Evidence map›Paper›PMID 40939117›Full record

ArticleJMIR aging2025

Toward Data-Informed Care in Long-Term Care: Qualitative Analysis.

Suleyman Bouchmal, Katya Yj Sion, Jan Ph Hamers, Sil Aarts

Abstract read
In one paragraph

Article in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Data Maturity Assessment in Long-Term Care: Mixed Methods Study.Journal of medical Internet research · 2026
    Article
  2. 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

4 authors.

Suleyman BouchmalDepartment of Health Services Research, Limburg Living Lab in Ageing and Long-Term Care, Maastricht University, Duboisdomein 30, Maastricht, 6229 GT, The Netherlands, 31 433882222.ORCID http://orcid.org/0009-0005-8106-0009
Katya Yj SionDepartment of Health Services Research, Limburg Living Lab in Ageing and Long-Term Care, Maastricht University, Duboisdomein 30, Maastricht, 6229 GT, The Netherlands, 31 433882222.ORCID http://orcid.org/0000-0002-7190-7238
Jan Ph HamersDepartment of Health Services Research, Limburg Living Lab in Ageing and Long-Term Care, Maastricht University, Duboisdomein 30, Maastricht, 6229 GT, The Netherlands, 31 433882222.ORCID http://orcid.org/0000-0003-1228-3493
Sil AartsDepartment of Health Services Research, Limburg Living Lab in Ageing and Long-Term Care, Maastricht University, Duboisdomein 30, Maastricht, 6229 GT, The Netherlands, 31 433882222.ORCID http://orcid.org/0000-0002-3121-412X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In long-term care (LTC) for older adults, data on client, employee, and organization levels are collected in various ways, covering quality of care, life, and work. There is, however, a lack of understanding of how to introduce data-informed care in LTC and thus create value from data. Objective: This study aims to investigate the experiences and perceptions of various stakeholders in LTC regarding data and data-informed care. Methods: A qualitative study using the World Café cocreation technique was conducted with a diverse group of LTC stakeholders. Four questions were addressed: (1) What thoughts do you have when you hear the term "data" in relation to LTC? (2) What purposes do data have (in the future) in LTC? (3) What knowledge and skills are needed to enable data-informed care? (4) How can data contribute to and improve multidisciplinary learning? Stakeholders' notes and the plenary summary were analyzed using conventional content analysis. Results: Stakeholders included nurses, members of client councils, data specialists, researchers, and managers (N=20; mean age 50, SD 13 years). Five themes were identified: (1) despite uncertainty, the benefits of using data outweigh the associated risks; (2) the lack of accessibility and uniformity hinders integrating data-informed care; (3) human resources and finance departments pioneer data usage; however, potential lies in clinical decision-making; (4) data-informed care demands individual, collective, and organizational prerequisites; and (5) multidisciplinary collaboration enriches collective knowledge regarding data. Conclusions: Introducing data-informed care requires enhancing data literacy of health care professionals, establishing clear communication about the role of data within the organization, and introducing new job positions, such as data scientists. Data-informed care was considered a multidisciplinary approach in which data have a supportive role to enhance collective understanding and are considered crucial for improving quality of care. .

Indexed as

Long-Term CareAdultAgedFemaleHumansMaleMiddle AgedQualitative Researchcocreationdatadata-informedlong-term carequality of care

Identifiers

PMID40939117
PMCPMC12431161

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.