Electronic Health Records: Origination, Adoption, and Progression

Part of the Health Informatics book series (HI)


The electronic health record (EHR) represents the evolution and convergence of technology and administration of medicine. Its advent has significantly changed the landscape in which medical policy and process can be created. As vast amounts of data are gathered in the management of care and administration of health systems, these clinical big data provide opportunities to enhance public health practice. This work delineates core functionalities and primary and secondary uses of EHRs that are aligned with these practices, including uses of EHRs for healthcare, public health, and population health outcomes. From EHRs origins as simple billing and accounting systems, to its adoption as, and progression toward, full-fledged interactive records, the medical, public health, and governmental stakeholders have at times been at odds to ensure their concerns and requirements are adequately represented in implementations. Legislation to promote the adoption of EHRs capable of recording and reporting health data in a standardized, structured, and secure format, and technologies to facilitate the progress towards the goals of EHRs, such as achieving portability, have had varying results. Various milestones to EHR goals are discussed, with respect to legislation, regulation, policies, and the importance of standards and technologies. This work examines some lessons learned from EHR developments and implementations, which also exposes limitations, disparities, and unintended consequences of EHR adoption and progression globally. It concludes with forward looking perspectives on EHRs, a crucial cornerstone of public health informatics and information systems.


Acknowledgement logic Computerized provider order entry Electronic data interchange Electronic health record Electronic prescribing Health information technology Integration engines Meaningful Use Picture archiving and communications systems Protected health information 



The authors gratefully acknowledge the editorial assistance from J. A. Magnuson and Brian E. Dixon. The authors also gratefully acknowledge the guidance on this intellectual work from advisors, Charles M. Heilig and Mark L. Messonnier, as well as the comments on it from several reviewers, including Adi V. Gundlapalli, Sanjeev Tandon, Michael Paul Reid, and Fatima Coronado, at the Centers for Disease Control and Prevention (CDC). This work was supported by CDC Public Health Informatics Fellowship Program (PHIFP) Fellowships (to F.R., and to J.T.P.). The CDC Population Health Workforce Initiative (PHWI) also provided support for this work (to F.R., and to J.T.P.). This work was also supported by a Biomedical Engineering Society (BMES) Career Development Award (to F.R.). The findings and conclusions in this work are those of the authors, and do not necessarily represent the official position of the CDC, or of the Mayo Clinic. The authors declared no conflict of interest.


