Evidence map›Paper›PMID 25670750›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2015

Harmonizing and extending standards from a domain-specific and bottom-up approach: an example from development through use in clinical applications.

Marcelline R Harris, Laura Heermann Langford, Holly Miller, Mary Hook, Patricia C Dykes, Susan A Matney

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
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

18 citing papers in PubMed, 36 citations in OpenAlex.

  1. The case for expressing nursing theories using ontologies.Journal of the American Medical Informatics Association : JAMIA · 2023
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  7. Automatic population of eMeasurements from EHR systems for inpatient falls.Journal of the American Medical Informatics Association : JAMIA · 2018
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  9. Observational
  10. Modeling Flowsheet Data to Support Secondary Use.Computers, informatics, nursing : CIN · 2017
    Observational
  11. Article
  12. Article
  13. Expanding Interprofessional EHR Data in i2b2.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016
    Article
  14. Article
  15. CKD as a Model for Improving Chronic Disease Care through Electronic Health Records.Clinical journal of the American Society of Nephrology : CJASN · 2015
    Article
  16. Article
  17. Review
  18. AMIA--Setting the Standard.Journal of the American Medical Informatics Association : JAMIA · 2015
    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 at 5 institutions in 1 country.

Marcelline R HarrisDepartment of Systems Leadership and Effectiveness Science, School of Nursing, University of Michigan, Ann Arbor, MI, USA mrhrrs@umich.edu.
Laura Heermann LangfordHomer Warner Center for Informatics Research, Intermountain Healthcare, Salt Lake City, UT, USA.
Holly MillerTerminology Division, Knowledge Based Systems, Veterans Health Administration Office of Informatics and Analytics, Salt Lake City, UT, USA.
Mary HookKnowledge-Based Nursing Department, Aurora Health System, Milwaukee, WI, USA.
Patricia C DykesCenter for Nursing Excellence, Harvard Medical School, Boston, MA, USA.
Susan A Matney3M Health Information Systems, Murray, UT, USA.
Aurora Health Care · USHarvard University · USIntermountain Healthcare · USKnowledge Based Systems (United States) · USUniversity of Michigan–Ann Arbor · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCurrently, the processes for harmonizing and extending standards by leveraging the knowledge within local documentation artifacts are not well described. We describe a collaborative project to develop common information models, terminology bindings, and term definitions based on nursing documentation systems, and carry the findings through to the adoption in standards development organizations (SDOs) and technical implementations in clinical applications. MATERIALS AND

methodsNursing flowsheet documents from six large organizations were analyzed to generate a common information model and terminologies that fully expressed documentation across all systems, and were sufficient for evidence-based decision support, reporting, and analysis.

resultsSignificant gaps in existing standards were identified. The models and terminologies were submitted to and incorporated by SDOs, are published, implemented, and now serving as a foundation for an eMeasure. DISCUSSION: There are few examples in the literature of success working through the standards development process from a bottom-up perspective. Subsequently, standards do not yet fully address the need for detailed clinical data that enables, for example, decision support as well as a range of reporting and analytic requirements. Recommendations from this project include transparent processes within SDOs, registries that make models and associated terminologies freely available, and coordinated governance processes.

conclusionWe demonstrated the feasibility of using documentation artifacts in a bottom-up approach to develop common models and sets of terms that are complete from the perspective of clinical implementation. Importantly, we demonstrated a process by which a community of practice can contribute to closing gaps in existing standards using SDO processes.

Indexed as

DocumentationHealth Level SevenLogical Observation Identifiers Names and CodesModels, TheoreticalNursing RecordsSystematized Nomenclature of MedicineharmonizationHL7LOINCSNOMED CTstandards

Identifiers

PMID25670750
PMCPMC11737593
OpenAlexW2163052755

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.