Implications of an emerging EHR monoculture for hospitals and healthcare systems

Koppel, Ross; Lehmann, Christoph U

doi:10.1136/amiajnl-2014-003023

Cited by 140Electronic Health Records SystemsHealthcare Policy and ManagementMedical Coding and Health Information

Implications of an emerging EHR monoculture for hospitals and healthcare systems

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Koppel, Ross, Lehmann, Christoph U·2015·Journal of the American Medical Informatics Association

DOI 10.1136/amiajnl-2014-003023PMC PMC11749203

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Abstract

In many hospitals and health systems, a ‘new’ electronic health record means a shift to one vendor: Epic, a vendor that dominates in large and medium hospital markets and continues its success with smaller institutions and ambulatory practices. Our paper examines the implications of this emerging monoculture: its advantages and disadvantages for physicians and hospitals and its role in innovation, professional autonomy, implementation difficulties, workflow, flexibility, cost, data standards, interoperability, and interactions with other information technology (IT) systems.

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There are concerns that the large market shares of relatively few EHR vendors may make vendors less responsive to designing EHRs to meet patients' and clinicians' needs, particularly while controlling costs and promoting interoperability.
“While health care systems may influence the development of EHR features, there are concerns that the large market shares of relatively few EHR vendors may make vendors less responsive to designing EHRs to meet patients’ and clinicians’ needs, particularly while controlling costs and promoting interoperability [22].”
From Incorporating Social Determinants of Health in Electronic Health Records: Qualitative Study of Current Practices Among Top Vendors (2019) · cites this paper as [22]

