Evidence map›Paper›PMID 23646084›Full record

ArticleApplied clinical informatics2012

Transitioning from a legacy EHR to a commercial, vendor-supplied, EHR: one academic health system's experience.

A Gettinger, A Csatari

Abstract read
In one paragraph

Article in Applied clinical informatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Electronic Health Record (EHR) Abstraction.Perspectives in health information managemen · 2021
    Article
  8. Article
  9. Implications of electronic health record transition on drug allergy labels.The journal of allergy and clinical immunology. In practice · 2020
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. A rational approach to legacy data validation when transitioning between electronic health record systems.Journal of the American Medical Informatics Association : JAMIA · 2016
    Article
  16. Observational
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

2 authors.

A GettingerDepartment of Pediatrics, Hospital for Special Surgery.
A Csatari

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDescribe the planning, decisions, and implementation results experienced during the large-scale transition from one EHR to another throughout a large academic health system, which occurred simultaneously throughout both in-patient and all ambulatory settings.

methodsReview of internal decision-making documents, interviews with key participants, and data from conversion software.

resultsOver 7,000 unique users caring for a population of more than 1.2 million patients in both inpatient and outpatient venues and distributed across two states were successfully transitioned to a new EHR simultaneously. Challenges in data conversion were encountered resulting in more work for end-users than desired or anticipated. Users continued to access older information (principally schedules) in the legacy EHR one year later.

conclusionData conversion from one EHR to another can be unsuccessful due to differences in how EHR's structure data obtained from underlying feeder applications or databases. Abstraction of only the pertinent clinical content is difficult in the context of transitioning to a new EHR. Clinicians require facile access to legacy content that can be achieved by implanting CCOW compliant solutions.

Indexed as

CommerceHealth FacilitiesAcademic Medical CentersDocumentationElectronic Health RecordsHumansCCOWElectronic Health Record (EHR)enterprise conversionlegacy systemsmedical record conversion

Identifiers

PMID23646084
PMCPMC3613040

What OpenQuestion holds

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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.