The Impact of Health Information Exchange on In-Hospital and Postdischarge Mortality in Older Adults with Alzheimer Disease Readmitted to a Different Hospital Within 30 Days of Discharge: Cohort Study of Medicare Beneficiaries
Notice bibliographique
Résumé
BACKGROUND: Although electronic health information sharing is expanding nationally, it is unclear whether electronic health information sharing improves patient outcomes, particularly for patients who are at the highest risk of communication challenges, such as older adults with Alzheimer disease. OBJECTIVE: To determine the association between hospital-level health information exchange (HIE) participation and in-hospital or postdischarge mortality among Medicare beneficiaries with Alzheimer disease or 30-day readmissions to a different hospital following an admission for one of several common conditions. METHODS: This was a cohort study of Medicare beneficiaries with Alzheimer disease who had one or more 30-day readmissions in 2018 following an initial admission for select Hospital Readmission Reduction Program conditions (acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, and pneumonia) or common reasons for hospitalization among older adults with Alzheimer disease (dehydration, syncope, urinary tract infection, or behavioral issues). Using unadjusted and adjusted logistic regression, we examined the association between electronic information sharing and in-hospital mortality during the readmission or mortality in the 30 days following the readmission. RESULTS: A total of 28,946 admission-readmission pairs were included. Beneficiaries with same-hospital readmissions were older (aged 81.1, SD 8.6 years) than beneficiaries with readmissions to different hospitals (age range 79.8-80.3 years, P<.001). Compared to admissions and readmissions to the same hospital, beneficiaries who had a readmission to a different hospital that shared an HIE with the admission hospital had 39% lower odds of dying during the readmission (adjusted odds ratio [AOR] 0.61, 95% CI 0.39-0.95). There were no differences in in-hospital mortality observed for admission-readmission pairs to different hospitals that participated in different HIEs (AOR 1.02, 95% CI 0.82-1.28) or to different hospitals where one or both hospitals did not participate in HIE (AOR 1.25, 95% CI 0.93-1.68), and there was no association between information sharing and postdischarge mortality. CONCLUSIONS: These results indicate that information sharing between unrelated hospitals via a shared HIE may be associated with lower in-hospital, but not postdischarge, mortality for older adults with Alzheimer disease. In-hospital mortality during a readmission to a different hospital was higher if the admission and readmission hospitals participated in different HIEs or if one or both hospitals did not participate in an HIE. Limitations of this analysis include that HIE participation was measured at the hospital level, rather than at the provider level. This study provides some evidence that HIEs can improve care for vulnerable populations receiving acute care from different hospitals.
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».