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Single-Vendor Electronic Health Record Use Is Associated With Greater Opportunities for Organizational and Clinical Care Improvements
Hamadi, H. Y., Niazi, S., Zhao, M., & Spaulding, A. C. (2022) · Mayo Clinic Proceedings: Innovations, Quality & Outcomes · doi:10.1016/j.mayocpiqo.2022.05.001 · Cited by 9 · see citing works
“6,8,23 As a result, it is not surprising that hospitals using the same vendor EHR system in both their inpatient and outpatient services are more likely to use resultant data to inform their clinical care decisions and organizational management process.”
Background
Policy Statement on Clinical Informatics Fellowships and the Future of Informatics-Driven Medicine
Kannry, J. L., Smith, J., Mohan, V., Levy, B. P., Finnell, J., Lehmann, C. U., & on behalf of the Clinical Informatics Program Directors Group-AMIA (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1717117 · Cited by 14 · see citing works
Self-citation
Mining User-generated Content of Mobile Patient Portal
Al-Ramahi, M. A., & Noteboom, C. (2020) · ACM Transactions on Social Computing · doi:10.1145/3394831 · Cited by 7 · see citing works
“It has been described as the default EHR choice, not for its superior performance, but because other systems are considered inferior [26].”
Background
What are the Gaps in Mobile Patient Portal? Mining Users Feedback Using Topic Modeling
Noteboom, C., & Al-Ramahi, M. (2018) · Hawaii International Conference on System Sciences · doi:10.24251/hicss.2018.072 · Cited by 9
Progress Achieved, Landmarks, and Future Concerns in Biomedical and Health Informatics
Ognjanovic, I., Zoulias, E., & Mantas, J. (2024) · Healthcare · doi:10.3390/healthcare12202041 · Cited by 8 · see citing works
“…real-world data sources to support clinical research [62]. such . both issue a during the design of EHR systems, at times influenced by vendor lock-in policies [71], and a lack of adequate methods to describe and formally represent healthcare processes and their associated information requirements.”
Background
Physician Perspectives on Training for an EHR Implementation
Pirtle, C. J., Reeder, R. R., Lehmann, C. U., Unertl, K., & Lorenzi, N. (2019) · Medinfo · doi:10.3233/shti190440 · Cited by 8
“[1] Organizations use multiple techniques to prepare and train clinicians for an impending electronic health record implementation from remote phone training, class-room training, role-based training, web-based training, [2] and the “ specialist training the speciali st” training model.”
MethodSelf-citation
Barriers to Pediatric Health Information Exchange
Lehmann, C. U., Kressly, S. J., Hart, W. C., Johnson, K. B., & Frisse, M. (2017) · Pediatrics · doi:10.1542/peds.2016-2653 · Cited by 8
Self-citation
Unintended Consequences: New Problems, New Solutions
Koppel, R., & Chen, Y.-N. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-048 · Cited by 8 · see citing works
“Hospital personnel spend up to five years and sometimes billions of dollars with the implementation process [11].”
Self-citation
Framework for Smart Health: Toward Connected Data from Big Data
Raja, P., Sivasankar, E., & Pitchiah, R. (2015) · doi:10.1007/978-81-322-2268-2_44 · Cited by 8
“The advent of health informatics has been creating a tremendous change in the field of health care [1].”
Background
Patient Experiences of and Priorities for Traumatic Brain Injury Health Care in a US Level 1 Trauma Center: A Qualitative Study
Nelson, L. D., Gray, S., Barry, C. O., Young, S. A., deRoon-Cassini, T. A., Hedayat, H., Kobayashi, Y., McCrea, M., Tobes, N., Trevino, C. M., et al. (2025) · Mayo Clinic Proceedings: Innovations, Quality & Outcomes · doi:10.1016/j.mayocpiqo.2025.100630 · Cited by 7 · see citing works
“21,22 Furthermore, because patient access to such technologies is not ubiquitous, 23,24 such tools do not replace the need for resources and training that promote strong communication between individuals working in health care and consumers of health care.”
From “Local Control” to “Dependency”: Transitions to Single-Vendor Integrated Electronic Health Record Systems and Their Implications for the EHR Workforce
Brunner, J., Anderson, E., Mohr, D. C., Cohen-Bearak, A., & Rinne, S. T. (2023) · Journal of general internal medicine · doi:10.1007/s11606-023-08281-6 · Cited by 7 · see citing works
Hospital characteristics associated with HIPAA breaches
Heath, M. L., Porter, T. H., & Silvera, G. A. (2021) · International Journal of Healthcare Management · doi:10.1080/20479700.2020.1870349 · Cited by 9 · see citing works
