Evidence map›Paper›PMID 37079268›Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2023

A Randomised Control Trial to Explore the Impact and Efficacy of the Healum Collaborative Care Planning Software and App on Condition Management in the Type 2 Diabetes Mellitus Population in NHS Primary Care.

Adrian H Heald, Sarah Roberts, Lucia Albeda Gimeno, Erin Gilingham, Morwenna James, Alison White, Anuj Saboo, Laura Beresford, Alan Crofts, Jonathan Abraham

Abstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 2 pooled it
–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

2 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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.

Adrian H HealdDepartment of Diabetes and Endocrinology, Salford Royal Hospital, Salford, UK. adrian.heald@manchester.ac.uk.
Sarah RobertsHealum Ltd, London, UK.
Lucia Albeda GimenoHealum Ltd, London, UK.
Erin GilinghamPark Lane Surgery, Waters Green Medical Centre, Macclesfield, UK.
Morwenna JamesMiddlewood Partnership, Bollington, Cheshire, UK.
Alison WhiteMiddlewood Partnership, Bollington, Cheshire, UK.
Anuj SabooHealum Ltd, London, UK.
Laura BeresfordMiddlewood Partnership, Bollington, Cheshire, UK.
Alan CroftsAlan Crofts Evaluation, Southport, UK.
Jonathan AbrahamHealum Ltd, London, UK.

Funding

Innovate UK 27744
6 · The paper itself

Abstract

introductionEffective and scalable solutions to support management of Type 2 Diabetes (T2D) at a distance are a priority for health systems worldwide. The use of personalised care planning has been shown to be effective at improving the health outcomes and the experience of care amongst people with T2D and other long-term health conditions. Here we describe a specific example of such an intervention.

methodsThe sample comprised 197 participants with T2D randomised to either the active intervention group with digital health planning (App + usual care), with 115 participants, or the control group (usual care), with 82 participants. We analysed data in relation to changes in body mass index (BMI) and glycated haemoglobin (HbA1c) over a 6-month follow-up period. We also analysed responses to questionnaires sent out and held interviews with participants that were in the active treatment group and therefore had a care plan created and access to an app.

resultsThe active treatment group had significant reductions in HbA1c (p < 0.01) and BMI (p < 0.037) vs the control group (no significant change). The average percentage change in HbA1c for the treatment group over 6 months was - 7.4% (± SE 1.4%), compared with 1.8% (± SE 2.1%) for the control group. The average percentage change in BMI for the treatment group was - 0.7% (± SE 0.4%) and it was - 0.2% (± SE 0.5%) for the control group. A higher percentage of the active treatment group reduced their HbA1c and BMI than the control group. For HbA1c, 72.4% of the active treatment group reduced their HbA1c, compared to 41.5% of the control group. For BMI, 52.7% of the active treatment group experienced a reduction, compared to 42.9% for the control group. Self-measured quality of life (QoL) improved for patients in the active treatment group, shown by an increase in their pre-trial to post-trial EQ-5D-5L rating by an average of 0.0464 (± SE 0.0625), compared to a decrease of 0.0086 (± SE 0.0530) for the control group. The average EQ VAS score also increased pre- to post-trial for the active treatment group, on average by 8.2%, whereas it decreased by an  average of - 2.8% for the control group.

conclusionThese findings point to how the provision of personalised plans of care, support and education linked to a mobile app, can result in HbA1c and BMI reduction for many individuals with T2D. The use of a patient management app as well as a personalised care plan also led to an improvement in patient self-rated QoL and engagement.

Indexed as

Digital care planningHbA1cType 2 diabetes

Identifiers

PMID37079268
PMCPMC10116475

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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.