Health‐care resource use among patients who use illicit opioids in England, 2010–20: A descriptive matched cohort study
Notice bibliographique
Résumé
BACKGROUND AND AIMS: People who use illicit opioids have higher mortality and morbidity than the general population. Limited quantitative research has investigated how this population engages with health-care, particularly regarding planned and primary care. We aimed to measure health-care use among patients with a history of illicit opioid use in England across five settings: general practice (GP), hospital outpatient care, emergency departments, emergency hospital admissions and elective hospital admissions. DESIGN: This was a matched cohort study using Clinical Practice Research Datalink and Hospital Episode Statistics. SETTING: Primary and secondary care practices in England took part in the study. PARTICIPANTS: A total of 57 421 patients with a history of illicit opioid use were identified by GPs between 2010 and 2020, and 172 263 patients with no recorded history of illicit opioid use matched by age, sex and practice. MEASUREMENTS: We estimated the rate (events per unit of time) of attendance and used quasi-Poisson regression (unadjusted and adjusted) to estimate rate ratios between groups. We also compared rates of planned and unplanned hospital admissions for diagnoses and calculated excess admissions and rate ratios between groups. FINDINGS: A history of using illicit opioids was associated with higher rates of health-care use in all settings. Rate ratios for those with a history of using illicit opioids relative to those without were 2.38 [95% confidence interval (CI) = 2.36-2.41] for GP; 1.99 (95% CI = 1.94-2.03) for hospital outpatient visits; 2.80 (95% CI = 2.73-2.87) for emergency department visits; 4.98 (95% CI = 4.82-5.14) for emergency hospital admissions; and 1.76 (95% CI = 1.60-1.94) for elective hospital admissions. For emergency hospital admissions, diagnoses with the most excess admissions were drug-related and respiratory conditions, and those with the highest rate ratios were personality and behaviour (25.5, 95% CI = 23.5-27.6), drug-related (21.2, 95% CI = 20.1-21.6) and chronic obstructive pulmonary disease (19.4, 95% CI = 18.7-20.2). CONCLUSIONS: Patients who use illicit opioids in England appear to access health services more often than people of the same age and sex who do not use illicit opioids among a wide range of health-care settings. The difference is especially large for emergency care, which probably reflects both episodic illness and decompensation of long-term conditions.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».