Evidence map›Paper›PMID 33371024›Full record

ArticleBMJ open2020

Future Health Today: codesign of an electronic chronic disease quality improvement tool for use in general practice using a service design approach.

Barbara Hunter, Ruby Biezen, Karyn Alexander, Natalie Lumsden, Christine Hallinan, Anna Wood, Rita McMorrow, Julia Jones, Craig Nelson, Jo-Anne Manski-Nankervis

Abstract 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 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  8. Consumer Involvement in the Design and Development of Medication Safety Interventions or Services in Primary Care: A Scoping Review.Health expectations : an international journal of public participation in health care and health policy · 2024
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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

10 authors.

Barbara HunterDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia barbara.hunter@unimelb.edu.au.ORCID 0000-0002-1268-3166
Ruby BiezenDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-1736-9675
Karyn AlexanderDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.
Natalie LumsdenDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.
Christine HallinanDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.
Anna WoodDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.
Rita McMorrowDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0002-2835-9504
Julia JonesDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.
Craig NelsonWestern Health Chronic Disease Alliance, Sunshine Hospital, Western Health, Footscray, Victoria, Australia.
Jo-Anne Manski-NankervisDepartment of General Practice, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-2153-3482

Funding

Pathways to Mental Health Services Among Native WomenK01MH002018 · NIMH · UNIVERSITY OF NEW MEXICO · PI DURAN, BONNIE M · 2001 to 2005
$667k
NIMH NIH HHS K01 MH002018
6 · The paper itself

Abstract

objectiveTo codesign an electronic chronic disease quality improvement tool for use in general practice.

designService design employing codesign strategies.

settingGeneral practice.

participantsSeventeen staff (general practitioners, nurses and practice managers) from general practice in metropolitan Melbourne and regional Victoria and five patients from metropolitan Melbourne.

interventionsCodesign sessions with general practice staff, using a service design approach, were conducted to explore key design criteria and functionality of the audit and feedback and clinical decision support tools. Think aloud interviews were conducted in which participants articulated their thoughts of the resulting Future Health Today (FHT) prototype as they used it. One codesign session was held with patients. Using inductive and deductive coding, content and thematic analyses explored the development of a new technological platform and factors influencing implementation of the platform.

resultsParticipants identified that the prototype needed to work within their existing workflow to facilitate automated patient recall and track patients with or at-risk of specific conditions. It needed to be simple, provide visual snapshots of information and easy access to relevant guidelines and facilitate quality improvement activities. Successful implementation may be supported by: accuracy of the algorithms in FHT and data held in the practice; the platform supporting planned and spontaneous interactions with patients; the ability to hide tools; links to Medicare Benefits Schedule; and prefilled management plans. Participating patients supported the use of the platform in general practice. They suggested that use of the platform demonstrates a high level of patient care and could increase patient confidence in health practitioners.

conclusionStudy participants worked together to design a platform that is clear, simple, accurate and useful and that sits within any given general practice setting. The resulting FHT platform is currently being piloted in general practices and will continue to be refined based on user feedback.

Indexed as

General PracticeQuality ImprovementAgedChronic DiseaseElectronicsHumansMedicareUnited Statesaudithealth informaticsprimary carequalitative researchquality in health care

Identifiers

PMID33371024
PMCPMC7751202

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.