Evidence map›Paper›PMID 15829475›Full record

ArticleJournal of medical Internet research2005

The emergence of national electronic health record architectures in the United States and Australia: models, costs, and questions.

Tracy D Gunter, Nicolas P Terry

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 3 pooled it
–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

75 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Personal Health Records: A Systematic Literature Review.Journal of medical Internet research · 2017
    Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Review
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  9. Article
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  12. MedComm · 2025
    Article
  13. EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Digital health, digital medicine, and digital therapeutics in cardiology: current evidence and future perspective in Japan.Hypertension research : official journal of the Japanese Society of Hypertension · 2023
    Review
  20. Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Tracy D GunterDepartment of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, USA.
Nicolas P Terry

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging electronic health record models present numerous challenges to health care systems, physicians, and regulators. This article provides explanation of some of the reasons driving the development of the electronic health record, describes two national electronic health record models (currently developing in the United States and Australia) and one distributed, personal model. The US and Australian models are contrasted in their different architectures ("pull" versus "push") and their different approaches to patient autonomy, privacy, and confidentiality. The article also discusses some of the professional, practical, and legal challenges that health care providers potentially face both during and after electronic health record implementation.

Indexed as

ConfidentialityMedical Records Systems, ComputerizedAustraliaCosts and Cost AnalysisDelivery of Health CareHealth PolicyHumansMedical ErrorsMedical Record LinkageUnited States

Identifiers

PMID15829475
PMCPMC1550638

What OpenQuestion 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 OpenQuestion graph.