Seminar on “Intelligent data analysis and data mining – Application in medicine”

1. Seminar on “Intelligent data analysis and data mining – Application in medicine” Research on poisonings in children: public health perspective for the development of clinical algorithms by Dr Sergio Pièche Clinical algorithms in public health

2. Developing clinical algorithms in public health The problem The target Principles Research Clinical algorithms in public health

3. Developing clinical algorithms in public health: The problem Injuries • Mortality: causing deaths • Morbidity: burden of the condition • Age group at risk • Costs: hospital and primary health care • Likely impact of interventions Clinical algorithms in public health

4. Developing clinical algorithms in public health: The target Health providers at primary health care level: • Health background: doctors, medical assistants, nurses, other health workers • Type of facility: equipment, supply, access to referral facility Clinical algorithms in public health

5. Developing clinical algorithms in public health: Principles • Safe and effective guidelines: • Sensitive and specific clinical signs • Minimum number of clinical signs • Requiring simple skills to be used • Standard and simple assess-classify-treat system • Possible to teach and learn • Minimum number of essential drugs • Best care possible for severe cases Clinical algorithms in public health

6. Clinical algorithm Clinical algorithms in public health

7. Developing clinical algorithms in public health: Research • Hydrocarbon poisoning • Organophosphate poisoning Clinical algorithms in public health

8. Developing clinical algorithms in public health: Research on poisoning: prospective study Clinical predictors of severity of accidental poisoning from hydrocarbons and organophosphates in children below 5 years old Clinical algorithms in public health

9. Developing clinical algorithms in public health: Research on poisoning: aim …to develop an algorithm for the outpatient management of children with hydrocarbon and organophosphate poisonings at primary health care facilities in developing countries. Clinical algorithms in public health

10. Developing clinical algorithms in public health: Research steps • Derivation of clinical decision rule (factors with predictive power) • Prospective validation of the algorithm in different settings • Provider performance analysis • Impact Clinical algorithms in public health

11. Developing clinical algorithms in public health: Research approach • Identification and standard definition of signs and symptoms • Gold standards for diagnoses • Definition of outcomes • Observer variability and bias • Procedures (protocol and instruments; training, supervision) Clinical algorithms in public health

12. Developing clinical algorithms in public health: Research methodology - 1 Enrolment • Children 2 to 59 months old • History: unintentional exposure to hydrocarbons or organophosphates • Acute exposure • Seen within 48 hours of exposure to poison • New cases Clinical algorithms in public health

13. Developing clinical algorithms in public health: Research methodology - 2 Procedures • All children admitted for at least 48 hours post-exposure irrespective of severity (written consent and free admission) • Examined by study physician + investigations upon admission • Followed up at 6, 12, 24, 48 hours post-exposure • No delay or interference with quality care Clinical algorithms in public health

14. Follow-up Clinical algorithms in public health

15. E.g. Hydrocarbon poisoning Clinical algorithms in public health

16. Developing clinical algorithms in public health: Research methodology - 3 Sample size • To detect the overall association and prediction of common symptoms and signs with poisoning severity and outcome • To account in the analysis for stratification of cases in sub-groups based on time of exposure to poison Clinical algorithms in public health

17. Key questions • Which common clinical signs and symptoms best predict poisoning severity and outcome? • How long is the safe clinical observation period before sending home a child who has been exposed to hydrocarbons or organophosphates? Clinical algorithms in public health

18. Developing clinical algorithms in public health: Research: Analysis • Chi-square statistics or Fisher exact test, risk differences, risk ratios, odds ratios • Multivariate logistics regression - incl. stepwise techniques • Data mining techniques to be considered • Sensitivity, specificity, predictive accuracy Clinical algorithms in public health

19. Data analysis: The challenge! Clinical algorithms in public health