Evidence map›Paper›PMID 38414546›Full record

ArticleInternational journal of population data science2023

The practicalities of adapting UK maternity clinical information systems for observational research: Experiences of the POOL study.

Fiona Lugg-Widger, Christian Barlow, Rebecca Cannings-John, Chris Gale, Nicola Houlding, Rebecca Milton, Rachel Plachcinski, Michael Robling, Julia Sanders

Open access · goldAbstract read
In one paragraph

Article in International journal of population data science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

9 authors at 4 institutions in 2 countries.

Fiona Lugg-WidgerCentre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.
Christian BarlowCentre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.
Rebecca Cannings-JohnCentre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.
Chris GaleNeonatal Medicine, School of Public Health, Faculty of Medicine, Imperial College London, Chelsea and Westminster Hospital campus, London, SW10 9NH, UK.
Nicola HouldingWellbeing Software Group, i2 Mansfield, Hamilton Court, Oakham Business Park, Mansfield, NG18 5FB.
Rebecca MiltonCentre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.
Rachel PlachcinskiParent, patient and public representative, National Childbirth Trust [NCT], Brunel House, Clifton, Bristol BS8 3NG.
Michael RoblingCentre for Trials Research, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.
Julia SandersSchool of Healthcare Sciences, Cardiff University, Ty Dewi Sant, Heath Park, Cardiff. CF14 4YS, UK.
Cardiff University · GBChelsea and Westminster Hospital · GBMansfield University · USNational Childbirth Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Using routinely collected clinical data for observational research is an increasingly important method for data collection, especially when rare outcomes are being explored. The POOL study was commissioned to evaluate the safety of waterbirth in the UK using routine maternity and neonatal clinical data. This paper describes the design, rationale, set-up and pilot for this data linkage study using bespoke methods. Methods: Clinical maternity information systems hold many data items of value for research purposes, but often lack specific data items required for individual studies. This study used the novel method of amending an existing clinical maternity database for the purpose of collecting additional research data fields. In combination with the extraction of existing data fields, this maximised the potential use of existing routinely collected clinical data for research purposes, whilst reducing NHS staff data collection burden.Wellbeing Software Results: Twenty-six NHS sites were set-up over 27 months (January 2019 - April 2021). Twenty-four thousand maternity records were extracted from the one NHS site, pertaining to the period January 2015 to March 2019. Data field completeness for maternal and neonatal primary outcomes were mostly acceptable. Neonatal identifiers flowed to the National Neonatal Research Database for successful matching and linkage between maternity and neonatal unit records. Discussion: Piloting the data extraction and linkage highlighted the need for additional governance arrangements, training at NHS sites and new processes for the study team to ensure data quality and confidentiality are upheld during the study. Amending existing NHS electronic information systems and accessing clinical data at scale, is possible, but continues to be a time consuming and a technically challenging exercise.

Indexed as

Natural ChildbirthData AccuracyData CollectionFemaleHumansInfantInfant, NewbornInformation SystemsPregnancyUnited Kingdomclinical information systemsfeasibilityobservational researchroutine datawaterbirth

Identifiers

PMID38414546
PMCPMC10897763
OpenAlexW4385636806

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.