Enhancing community health through patient navigation, advocacy, and social support: A community health navigator pilot study
Notice bibliographique
Résumé
Background: The healthcare system is complex and difficult to navigate, particularly for patients with multiple chronic conditions and complex care plans. Patient adherence to care plans and patient health outcomes can be negatively impacted by language, financial, and other social barriers. Community Health Navigators (CHNs) are community members that are hired and trained to navigate the healthcare system, who work with patients to overcome barriers to care and support patient self-management by providing services tailored to needs. While these types of interventions can improve access to care in other settings, they are not well studied in Canada nor in Canadian primary care settings. Objective: For this pilot study, we aimed to determine the feasibility of a CHN intervention for patients with multiple chronic conditions. Our secondary objective was to assess the potential impact of a CHN intervention on patient-reported outcome measures. Methods: We used an observational single arm pre-post study design. Using interviewer-administered patient surveys, we assessed patient-reported outcomes at baseline (pre-enrolment), and 6-months and 12-months post-enrolment. The survey included instruments to assess quality of life (EQ-5D-5L), patient chronic disease care experience (PACIC), social support (mMOS-SS), and cost-related adherence to care (i.e. financial security to pay for care-related costs). Descriptive analysis was performed on survey data, and the sample was restricted to participants who completed both follow-up surveys (6- and 12-month). Results: Of the 21 participants enrolled in our pilot study, the mean age was 61.3 years, 56% had an annual household income below $30,000, and 68% were born outside of Canada. The three most common conditions reported were hypertension (77%), diabetes (59%), and back problems (55%). The mean number of conditions a patient reported was 5.4 (SD 2.3, range 3-11). Of the sample enrolled, 14 (67%) patients completed both follow-up surveys. Mean social support (scale: 0-100), was 56, 68, and 75 at baseline, 6, and 12 months, respectively—indicating a potential increase in social support after the intervention. Mean self-ranked health (scale: 0-100) did not change over time. Mean patient experience with chronic disease care (scale: 1-3) was 2.01 at baseline; 2.24 at 6 months, and 1.89 at 12 months. The proportion of patients who reported no difficulty paying for medical expenses increased from 36% at baseline to 79% at 6 months and 86% at 12 months. In other words, fewer patients reported difficulty paying for medical expenses at 6 months and at 12 months. Results presented here are preliminary; further analysis is underway which will include analysis of health outcomes using administrative data, statistical tests of survey data (where appropriate), and qualitative analysis of interview data. Conclusions: CHNs may improve patients’ social and financial support and satisfaction with care. Our pilot study demonstrates that a CHN intervention is feasible to implement in primary care for patients with multiple chronic conditions. These findings informed a large ongoing cluster-randomized pragmatic trial.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, pas un consensus.
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