1. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Proportion of patients admitted following injury – setting a “frame” for analysis of variation with diagnosis, calendar year, age and sex? JM.Lauritsen Accident/Injury AnalysisGroup. Dept. of Orthopaedics Odense University Hospital, Odense Denmark. Contributions by Thomas Foged.

2. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Setting Denmark – Europe Odense University Hospital A&E dept. Public financing (tax) no fee for contact Data Recording: Patient system Population: 225000 Trauma center level 1 (one fifth of Denmark about 1 mio) Previous study showed that ICISS figures are comparable btw. Denmark and Australia

3. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community ICISS severity grading of emergency room contacts – Are Danish values comparable to the original AUS/NZ values ? Overall comparability between Denmark and Australia. Although there are differences in diagnosis specific survival proportions btw. Danish and Australia – the good story is that when calculating overall survival probability (ICISS) differences are minor. This indicates that possibly ICISS can be calculated based on SRRs derived from data from other parts of the world. The question is then about patterns of diagnosis and admission

4. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Material for study Period : Jan 1st 1994 to June 30th 2006 Contacts : Injury general: (n=421283) Violence: (n=12104) Excluding : Medical cause and attempted suicide Data completeness : No diagnosis coded: n=1 (whole period) No admission status:n=5 (whole period) No cause of contact registration: < 50 records per year

5. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Material in analysis Period: Jan 1st 1994 to June 30th 2006 From 1 – 5 S/T diagnoses per patient Only contacts with at least one S/T diagnosis are included in analysis: n= 410139 patients nd = 481778 diagnosis codings ndc= 1024 different S/T codes (3 digit) 108 (2 digit)

6. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Analysis phases Phase 1:Variation in admission by age, sex and period (patient level) Phase 2:Investigation of positional stability of diagnosis Phase 3:Proportion of mortality known Phase 4: Analysis of variation by diagnosis

7. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Phase 1: Percentage of admission by age, sex and period (patient level): AgePercent95% CI < 20 5.45.3- 5.5 20-40: 6.86.7- 6.9 41-64: 10.9 10.7-11.2 65+Males: 25.024.2-25.8 Females:30.029.5-31.0 No Period effect

8. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Phase 2: Position of diagnosis From 1- 6 diagnoses coded. For 1% of patients S/T was not the first. –These patients had 15.8 % of all S/T diagnosis Admission percentage: –S/T was not first: 22.3% (CI 22.0-22.6) –S/T was first: 9.0% (CI 8.9-9.1) No period effect, but large “position effect” - OR 2.6 (CI 2.5-2.7)

9. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Phase 3 Variation in proportion of ”dead on arrival” and “all mortality” Died as inpatient: N=736 Dead on arrival:N=382total: 1118 Diagnostic problem: Only 1/3 autopsy Time pattern: percentage ”dead on arrival” 40% in 1994 26% at end of period (Highly significant trend) Consequence: Registerfollow-up to determine e.g. 7 day, 30 day and 1 year mortality, plus alternate sources.

10. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community The problem is what we do not see (unreported cases)

11. Department of OrthopaedicsAccident/Injury Analysis Group Funen County a WHO Safe Community Conclusion Phase1: Variation in admission levels with - sex and age, but not with period. Phase 2: Variation with position of first S/T diagnosis, but no period effect. Phase 3: Highly significant variation (trend) in composition of mortality known at hospital (Underreporting and insufficient diagnostics). Phase 4: Before starting we need clear definitions of who to include, how to handle mortality, age and sex issues.