  1. 1.
    Institute of Medicine. Key capabilities of an electronic health record system: letter report. Washington, DC: The National Academies Press; 2003.Google Scholar
  2. 2.
    HHS Summary of the HIPAA Privacy Rule. Public law 104-191. HHS Office for Civil Rights (OCR). 2013.
  3. 3.
  4. 4.
    Romano MJ, Stafford RS. Electronic health records and clinical decision support systems: impact on national ambulatory care quality. Arch Intern Med. 2011;171:897–903.PubMedPubMedCentralGoogle Scholar
  5. 5.
    Sittig DF, Wright A, Osheroff JA, Middleton B, Teich JM, Ash JS, Campbell E, Bates DW. Grand challenges in clinical decision support. J Biomed Inform. 2008;41:387–92.CrossRefGoogle Scholar
  6. 6.
    Columbus S. Small practice, big decision: selecting an EHR system for small physician practices. J AHIMA. 2006;77:42–6.PubMedGoogle Scholar
  7. 7.
    Fleming NS, Becker ER, Culler SD, Cheng D, McCorkle R, Graca BD, Ballard DJ. The impact of electronic health records on workflow and financial measures in primary care practices. Health Serv Res. 2014;49:405–20.CrossRefGoogle Scholar
  8. 8.
    Patra D, Ray S, Mukhopadhyay J, Majumdar B, Majumdar AK. Achieving e-health care in a distributed EHR system. In: 2009 11th international conference on e-health networking, applications and services. Piscataway: IEEE; 2010. p. 101–7.Google Scholar
  9. 9.
    Jamoom E, Beatty P, Bercovitz A, Woodwell D, Palso K, Rechtsteiner E. Physician adoption of electronic health record systems: United States, 2011. 2012.
  10. 10.
    History of Electronic Data Interchange. 2005-2013.
  11. 11.
    About HL7. HL7 International.
  12. 12.
    Pianykh OS. Digital imaging and communications in medicine (DICOM) - a practical introduction and survival guide. New York: Springer; 2012.Google Scholar
  13. 13.
    The switch from ICD-9 to ICD-10: when and why.
  14. 14.
  15. 15.
    ICD - ICD-10-CM - International Classification of Diseases, Tenth Revision, clinical modification.
  16. 16.
    WHO|International Classification of Diseases (ICD) Information Sheet.
  17. 17.
  18. 18.
    Executive Order 13335 - incentives for the use of health information technology and establishing the position of the National Health Information Technology Coordinator. 2004.Google Scholar
  19. 19.
  20. 20.
    H.R. 1. - American Recovery and Reinvestment Act of 2009 (ARRA). Public Law 111-5.
  21. 21.
  22. 22.
  23. 23.
    CMS Medicare and Medicaid EHR Incentive Programs Milestone Timeline. In: HIMSS. 2011.
  24. 24.
    About Health Level Seven International|HL7 International.
  25. 25.
    About LOINC – LOINC. In: LOINC.
  26. 26.
    What is SNOMED CT (Systematized Nomenclature of Medicine -- Clinical Terms)? - Definition from In: SearchHealthIT.
  27. 27.
  28. 28.
    ICD - ICD-10-CM - International Classification of Diseases, Tenth Revision, clinical modification. 2019.
  29. 29.
  30. 30.
    CPT® purpose & mission. In: American Medical Association.
  31. 31.
    David Kindig GS. What is population health? Am J Public Health. 2003;93:380.CrossRefGoogle Scholar
  32. 32.
    How can electronic health records improve public and population health outcomes?
  33. 33.
    Lurio J, Morrison FP, Pichardo M, Berg R, Buck MD, Wu W, Kitson K, Mostashari F, Calman N. Using electronic health record alerts to provide public health situational awareness to clinicians. J Am Med Inform Assoc. 2010;17:217–9.CrossRefGoogle Scholar
  34. 34.
    Fiks AG, Grundmeier RW, Biggs LM, Localio AR, Alessandrini EA. Impact of clinical alerts within an electronic health record on routine childhood immunization in an urban pediatric population. Pediatrics. 2007;120:707–14.CrossRefGoogle Scholar
  35. 35.
    Friedman DJ, Gibson Parrish R, Ross DA. Electronic health records and US Public Health: current realities and future promise. Am J Public Health. 2013;103:1560.CrossRefGoogle Scholar
  36. 36.
  37. 37.
    DeSalvo KB. Public Health 3.0: a call to action for public health to meet the challenges of the 21st century. Prev Chronic Dis. 2017;14Google Scholar
  38. 38.
    Cantor MN, Thorpe L. Integrating data on social determinants of health into electronic health records. Health Aff. 2018;37:585–90.CrossRefGoogle Scholar
  39. 39.
