Injury indicators: purposes, progress, prognosis

1. Injury indicators: purposes, progress, prognosis James Harrison AIHW National Injury Surveillance Unit Research Centre for Injury Studies Flinders University - Adelaide - South Australia

2. Overview • Injury indicators • Purposes: Why have indicators? • Principles: Concepts, definitions & standards • Progress: Where are we up to? • Problems: Constraints • Prognosis: Next steps… AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

3. Purposes: Why have indicators? Information to support injury prevention & control • Support planning and policy-making • Guide targeting and priority-setting by • Measuring and monitoring injury, its consequences, injury risk-factors and exposure to them • (Contributing to) evaluation of interventions AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

4. Purposes: Origin of indicators AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

5. Purposes: Origin of indicators AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

6. Steam-engine Risk of explosion Efficiency Effect of altered settings Injury prevention Burden of injury Risk exposure Effect of intervention What to indicate? Things worth knowing …especially if not directly observable AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

7. Steam-engine Pressure-time relationship Injury prevention Injury incidence Prevalence of risk exposure Reach of an intervention How to indicate it? A. Identify and specify another thing, which: • Can be measured • Varies with the ‘thing worth knowing’ B. Make a device / information system able to provide measured values of A. Steam-engine indicator Injury indicator AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

8. Steam-engine indicator Varies predictably with time-pressure Not much influenced by other things Sensitive enough to show important changes Timely enough to allow good control of engine Injury prevention indicator Varies predictably with injury occurrence Not much influenced by other things Sensitive enough to show important changes Timely enough to allow effective response to findings Well-defined Comparable (esp. over time) What is a good indicator? One with attributes suitable for its purpose AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

9. I What is a good indicator? AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

10. Principles: concepts, definitions, standards Indicators require data • Necessarybut not sufficient • Must be COMPARABLE Foundations for comparability • Clear meaning for key concepts: eg. ‘injury’, ‘severity’, ‘outcome’ • Classifications • eg. ICD-10, ICD-10-AM, ICECI • Operational definitions • eg. STIPDA Consensus Recommendations for using hospital discharge data for Injury Surveillance • Reporting standards • eg. Recommended Framework for reporting injury mortality data • Derived measures • eg. ICISS severity, remoteness, Socio-Economic Status • Institutional arrangements • eg. WHO-FIC, Injury ICE, STIPDA AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

11. Injury outcome indicators • Consensus criteria (ICE on Injury Statistics) • Define in terms of anatomical/physiological damage • Serious injury • Case ascertainment independent of extraneous factors • Representative of target population • Available data • Well-documented (definitions, methods, etc) (Cryer, Langley, et al 2005) AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

12. Progress: Where are we up to? Australia as an example Focus on trends in severe & fatal injury • c. 10 years at national level • Deaths and hospitalised injury • Onion metaphor: layers of work (iterative) • Getting, understanding, ‘cleaning’ & documenting data • Scope: defining and operationalising definition of ‘injury’ • Methods to avoid multiple counting • Methods to assess & control changing sample fraction AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

13. Full specification can be complex Incident fatal and severe injury due to Transport AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

14. …but different methods can give very different values How many deaths following injury due to a fall are recognised as such? Of deaths registered in Australia in 2002: AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

15. …even if differences are subtle AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University Age-adjusted rates

16. Has the age-adjusted rate risen? AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University Age-adjusted rates

17. Aspects of burden of hospitalised injury Hospitalisation due to Accidental Falls ages 65 and older, Australia 1995-6 to 2002-3 AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

18. Aspects of burden of hospitalised injury Hospitalisation due to Accidental Falls ages 65 and older, Australia 1995-6 to 2002-3 AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

