Comparing the Trends of Electronic Health Record Adoption Among Hospitals of the United States and Japan

  • Takako Kanakubo
  • Hadi KharraziEmail author
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement


The goal of this study is to examine the trends of Electronic Health Record (EHR) adoption among hospitals in Japan compared to those in the United States. Japan’s nationwide survey of hospitals was utilized to extract the EHR adoption rates among Japanese hospitals. Comparable datasets from the Healthcare Information and Management System Society (HIMSS) and the American Hospital Association (AHA) were utilized to extract EHR adoption rates among U.S. hospitals. The trends of EHR adoption were stratified and analyzed by hospital size and hospital ownership status. As of 2014, the U.S. hospitals had a wider adoption of ‘basic with clinical notes’ EHRs compared to Japan (45.6% vs. 27.3%), but large hospitals (400+ beds) in Japan have shown a similar adoption rate of EHR systems than those of U.S. (65.6% vs. 68.5%). Governmental hospitals tend to be more advanced in EHR adoption than non-profit hospitals in Japan (53.0% vs. 21.5%). Non-profit hospitals show the highest adoption rate of ‘basic’ EHR systems in the U.S. as of 2014 (63.3%). Using the ‘certified’ definition of EHRs, the EHR adoption rate was close to 96% among U.S. hospitals as of 2016; however, updated EHR adoption data from Japanese hospitals has yet to be collected and published. U.S. and Japan have considerably increased EHR adoption among hospitals; however, this analysis indicates different trends of EHR adoption among hospitals by size and ownership status in both countries. Learnings from government programs supporting EHR adoption in the U.S. and Japan can be helpful in planning useful strategies for future hospital-oriented health IT policies in other developed nations.


Electronic health records (EHR) EHR adoption rate Hospitals Japan United States 



We thank Dr. Okada Chiharu, MD PhD, from the National Hospital Organization (Tokyo, Japan), for his support and feedback about the MHLW data as well as the overall interpretation of our results within the Japanese healthcare context. We also acknowledge Dr. Eric Ford at the Johns Hopkins School of Public Health (Baltimore, U.S.) for his insightful input and HIMSS (Chicago, U.S.) for providing us with the EMRAM datasets.

Availability of Data

MHLW data are publicly available [13, 14]. EMRAM data are proprietary and can be acquired for a fee from HIMSS [35].

Authors’ Contributions

All authors were actively involved in the development of the study’s aim. All authors reviewed, commented, and revised the manuscript as needed. HK and TK led the study. HK and TK co-led the analysis and interpretation of the results, as well as drafting the manuscript. HK prepared the manuscript for submission.



Compliance with Ethical Standards

Conflict of Interest

Authors do not have any conflict of interest to report.

