI 0.31-0.82; p = 0.006). No significant association was found between EMR implementation and labor productivity growth. CONCLUSION EMR implementation has an adverse effect on the productivity of municipal hospitals in Japan. This finding should be considered when developing future healthcare policies promoting the implementation of IT.

[1]  Nirup M. Menon,et al.  The Effect of Information Technology Investments in Healthcare: A Longitudinal Study of its Lag, Duration, and Economic Value , 2011, IEEE Transactions on Engineering Management.

[2]  John Doucette,et al.  Adopting electronic medical records in primary care: Lessons learned from health information systems implementation experience in seven countries , 2009, Int. J. Medical Informatics.

[3]  N. Menachemi,et al.  Does electronic health record use improve hospital financial performance? Evidence from panel data. , 2016, Health care management review.

[4]  J. Cromwell,et al.  Trends in hospital labor and total factor productivity, 1981-86 , 1989, Health care financing review.

[5]  Kurt M. Bretthauer,et al.  Effect of armed conflicts on humanitarian operations: Total factor productivity and efficiency of rural hospitals , 2016 .

[6]  N. Sood,et al.  US hospitals experienced substantial productivity growth during 2002-11. , 2015, Health affairs.

[7]  Liette Lapointe,et al.  The IT productivity paradox in health: A stakeholder's perspective , 2011, Int. J. Medical Informatics.

[8]  O. Ben-Assuli,et al.  Electronic health records, adoption, quality of care, legal and privacy issues and their implementation in emergency departments. , 2015, Health policy.

[9]  Spencer S Jones,et al.  Unraveling the IT productivity paradox--lessons for health care. , 2012, The New England journal of medicine.

[10]  Francis Y. Lau,et al.  Measuring value for money: a scoping review on economic evaluation of health information systems , 2013, J. Am. Medical Informatics Assoc..

[11]  Michel Rousseau,et al.  Electronic health record acceptance by physicians: Testing an integrated theoretical model , 2014, J. Biomed. Informatics.

[12]  Julia Adler-Milstein,et al.  Electronic Health Record Adoption In US Hospitals: Progress Continues, But Challenges Persist. , 2015, Health affairs.

[13]  Sarah Read-Brown,et al.  Impact of an electronic health record operating room management system in ophthalmology on documentation time, surgical volume, and staffing. , 2014, JAMA ophthalmology.

[14]  Brian W. Pickering,et al.  Impact of the Electronic Medical Record on Mortality, Length of Stay, and Cost in the Hospital and ICU: A Systematic Review and Metaanalysis* , 2015, Critical care medicine.

[15]  Dimitrios Niakas,et al.  A 12-year Analysis of Malmquist Total Factor Productivity in Dialysis Facilities , 2006, Journal of Medical Systems.

[16]  Jinhyung Lee,et al.  The Impact of Health Information Technology on Hospital Productivity , 2012 .

[17]  Yuichi Yoshida,et al.  The trends in EMR and CPOE adoption in Japan under the national strategy , 2013, Int. J. Medical Informatics.

[18]  C. Mclaughlin,et al.  Physician EHR Adoption and Potentially Preventable Hospital Admissions among Medicare Beneficiaries: Panel Data Evidence, 2010-2013. , 2016, Health services research.

[19]  Patrice Degoulet,et al.  Impact of Health Care Information Technology on Hospital Productivity Growth: a Survey in 17 Acute University Hospitals , 2007, MedInfo.

[20]  E. Brynjolfsson,et al.  Computing Productivity: Firm-Level Evidence , 2003 .

[21]  Morgane Plantier,et al.  Does adoption of electronic health records improve the quality of care management in France? Results from the French e-SI (PREPS-SIPS) study , 2017, Int. J. Medical Informatics.

[22]  LeMai Nguyen,et al.  Electronic health records implementation: An evaluation of information system impact and contingency factors , 2014, Int. J. Medical Informatics.

[23]  Eitaro Nishihara,et al.  Transforming healthcare with information technology in Japan: A review of policy, people, and progress , 2011, Int. J. Medical Informatics.

[24]  Eric W. Ford,et al.  Electronic health record implementation and hospitals' total factor productivity , 2013, Decis. Support Syst..

[25]  Hideo Yasunaga,et al.  Computerizing medical records in Japan , 2008, Int. J. Medical Informatics.

[26]  Hajime Sato,et al.  Motivations and barriers to implementing electronic health records and ED information systems in Japan. , 2014, The American journal of emergency medicine.

[27]  Luis Villa,et al.  A literature review for large-scale health information system project planning, implementation and evaluation , 2017, Int. J. Medical Informatics.

[28]  Robert L. Wears,et al.  Health information technology: fallacies and sober realities , 2010, J. Am. Medical Informatics Assoc..

[29]  Soung Hie Kim,et al.  A Lag Effect of IT Investment on Firm Performance , 2006, Inf. Resour. Manag. J..

[30]  J. Goodwin,et al.  The effect of electronic medical record adoption on outcomes in US hospitals , 2013, BMC Health Services Research.

[31]  Kazuhiko Ohe,et al.  Regional differences in electronic medical record adoption in Japan: A nationwide longitudinal ecological study , 2018, Int. J. Medical Informatics.

[32]  Tiankai Wang,et al.  Do health information technology investments impact hospital financial performance and productivity? , 2018, Int. J. Account. Inf. Syst..

[33]  Sowmya R. Rao,et al.  Use of electronic health records in U.S. hospitals. , 2009, The New England journal of medicine.

[34]  Nirup M. Menon,et al.  Productivity of Information Systems in the Healthcare Industry , 2000, Inf. Syst. Res..

[35]  Peter Hoonakker,et al.  Impact of electronic health record technology on the work and workflow of physicians in the intensive care unit , 2015, Int. J. Medical Informatics.

[36]  J. Cylus,et al.  Hospital Multifactor Productivity: A Presentation and Analysis of Two Methodologies , 2007, Health care financing review.

[37]  Helana Scheepers,et al.  Health information systems evaluation frameworks: A systematic review , 2017, Int. J. Medical Informatics.

[38]  Robin C. Meili,et al.  Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. , 2005, Health affairs.

[39]  David W. Bates,et al.  The use of health information technology in seven nations , 2008, Int. J. Medical Informatics.