Evidence map›Paper›PMID 38152074›Full record

ReviewClinical interventions in aging2023

Use of Electronic Medical Records (EMR) in Gerontology: Benefits, Considerations and a Promising Future.

Adam Bednorz, Jonathan K L Mak, Juulia Jylhävä, Dorota Religa

Abstract readReview
In one paragraph

Review in Clinical interventions in aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Machine learning prediction of survival in centenarians after age 100: a retrospective, population-based cohort study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Artificial intelligence: Revolutionizing pediatric emergency care - A narrative review.International journal of critical illness and injury science
    Review
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

4 authors.

Adam BednorzJohn Paul II Geriatric Hospital, Katowice, Poland.ORCID 0009-0006-7672-3039
Jonathan K L MakDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-4454-8580
Juulia JylhäväDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Dorota ReligaDivision of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-4583-4570

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic medical records (EMRs) have many benefits in clinical research in gerontology, enabling data analysis, development of prognostic tools and disease risk prediction. EMRs also offer a range of advantages in clinical practice, such as comprehensive medical records, streamlined communication with healthcare providers, remote data access, and rapid retrieval of test results, ultimately leading to increased efficiency, enhanced patient safety, and improved quality of care in gerontology, which includes benefits like reduced medication use and better patient history taking and physical examination assessments. The use of artificial intelligence (AI) and machine learning (ML) approaches on EMRs can further improve disease diagnosis, symptom classification, and support clinical decision-making. However, there are also challenges related to data quality, data entry errors, as well as the ethics and safety of using AI in healthcare. This article discusses the future of EMRs in gerontology and the application of AI and ML in clinical research. Ethical and legal issues surrounding data sharing and the need for healthcare professionals to critically evaluate and integrate these technologies are also emphasized. The article concludes by discussing the challenges related to the use of EMRs in research as well as in their primary intended use, the daily clinical practice.

Indexed as

Electronic Health RecordsGeriatricsArtificial IntelligenceClinical Decision-MakingDelivery of Health CareHumansagingartificial intelligenceelectronic medical recordsgeriatricsgerontology

Identifiers

PMID38152074
PMCPMC10752027

What OpenQuestion holds

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LicenceCC BY-NC
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 OpenQuestion graph.