Evidence map›Paper›PMID 42044947›Full record

ArticleBMJ open quality2026

Collecting Accurate and Robust Equity (CARE) data: an analysis of a pilot quality improvement initiative in ambulatory settings.

Fatima Sheikh, Marlena Dang Nguyen, Kamal Babrah, Nili Begum, Nagham Azzam Iqbal, Lawrence Mbuagbaw, Jennifer Walker, Rochelle Reid, Alison Fox-Robichaud, Lisa Schwartz

Abstract read
In one paragraph

Article in BMJ open quality, 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

10 authors.

Fatima SheikhDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada sheikf9@mcmaster.ca.ORCID 0000-0002-1327-2203
Marlena Dang NguyenDepartment of Equity, Diversity, Inclusion and Human Rights, Hamilton Health Sciences, Hamilton, Ontario, Canada.
Kamal BabrahDepartment of Equity, Diversity, Inclusion and Human Rights, Hamilton Health Sciences, Hamilton, Ontario, Canada.
Nili BegumDepartment of Quality and Performance, Hamilton Health Sciences, Hamilton, Ontario, Canada.
Nagham Azzam IqbalDepartment of Equity, Diversity, Inclusion and Human Rights, Hamilton Health Sciences, Hamilton, Ontario, Canada.
Lawrence MbuagbawDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.ORCID 0000-0001-5855-5461
Jennifer WalkerDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
Rochelle ReidDepartment of Equity, Diversity, Inclusion and Human Rights, Hamilton Health Sciences, Hamilton, Ontario, Canada.
Alison Fox-RobichaudMedicine, McMaster University Faculty of Health Sciences, Hamilton, Ontario, Canada.
Lisa SchwartzDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial determinants of health (SDoH) influence disease incidence, access to care, experiences, and outcomes. Recognising their importance, researchers and governments have emphasised the need to collect SDoH data in healthcare settings. However, gaps remain in understanding how to collect this information respectfully and equitably. To address these gaps, we aimed to understand local community perspectives on patient-centred SDoH data collection.

methodWe held a community engagement session to gather input from equity-denied communities on SDoH questions, response options, preferred methods of answering and appropriate data use. Qualitative data were analysed using content analysis, guided by the Capability, Opportunity and Motivation-Behaviour (COM-B) model. We also collected patient feedback from the first six months of implementing patient-centred SDoH data collection in ambulatory services at a large academic health science centre. This feedback was collected through an anonymous Microsoft Forms survey on comfort, safety and ease of responding to the SDoH questions and was summarised using medians and frequencies.

resultsThe community engagement session included 22 participants, including eight patient advisors from diverse community organisations. Participants identified COM-B-related barriers to completing the questionnaire, such as unclear terminology, privacy concerns and mistrust of data use. Facilitators included inclusive language, multiple response methods, and transparency, particularly around data use. After integrating this feedback, the early implementation demonstrated high levels of comfort and safety. Additional feedback from the implementation highlighted opportunities to expand response methods, enhance staff engagement and education and establish ongoing partnerships with patients and communities to support the equitable use of SDoH data.

conclusionsCollecting SDoH data in healthcare settings is essential for facilitating equity-informed quality improvement, research, and decision-making. Our project highlights opportunities to overcome barriers by expanding response methods, enhancing staff engagement and education and fostering ongoing partnerships with patients and communities to support equitable SDoH data use and reporting.

Indexed as

Ambulatory CareAmbulatory Care FacilitiesData CollectionHealth EquityQuality ImprovementHumansPilot ProjectsQualitative ResearchSocial Determinants of HealthSurveys and QuestionnairesAmbulatory careHealthcare quality improvementHealth Equity

Identifiers

PMID42044947
PMCPMC13141222

What Socratic 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 Socratic graph.