Evidence map›Paper›PMID 33046472›Full record

ArticleBMJ open2020

Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation.

Craig Scowen, Nasir Wabe, Alex Eigenstetter, Robert Lindeman, Melissa Miao, Johanna I Westbrook, Andrew Georgiou

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2020. 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
0.6field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  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

7 authors at 3 institutions in 1 country.

Craig ScowenNSW Health Pathology, Sydney, New South Wales, Australia.
Nasir WabeCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, North Ryde, New South Wales, Australia nasir.wabe@mq.edu.au.ORCID 0000-0002-9740-6319
Alex EigenstetterNSW Health Pathology, Sydney, New South Wales, Australia.
Robert LindemanNSW Health Pathology, Sydney, New South Wales, Australia.
Melissa MiaoGraduate School of Health, University of Technology Sydney, Broadway, New South Wales, Australia.
Johanna I WestbrookCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, North Ryde, New South Wales, Australia.
Andrew GeorgiouCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, North Ryde, New South Wales, Australia.ORCID 0000-0002-7619-3668
Macquarie University · AUNew South Wales Department of Health · AUUniversity of Technology Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionVariation in test ordering is a major issue in Australia and globally with significant financial and clinical impacts. There is currently a lack of research identifying and remediating variation in the use of pathology tests in emergency departments (EDs). In 2019, NSW Health Pathology introduced the Pathology Atlas of Variation that uses a data-driven tool (the Atlas Analytical Model) to investigate test order variation across New South Wales (NSW) and engage with local health districts (LHDs) to reduce variation. The objectives of this study are to evaluate whether this data-driven approach is associated with: (1) a reduction in test order variation; (2) improvements in patient outcomes and (3) cost benefits, for the five most frequent ED presentations. METHODS AND ANALYSIS: This is a large multisite study including 45 major public hospitals across 15 LHDs in NSW, Australia. The Atlas Analytical Model is a data analytics and visualisation tool capable of providing analytical insights into variation in pathology investigations across NSW EDs, which will be used as feedback to inform LHDs efforts to reduce variation. Interrupted time series analyses using 2 years pre Atlas (2017-2018) and 2 years post Atlas (2021-2022) data will be conducted. Study data will be obtained by linking hospital and laboratory databases. Funnel plots will be used to identify EDs with outlying pathology test ordering practices. The outcome measures include changes in test ordering practices, ED length of stay, hospital admission and cost benefits (total pathology costs per ED encounter). ETHICS AND DISSEMINATION: The study has received ethical approval from the NSW Population and Health Service Research Ethics Committee (reference, 2019/ETH00184). The findings of the study will be published in peer-reviewed journals and disseminated via presentations at conferences. We will also engage directly with key stakeholders to disseminate the findings and to inform policies related to pathology testing in the ED.

Indexed as

Emergency Service, HospitalPathologyAdultAustraliaHospitals, PublicHumansNew South Waleshealth & safetyinternational health servicesprotocols & guidelines

Identifiers

PMID33046472
PMCPMC7552857
OpenAlexW3092003246

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.