Toward Application of Blockchain for Improved Health Records Management and Patient Care
Carter, G., White, D., Nalla, A., Shahriar, H., & Sneha, S. (2019) · Blockchain in Healthcare Today · doi:10.30953/bhty.v2.37 · Cited by 7 · see citing works
Uncovering differences in interoperability across hospital size
Pylypchuk, Y., Alvarado, C. S., Patel, V., & Searcy, T. (2019) · Healthcare · doi:10.1016/j.hjdsi.2019.04.001 · Cited by 7 · see citing works
The Virtuous Circles of Clinical Information Systems: a Modern Utopia
Degoulet, P. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-030 · Cited by 7 · see citing works
“In Bassi’s review of 33 HIT economic evaluation papers, only four papers focused on full institutional information systems [10] among which one was considered negative [27].”
Background
Development of user-friendly and interactive data collection system for cerebral palsy
Raharjo, I., Burns, T. G., Venugopalan, J., & Wang, M. (2016) · 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) · doi:10.1109/bhi.2016.7455920 · Cited by 6
“MD Wang is with the Wallace H. Coulter Department of Biomedical Engineering Department, Georgia Institute of Technology and Emory University, Electrical and Computer Engineering, Winship Cancer Institute, Parker H. Petit Institute of Bioengineering and Biosciences, Institute of People and…”
Method
Current Advances in Patient-Perceived Quality Assessment Within Romanian Healthcare
Bancsik, K., Daina, M. D., Ghitea, T. C., Bancsik, R., & Daina, L. (2024) · Cureus · doi:10.7759/cureus.70111 · Cited by 2 · see citing works
Do electronic health record systems "dumb down" clinicians?
Melton, G., Cimino, J., Lehman, C. U., Sengstack, P. R., Smith, J. C., Tierney, W., & Miller, R. A. (2022) · J. Am. Medical Informatics Assoc. · doi:10.1093/jamia/ocac163 · Cited by 5 · see citing works
Design and Evaluation of a Computational Phenotype to Identify Patients With Metastatic Breast Cancer Within the Electronic Health Record.
Neely, B., Shahsahebi, M., Marks, C. E., Power, S., Kanter, A., Howell, C., Hyslop, T., & Plichta, J. (2022) · JCO Clinical Cancer Informatics · doi:10.1200/cci.22.00056 · Cited by 5
Acceptance of Acute Kidney Injury Alert by Providers in Cardiac Surgery Intensive Care Unit
Nevin, C., Shawwa, K., Pincavitch, J. D., Neely, R. L., Goodwin, D., McCarthy, P. J., Mohamed, N. M., Mullett, C. J., Smith, G. S., Kellum, J. A., et al. (2022) · Applied Clinical Informatics · doi:10.1055/a-2000-7499 · Cited by 4 · see citing works
Computerized Clinical Decision Support Systems for Prevention of Venous Thromboembolism: Why Can't My Electronic Health Record Be More Like Netflix, Amazon, Google, and Apple?
Lau, B. D., & Haut, E. (2017) · JAMA Surgery · doi:10.1001/jamasurg.2017.0107 · Cited by 5 · see citing works
Buy or build: challenges developing consumer digital health interventions
Saver, B. G., Marquard, J. L., Gummeson, J., Stekler, J., & Scanlon, J. M. (2023) · Applied Clinical Informatics · doi:10.1055/a-2148-8036 · Cited by 4 · see citing works
“20 Our experiences are certainly not unique.”
Revolutionizing decision support: a systematic literature review of contextual implementation models for electronic health records systems.
Mwogosi, A., Shao, D., Kibusi, S. M., & Kapologwe, N. (2024) · Journal of health organization and management · doi:10.1108/jhom-04-2023-0122 · Cited by 4 · see citing works
Neonatal informatics: past, present and future
Patel, S. Y., Palma, J. P., Hoffman, J., & Lehmann, C. U. (2024) · Journal of Perinatology · doi:10.1038/s41372-024-01924-4 · Cited by 5 · see citing works
“Analogous to the transitions from three decades earlier, we are again struggling to make EHRs work for clinicians instead of clinicians working to satisfy the demands of the EHR [20].”
BackgroundSelf-citation
Towards a universal patient-centric health record sharing platform
Azarm, M., Meehan, R. A., & Kuziemsky, C. E. (2023) · Health Policy and Technology · doi:10.1016/j.hlpt.2023.100819 · Cited by 4 · see citing works
Discovering Patient Portal Features Critical to User Satisfaction: A Systematic Analysis
Wahbeh, A., Al-Ramahi, M., Noteboom, C., & Nasralah, T. (2019) · Hawaii International Conference on System Sciences · doi:10.24251/hicss.2019.104 · Cited by 4
Improving Bridging from Informatics Practice to Theory
Lehmann, C. U., & Gundlapalli, A. (2015) · Methods of Information in Medicine · doi:10.3414/me15-01-0138 · Cited by 4 · see citing works
