Profiling patterns of patient experiences of access and continuity at team-based primary healthcare clinics (Canada): a latent class analysis
Notice bibliographique
Résumé
BACKGROUND: Access to primary healthcare services is a core lever for reducing health inequalities. Population groups living with certain individual social characteristics are disproportionately more likely to experience barriers accessing care. This study identified profiles of access and continuity experiences of patients registered with a family physician working in team-based primary healthcare clinics and explored the associations of these profiles with individual and organizational characteristics. METHODS: A cross-sectional e-survey was conducted between September 2022 and April 2023. All registered adult patients with an email address at 104 team-based primary healthcare clinics in Quebec were invited to participate. Latent class analysis was used to identify patient profiles based on nine components of access to care and continuity experiences. Multinomial logistic regression models were fit to analyze each profile's association with ten characteristics related to individual sociodemographics, perceived heath status, chronic conditions and two related to clinic area and size. RESULTS: Based on 87,155 patients who reported on their experience, four profiles were identified. "Easy access and continuity" (42% of respondents) was characterized by ease in almost all access and continuity components. Three profiles were characterized by diverging access and/or continuity difficulties. "Challenging booking" (32%) was characterized by patients having to try several times to obtain an appointment at their clinic. "Challenging continuity" (9%) was characterized by patients having to repeat information that should have been in their file. "Access and continuity barriers" (16%) was characterized by difficulties with all access and continuity components. Female gender and poor perceived health significantly increased the risk of belonging to the three profiles associated with difficulties by 1.5. Being a recently arrived immigrant (p = 0.036), having less than a high school education (p = 0.002) and being registered at a large clinic (p < 0.001) were associated with experiencing booking difficulties. Having at least one chronic condition (p = 0.004) or poor perceived mental health (p = 0.048) were associated with experiencing continuity difficulties. CONCLUSIONS: These results highlight individual social and health characteristics associated with increased risk of experiencing healthcare access difficulties, such as immigration status and education level and/or continuity difficulties when having a chronic condition and poor perceived mental health. Facilitating appointment booking for recently arrived immigrants and patients with low education, integrating interprofessional collaboration practices for patients with chronic conditions and improving care coordination and communication for patients with mental health needs are recommended.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».