Ethics Approval


Consent for Publication



  1. 1.
    The Commonwealth Fund. What is the status of electronic health records?. [Internet]. 2016 [cited 2017 Aug 10]. Available from:
  2. 2.
    Healthcare Information and Management Systems Society (HIMSS). Electronic health records: A global perspective. [internet]. 2010 [cited 2017 Jul 9]. Available from:
  3. 3.
    Stone, C.P., A glimpse at EHR implementation around the world: The lessons the US can learn. [Internet]. 2014 [cited 2017 Jul 8]. Available from:
  4. 4.
    The Office of the National Coordinator for Health Information Technology. Non-federal acute care hospital health IT adoption. [internet]. 2016 [cited 2017 Jun 2]. Available from:
  5. 5.
    The Office of the National Coordinator for Health Information Technology. Adoption of electronic health record systems among U.S. non-Federal Acute Care Hospitals: 2008-2015. [Internet]. 2016 [cited 2017 Jun 2]. Available from:
  6. 6.
    Japan Ministry of Health, Labour and Welfare. Facilitation in informatization in healthcare field. [internet]. [cited 2016 Dec 10]. Available from:
  7. 7.
    Kim, Y. G., Jung, K., Park, Y. T., Shin, D., Cho, S. Y., Yoon, D., and Park, R. W., Rate of electronic health record adoption in South Korea: A nation-wide survey. Int. J. Med. Inform. 101:100–107, 2017.CrossRefGoogle Scholar
  8. 8.
    The Commonwealth Fund. A survey of primary care doctors in ten countries shows progress in use of health information technology, less in other areas. [internet]. 2012 [cited 2017 Jun 8]. Available from:
  9. 9.
    The Commonwealth Fund. 2015 Commonwealth Fund international survey of primary care physicians in 10 nations. [Internet]. 2015 [cited 2017 Jun 18]. Available from:
  10. 10.
    The Commonwealth Fund. 2015 International Survey of Physicians. [Internet]. 2015 [cited 2017 Jun 19]. Available from:
  11. 11.
    Jha, A., Burke, M., DesRoches, C., Joshi, M., Kralovec, B., Campbell, E., and Buntin, M., Progress toward meaningful use: Hospitals’ adoption of electronic health records. The American Journal of Managed Care., 17(Special Issue), 2011.Google Scholar
  12. 12.
    Adler-Milstein, J., DesRoches, C.M., Kralovec, P., Foster, G., Worzala, C., Charles, D., Searcy, T., and Jha, A.K. Electronic health record adoption in US hospitals: Progress continues, but challenges persist. Health Affairs. ;34(12), 2015.CrossRefGoogle Scholar
  13. 13.
    Japan Ministry of Health, Labour and Welfare. Survey of medical institutions: Feb 2017 report. [internet]. [cited 2017 Feb 27]. Available from:
  14. 14.
    Japan Ministry of Health, Labour and Welfare. Survey of medical institutions: Oct 2017 report. [internet]. [cited 2018 Feb 3]. Available from:
  15. 15.
    Tanaka, H., Current status of electronic health record dissemination in Japan. Jap. Med. Assoc. J. 50(5):399–404, 2007.Google Scholar
  16. 16.
    Yoshida, Y., Imai, T., and Ohe, K., The trends in EMR and CPOE adoption in Japan under the national strategy. Int. J. Med. Inform. 82(10):1004–1011, 2013.CrossRefGoogle Scholar
  17. 17.
    Japan Ministry of Health, Labour and welfare. Grand design for development of information systems in the healthcare and medical fields. [internet]. 2001 [cited 2017 May 30]. Available from:
  18. 18.
    Health Information Technology for Economic and Clinical Health (HITECH) act, title XIII of division a and title IV of division B of the American recovery and reinvestment act of 2009 (ARRA). Feb 17 2009. Available from:
  19. 19.
    Blumenthal, D., and Tavenner, M., The meaningful use regulation for electronic health records. New England Journal of Medicine. 363(6):501–504, 2010.CrossRefGoogle Scholar
  20. 20.
    The Office of the National Coordinator for Health Information Technology. Health IT strategic planning. [internet]. [cited 2017 Aug 8]. Available from:
  21. 21.
    The Office of the National Coordinator for Health Information Technology. 2016 Report to congress on health IT Progress: Examining the HITECH era and the future of health IT. [internet]. 2016 [cited 2016 Nov 2]. Available from:
  22. 22.
    The Office of the National Coordinator for Health Information Technology. Meaningful use definition & objectives. [internet]. [cited 2017 Apr 3]. Available from:
  23. 23.
    Jamoom, E. W., Patel, V., Furukawa, M. F., and King, J., EHR adopters vs. non-adopters: Impacts of, barriers to, and federal initiatives for EHR adoption. Healthcare (Amst). 2(1):33–39, 2014.CrossRefGoogle Scholar
  24. 24.
    Centers for Medicare & Medicaid Services. Electronic health records (EHR) incentive programs. [internet]. [cited 2017 Apr 14]. Available from:
