Evidence map›Paper›PMID 37669810›Full record

ArticleBMJ open quality2023

Improving personalised care, through the development of a service evaluation tool to assess, understand and monitor delivery.

Louise Johnson, Hayden Kirk, Beth Clark, Stephanie Heath, Carolyn Royse, Carl Adams, Mari Carmen Portillo

Open access · goldAbstract read
In one paragraph

Article in BMJ open quality, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. A Patient Charter to Improve Care for Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025
    Review
  7. Article
  8. A Qualitative Exploration of the Role of Culturally Relevant Social Prescribing in Supporting Pakistani Carers Living in the UK.Health expectations : an international journal of public participation in health care and health policy · 2024
    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

7 authors at 2 institutions in 1 country.

Louise JohnsonSchool of Health Sciences, University of Southampton, Southampton, Hampshire, UK lj1b06@soton.ac.uk.ORCID 0000-0001-9445-0069
Hayden KirkAdult Services, Solent NHS Trust, Southampton, UK.
Beth ClarkSchool of Health Sciences, University of Southampton, Southampton, Hampshire, UK.
Stephanie HeathWessex Cancer Alliance, Southampton, UK.
Carolyn RoyseSchool of Health Sciences, University of Southampton, Southampton, Hampshire, UK.
Carl AdamsAcademy of Research and Improvement, Solent NHS Trust, Southampton, UK.
Mari Carmen PortilloSchool of Health Sciences, University of Southampton, Southampton, Hampshire, UK.
University of Southampton · GBSolent NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systematically implementing personalised care has far reaching benefits to individuals, communities and health and social care systems. If done well, personalised care can result in better health outcomes and experiences, more efficient use of health services and reduced health inequalities. Despite these known benefits, implementation of personalised care has been slow. Evaluation is an important step towards achieving the ambition of universally delivered personalised care. There are currently few comprehensive assessments or tools that are designed to understand the implementation of personalised care at a service or system level, or the cultural, practical and behavioural factors influencing this. The aim of this paper is to describe the development and testing of a system-wide evaluation tool. The tool offers a process through which healthcare systems can better understand the current delivery of personalised care and the factors influencing this. With a focus on implementation, the development of the tool was informed by the Consolidated Framework for Implementation Research, and its content is structured using behaviour change theory (COM-B Theory of Behaviour Change Model). The tool consists of four mirrored surveys, which were developed using an iterative exploratory design. This included a series of testing cycles, in which its structure and content were continually refined. To date, it has been used by 24 clinical services, involving 397 service users, 313 front-line practitioners, 73 service managers and 40 commissioners. These services have used the evaluation process to initiate quality improvement, targeted at one of the more aspects of personalised care. The use of the COM-B model increases the likelihood of those improvements being sustained, through identification of the core factors that enable or limit personalised care behaviours among healthcare staff. We have shown this process to be applicable in a wide range of settings, thus it potentially has broad applicability as a tool for cultural change and quality improvement. The next stage of this work will focus on implementation and evaluation, to fully understand if and how the tool can be used to drive improvements in personalised care delivery.

Indexed as

Health FacilitiesProcess Assessment, Health CareHumansQuality ImprovementHealth policyPatient-centred careQuality improvementQuality measurement

Identifiers

PMID37669810
PMCPMC10481846
OpenAlexW4386461830

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.