Exploring Patient Understandings of Navigation Services Within Alberta's Healthcare System: A Qualitative Study
Notice bibliographique
Résumé
INTRODUCTION: Patient navigation was first envisioned to assist marginalized cancer patients access timely healthcare services by identifying and addressing social barriers to care. While this understanding of patient navigation may still hold for a subgroup of programs today, its expansion over the past 30 years has resulted in a diverse set of interventions with distinct care settings, patient eligibility criteria, navigator training requirements and program goals. This study aimed to explore patients' understanding of patient navigation programs to identify program features that are of particular value and importance to them. METHODS: In this qualitative study, we conducted one-on-one semi-structured interviews from November 2023 to February 2024 with patients involved in five distinct hospital-, clinic- and community-based patient navigation programs across Alberta. Inductive thematic analysis and interpretive exercises were performed to construct a coherent narrative relevant to the research objective. Study participants were adult patients with patient navigation program exposure for at least 1 month (range: 2 months to 11 years). RESULTS: Twenty-three patient experiences were captured in the study (12 [52%] women; median [IQR] age, 59 [48-67] years), with approximately half receiving support from a nurse navigator (11/23, 48%). Regardless of navigation type, the patients' stories were tethered by their navigators' provision of personalized, seamless and humanized care. These perceived navigator functions were accomplished through patient-identified navigator characteristics, including navigator approachability, accessibility and comprehensive systems knowledge. While the identified functions and characteristics of navigators were consistent across patients, the operationalization of these components varied based on the program's setting and the particular needs of each patient. CONCLUSIONS: The commonalities in patient perceptions of patient navigation indicate continued points of overlap across programs despite their increasing heterogeneity. Additionally, our findings provide insight into the functions and characteristics of patient navigation most valued by patients, which may inform future program development and implementation efforts. PATIENT AND PUBLIC CONTRIBUTION: Continued collaboration with two patient partners was maintained throughout the study to ensure responsiveness to patient priorities.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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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