Evidence map›Paper›PMID 39957319›Full record

ArticleDiabetic medicine : a journal of the British Diabetic Association2025

DEKODE-A cloud-based performance feedback model improved DKA care across multiple hospitals in the UK.

Lakshmi N Rengarajan, Catherine Cooper, Kashish Malhotra, Angelica Sharma, Nevil Philip, Anu Ann Abraham, Ketan Dhatariya, Parth Narendran, Punith Kempegowda, DEKODE and DEVI Group

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetic medicine : a journal of the British Diabetic Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Observational
  7. DEKODE-A cloud-based performance feedback model improved DKA care across multiple hospitals in the UK.Diabetic medicine : a journal of the British Diabetic Association · 2025
    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

10 authors.

Lakshmi N RengarajanDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Catherine CooperWalsall Manor Hospital, The Walsall Healthcare NHS Trust, Walsall, UK.
Kashish MalhotraDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.ORCID https://orcid.org/0000-0002-6985-5731
Angelica SharmaDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Nevil PhilipDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Anu Ann AbrahamDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
Ketan DhatariyaNorfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK.ORCID https://orcid.org/0000-0003-3619-9579
Parth NarendranQueen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.ORCID https://orcid.org/0000-0002-4583-8793
Punith KempegowdaDepartment of Applied Health Sciences, University of Birmingham, Birmingham, UK.
DEKODE and DEVI Group

Funding

National Institute for Health and Care Research
6 · The paper itself

Abstract

aimA current gap in Diabetes-related ketoacidosis (DKA) research is understanding the factors contributing to variations in care and outcomes between people admitted with DKA. We aimed to create a system to facilitate gathering data on DKA management across multiple centres and identify trends in complications and outcomes associated with DKA. RESEARCH DESIGN AND

methodsBetween January 2020 and December 2022, we set up a cloud-based Quality improvement project (QIP) that provided regular feedback to 11 hospitals in the United Kingdom (UK).

resultsOf the 1977 episodes, we observed an increase in adherence in fluid prescription in hospitals C, D, E, F and G (C- 23% vs. 75% p = <0.001; D- 27% vs. 60%, p = <0.001; E- 17 vs. 79% p = <0.001; F- 16% vs. 57%, p = <0.001; G- 36% vs. 75% p = <0.001). Notable improvements in adherence to glucose monitoring were observed in hospitals B, D, and G (B- 11 vs. 38% p = <0.001; D- 36% vs. 56%, p = 0.05; G- 22% vs. 67% p = <0.001). Although we didn't observe significant changes in complications and outcomes among participating hospitals from the start to the end of the reported period, notable fluctuations were evident across quarters. These variations were relayed to the respective hospitals, underscoring how feedback and interventions could influence the care provided. This initiative also marks the initial move towards establishing and improving data collection practices in acute diabetes.

conclusionsWe demonstrate a sustainable QIP that improves adherence to national guidelines in some indicators for DKA care and serves as an early warning system to identify adverse trends.

Indexed as

Cloud ComputingDiabetic KetoacidosisHospitalsQuality ImprovementFeedbackFemaleGuideline AdherenceHumansMaleUnited Kingdomadherence to guidelinesdiabetic ketoacidosisglucose monitoringhealth equityquality improvement project

Identifiers

PMID39957319
PMCPMC12080979

What OpenQuestion holds

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Registered trials

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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.