19. Problems: Constraints • Data quality (incl timeliness) • Variation in % of cases incident in population admitted to hospital?(Especially for low severity injuries?) • Difficulty and costliness of validation studies • special studies; WA linked data • Data (mostly) not person-linked • >episode (ie record) / incident case of admitted injury: tricky to allow for this source of multiple counting of cases • hospital data and deaths data: do in-hospital ‘injury deaths’ appear as ‘injury deaths’ in national deaths data collection? • Access (administrative issues, privacy) • Complexity (esp for ‘clever data cleaning’) • Classification • Australian clinical modification of ICD-10 (ICD-10-AM) • revisions (each 2y) allow useful enhancement of Injury & External Cause codes • … but (so far) the revised codes are not used for routine mortality data AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

20. Signal & noise: example 1 AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University Age-adjusted rates

21. Signal & noise: example 2 AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University Age-adjusted rates

22. Prognosis: Next steps… • What? • Broader scope: of burden (eg rehab, late care) • Broader scope: of severity (eg ED) • Broader scope: exposures as well as outcomes • Prediction of non-fatal outcomes • Better denominators • Shorter lag (+/- model-based prediction) • How? • Standards (more, better, more widely used) • Linkage • Incremental system improvements AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

23. Summary • Purposes: Why have indicators? • To estimate trends (and differences) in important phenomena, which are not directly observable • Principles: concepts, definitions & standards • The technical foundation; essential for comparability • Progress: • Coming together… quite good trends data for serious injury • Problems: • Constraints are real, tricky but generally manageable • Prognosis: • Exciting times (nb linkage) • Grail: ICISS-like measure(s) for important non-fatal outcomes AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

24. AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

25. After dinner…? AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

26. AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

27. Understanding the issue • Demographics of injured people • Types of injury • Severity and outcomes • Risk factors and exposure • Effectiveness and use of interventions AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

28. Targeting and priority-setting • (potential) topics for indicators • Frequency • Risk • Burden • Potential for improvement AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

29. Approaches • Opportunistic • Using existing data and other resources • Making the most of them for injury surveillance • Understanding, creative use, incremental enhancements • Purposive / strategic • Data sources and other components of injury surveillance developed specially to serve this purpose AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

30. Approaches AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

31. Status Fatal and serious injury • Hospital separations and deaths • Cross-sectional and trends • Better understanding of data -> better use • Good useable system • Will benefit from further validation, etc • Basis for • Reporting of indicators • Numerous analyses of specific topics • Use with cost-models for good injury costings • Use in GBD models • … AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

32. Status Occurrence • Incident fatal & severe injury • Characterised in terms of ICD-10-AM, LoS, threat to life, demographic characteristics etc. • Period: deaths - many years, hospitalised – c. 10 years • 1-2 year lag (2-3 y latency for system changes) Risks and burden • Population-based rates • Age/sex/remoteness/SEIFA/CoB/etc (+/- indigenous status) • Other denominators • Potentially diverse; patchy availability • Other units • Cost, DALYs AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

33. Status Change in occurrence (trends) • Challenges: • Hospital data • (largely) not person-linked: multiple counting • differences in admission/recording: variable sample • variations in data quality • Deaths • ‘Injury death’ vs UCoD External Cause • changes in coding some types of death • Manageable with care … AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

34. Future? • Technical developments • Maintenance • Operational links AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

35. Future? Technical developments 1. Standards For comparable & meaningful data… 2. Outcomes Measure & describe outcomes of injury (in addition to death) 3. Linkage Illness service utilisation data, case data/event data, case data/population data 4. Denominators / exposure data Better population data (nb Indigenous); other denominators 5. Knowledge, attitudes, behaviour …of Australians concerning injury, injury prevention, interventions AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

36. 1. Standards Needed for comparable & meaningful data • Including: • Operational definition(s) of ‘injury’ • For deaths, hospital data, other sources • Australia: Technical Review & Revision of injury indicators • International: ICE on Injury Statistics; ICECI • Classifications • ICD-10, ICD-10-AM, ICECI • Data standards / minimum data sets • NDS-IS, NCIS data set • Survey questions • Opportunities: • Consideration/contribution to/adoption of international standards • Further development & updating of Australian standards AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

