Evidence map›Paper›PMID 35670870›Full record

ReviewJournal of medical systems2022

Rebooting the Electronic Health Record.

Erik J Zhang, Heng Tan, Joseph A Sanford, James D Michelson, Brian M Waldschmidt, Mitchell H Tsai

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of medical systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Observational
  2. Article
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

6 authors.

Erik J ZhangUniversity of Vermont Larner College of Medicine, 89 Beaumont Avenue, 05405-0068, Burlington, VT, U.S.. erik.zhang@med.uvm.edu.ORCID http://orcid.org/0000-0002-7812-3479
Heng TanDepartment of Medicine, Division of Internal Medicine, University of Miami, Miami, FL, U.S.
Joseph A SanfordUniversity of Arkansas for Medical Sciences, Fayetteville, AR, U.S.
James D MichelsonDepartment of Orthopaedics and Rehabilitation, University of Vermont Larner College of Medicine, Burlington, VT, U.S.
Brian M WaldschmidtDepartment of Anesthesiology, University of Vermont Larner College of Medicine, Burlington, VT, U.S.
Mitchell H TsaiDepartment of Anesthesiology, Department of Orthopaedics and Rehabilitation (by courtesy), Department of Surgery (by courtesy), University of Vermont Larner College of Medicine, Burlington, VT, U.S.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Justifications for the widespread adoption and integration of an electronic health record (EHR) have long leaned on the purported benefits of the technology. However, the performance of the EHR has been underwhelming relative to the promises of immediate access to relevant patient information, clinical decision supports, computerized ordering, and transferable patient data. In this narrative review, we provide an overview of the historical problems and limitations of the EHR, detail the core principles that define agile processes that may overcome the barriers faced by the current EHR, and re-imagine what an integrated, seamless EHR that serves its users and patients might look like. Moving forward, the EHR should be redesigned using a middle-out framework and empowering dual-type champions to maintain the sustainable diffusion of future innovations.

Indexed as

Electronic Health RecordsHumansAgile developmentDual-type championEHR adoptionElectronic Health RecordMachine learning

Identifiers

PMID35670870

What OpenQuestion holds

Textmetadata
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.