Evidence map›Paper›PMID 38336467›Full record

ArticleBMJ sexual & reproductive health2024

Preconception health risk factors documented in general practice electronic medical records.

Nishadi Nethmini Withanage, Jessica R Botfield, Kirsten Black, Danielle Mazza

Abstract read
In one paragraph

Article in BMJ sexual & reproductive health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

4 authors.

Nishadi Nethmini WithanageSPHERE, NHMRC Centre of Research Excellence, Department of General Practice, Monash University, Melbourne, Victoria, Australia nishadi.withanage@monash.edu.ORCID http://orcid.org/0000-0003-4904-0372
Jessica R BotfieldSPHERE, NHMRC Centre of Research Excellence, Department of General Practice, Monash University, Melbourne, Victoria, Australia.ORCID http://orcid.org/0000-0001-6157-9739
Kirsten BlackSPHERE, NHMRC Centre of Research Excellence, Department of General Practice, Monash University, Melbourne, Victoria, Australia.ORCID http://orcid.org/0000-0003-0030-2431
Danielle MazzaSPHERE, NHMRC Centre of Research Excellence, Department of General Practice, Monash University, Melbourne, Victoria, Australia.ORCID http://orcid.org/0000-0001-6158-7376

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDocumenting medical and lifestyle preconception health risk factors in electronic medical records (EMRs) could assist general practitioners (GPs) to identify those reproductive-aged women who could most benefit from preconception care (PCC). However, it is unclear to what extent PCC risk factors are identifiable in general practice records. This study aimed to determine the extent to which medical and lifestyle preconception health risk factors are documented in general practice EMRs.

methodsWe conducted an audit of the documentation of medical and lifestyle preconception risk factors in 10 general practice EMRs in Melbourne, Australia. We retrospectively analysed the EMRs of 100 consecutive women aged 18-44 years who visited each practice between January and September 2022. Using a template informed by PCC guidelines, we extracted data from structured fields in the EMR and conducted a descriptive analysis.

resultsAmong the data extracted, the more commonly documented medical and lifestyle preconception health risk factors in the EMRs included smoking (79%), blood pressure (74%), alcohol consumption (63%) and body mass index (57%). Among the women audited, 14% were smokers, 24% were obese, 7% had high blood pressure, 5% had diabetes, 28% had a mental health condition, 13% had asthma, 6% had thyroid disease and 17% had been prescribed and could be using a potentially teratogenic medication.

conclusionsBetter documentation of medical and lifestyle preconception health risk factors in structured fields in EMRs may potentially assist primary care providers including GPs in identifying and providing PCC to women who could most benefit from it.

Indexed as

Electronic Health RecordsGeneral PracticePreconception CareAdolescentAdultAlcohol DrinkingAustraliaDocumentationFemaleHumansLife StyleRetrospective StudiesRisk FactorsSmokingYoung AdultCounselinggeneral practiceReproductive HealthReproductive Health ServicesSexual Health

Identifiers

PMID38336467
PMCPMC11287648

What Socratic holds

Textmetadata
LicenceCC BY-NC
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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 Socratic graph.