Evidence map›Paper›PMID 38607672›Full record

ArticleJMIR medical informatics2024

Impact of Electronic Health Record Use on Cognitive Load and Burnout Among Clinicians: Narrative Review.

Elham Asgari, Japsimar Kaur, Gani Nuredini, Jasmine Balloch, Andrew M Taylor, Neil Sebire, Robert Robinson, Catherine Peters, Shankar Sridharan, Dominic Pimenta

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 1 pooled it
50.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

65 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Observational
  13. Digital Transformation in Health Care: Are We on the Right Track?Journal of medical Internet research · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 2 countries.

Elham AsgariGuy's and St Thomas' NHS Trust, London, United Kingdom.ORCID https://orcid.org/0000-0002-5692-0784
Japsimar KaurManchester University NHS Foundation Trust, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-0082-5868
Gani NurediniBarts Health NHS Trust, London, United Kingdom.ORCID https://orcid.org/0000-0001-5971-9843
Jasmine BallochTortus AI, London, United Kingdom.ORCID https://orcid.org/0009-0004-2322-1356
Andrew M TaylorGreat Ormond Street Hospital, London, United Kingdom.ORCID https://orcid.org/0000-0003-4194-7113
Neil SebireGreat Ormond Street Hospital, London, United Kingdom.ORCID https://orcid.org/0000-0001-5348-9063
Robert RobinsonGreat Ormond Street Hospital, London, United Kingdom.ORCID https://orcid.org/0000-0002-9817-7538
Catherine PetersGreat Ormond Street Hospital, London, United Kingdom.ORCID https://orcid.org/0000-0003-1423-3529
Shankar SridharanGreat Ormond Street Hospital, London, United Kingdom.ORCID https://orcid.org/0000-0002-3159-8557
Dominic PimentaTortus AI, London, United Kingdom.ORCID https://orcid.org/0000-0002-3179-7249
Great Ormond Street Hospital · GBNicolaus Copernicus University · PLBarts Health NHS Trust · GBGuy's and St Thomas' NHS Foundation Trust · GBManchester University NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cognitive load theory suggests that completing a task relies on the interplay between sensory input, working memory, and long-term memory. Cognitive overload occurs when the working memory's limited capacity is exceeded due to excessive information processing. In health care, clinicians face increasing cognitive load as the complexity of patient care has risen, leading to potential burnout. Electronic health records (EHRs) have become a common feature in modern health care, offering improved access to data and the ability to provide better patient care. They have been added to the electronic ecosystem alongside emails and other resources, such as guidelines and literature searches. Concerns have arisen in recent years that despite many benefits, the use of EHRs may lead to cognitive overload, which can impact the performance and well-being of clinicians. We aimed to review the impact of EHR use on cognitive load and how it correlates with physician burnout. Additionally, we wanted to identify potential strategies recommended in the literature that could be implemented to decrease the cognitive burden associated with the use of EHRs, with the goal of reducing clinician burnout. Using a comprehensive literature review on the topic, we have explored the link between EHR use, cognitive load, and burnout among health care professionals. We have also noted key factors that can help reduce EHR-related cognitive load, which may help reduce clinician burnout. The research findings suggest that inadequate efforts to present large amounts of clinical data to users in a manner that allows the user to control the cognitive burden in the EHR and the complexity of the user interfaces, thus adding more "work" to tasks, can lead to cognitive overload and burnout; this calls for strategies to mitigate these effects. Several factors, such as the presentation of information in the EHR, the specialty, the health care setting, and the time spent completing documentation and navigating systems, can contribute to this excess cognitive load and result in burnout. Potential strategies to mitigate this might include improving user interfaces, streamlining information, and reducing documentation burden requirements for clinicians. New technologies may facilitate these strategies. The review highlights the importance of addressing cognitive overload as one of the unintended consequences of EHR adoption and potential strategies for mitigation, identifying gaps in the current literature that require further exploration.

Indexed as

burnoutcliniciancognitive loadelectronic health recordtechnology

Identifiers

PMID38607672
PMCPMC11053390
OpenAlexW4392668324

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.