  25. 25.
    Centers for Medicare & Medicaid Services. Stage 3 program requirements for providers attesting to their state’s Medicaid EHR incentive program. [internet]. [cited 2017 Apr 12]. Available from:
  26. 26.
    International Labor Organization. Medical Care Act [Japan]. [Internet]. 2014 [cited 2017 Sep 10]. Available from:
  27. 27.
    Japan Ministry of Health, Labour and Welfare. Overview of residency program. [internet]. [cited 2017 Apr 14]. Available from:
  28. 28.
    Japan Ministry of Health, Labour and Welfare. Residency program. [Internet]. [cited 2017 Apr 10]. Available from:
  29. 29.
    Japan Ministry of Internal Affairs and Communications. Category of local government. [Internet]. [cited 2017 Apr 10]. Available from:
  30. 30.
    United States Census Bureau. Metropolitan and Micropolitan glossary. [internet]. [cited 2017 Apr 10]. Available from:
  31. 31.
    American Hospital Association. AHA Data and Directories. [Internet]. [cited 2017 Sep 2]. Available from:
  32. 32.
    Jha, A. K., DesRoches, M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris, T. G., Shields, A., Rosenbaum, S., and Blumenthal, D., Use of electronic health records in U.S. hospitals. New England J. Med. 360(16):1628–1638, 2009.CrossRefGoogle Scholar
  33. 33.
    Blumenthal, D., DesRoches, C., Donelan, K., Ferris, T., Jha, A., Kaushal, R., Rao, S., and Rosenbaum, S., Health information Technology in the United States: The Information Base for Progress. Princeton, NJ: Robert Wood Johnson Foundation, 2006.Google Scholar
  34. 34.
    Inokuchi, R., Sato, H., Nakamura, K., Aoki, Y., Shinohara, K., Gunshin, M., Matsubara, T., Kitsuta, Y., Yahagi, N., and Nakajima, S., Motivations and barriers to implementing electronic health records and ED information systems in Japan. Am. J. Emerg. Med. 32:725–730, 2014.CrossRefGoogle Scholar
  35. 35.
    Healthcare Information and Management Systems Society (HIMSS). Electronic medical record adoption model (EMRAM). [internet]. [cited 2017 Feb]. Available from:
  36. 36.
    American Hospital Association. Fast Facts on U.S. Hospitals 2017. [Internet]. 2017 [cited 2017 Dec 20]. Available from:
  37. 37.
    National Hospital Organization [Japan]. Project to establish IT infrastructure for standardizing EHR. [internet]. [cited 2017 Apr 14]. Available from:
  38. 38.
    Japan Hospital Association. List of membership. [internet]. [cited 2017 Apr 15]. Available from:
  39. 39.
    Hatef, E., Lasser, E. C., Kharrazi, H. H., Perman, C., Montgomery, R., and Weiner, J. P., A population health measurement framework: Evidence-based metrics for assessing community-level population health in the global budget context. Popul. Health Manag. 21(4):261–270, 2018.CrossRefGoogle Scholar
  40. 40.
    Hatef, E., Kharrazi, H., VanBaak, E., Falcone, M., Ferris, L., Mertz, K., Perman, C., Bauman, A., Lasser, E. C., and Weiner, J. P., A state-wide health IT infrastructure for population health: Building a community-wide electronic platform for Maryland's all-payer global budget. Online J. Publ. Health Inform. 9(3):e195, 2017.CrossRefGoogle Scholar
  41. 41.
    Dixon, B. E., Kharrazi, H., and Lehmann, H. P., Public health and epidemiology informatics: Recent research and trends in the United States. Yearb Med. Inform. 10(1):199–206, 2015.CrossRefGoogle Scholar
  42. 42.
    Dixon, B. E., Pina, J., Kharrazi, H., Gharghabi, F., and Richards, J., What's past is prologue: A scoping review of recent public health and Global Health informatics literature. Online J. Publ. Health Inform. 7(2):e216, 2015.Google Scholar
  43. 43.
    Gamache, R., Kharrazi, H., and Weiner, J. P., Public and population health informatics: The bridging of big data to benefit communities. Yearb Med. Inform. 27(1):199–206, 2018.CrossRefGoogle Scholar
  44. 44.
    Kharrazi, H., Chi, W., Chang, H. Y., Richards, T. M., Gallagher, J. M., Knudson, S. M., and Weiner, J. P., Comparing population-based risk-stratification model performance using demographic, diagnosis and medication data extracted from outpatient electronic. Med. Care. 55(8):789–796, 2017.CrossRefGoogle Scholar
  45. 45.
    Chang, H. Y., Richards, T. M., Shermock, K. M., Elder Dalpoas, D. S., J Kan, K. H., Alexander, G. C., Weiner, J. P., and Kharrazi, H., Evaluating the impact of prescription fill rates on risk stratification model performance. Med. Care. 55(12):1052–1060, 2017.CrossRefGoogle Scholar
  46. 46.
    Lemke, K. W., Gudzune, K. A., Kharrazi, H., and Weiner, J. P., Assessing markers from ambulatory laboratory tests for predicting high-risk patients. Am. J. Manag. Care. 24(6):e190–e195, 2018.PubMedGoogle Scholar
