Evidence map›Paper›PMID 30727002›Full record

ArticleApplied clinical informatics2019

Lessons Learned in Creating Interoperable Fast Healthcare Interoperability Resources Profiles for Large-Scale Public Health Programs.

Susan A Matney, Bret Heale, Steve Hasley, Emily Decker, Brittni Frederiksen, Nathan Davis, Patrick Langford, Nadia Ramey, Stanley M Huff

Abstract read
In one paragraph

Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Usability Evaluation of the RevisedChildren (Basel, Switzerland) · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. HL7 FHIR-based tools and initiatives to support clinical research: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  9. Article
  10. Article
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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

9 authors.

Susan A MatneyDepartment of Biomedical Informatics, Intermountain Healthcare, Murray, Utah, United States.
Bret HealeDepartment of Biomedical Informatics, Intermountain Healthcare, Murray, Utah, United States.
Steve HasleyAmerican College of Obstetricians and Gynecologists, Washington, District of Columbia, United States.
Emily DeckerU.S. Department of Health and Human Services, Office of the Assistant Secretary for Health, Office of Population Affairs, Rockville, Maryland, United States.
Brittni FrederiksenU.S. Department of Health and Human Services, Office of the Assistant Secretary for Health, Office of Population Affairs, Rockville, Maryland, United States.
Nathan DavisDepartment of Biomedical Informatics, Intermountain Healthcare, Murray, Utah, United States.
Patrick LangfordDepartment of Biomedical Informatics, Intermountain Healthcare, Murray, Utah, United States.
Nadia RameyAmerican College of Obstetricians and Gynecologists, Washington, District of Columbia, United States.
Stanley M HuffDepartment of Biomedical Informatics, Intermountain Healthcare, Murray, Utah, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis article describes lessons learned from the collaborative creation of logical models and standard Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) profiles for family planning and reproductive health. The National Health Service delivery program will use the FHIR profiles to improve federal reporting, program monitoring, and quality improvement efforts. MATERIALS AND

methodsOrganizational frameworks, work processes, and artifact testing to create FHIR profiles are described.

resultsLogical models and FHIR profiles for the Family Planning Annual Report 2.0 dataset have been created and validated. DISCUSSION: Using clinical element models and FHIR to meet the needs of a real-world use case has been accomplished but has also demonstrated the need for additional tooling, terminology services, and application sandbox development.

conclusionFHIR profiles may reduce the administrative burden for the reporting of federally mandated program data.

Indexed as

Health Information InteroperabilityPublic HealthHumansIntersectoral CollaborationReference StandardsReproductive HealthTime Factors

Identifiers

PMID30727002
PMCPMC6365290

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.