Evidence map›Paper›PMID 41985966›Full record

ArticleBMJ open2026

Implementation of a comprehensive template to support personalised care for people with multiple long-term conditions: a mixed-methods evaluation in primary care.

Rachel Johnson, Andrew Turner, Clare Jinks, Mari Carmen Portillo, Caroline Michaela Coope, Alice Louise Moult, Kate Alice Lippiett, Dereth June Baker, Cindy Mann, Lauren J Scott and 6 more

Abstract read
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Rachel JohnsonBristol Medical School, University of Bristol, Bristol, England, UK rachel.johnson@bristol.ac.uk.ORCID http://orcid.org/0000-0003-0266-3433
Andrew TurnerBristol Medical School, University of Bristol, Bristol, England, UK.ORCID http://orcid.org/0000-0002-7121-3121
Clare JinksSchool of Medicine, Keele University, Keele, UK.
Mari Carmen PortilloFaculty of Health Sciences, University of Southampton, Southampton, UK.
Caroline Michaela CoopeBristol Medical School, University of Bristol, Bristol, England, UK.ORCID http://orcid.org/0000-0001-7803-8760
Alice Louise MoultKeele University, Newcastle-under-Lyme, UK.
Kate Alice LippiettFaculty of Health Sciences, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0003-2626-498X
Dereth June BakerSchool of Medicine, Keele University, Newcastle-under-Lyme, UK.
Cindy MannBristol Medical School, University of Bristol, Bristol, England, UK.ORCID http://orcid.org/0000-0002-1256-1820
Lauren J ScottBristol Medical School, University of Bristol, Bristol, England, UK.ORCID http://orcid.org/0000-0003-3129-5123
Krysia DziedzicSchool of Medicine, Keele University, Keele, UK.
Zoe PaskinsSchool of Medicine, Keele University, Keele, UK.ORCID http://orcid.org/0000-0002-7783-2986
Richard ByngPeninsula Medical School, Plymouth University, Plymouth, UK.
Simon ChilcottBristol Medical School, University of Bristol, Bristol, England, UK.
Grace ScrimgeourBristol Medical School, University of Bristol, Bristol, England, UK.
Chris SalisburyBristol Medical School, University of Bristol, Bristol, England, UK.ORCID http://orcid.org/0000-0002-4378-3960

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthcare services are mainly organised around single health conditions and need reconfiguration to meet the needs of people with multiple long-term conditions (multimorbidity). Typically, people are offered annual reviews for each of their long-term conditions separately. In a randomised controlled trial, a comprehensive computerised template based on a personalised care model increased the person-centredness of multimorbidity reviews in primary care, but there were implementation challenges. We sought to understand and address the challenges of implementing a template to support personalised primary care for people with multimorbidity (PP4M).

objectivesTo explore the extent of implementation and factors influencing uptake of the PP4M intervention. To understand factors influencing implementation and normalisation of the template.

designConvergent parallel mixed methods within a non-randomised hybrid implementation-effectiveness study. Normalisation Process Theory (NPT) informed design, data collection and analysis.

settingPrimary care (general practices) in three English regions.

participantsQuantitative: Patients aged 18 years or over and had at least three types of long-term conditions (routine data collection); staff involved in using the template in implementation practices (Normalisation MeAsure Development (NoMAD) questionnaire).Qualitative: Staff at implementation practices.

interventionA multimorbidity computerised template to support personalised annual reviews. NPT-informed implementation package delivered to implementation practices included: process mapping, software support and training. DATA COLLECTION: Routine medical record data; NoMAD questionnaires and qualitative interviews in implementation practices. PRIMARY/SECONDARY OUTCOMES: Measures of reach, fidelity, acceptability and sustainability. ANALYSIS: Quantitative data: descriptive statistics, logistic regression and difference-in-difference models. Qualitative data analysis conducted using NPT coding manual.

resultsIn practices that received an NPT-informed implementation package, use of the template increased more, across patients with a range of demographics and health conditions, than in those that did not receive the implementation package (OR 2.86 (95% CI 2.34 to 3.49)). The implementation package successfully triggered NPT processes of coherence and cognitive participation, and, to a lesser extent, collective action and reflexive monitoring. Contextual factors, including a lack of staff generalist skills and disease-specific incentives, impeded engagement and sustained implementation.

conclusionsFocusing on the processes of normalisation as mechanisms of implementation facilitated development of an implementation strategy with potential to trigger those mechanisms, but did not sufficiently address contextual factors. Implementation strategies to support personalised care must consider wider system and practice level contextual factors, such as incentives and staff training. TRAIL REGISTRATION NUMBER: https://doi.org/10.1186/ISRCTN40295449 (2022-08-03, retrospectively registered.).

Indexed as

MultimorbidityMultiple Chronic ConditionsPatient-Centered CarePrecision MedicinePrimary Health CareAdultAgedFemaleHumansMaleMiddle AgedQualitative ResearchSurveys and QuestionnairesDelivery of Health Care, IntegratedImplementation ScienceMultimorbidityPatient-Centered CarePrimary Health CareQUALITATIVE RESEARCH

Identifiers

PMID41985966
PMCPMC13084922

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.