Patient Safety Issues From Information Overload in Electronic Medical Records
Open accessAbstract
Background and Objective: Electronic health records (EHRs) have become ubiquitous in medicine and continue to grow in informational content. Little has been documented regarding patient safety from the resultant information overload. The objective of this literature review is to better understand how information overload in EHR affects patient safety. Methods: A literature search was performed using the Transparent Reporting of Systematic Reviews and Meta-Analyses standards for literature review. PubMed and Web of Science were searched and articles selected that were relevant to EHR information overload based on keywords. Results: The literature search yielded 28 articles meeting the criteria for the study. Information overload was found to increase physician cognitive load and error rates in clinical simulations. Overabundance of clinically irrelevant information, poor data display, and excessive alerting were consistently identified as issues that may lead to information overload. Conclusions: Information overload in EHRs may result in higher error rates and negatively impact patient safety. Further studies are necessary to define the role of EHR in adverse patient safety events and to determine methods to mitigate these errors. Changes focused on the usability of EHR should be considered with the end user (physician) in mind. Federal agencies have a role to play in encouraging faster adoption of improved EHR interfaces.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
As EHRs accumulate increasingly large volumes of structured and unstructured data, physicians face additional challenges in finding relevant information, resulting in information overload and further elevating cognitive load.
“As EHRs accumulate increasingly large volumes of structured and unstructured data, physicians face additional challenges in finding relevant information, resulting in information overload and further elevating cognitive load19–21.”
From When better data meets better design: How EHR data usability and system usability shape physicians' cognitive load (2026) · cites this paper as [21]
EHR information overload poses risk to patient safety and excessive alerting is among the primary contributors to this overload.
“EHR information overload poses risk to patient safety and excessive alerting is among the primary contributors to this overload.84”
From Electronic health record activity changes around new decision support implementation: monitoring using audit logs and topic modeling (2025) · cites this paper as [84]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties
Sinsky, C., Colligan, L., Li, L., Prgomet, M., Reynolds, S., Goeders, L., Westbrook, J., Tutty, M., & Blike, G. (2016) · Annals of Internal Medicine · doi:10.7326/m16-0961 · Cited by 1,494 · see citing works
Shanafelt, T. D., Dyrbye, L. N., Sinsky, C., Hasan, O., Satele, D., Sloan, J., & West, C. P. (2016) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2016.05.007 · Cited by 1,086 · see citing works
Arndt, B. G., Beasley, J. W., Watkinson, M. D., Temte, J. L., Tuan, W.-J., Sinsky, C. A., & Gilchrist, V. J. (2017) · The Annals of Family Medicine · doi:10.1370/afm.2121 · Cited by 972 · see citing works
with the HITEC Investigators, Ancker, J. S., Edwards, A., Nosal, S., Hauser, D., Mauer, E., & Kaushal, R. (2017) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-017-0430-8 · Cited by 709 · see citing works
Melnick, E. R., Dyrbye, L. N., Sinsky, C. A., Trockel, M., West, C. P., Nedelec, L., Tutty, M. A., & Shanafelt, T. (2020) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2019.09.024 · Cited by 413 · see citing works
Electronic Health Record Usability Issues and Potential Contribution to Patient Harm
Howe, J. L., Adams, K. T., Hettinger, A. Z., & Ratwani, R. M. (2018) · JAMA · doi:10.1001/jama.2018.1171 · Cited by 281 · see citing works