37. 2. Outcomes Measure & describe outcomes of injury • Overview: • Fairly good methods to measure threat to life of injury • AIS & derivatives, GCS etc, ICISS • Much of burden of injury is due to consequences other than death • Methods to measure ‘threat to health’ of injury are immature • Progress is likely to require large and expensive prospective studies • Opportunities: • Collaborative project(s), national or international AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

38. 3. Linkage Potential for more information from existing data • May include: • Person-based linkage of illness service utilisation data, etc • Linking case data to event data (eg hospital / crash) • Linking case data to population data (eg enhanced census) • Linking special injury register data to any of these • Opportunities: • Collaborative projects using WA Linked Health Data • Advocacy for similar capabilities elsewhere • National developments AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

39. 4. Denominators/exposure data Potential for more information from existing case data • Types of denominators: • Better population data • nb reliable estimates of Indigenous population • Injury risk factor / exposure data • Eg. more specific sports-participation data, alcohol use data, travel/vehicle use data • Injury protective factor / intervention • Eg participation by older persons in specified exercise activities • Opportunities: • Diverse AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

40. 5. Knowledge, attitudes, behaviour Knowledge, attitudes, behaviour • …of Australians concerning injury, injury prevention, interventions • Themes: • Knowledge • What is the extent, distribution and reliability of knowledge about injury occurrence, consequences and potential for prevention. • Attitudes • What is the direction (positive or negative) and strength of attitudes towards injury prevention generally and to specific interventions. • Behaviour • What are the population patterns of certain behaviours that increase or decrease injury risk • Opportunities: • CATI surveys AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

41. Future? Maintenance • Maintain current data sources & quality • eg loss of items from ABS mortality data • eg signs of possible deterioration of injury coding in some hospital records • Ensure good understanding of data • Validation studies (eg ARC project) • Continue to tap value from existing sources • Novel analytic methods (eg ICISS) • More efficient analysis & access (cf US WISQARS) • Minor changes (eg ICD-10-AM biennial revisions) AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

42. Future? Operational links • Better understanding of uses and users • Governments, researchers, industry, community • Consult, discuss, seek feedback • Look for lessons in related activities • Other public health surveillance ane information activities • Injury surveillance elsewhere • Close liaison with policy-makers • Individually and though national forums • Health and other sectors • Seek two-way connection with policy • … in which surveillance information • helps shape policy • supports its implementation and monitoring AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

43. Review Injury surveillance systems & information Purposes Information to support injury prevention & control Approaches Opportunistic and purposive Status Good system for severe and fatal injury Future • Standards; Outcomes; Linkage; Denominators/exposure data; Knowledge, attitudes, behaviour • Maintenance • Operational links and relationships AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

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45. Why better now? • Ten year series of data • Quality fairly good and has generally improved • Completeness • Similarity between jurisdictions • Better understanding • Of data strengths and limitations • Development of concepts and methods • Eg severity measures, injury definitions AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

46. Trends in injury incidence: issues • Records are for inpatient episodes, not persons injured • Proportion of incident injury cases resulting in admission might change over time. • Identifiability of separation records as relating to an “injury” might change over time AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

47. Burden of hospitalised injury Hospitalisation due to Accidental Falls ages 65 and older, Australia 1995-6 to 2002-3 AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

48. SCI: trends and priorities Persisting Spinal Cord Injury due to motor vehicle accidents, ages 15y and older, Australia 1995-6 to 2003-4 AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

49. Improvements • Understanding the data • Estimating incident cases • Comparability over time & between places • Coding validation (ARC project) • Completeness (external cause codes, activity, etc) • New uses of the data • ICD-based severity measures • Classification • ICD-10-AM 3rd • ICD-10-AM 5th AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University

50. Classification • ICECI • Development was prompted by dissatisfaction with ICD External Causes classification: • Lagged behind theory (eg energy transfer concept) • Technical defects (eg not multi-axial) • Developed by international collaborative group • Challenges: • Enable refinement • Keep current • Translation (concepts as well as language) • Minimise burden of maintenance AIHW National Injury Surveillance Unit Research Centre for Injury Studies, Flinders University