Associations Between Successful Home Discharge and Posthospitalization Care Planning: Cross-Sectional Ecological Study
Notice bibliographique
Résumé
Background Effective discharge planning is crucial for successful care transitions, reducing hospital length of stay and readmission rates. Japan offers a financial incentive to enhance the coordination of posthospitalization care planning for patients with complex needs. However, the national impact of this incentive remains unclear. Objective This study aimed to (1) assess the association between the number of claims submitted for discharge planning, as an indicator of the provision of posthospitalization care planning, and key health care outcomes, including discharges to home, 30-day readmissions, length of stay, and medical expenditures at the prefectural level in Japan, and (2) to describe regional differences in the provision of posthospitalization care planning and explore associated factors. Methods This ecological study used prefectural-level data from fiscal year 2020. Claims submitted for discharge planning were used as indicators that posthospitalization care planning was provided. Supply-adjusted standardized claim ratios (SCRs) were calculated using data from the Seventh National Database of Health Insurance Claims, to evaluate and compare the number of claims across 47 prefectures in Japan, accounting for differences in population structure. Key outcomes included discharges to home, 30-day readmissions, length of stay, and medical expenditures. Multivariate negative binomial regression models assessed associations between SCRs and outcomes, adjusting for socioeconomic covariates. In addition, regional differences in the provision of posthospitalization care planning and associated factors were analyzed using the Mann-Whitney U test. Prefectures were divided into 3 groups (low, medium, and high) based on tertiles of each factor, and supply-adjusted SCRs were compared across these groups. Results The ratio of the minimum to maximum supply-adjusted SCR was 10.63, highlighting significant regional variation. Higher supply-adjusted SCRs, indicating more frequent provision of posthospitalization care planning, were associated with an increase of 9.68 (95% CI 0.98-18.47) discharges to home per 1000 patients for each SD increase in supply-adjusted SCR. Several factors contributed to regional differences in the supply-adjusted SCR for posthospitalization care planning. A higher supply-adjusted SCR was significantly associated with a greater number of nurses per 100 hospital beds (median SCR in low, medium, and high groups: 0.055, 0.101, and 0.103, respectively); greater number of care manager offices per 100 km2 of habitable area (0.088, 0.082, and 0.116); higher proportion of hospitals providing electronic medical information to patients (0.083, 0.095, and 0.11); lower proportion of older adults living alone (0.116; 0.092; 0.071); and higher average per capita income (0.078, 0.102, and 0.102). Conclusions The provision of posthospitalization care planning is associated with an increased likelihood of discharge to home, underscoring its importance in care transitions. However, significant regional disparities in care coordination exist. Addressing these disparities is crucial for equitable health care outcomes. Further research is needed to clarify causal mechanisms.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».