physician information needs and electronic health records (EHRs): time to reengineer the clinic note
Koopman, R. J., Steege, L. M. B., Moore, J. L., Clarke, M. A., Canfield, S. M., Kim, M. S., & Belden, J. L. (2015) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2015.03.140244 · Cited by 90 · see citing works
Flagged first, then by citations
Research works printed but not linked: 24
- [1]Zelmer J Ronchi E Hyppönen H,. International health IT benchmarking: learning from cross-country comparisons. J Am Med Inform Assoc. 2017; 24: 371– 379. 27554825 PMC7651944
- [3]Adler-Milstein J Everson J Lee SD. EHR adoption and hospital performance: time-related effects. Health Serv Res. 2015; 50: 1751– 1771. 26473506 PMC4693851
- [4]Middleton B Bloomrosen M Dente MA,. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J Am Med Inform Assoc. 2013; 20: e2– e8. 23355463 PMC3715367
- [6]March CA Steiger D Scholl G,. Use of simulation to assess electronic health record safety in the intensive care unit: a pilot study. BMJ Open. 2013; 3: e002549. PMC3641430 23578685
- [7]Zulman DM Shah NH Verghese A. Evolutionary pressures on the electronic health record: caring for complexity. JAMA. 2016; 316: 923– 924. 27532804
- [9]Sittig DF Wright A Ash J,. New unintended adverse consequences of electronic health records. Yearb Med Inform. 2016; 1: 7– 12. PMC5171566 27830226
- [12]Vainiomäki S Aalto AM Lääveri T,. Better usability and technical stability could lead to better work-related well-being among physicians. Appl Clin Inform. 2017; 8: 1057– 1067. 29241245 PMC5802304
- [13]Beasley JW Wetterneck TB Temte J,. Information chaos in primary care: implications for physician performance and patient safety. J Am Board Fam Med. 2011; 24: 745– 751. 22086819 PMC3286113
- [14]Singh H Spitzmueller C Petersen NJ,. Information overload and missed test results in electronic health record–based settings. JAMA Intern Med. 2013; 173: 702– 704. 23460235 PMC3822526
- [15]Wright MC Dunbar S Macpherson BC,. Toward designing information display to support critical care. A qualitative contextual evaluation and visioning effort. Appl Clin Inform. 2016; 7: 912– 929. 27704138 PMC5228134
- [16]Ahmed A Chandra S Herasevich V,. The effect of two different electronic health record user interfaces on intensive care provider task load, errors of cognition, and performance. Crit Care Med. 2011; 39: 1626– 1634. 21478739
- [17]Al Ghalayini M Antoun J Moacdieh NM. Too much or too little? Investigating the usability of high and low data displays of the same electronic medical record. Health Informatics J. 2020; 26: 88– 103. 30501370
- [18]Berg GM Shupsky T Morales K. Resident Indentified violations of usability heuristic principles in local electronic health records. Kans J Med. 2020; 13: 84– 89. 32499860 PMC7266506
- [19]Clarke MA Steege LM Moore JL,. Determining primary care physician information needs to inform ambulatory visit note display. Appl Clin Inform. 2014; 5: 169– 190. 24734131 PMC3974234
- [20]Belden JL Koopman RJ Patil SJ,. Dynamic electronic health record note prototype: seeing more by showing less. J Am Board Fam Med. 2017; 30: 691– 700. 29180544
- [21]Kahn D Stewart E Duncan M,. A prescription for note bloat: an effective progress note template. J Hosp Med. 2018; 13: 378– 382. 29350222
- [22]Senathirajah Y Kaufman D Bakken S. User-composable electronic health record improves efficiency of clinician data viewing for patient case appraisal: a mixed-methods study. EGEMS (Wash DC). 2016; 4: 1176. 27195306 PMC4862763
- [23]Ratwani RM Savage E Will A,. A usability and safety analysis of electronic health records: a multi-center study. J Am Med Inform Assoc. 2018; 25: 1197– 1201. 29982549 PMC7646875
- [25]Shah T Patel-Teague S Kroupa L,. Impact of a national QI programme on reducing electronic health record notifications to clinicians. BMJ Qual Saf. 2019; 28: 10– 14. PMC6365918 29507122