“One of the consequences of MU – the change to a new EHR vendor [65] – was addressed in a paper discussing data migration from one EHR to another [66].”
BackgroundSelf-citation
Identifying a Clinical Informatics or Electronic Health Record Expert Witness for Medical Professional Liability Cases
Sittig, D. F., & Wright, A. (2022) · Applied Clinical Informatics · doi:10.1055/a-2018-9932 · Cited by 3 · see citing works
Response to: An Evidence-Based Tool for Safe Configuration of Electronic Health Records: The eSafety Checklist
Koppel, R. (2018) · Applied Clinical Informatics · doi:10.1055/s-0038-1675811 · Cited by 3 · see citing works
Self-citation
Features Related to Patient Portal User Satisfaction: N-Gram-Based Analysis of Users' Feedback
Al-Ramahi, M., Wahbeh, A., & Noteboome, C. (2018) · SIGMIS-CPR · doi:10.1145/3209626.3209729 · Cited by 3
“It has been described as the default EHR choice not for its superior performance, but because other systems are considered inferior [8].”
Background
Advancing the integration of hospital IT
Engelmann, C., & Ametowobla, D. (2017) · Applied Clinical Informatics · doi:10.4338/aci-2016-06-ra-0100 · Cited by 3 · see citing works
Barriers to Information Access in Electronic Health Records during Initial Patient Visits: A Qualitative Study
Doberne, J., Kakaday, R., Redd, T. K., Eriksson, C. O., Yackel, T. R., Marquard, J. L., Gold, J. A., Mohan, V., Ash, J. S., & Chiang, M. F. (2015) · Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care · doi:10.1177/2327857915041009 · Cited by 2 · see citing works
“With implementation costs up to $1 billion or more (Koppel & Lehmann, 2014), health systems are often unable to switch EHRs despite their dissatisfaction with and poor performance of the systems (Murphy, 2013).”
Background
Exploring the Emergence of Open Platforms in Healthcare: Design Considerations and Experiences from an Initial Case in Norwegian Primary Care
Malm-Nicolaisen, K., Fagerlund, A. J., & Pedersen, R. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.345 · Cited by 6 · see citing works
“Consequently, organizations become heavily reliant on single vendors and siloed ‘closed sy stems’ with limited flexibility and a fragmented HIT portfolio (Koppel & Lehmann, 2015).”
Background
A problem of Epic proportion
Abulibdeh, R., Crowson, M. G., Douglas, M. J., Ramos, M., Saillant, N., & Celi, L. (2026) · PLOS Digital Health · doi:10.1371/journal.pdig.0001143 · Cited by 2 · see citing works
Disparities in electronic health record patient portal activation and use among people with hematological malignancies
Trammel, A. M., Sisk, B. A., & Fiala, M. (2024) · Journal of Geriatric Oncology · doi:10.1016/j.jgo.2024.102135 · Cited by 2
“[11] At WUSM, patients can activate their patient portal through a website, over the phone, or at their provider’s office.”
Leveraging Electronic Health Records (EHR) for Enhanced Patient Care
Divyeshkumar, V. (2024) · International Journal of Current Science Research and Review · doi:10.47191/ijcsrr/v7-i5-58 · Cited by 2
“A vast healthcare system adopting an Electronic Health Record System can spend hundreds of millions of dollars to buy, implement, maintain, and educate their staff on how to use these systems 5 .”
Background

Authors: Koppel, R., & Lehmann, C. U.
Affiliations: University of Pennsylvania (US)
Vanderbilt University (US)
ORCID: Koppel, Ross
Lehmann, Christoph U
Venue: Journal of the American Medical Informatics Association
Publisher: Oxford University Press (OUP)
Published: 2014-10-23
Volume: 22
Issue: 2
Pages: 465-471
ISSN: 1067-5027 (ISSN-L)
1527-974X
DOI: 10.1136/amiajnl-2014-003023
PMC: PMC11749203
OpenAlex: W2155767215
Cited by: 140
References: 0
Citations by year: 2026: 2 · 2025: 5 · 2024: 11 · 2023: 15 · 2022: 13 · 2021: 7 · 2020: 13 · 2019: 13 · 2018: 15 · 2017: 13 · 2016: 19 · 2015: 14
FWCI: 28.03
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Journal of the American Medical Informatics Association (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: National Science Foundation
Topics: Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Keywords: electronic health records, epic, market concentration, hospital information systems, interoperability, data standards, implementation barriers, physician workflow, professional autonomy
MeSH terms: Commerce, Delivery of Health Care, Health Facilities, Hospitals, United States, Medical Records Systems, Computerized, Systems Integration, Electronic Health Records

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