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Sharon Matthews Jason Ferris Belinda Lloyd

Three datasets are better than one! Alcohol related diagnoses from ambulance to hospital admission, Melbourne, Australia. Sharon Matthews Jason Ferris Belinda Lloyd. Background. Routine monitoring plays a significant role in the development of responsive policy, prevention and intervention

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Sharon Matthews Jason Ferris Belinda Lloyd

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  1. Three datasets are better than one! Alcohol related diagnoses from ambulance to hospital admission, Melbourne, Australia Sharon Matthews Jason Ferris Belinda Lloyd

  2. Background • Routine monitoring plays a significant role in the development of responsive policy, prevention and intervention • Need to explore innovative methods to understand and respond to alcohol and drug related harms

  3. Aims • To use linked data to explore the diagnostic path from an alcohol related ambulance attendance to emergency and hospital admission in Melbourne , Australia between 2004/05 – 2008/09

  4. Methods Data • Alcohol related ambulance attendances • Victorian emergency department admissions (VEMD) • Victorian hospital admissions (VAED) • 2004/05 – 2008/09 Linked data : Ambulance  ED  Hospital admission

  5. Ambulance Attendances • Ambo Project database 1998 - present • Additional coding of Ambulance Victoria Patient Care Records (electronic from 2006) to identify alcohol and other drug related attendances • 17885 alcohol only cases 2004/05 to 2008/09

  6. Emergency Department Presentations • Victorian Emergency Minimum dataset (VEMD) • Detailed demographic, clinical and administrative information on all presentations to Victorian public hospitals with 24/7 ED

  7. Hospital Admissions • Victorian Admitted Episodes Dataset (VAED) • Acute hospital separations (public, private, denominational hospitals) • Principal diagnosis using ICD10 classification • 2004/05 – 2008/09

  8. Staged linkage – using: • Ambulance case number • Ambulance case date (time/date stamp) Validated using: • Patient age • Patient gender • Hospital • Time between attendance and ED (<2 hours) Outcome –63,156 linked records = 90.3% patients transported to ED (any AOD involvement)

  9. Treatment pathway – Alcohol intoxication attendances

  10. Age of alcohol intoxicated patients transported to ED (%)

  11. Alcohol intoxication attendances coded in ED presentations (%)

  12. Alcohol intoxication attendances coded in hospital admissions (%)

  13. Limitations • Data are not collected for research purposes • Coding practices can change over time • Some missing cases

  14. Summary • Increase in older patients – particularly 60 years and over • Less than half of acutely alcohol intoxicated patients have AOD principal diagnosis in ED or hospital • Single dataset usage provides an incomplete picture resulting in underestimation of the role of alcohol in cases • Increase in external causes for acutely intoxicated patients – particularly head injuries

  15. Utility of linkage • Use of multiple data sources necessary to examine and respond to AOD harms • Enhanced models to estimate AOD burden • Provide an evidence base regarding the nature of AOD presentations in settings where data are not routinely available • Monitor outcomes following intervention • Contribute to policy and intervention across acute, treatment and other settings

  16. Acknowledgements • Funded by Victorian Department of Health • VEMD and VAED data provided by the Victorian Department of Health • Ambulance data derived from the Ambo Project – a collaborative project between Turning Point and Ambulance Victoria, and funded by the Victorian Department of Health • Thanks to project team

  17. Sharon Matthews Research Fellow Population Health Research PhD Candidate Monash University T: +61 3 9412 9957 sharonm@turningpoint.org.au

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