Using data linkage to identify newly acquired hepatitis C infections in Queensland Jonathan Malo MAE Scholar & AFPHM Advanced Trainee 28 June 2017 Then Hepatitis C (newly acquired) notifications 2 1
Now Hepatitis C (newly acquired) notifications >50% 3 Confusion @ Commonwealth seem higher than what would be expected compared to other jurisdictions more than triple of what was reported in WA and Victoria is there an explanation as to why these numbers are so high? 4 2
Background Hepatitis C Hepatitis C virus (HCV) Most commonly transmitted via injecting drug use (IDU) ~10,000 notifications/year Australia-wide ~2,500 in QLD ~25% of acute infections symptomatic ~25% spontaneously clear virus Curative treatments available 6 3
Laboratory notification Anti-hepatitis C antibody Hepatitis C RNA by nucleic acid test Classification Newly acquired (infected <24m) Unspecified 7 Newly acquired Laboratory evidence Negative anti-hepatitis C antibody test <24m Clinical evidence <24 m Alanine transaminase (ALT) levels >10x upper limit of normal, OR Jaundice, OR Bilirubin in urine *Other causes of acute hepatitis excluded 8 4
Surveillance issues Need previous testing history Public and private labs Anonymity coded patients (e.g. Ma, Jo) Clinical details required if no previous negative antibody test Asymptomatic acute infections Marginalised population Resources 9 Hepatitis C surveillance A/Prof Martyn Kirk Hep C is the absolute worst disease for surveillance You have made hep C worth doing surveillance 10 5
Hepatitis C surveillance Newly acquired infections Monitor trends in Demographics Risk factors for transmission Identify groups for targeted treatment Evaluate public health interventions Identify threats to public health 11 Establishing a surveillance system 6
System objectives Identify newly acquired HCV infections Collect and report reasons for testing and risk factors for HCV transmission Monitor for cases or clusters of non-idurelated HCV transmission Sustainable 13 Methods to identify newly acquired infections 7
AUSLAB Public pathology test results software Public hospitals Community clinics Prisons 15 AUSLAB 16 8
AUSLAB Data extracts 17 18 9
Notifiable conditions system NOCS Data extracts through SQL Demographics Notification date Patient location 19 Data linkage AUSLAB data extract (previous 24m) Non-reactive anti-hcv antibody test results Elevated ALT levels (F 340; M 450 U/L) Hep C notifications from NOCS Probability matching in Stata (reclink) Name, Sex, DOB* First 2 letters first name First 2 letters last name 20 10
System Design New hepatitis C notification received by NOCS unspecified AUSLAB test data extracted and linked to new notifications (weekly) Newly acquired cases identified & classification changed in NOCS If current or previous imprisonment record in NOCS Diagnosing clinician surveillance form faxed No further action 22 11
23 New hepatitis C notification received by NOCS unspecified AUSLAB test data extracted and linked to new notifications (weekly) Newly acquired cases identified & changed in NOCS If current or previous imprisonment record in NOCS Diagnosing clinician surveillance form faxed No further action IDU or imprisonment identified as a risk factors? No Follow-up by Public Health Unit Yes Record in NOCS 24 12
Results System 30 minutes 26 13
Year to date 1121 Total hepatitis C notifications 124 Newly acquired 11% 93 Imprisonment (previous or at diagnosis) 75% 27 Diagnosing clinician form 44 Faxes sent 34 Returned 77% Response rate 10 IDU identified in EMR 6 Cases for PHU follow-up 28 14
Discussion & Implications Data linkage for surveillance Efficient Match anonymity coded test results & notifications Relatively high case ascertainment Identify those imprisoned previously or at diagnosis 30 15
Limitations Only previous public pathology results 31 Implications Underestimating newly acquired infections Importance of access to negative testing data Identify groups for targeted treatment interventions 32 16
Acknowledgements Stephen Lambert Stephanie Davis Communicable Diseases Branch staff Queensland Public Health Units 33 Thank you Questions? 34 17
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