 Electronic Health Records
"Electronic Health Records" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Media that facilitate transportability of pertinent information concerning patient's illness across varied providers and geographic locations. Some versions include direct linkages to online consumer health information that is relevant to the health conditions and treatments related to a specific patient.
| Descriptor ID |
D057286
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| MeSH Number(s) |
E05.318.308.940.968.625.500
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| Concept/Terms |
Electronic Health Records- Electronic Health Records
- Electronic Medical Records
- Electronic Medical Record
- Medical Record, Electronic
- Medical Records, Electronic
- Record, Electronic Medical
- Records, Electronic Medical
- Electronic Health Record
- Health Record, Electronic
- Health Records, Electronic
- Record, Electronic Health
- Records, Electronic Health
Medical Records, Computerized- Medical Records, Computerized
- Medical Record, Computerized
- Computerized Medical Record
- Record, Computerized Medical
- Records, Computerized Medical
- Computerized Medical Records
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Below are MeSH descriptors whose meaning is more general than "Electronic Health Records".
Below are MeSH descriptors whose meaning is more specific than "Electronic Health Records".
This graph shows the total number of publications written about "Electronic Health Records" by people in this website by year, and whether "Electronic Health Records" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2009 | 2 | 1 | 3 | | 2010 | 11 | 4 | 15 | | 2011 | 13 | 9 | 22 | | 2012 | 18 | 6 | 24 | | 2013 | 26 | 17 | 43 | | 2014 | 30 | 24 | 54 | | 2015 | 21 | 11 | 32 | | 2016 | 23 | 25 | 48 | | 2017 | 17 | 26 | 43 | | 2018 | 27 | 27 | 54 | | 2019 | 21 | 18 | 39 | | 2020 | 27 | 25 | 52 | | 2021 | 16 | 34 | 50 | | 2022 | 15 | 23 | 38 | | 2023 | 18 | 24 | 42 | | 2024 | 28 | 33 | 61 | | 2025 | 29 | 25 | 54 | | 2026 | 7 | 3 | 10 |
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Below are the most recent publications written about "Electronic Health Records" by people in Profiles.
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Conderino S, Kirchner HL, Thorpe LE, Divers J, Hirsch AG, Nordberg CM, Schwartz BS, Zhang L, Cai B, Rudisill C, Obeid JS, Liese A, Allen KS, Dixon BE, Crume T, Dabelea D, Burgett S, Bellatorre A, Shao H, Bian J, Guo Y, Bost S, Lyu T, Reynolds K, Mefford MT, Zhou H, Zhou M, Lustigova E, Utidjian LH, Maltenfort M, Kamboj M, Mendonca EA, Hanley P, Zaganjor I, Pavkov ME, Rosenman M, Titus AR. Multi-site analysis of COVID-19 and new-onset diabetes reveals need for improved sensitivity of EHR-based COVID-19 phenotypes-a DiCAYA Network analysis. J Am Med Inform Assoc. 2026 Mar 01; 33(3):710-718.
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Stein AB, Williams JTB, Hurley LP, Breslin K, Kurlandsky K, Hambidge SJ, Nelson JC, Fuller CC, Crane B, Hanson KE, Glenn SC, Jazwa A, Reifler LM. Accuracy of COVID-19 vaccination self-report compared with data from VSD electronic health records for pregnant women and non-pregnant adults, 2021-2022. Am J Epidemiol. 2026 Feb 05; 195(2):515-523.
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Ganguli I, Daley NE, Soto MJ, Sloan CE, Goss FR, Sinaiko AD. Prescription Real-Time Benefit Tools: Clinicians Receive Frequent Alerts Yet Rarely Accept The Suggested Changes. Health Aff (Millwood). 2026 Feb; 45(2):146-153.
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Sinvani L, Perrin A, Huebschmann AG, Basile M, Groton S, Barnaby D, Sanchez G, Chiuzan C, Chua V, Slotnick S, Porreca K, Romano K, Kwiatek S, Cary K, Garg N, Sud P, Makhnevich A. Improving Delirium Screening and Detection in the Emergency Department (ED): The Implementation and Evaluation of the ED Delirium Detection Program. Acad Emerg Med. 2026 Feb; 33(2):e70235.
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Liese AD, Dixon BE, Crume T, Divers J, Guo Y, Hirsch AG, Reynolds K, Utidjian L, Zaganjor I, Rosenman M. Public health monitoring of diabetes in the era of electronic health records: Insights from the Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network. Ann Epidemiol. 2026 Mar; 115:45-49.
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Sivarajkumar S, Edupuganti S, Lazris D, Bhattacharya M, Davis M, Dressman D, Thomas R, Hu Y, Ren Y, Xu H, Yang P, Huang Y, Wang Y. Extraction of Treatments and Responses From Non-Small Cell Lung Cancer Clinical Notes Using Natural Language Processing. JCO Clin Cancer Inform. 2026 Jan; 10:e2500138.
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Chen LA, Wang SY, Lin SA. Predicting Postoperative Outcomes in Lower Gastrointestinal Surgery: A Machine Learning Approach Using Electronic Health Records. AORN J. 2026 Jan; 123(1):68-80.
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Giarrizzo-Wilson S, Stimson N. Using Analytics to Reduce Perioperative Clinical Variance. AORN J. 2026 Jan; 123(1):59-67.
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El Rouby N, Aquilante CL, Bargal SA, Cavallari LH, Duarte JD, Gunderson K, Mazhindu T, Nagy M, Nie X, Nguyen DG, Patel JN, Skaar TC, Smith DM, Tuteja S, van Schaik RHN, Hicks JK. Global Investigation of Clinical Implementation Strategies for DPYD Testing to Guide Fluoropyrimidine Therapy. Clin Transl Sci. 2026 Jan; 19(1):e70466.
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Eyre H, Prince DK, Abrahamson S, Blankenhorn RK, Carey EP, Laundry RJ, Showalter W, Todd-Stenberg J, O'Hare AM, Butler CR. Using Natural Language Processing to Characterize Early Steps in the Kidney Transplant Evaluation Process Documented in the National Veterans Affairs Electronic Health Record. Clin Transplant. 2026 Jan; 40(1):e70441.
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