Evidence map›Paper›PMID 37562854›Full record

ArticleBMJ health & care informatics2023

Experiences in aligning WHO SMART guidelines to classification and terminology standards.

Filippa Pretty, Tigest Tamrat, Natschja Ratanaprayul, Maria Barreix, Nenad Friedrich Ivan Kostanjsek, Mary-Lyn Gaffield, Jenny Thompson, Bryn Rhodes, Robert Jakob, Garrett Livingston Mehl and 1 more

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

11 authors.

Filippa PrettyMetadata, Information Management & Classifications Unit, Australian Institute of Health and Welfare, Canberra, Australian Capital Territory, Australia.
Tigest TamratUNDP/UNFPA/UNICEF/World Bank Special Program of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland tamratt@who.int.ORCID http://orcid.org/0000-0001-8579-5698
Natschja RatanaprayulDepartment of Digital Health and Innovations, World Health Organization, Geneva, Switzerland.ORCID http://orcid.org/0000-0003-0085-2900
Maria BarreixUNDP/UNFPA/UNICEF/World Bank Special Program of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland.ORCID http://orcid.org/0000-0003-3613-9672
Nenad Friedrich Ivan KostanjsekDepartment of Data and Analytics, World Health Organization, Geneva, Switzerland.
Mary-Lyn GaffieldUNDP/UNFPA/UNICEF/World Bank Special Program of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland.
Jenny ThompsonPATH, Seattle, Washington, USA.ORCID http://orcid.org/0000-0003-1125-6434
Bryn RhodesAlphora, Salt Lake City, Utah, USA.
Robert JakobDepartment of Data and Analytics, World Health Organization, Geneva, Switzerland.
Garrett Livingston MehlDepartment of Digital Health and Innovations, World Health Organization, Geneva, Switzerland.
Özge TunçalpUNDP/UNFPA/UNICEF/World Bank Special Program of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

objectivesDigital adaptation kits (DAKs) distill WHO guidelines for digital use by representing them as workflows, data dictionaries and decision support tables. This paper aims to highlight key lessons learnt in coding data elements of the antenatal care (ANC) and family planning DAKs to standardised classifications and terminologies (CATs).

methodsWe encoded data elements within the ANC and family planning DAKs to standardised CATs from the WHO CATs and other freely available CATs.

resultsThe coding process demonstrated approaches to refine the data dictionaries and enhance alignment between data elements and CATs. DISCUSSION: Applying CATs to WHO clinical and public health guidelines can ensure that recommendations are operationalised in a digital system with appropriate consistency and clarity. This requires a multidisciplinary team and careful review to achieve conceptual equivalence between data elements and standardised terminologies.

conclusionThe systematic translation of guidelines into digital systems provides an opportunity for leveraging CATs; however, this approach needs further exploration into its implementation in country contexts and transition into machine-readable components.

Indexed as

Prenatal CareFemaleHumansPregnancyWorld Health Organizationdata systemsdecision support systemsdelivery of health careinformaticsmedical records

Identifiers

PMID37562854
PMCPMC10439311

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.