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1.
Drug Alcohol Rev ; 41(7): 1543-1553, 2022 11.
Article de Anglais | MEDLINE | ID: mdl-36053863

RÉSUMÉ

INTRODUCTION: People who inject drugs are at risk of hospitalisation with injection-related infections (IRI). We audited the clinical features, microbiology and management of IRI at a tertiary service in Melbourne to describe the burden and identify quality improvement opportunities. METHODS: We performed retrospective review of IRI admissions from January 2017 to April 2019. We extracted admissions where ICD-10 codes or triage text suggested injecting drug use, and the diagnosis suggested IRI. We reviewed these for eligibility and extracted data using a standardised form. We performed mixed-effects logistic regression to determine predictors of unplanned discharge. RESULTS: From 574 extracted candidate admissions, 226 were eligible, representing 178 patients. Median age was 41 years (interquartile range 36-47), 66% (117/178) male and 49% (111/226) had unstable housing. Over 50% (96/178) had a psychiatric diagnosis and 35% (62/178) were on opioid agonist therapy (OAT) on admission. Skin and soft tissue infection was the most common IRI (119/205, 58%), followed by bacteraemia (36/205, 18%) and endocarditis (26/205, 13%). Management included addictions review (143/226, 63%), blood-borne virus screening (115/226, 51%), surgery (77/226, 34%) and OAT commencement (68/226, 30%). Aggression events (54/226, 15%) and unplanned discharge (69/226, 30%) complicated some admissions. Opioid use without OAT was associated with almost 3-fold increased odds of unplanned discharge compared to no opioid use (odds ratio 2.90, 95% confidence interval 1.23, 6.85, p = 0.015). DISCUSSION AND CONCLUSION: Comorbidities associated with IRI may be amenable to opportunistic intervention during hospitalisation. Further research is needed to develop optimal models of care for this vulnerable patient group.


Sujet(s)
Usagers de drogues , Troubles liés aux opiacés , Toxicomanie intraveineuse , Humains , Mâle , Adulte , Toxicomanie intraveineuse/psychologie , Troubles liés aux opiacés/traitement médicamenteux , Traitement de substitution aux opiacés , Hospitalisation
2.
Drug Alcohol Rev ; 41(5): 1053-1061, 2022 07.
Article de Anglais | MEDLINE | ID: mdl-35411617

RÉSUMÉ

INTRODUCTION: Injection-related infections (IRI) cause morbidity and mortality in people who inject drugs. Hospital administrative datasets can be used to describe hospitalisation trends, but there are no validated algorithms to identify injecting drug use and IRIs. We aimed to validate International Classification of Diseases (ICD) codes to identify admissions with IRIs and use these codes to describe IRIs within our hospital. METHODS: We developed a candidate set of ICD codes to identify current injecting drug use and IRI and extracted admissions satisfying both criteria. We then used manual chart review data from 1 January 2017 to 30 April 2019 to evaluate the performance of these codes and refine our algorithm by selecting codes with a high-positive predictive value (PPV). We used the refined algorithm to describe trends and outcomes of people who inject drugs with an IRI at Alfred Hospital, Melbourne from 2008 to 2020. RESULTS: Current injecting drug use was best predicted by opioid-related disorders (F11), 80% (95% confidence interval [CI] 74-85%), and other stimulant-related disorders (F15), 82% (95% CI 70-90%). All PPVs were ≥67% to identify specific IRIs, and ≥84% for identifying any IRI. Using these codes over 12 years, IRIs increased from 138 to 249 per 100 000 admissions, and skin and soft tissues infections (SSTI) were the most common (797/1751, 46%). DISCUSSION AND CONCLUSION: Validated ICD-based algorithms can inform passive surveillance systems. Strategies to reduce hospitalisation with IRIs should be supported by early intervention and prevention, particularly for SSTIs which may represent delayed access to care.


Sujet(s)
Classification internationale des maladies , Troubles liés à une substance , Algorithmes , Australie/épidémiologie , Bases de données factuelles , Hospitalisation , Humains , Centres de soins tertiaires
3.
Med J Aust ; 198(6): 324-6, 2013 Apr 01.
Article de Anglais | MEDLINE | ID: mdl-23545031

RÉSUMÉ

OBJECTIVES: To estimate the proportion of students in Australian medical schools who undertake international medical electives (IMEs), particularly in developing countries, and to ascertain which medical schools provide predeparture training and postelective debriefing. DESIGN, SETTING AND PARTICIPANTS: Extraction of data on the number of students undertaking electives from the Medical Schools Outcomes Database (MSOD) for the 2013s 2006 to 2010; and interviews with the directors of each medical school in Australia in May to July 2012 to ascertain the availability of predeparture training and postelective debriefing. MAIN OUTCOME MEASURES: The proportion of medical students undertaking IMEs overall and within developing countries and the proportion of medical schools with optional and mandatory predeparture training and postelective debriefing. RESULTS: Fifty-three per cent of graduate-entry (GE) program students and 35% of high-school entry (HSE) program students undertook IMEs. Fifty-nine per cent of electives undertaken by GE program students were in developing countries, compared with 56% for HSE program students. Predeparture training was offered by 12 of the 16 Australian medical schools, but it was mandatory in only six. Only eight schools offer postelective debriefing. CONCLUSIONS: A large proportion of Australian medical students undertake IMEs in developing countries. However, a considerable proportion of students do not undertake formal preparation for, or reflection on, their experiences. Predeparture training and postelective debriefing should be scaled up across Australian medical schools to provide students with the guidance and support to maximise the benefits and minimise risks associated with undertaking IMEs in developing countries.


Sujet(s)
Enseignement médical premier cycle/méthodes , Santé mondiale/enseignement et éducation , Santé publique/enseignement et éducation , Étudiant médecine/statistiques et données numériques , Australie , Prévision , Humains , Évaluation de programme
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