Evidence map›Paper›PMID 26955505›Full record

ArticleJournal of pathology informatics2016

Implementation of Epic Beaker Clinical Pathology at an academic medical center.

Matthew D Krasowski, Joseph D Wilford, Wanita Howard, Susan K Dane, Scott R Davis, Nitin J Karandikar, John L Blau, Bradley A Ford

Abstract read
In one paragraph

Article in Journal of pathology informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Measuring the rate of manual transcription error in outpatient point-of-care testing.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

8 authors.

Matthew D KrasowskiDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Joseph D WilfordHealth Care Information Services, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Wanita HowardDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Susan K DaneDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Scott R DavisDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Nitin J KarandikarDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
John L BlauDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Bradley A FordDepartment of Pathology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpic Beaker Clinical Pathology (CP) is a relatively new laboratory information system (LIS) operating within the Epic suite of software applications. To date, there have not been any publications describing implementation of Beaker CP. In this report, we describe our experience in implementing Beaker CP version 2012 at a state academic medical center with a go-live of August 2014 and a subsequent upgrade to Beaker version 2014 in May 2015. The implementation of Beaker CP was concurrent with implementations of Epic modules for revenue cycle, patient scheduling, and patient registration.

methodsOur analysis covers approximately 3 years of time (2 years preimplementation of Beaker CP and roughly 1 year after) using data summarized from pre- and post-implementation meetings, debriefings, and the closure document for the project.

resultsWe summarize positive aspects of, and key factors leading to, a successful implementation of Beaker CP. The early inclusion of subject matter experts in the design and validation of Beaker workflows was very helpful. Since Beaker CP does not directly interface with laboratory instrumentation, the clinical laboratories spent extensive preimplementation effort establishing middleware interfaces. Immediate challenges postimplementation included bar code scanning and nursing adaptation to Beaker CP specimen collection. The most substantial changes in laboratory workflow occurred with microbiology orders. This posed a considerable challenge with microbiology orders from the operating rooms and required intensive interventions in the weeks following go-live. In postimplementation surveys, pathology staff, informatics staff, and end-users expressed satisfaction with the new LIS.

conclusionsBeaker CP can serve as an effective LIS for an academic medical center. Careful planning and preparation aid the transition to this LIS.

Indexed as

Clinical chemistryclinical laboratory information systemelectronic health recordshematologymedical informaticsmicrobiology

Identifiers

PMID26955505
PMCPMC4763507

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.