The experiences of patients who leave hospital against medical advice: analysis of survey data
Notice bibliographique
Résumé
Background: Historically, when patients leave hospital against medical advice (LAMA), the focus has often been on non-compliance or other patient-level factors, rather than on how services may be designed to better support these patients. Efforts to better understand why patients LAMA could strengthen the provision of patient-centered care that is responsive to individual needs and values. This study aimed to explore the experiences of Albertan adults who LAMA by examining patient-centered quality indicators (PC-QIs) derived from survey data. We sought to identify actionable insights that may inform service improvements and reduce the risks associated with LAMA discharges. Methods: We analyzed seven years of survey data, encompassing hospital discharges from April 2016 to March 2023. A random sample of respondents completed the Canadian Patient Experiences - Inpatient Care (CPES-IC) instrument by telephone within six weeks of hospital discharge. From the data, we assessed ten patient-centred quality indicators (PC-QI) which were previously co-created with patient advisors, researchers, and health system administrators. Survey responses/PC-QIs were reported as percent in "top box", as represented by the most positive answer choice. Differences between patients who LAMA and other medical/surgical discharges were assessed. Results: A total of 144,480 surveys were successfully linked with inpatient records and included for analysis. This included 1,177 (0.9%) respondents who LAMA. In our sample, those who LAMA were predominantly male, younger, had a lower level of educational attainment, and were living with a greater number of comorbid health conditions. They also had lower self-reported levels of physical and mental health and had a longer average length of stay. The LAMA group had significantly lower top-box percentages on all ten of the PC-QIs which we examined. This difference ranged from 20.7% (communicating test results; 51.6% LAMA group vs. 71.3% others) to 29.2% (patient involvement in decisions about their care and treatment; 39.8% vs. 69.0% respectively). Conclusion: Patients who LAMA reported lower ratings of patient experience across all PC-QIs studied. Our findings may provide actionable, service-related insights into the reasons why patients LAMA. This is important as those who do so may place themselves at increased risk for future unplanned healthcare events, mortality, and morbidity.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,006 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».