  47. 47.
    Kharrazi, H., Chang, H. Y., Heins, S. E., Weiner, J. P., and Gudzune, K. A., Assessing the impact of body mass index information on the performance of risk adjustment models in predicting health care costs and utilization. Med. Care. 56(12):1042–1050, 2018.CrossRefGoogle Scholar
  48. 48.
    Kharrazi, H., and Weiner, J. P., A practical comparison between the predictive power of population-based risk stratification models using data from electronic health records versus. Med. Care. 56(2):202–203, 2018.CrossRefGoogle Scholar
  49. 49.
    Hatef, E., Weiner, J. P., and Kharrazi, H., A public health perspective on using electronic health records to address social determinants of health: The potential for a national system of local community. Int. J. Med. Inform. 124:86–89, 2019.CrossRefGoogle Scholar
  50. 50.
    Kimura, M., Nakayasu, K., Ohshima, Y., Fujita, N., Nakashima, N., Jozaki, H., Numano, T., Shimizu, T., Shimomura, M., Sasaki, F. et al., SS-MIX: A ministry project to promote standardized healthcare information exchange. Methods Inform. Med. 50(2):131–139, 2011.CrossRefGoogle Scholar
  51. 51.
    The Consortium for SS-MIX Dissemination and Promotion. SS-MIX2. [Internet]. [cited 2017 Apr 15]. Available from:
  52. 52.
    Adler-Milstein, J., Embi, P., Middleton, B., Sarkar, I., and Smith, J., Crossing the health IT chasm: Considerations and policy recommendations to overcome current challenges and enable value-based care. J. Am. Med. Inform. Assoc. 24(5):1036–1043, 2017.CrossRefGoogle Scholar
  53. 53.
    Samarath, A., Sorace, J., Patel, V., Boone, E., Kemper, N., Rafiqi, F., Yencha, R., and Kharrazi, H., Measurement of interoperable electronic health care records utilization. Washington DC: U.S. Department of Health and Human Services (DHHS), 2016, HHSP233201500099I_HHSP23337001T. Available from: Scholar
  54. 54.
    The Office of the National Coordinator for Health Information Technology. Connecting health and care for the nation: A shared nationwide interoperability roadmap. [internet]. [cited 2017 Dec 12]. Available from:
  55. 55.
    The Office of the National Coordinator for Health Information Technology. Proposed interoperability standards measurement framework. [internet]. 2017 [cited 2017 Dec 22]. Available from:
  56. 56.
    The Sequoia Project. About the Sequia Project. [Internet]. [cited 2017 Dec 10]. Available from:
  57. 57.
    Chan, K., Kharrazi, H., Parikh, M., and Ford, E., Assessing electronic health record implementation challenges using item response theory. Am. J. Manag. Care. 22(12):e409–e415, 2016.PubMedGoogle Scholar
  58. 58.
    Kharrazi, H., Gonzalez, C. P., Lowe, K. B., Huerta, T. R., and Ford, E. W., Forecasting the maturation of electronic health record functions among US hospitals: Retrospective analysis and predictive model. J. Med. Internet Res. 20(8):e10458, 2018.CrossRefGoogle Scholar
  59. 59.
    Ikegami, N., Yoo, B. K., Hashimoto, H., Matsumoto, M., Ogata, H., Babazono, A., Watanabe, R., Shibuya, K., Yang, B. M., Reich, M. R. et al., Japanese universal health coverage: Evolution, achievements, and challenges. Lancet. 378(9796):1106–1115, 2011.CrossRefGoogle Scholar
  60. 60.
    Shimada H, Kondo J. Japan HIT Case Study. [Internet]. 2007 [cited 2017 Dec 12]. Available from:
  61. 61.
    Organization for Economic Co-operation and Development (OECD). Length of hospital stay. [internet]. [cited 2017 May 19]. Available from:
  62. 62.
    Japan Ministry of Health, Labour and welfare. Survey of medical institutions (annual). [internet]. [cited 2017 Feb 12]. Available from:
  63. 63.
    Japan Ministry of Health, Labour and Welfare. Survey of medical institutions: May 2011. [internet]. [cited 2018 Feb 10]. Available from:
  64. 64.
    Kharrazi, H., Lasser, E. C., Yasnoff, W. A., Loonsk, J., Advani, A., Lehmann, H. P., Chin, D. C., and Weiner, J. P., A proposed national research and development agenda for population health informatics: Summary recommendations from a national expert workshop. J. Am. Med. Inform. Assoc. 24(1):2–12, 2016.CrossRefGoogle Scholar
  65. 65.
    Kharrazi, H., and Weiner, J. P., IT-enabled community health interventions: Challenges, opportunities, and future directions. EGEMS (Wash DC). 2(3):1117, 2014.PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Johns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  2. 2.Center for Population Health IT, Department of Health Policy and ManagementJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA

Personalised recommendations