O2 Implementing a nurse-led early discharge clinic for patients with decompensated chronic liver disease to reduce readmission rates and length of hospital stay
Notice bibliographique
Résumé
Following a patient’s initial presentation with decompensated liver disease, the condition often progresses rapidly, ultimately resulting in death or liver transplantation (Taper, et al.,2016). In-hospital mortality for this population ranges from 10–20% (Volk et al.,2012), and frequent unplanned readmissions pose significant burden on patients and healthcare services. Most readmissions can be avoided with effective secondary preventative measures; however, patients are frequently readmitted prior to outpatients’ follow-up (Giles, et al.,2023). This project aims to implement a nurse-led Early Discharge Clinic (EDC) for patients with decompensated cirrhosis, intending to optimise patients‘ follow-up, subsequently reducing the waiting list for outpatient clinics, reducing the delay in implementing early interventions, reducing readmission rates and, where possible, the length of hospital stays. This clinic intends also to improve overall patient and families’ experiences, and ultimately reduce costs for the NHS. A first retrospective data analysis was conducted, looking at patients with decompensated cirrhosis admitted to hospital from September to December 2023 (cohort1). Patients’ length of admission, date of first appointment offered, date of first appointment and rate of readmissions between discharge and first outpatient appointment was evaluated. A further quantitative data analysis was conducted after implementing the EDC from February to August 2024 (cohort2). A patient and family feedback form was completed to include qualitative data. Following the implementation of the EDC, patients in cohort 2 experienced significantly shorter hospital stays (8days vs. 15days in cohort 1) and substantially reduced waiting times for outpatient follow-up, with cohort 1 facing delays nearly three times longer. Patients in cohort 2 demonstrated a lower readmission rate. While direct measurement of morbidity and mortality was not feasible in this project, existing evidence supports the association between early intervention and improved clinical outcomes in decompensated liver disease. Notably, 90% of patients and families (cohort2) rated the care received as ‘very good’ or’excellent.’ The implementation of a nurse-led EDC has demonstrated clear value in improving the care of patients with decompensated cirrhosis. While the findings are encouraging, it is important to acknowledge the small sample size. This project remains ongoing and continues to evolve, with the establishment of a direct partnership with dietitians and physiotherapists aiming to further enhance the quality and scope of holistic care provided. Additionally, a notable outcome of the project has been the increased job satisfaction reported by the Specialist Nurses leading the clinic, reinforcing the positive impact of such projects on staff engagement and professional fulfilment. 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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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| 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) | 0,009 | 0,001 |
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 ».