Barriers and facilitators of patient centered care for immigrant and refugee women: a scoping review
Bibliographic record
Abstract
BACKGROUND: Migrants experience disparities in healthcare quality, in particular women migrants. Despite international calls to improve healthcare quality for migrants, little research has addressed this problem. Patient-centred care (PCC) is a proven approach for improving patient experiences and outcomes. This study reviewed published research on PCC for migrants. METHODS: We conducted a scoping review by searching MEDLINE, CINAHL, SCOPUS, EMBASE and the Cochrane Library for English-language qualitative or quantitative studies published from 2010 to June 2019 for studies that assessed PCC for adult immigrants or refugees. We tabulated study characteristics and findings, and mapped findings to a 6-domain PCC framework. RESULTS: We identified 581 unique studies, excluded 538 titles/abstracts, and included 16 of 43 full-text articles reviewed. Most (87.5%) studies were qualitative involving a median of 22 participants (range 10-60). Eight (50.0%) studies involved clinicians only, 6 (37.5%) patients only, and 2 (12.5%) both patients and clinicians. Studies pertained to migrants from 19 countries of origin. No studies evaluated strategies or interventions aimed at either migrants or clinicians to improve PCC. Eleven (68.8%) studies reported barriers of PCC at the patient (i.e. language), clinician (i.e. lack of training) and organization/system level (i.e. lack of interpreters). Ten (62.5%) studies reported facilitators, largely at the clinician level (i.e. establish rapport, take extra time to communicate). Five (31.3%) studies focused on women, thus we identified few barriers (i.e. clinicians dismissed their concerns) and facilitators (i.e. women clinicians) specific to PCC for migrant women. Mapping of facilitators to the PCC framework revealed that most pertained to 2 domains: fostering a healing relationship and exchanging information. Few facilitators mapped to the remaining 4 domains: address emotions/concerns, manage uncertainty, make decisions, and enable self-management. CONCLUSIONS: While few studies were included, they revealed numerous barriers of PCC at the patient, clinician and organization/system level for immigrants and refugees from a wide range of countries of origin. The few facilitators identified pertained largely to 2 PCC domains, thereby identifying gaps in knowledge of how to achieve PCC in 4 domains, and an overall paucity of knowledge on how to achieve PCC for migrant women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".