- [26]Murphy DR Giardina TD Satterly T,. An exploration of barriers, facilitators, and suggestions for improving electronic health record inbox-related usability: a qualitative analysis. JAMA Netw Open. 2019; 2: e1912638. 31584683 PMC6784746
- [27]Pickering BW Herasevich V Ahmed A,. Novel representation of clinical information in the ICU: developing user interfaces which reduce information overload. Appl Clin Inform. 2010; 1: 116– 131. 23616831 PMC3632280
- [28]Khairat S Burke G Archambault H,. Perceived burden of EHRs on physicians at different stages of their career. Appl Clin Inform. 2018; 9: 336– 347. 29768634 PMC5955717
- [29]Khairat S Coleman C Ottmar P,. Physicians’ gender and their use of electronic health records: findings from a mixed-methods usability study. J Am Med Inform Assoc. 2019; 26: 1505– 1514. 31504578 PMC7647147
- [30]Melnick ER Sinsky CA Dyrbye LN,. Association of perceived electronic health record usability with patient interactions and work-life integration among US physicians. JAMA Netw Open. 2020; 3: e207374. 32568397 PMC7309439
Cited by
Sorted by citations
Next-generation agentic AI for transforming healthcare
Karunanayake, N. (2025) · Informatics and Health · doi:10.1016/j.infoh.2025.03.001 · Cited by 165 · see citing works
Moy, A. J., Hobensack, M., Marshall, K., Vawdrey, D. K., Kim, E. Y., Cato, K. D., & Rossetti, S. C. (2023) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocad038 · Cited by 98 · see citing works
Clay, B., Bergman, H. I., Salim, S., Pergola, G., Shalhoub, J., & Davies, A. H. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.109808 · Cited by 41 · see citing works
Fallon, A., Haralambides, K., Mazzillo, J., & Gleber, C. (2024) · Applied Clinical Informatics · doi:10.1055/a-2226-8144 · Cited by 22 · see citing works
Merriweather, Lyytinen, K., Aron, D., & Cauley, M. R. (2026) · npj Digital Medicine · doi:10.1038/s41746-025-02243-4 · Cited by 9 · see citing works
“As EHRs accumulate increasingly large volumes of structured and unstructured data, physicians face additional challenges in fi nding relevant information, resulting in information overload and further elevating cognitive load 19 – 21 .”
Electronic health record use and perceptions among urologic surgeons
Tan, H.-J., Chung, A. E., Gotz, D., Deal, A. M., Heiling, H. M., Teal, R., Vu, M. B., Meeks, W. D., Fang, R., Bennett, A. V., et al. (2023) · Applied Clinical Informatics · doi:10.1055/s-0043-1763513 · Cited by 8 · see citing works
AlHussainan, A., & Alhuwail, D. (2025) · JMIR Medical Informatics · doi:10.2196/70782 · Cited by 4 · see citing works
Chen, J., Cutrona, S. L., Dharod, A., Moses, A., Bridges, A., Ostasiewski, B., Foley, K. L., Houston, T. K., iDAPT (Implementation & Informatics Developing Adaptable Processes and Technologies for Cancer Control) Implementation Science Center for Cancer Control, Chen, J., et al. (2025) · JAMIA Open · doi:10.1093/jamiaopen/ooaf050 · Cited by 3 · see citing works
- Authors
- Nijor, S., Rallis, G., Lad, N., & Gokcen, E.
- Affiliations
- Temple University (US)
- Corresponding author
- Rallis, Gavin
- Venue
- Journal of Patient Safety
- Published
- 2022-04-07
- Volume
- 18
- Issue
- 6
- Pages
- e999-e1003
- ISSN
- 1549-8417 (ISSN-L)
- 1549-8425
- PMC
- PMC9422765
- OpenAlex
- W4225845990
- Cited by
- 137
- References
- 7
- Citations by year
- 2026: 43 · 2025: 45 · 2024: 31 · 2023: 16 · 2022: 1 · 2021: 1
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Patient Safety (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- TUScholarShare (Temple University) (submittedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Keywords
- electronic health records, information overload, patient safety, clinical decision support alerts, medical errors, EHR usability, data presentation, clinical simulation
- MeSH terms
- Systematic Reviews as Topic, Humans, Physicians, Electronic Health Records, Patient Safety
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