    Gold R, Cottrell E, Bunce A, Middendorf M, Hollombe C, Cowburn S, et al. Developing electronic health record (EHR) strategies related to health center patients’ social determinants of health. J Am Board Fam Med. 2017;30:428–47.CrossRefGoogle Scholar
  40. 40.
    BioSense Platform|NSSP|CDC. 2018.
  41. 41.
    Gray BH, Bowden T, Johansen IB, Koch S. Electronic health records: an international perspective on “meaningful use”. Issue Brief. 2011;28:1–18.PubMedGoogle Scholar
  42. 42.
    Timmins N. World’s biggest civil technology project comes alive. In: Financial Times. 2006.
  43. 43.
    Charette, RN. Troubled HealthSMART system finally cancelled in Victoria Australia. In: IEEE spectrum inside technology. 2012.
  44. 44.
    U.S. Department of Health and Human Services. The office of the national coordinator for health information technology. Health IT Dashboard.
  45. 45.
    Mack D, Zhang S, Douglas M, Sow C, Strothers H, Rust G. Disparities in primary care EHR adoption rates. J Health Care. 2016;27:327.Google Scholar
  46. 46.
    Whitacre BE. The influence of the degree of rurality on EMR adoption, by physician specialty. Health Serv Res. 2017;52:616.CrossRefGoogle Scholar
  47. 47.
    Johnson OA, Fraser HS, Wyatt JC, Walley JD. Electronic health records in the UK and USA. Lancet. 2014;384:954.CrossRefGoogle Scholar
  48. 48.
    Feng Chang NG. Progress in electronic medical record adoption in Canada. Can Fam Physician. 2015;61:1076.PubMedCentralGoogle Scholar
  49. 49.
    Stone CP. A glimpse at EHR implementation around the world: the lessons the US can learn.
  50. 50.
    Srivastava SK. Adoption of electronic health records: a roadmap for India. Healthc Inform Res. 2016;22:261.CrossRefGoogle Scholar
  51. 51.
    Tavares J, Oliveira T. Electronic health record portal adoption: a cross country analysis. BMC Med Inform Decis Mak. 2017;17:97.CrossRefGoogle Scholar
  52. 52.
    Transformation Health and Care in the Digital Single Market. 2019.
  53. 53.
    ΝEHR. Development of Nationwide Electronic Health Record (ΝEHR): an international survey. Health Policy Technol. 2017;6:124–33.CrossRefGoogle Scholar
  54. 54.
    Pan American Health Organization. Electronic medical records in Latin America and the Caribbean: an analysis of the current situation and recommendations for the region. 2016.
  55. 55.
    Registros Médicos Electrónicos - RELACSIS|OPS/OMS. In: Pan American Health Organization/World Health Organization. 2015.
  56. 56.
    Odekunle FF, Odekunle RO, Shankar S. Why sub-Saharan Africa lags in electronic health record adoption and possible strategies to increase its adoption in this region. Int J Health Sci. 2017;11:59.Google Scholar
  57. 57.
    Alqahtani A, Crowder R, Wills G. Barriers to the adoption of EHR systems in the Kingdom of Saudi Arabia: an exploratory study using a systematic literature review. JHIDC. 2017;11:1.Google Scholar
  58. 58.
    Epic. Cerner and others moving into expanding global EHR market, says KLAS. In: Healthcare IT News. 2018.
  59. 59.
    Sheikh A, Jha A, Cresswell K, Greaves F, Bates DW. Adoption of electronic health records in UK hospitals: lessons from the USA. Lancet. 2014;384:8–9.CrossRefGoogle Scholar
  60. 60.
    Silverman DC. The electronic medical record system: health care marvel or morass? (surfing the information technology wave). Physician Exec. 1998;24:26–31.PubMedGoogle Scholar
  61. 61.
    Lance Downing N, Bates DW, Longhurst CA. Physician burnout in the electronic health record era: are we ignoring the real cause? Ann Intern Med. 2018;169:50–1.CrossRefGoogle Scholar
  62. 62.
    Sieja A, Markley K, Pell J, Gonzalez C, Redig B, Kneeland P, Lin CT. Optimization sprints: improving clinician satisfaction and teamwork by rapidly reducing electronic health record burden. Mayo Clin Proc. 2019;94:793–802.CrossRefGoogle Scholar
  63. 63.
    Payne TH. EHR-related alert fatigue: minimal progress to date, but much more can be done. BMJ Qual Saf. 2019;28:1–2.CrossRefGoogle Scholar
  64. 64.
    Collier R. Rethinking EHR interfaces to reduce click fatigue and physician burnout. CMAJ. 2018;190:E994.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Division of Scientific Education and Professional Development, Center for Surveillance, Epidemiology, and Laboratory ServicesCenters for Disease Control and PreventionAtlantaUSA
  2. 2.Department of Laboratory Medicine and PathologyMayo ClinicRochesterUSA

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