Evidence map›Paper›PMID 31805928›Full record

ArticleBMC medicine2019

The quality of preventive care for pre-school aged children in Australian general practice.

Louise K Wiles, Carl de Wet, Chris Dalton, Elisabeth Murphy, Mark F Harris, Peter D Hibbert, Charlotte J Molloy, Gaston Arnolda, Hsuen P Ting, Jeffrey Braithwaite and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Louise K WilesAustralian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia.
Carl de WetHealthcare Improvement Unit, Clinical Excellence Division, Queensland Health, Brisbane, QLD, Australia.
Chris DaltonBupa ANZ, Sydney, NSW, Australia.
Elisabeth MurphyNew South Wales Ministry of Health, North Sydney, Sydney, NSW, Australia.
Mark F HarrisCentre for Primary Health Care and Equity, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
Peter D HibbertAustralian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia.
Charlotte J MolloyAustralian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia.
Gaston ArnoldaAustralian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia.
Hsuen P TingAustralian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia.
Jeffrey BraithwaiteAustralian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia. jeffrey.braithwaite@mq.edu.au.ORCID 0000-0003-0296-4957
CareTrack Kids Investigative Team

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVariable and poor care quality are important causes of preventable patient harm. Many patients receive less than recommended care, but the extent of the problem remains largely unknown. The CareTrack Kids (CTK) research programme sought to address this evidence gap by developing a set of indicators to measure the quality of care for common paediatric conditions. In this study, we focus on one clinical area, 'preventive care' for pre-school aged children. Our objectives were two-fold: (i) develop and validate preventive care quality indicators and (ii) apply them in general medical practice to measure adherence.

methodsClinical experts (n = 6) developed indicator questions (IQs) from clinical practice guideline (CPG) recommendations using a multi-stage modified Delphi process, which were pilot tested in general practice. The medical records of Australian children (n = 976) from general practices (n = 80) in Queensland, New South Wales and South Australia identified as having a consultation for one of 17 CTK conditions of interest were retrospectively reviewed by trained paediatric nurses. Statistical analyses were performed to estimate percentage compliance and its 95% confidence intervals.

resultsIQs (n = 43) and eight care 'bundles' were developed and validated. Care was delivered in line with the IQs in 43.3% of eligible healthcare encounters (95% CI 30.5-56.7). The bundles of care with the highest compliance were 'immunisation' (80.1%, 95% CI 65.7-90.4), 'anthropometric measurements' (52.7%, 95% CI 35.6-69.4) and 'nutrition assessments' (38.5%, 95% CI 24.3-54.3), and lowest for 'visual assessment' (17.9%, 95% CI 8.2-31.9), 'musculoskeletal examinations' (24.4%, 95% CI 13.1-39.1) and 'cardiovascular examinations' (30.9%, 95% CI 12.3-55.5).

conclusionsThis study is the first known attempt to develop specific preventive care quality indicators and measure their delivery to Australian children in general practice. Our findings that preventive care is not reliably delivered to all Australian children and that there is substantial variation in adherence with the IQs provide a starting point for clinicians, researchers and policy makers when considering how the gap between recommended and actual care may be narrowed. The findings may also help inform the development of specific improvement interventions, incentives and national standards.

Indexed as

AustraliaChild Health ServicesChild, PreschoolGeneral PracticeHumansInfantPreventive MedicineQuality of Health CareRetrospective StudiesGeneral practiceMedical recordsPaediatricsPreventive medicineProcess assessment (healthcare)Quality of healthcare

Identifiers

PMID31805928
PMCPMC6896286

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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.