3. TREAT -a Decision Support System for Antibiotic Treatment Supported by an EU 5 th Framework grant Coordinator: Steen Andreassen On behalf of the Treat group: Rabin Medical Centre, Israel Freiburg University Hospital, Germany Universitá Cattolica S. Cuore, Italy Judex Datasystems A/S, Denmark Aalborg University, Denmark

4. The magnitude of the problem The magnitude of the problem The mortality associated with severe bacterial infections is ~30%. The mortality associated with severe bacterial infections is ~30%. A third of patients are prescribed inappropriate empirical antibiotics, and ~20% superfluous drugs (J Intern Med 1998, 244:379; Chest 2000, 118:146 ; Scand J Infect Dis 1997, 29:601; Am J Med Sci 1978, 275: 271). A third of patients are prescribed inappropriate empirical antibiotics, and ~20% superfluous drugs (J Intern Med 1998, 244:379; Chest 2000, 118:146 ; Scand J Infect Dis 1997, 29:601; Am J Med Sci 1978, 275: 271). Inappropriate empirical Rx is associated with an increase in fatality rate: Multi-variable adjusted OR: 1.6 to 6.9 (J Intern Med 1998; 244:379 ); (Chest 2000; 118:146). Inappropriate empirical Rx is associated with an increase in fatality rate: Multi-variable adjusted OR: 1.6 to 6.9 (J Intern Med 1998; 244:379 ); (Chest 2000; 118:146).

5. The magnitude of the problem Maximum empirical antibiotic treatment is not a viable solution. Maximum empirical antibiotic treatment is not a viable solution. Antibiotics account for about 20% of drug expenditures: 7 million NIS for Beilinson per year. Antibiotics account for about 20% of drug expenditures: 7 million NIS for Beilinson per year.

6. The system Causal probabilistic network for the diagnosis and treatment of infections Causal probabilistic network for the diagnosis and treatment of infections Treatment based on cost-benefit model Treatment based on cost-benefit model Benefit: Benefit: –Improved survival with appropriate antibiotic treatment –Reduced beddays Costs: Costs: –Direct –Side-effects –Ecological costs

7. Advantages of a causal probabilistic network (CPN): Natural multiplication of the needed matrices (infection probability X pathogen probability X susceptibilities). Natural multiplication of the needed matrices (infection probability X pathogen probability X susceptibilities). Explicit modelling of universal and local factors. Explicit modelling of universal and local factors. The only way to deal with missing data. The only way to deal with missing data. The only way to combine between knowledge and data from different sources in one system. The only way to combine between knowledge and data from different sources in one system. Cost effectiveness (or benefit) analysis is a natural feature of the system. Cost effectiveness (or benefit) analysis is a natural feature of the system.

8. A model of infections A model of infections A (very) simplified version of the TREAT CPN will be used: 1.to demonstrate the concepts of infection sepsis prognosis (sepsis*) treatment coverage and mortality

9. Two urinary tract pathogens

10. Sepsis = Yes, Treatment = No, Res. Factor = Present (Hosp. Acq.)

11. Likelihood E. Coli * 2

12. Treatment = Gentamicin

13. The value of morphology, Gram stain and motility

14. DLL MB-table COMCOM MS IIS 5 ASP DSS Calib. Treat DB Calib.

15. Local calibration of TREAT Prevalence of pathogens causing infections Prevalence of pathogens causing infections Prevalence of risk factors for infection Prevalence of risk factors for infection Antibiotic susceptibility profiles Antibiotic susceptibility profiles Drugs used and costs Drugs used and costs Local measurement units with normal value ranges Local measurement units with normal value ranges Hint texts for user interface Hint texts for user interface

16. The value of morphology, Gram stain and motility

17. Gram negative rods isolated from blood culture

18. Urinary tract = Yes, Motility = Peritrichous

19. Databases for local calibrations To adapt the TREAT system to a given hospital, databases are needed for: Antibiotics and their costs Resistance of pathogns to antibiotics (hospital vs. community acquired) Pathogen prevalences

20. Database for crude mortality Database for crude mortality Mortality per site of infection dependent on coverage of empirical and semi-empirical treatment

21. Database for costs of treatments considered by TREAT

22. Database for antibiotics

23. 1. All patients for whom antibiotic treatment (but not prophylaxis) is started (whether with a community or hospital acquired disorder). 2. Patients from whom blood cultures are drawn. 3. Patients in whom two or more of the following are present: a.Temperature >38°C or 38°C or <36°C b.Heart rate >90 beats/min c.Respiratory rate >20 breaths/min or PaCO2 20 breaths/min or PaCO2 <32 mmHg d.WBC >12,000 cells/mm3, 10 percent immature (band) forms 4. Patients with a focus of infection, mainly: a new infiltrate on chest x- ray, urinary complaints and leukocyturia, skin findings compatible with skin or soft tissue infections, etc. 5. Patients with shock compatible with septic shock. 6. Febrile neutropenic patients (single oral temperature ≥38.3 or a temperature of 38 lasting ≥ 1 hour). Eligible patients

24. Exclusion criteria: Organ and bone-marrow transplant patients Organ and bone-marrow transplant patients Children<16 years Children<16 years Suspected travel infections Suspected travel infections Suspected tuberculosis Suspected tuberculosis Pregnancy Pregnancy HIV positive patients with a current suspected or identified opportunistic disease and/or AIDS defining illness currently or within the past 6 months HIV positive patients with a current suspected or identified opportunistic disease and/or AIDS defining illness currently or within the past 6 months Re-entries Re-entries HIV+ patients with sepsis included

25. How?

28. Demograhic data: Birth date Sex Department Place of acquisition of infection Background conditions: Background diseases Devices present prior to onset of infection Conditions predisposing to infection present prior to start of episode Antibiotic exposure during the last month Past Current Allergies Sepsis presentation: Vital signs Acute complications Available laboratory assessment

32. TREAT is working! Probability of infection Probability of specific diagnoses Probability of pathogens causing infection Coverage of single and combination antibiotic regimens Cost benefit of these treatments

34. Different determinants of the costs vs. benefits can be displayed

36. TREAT’s first choice shown Please document treatment prescribed to the patient

37. 24 hours later Blood culture Gram stain Blood culture Gram stain Patient still sick! Patient still sick!

39. Open new encounter

40. Enter new findings Add Gram stain results

41. Results may be displayed in life-years or in Euros

42. Please… Enter all patients fulfilling inclusion criteria to the TREAT system Enter all patients fulfilling inclusion criteria to the TREAT system Do not use TREAT as an expert system – it does not replace your infectious disease consultations! Do not use TREAT as an expert system – it does not replace your infectious disease consultations! Be nice to us – we will come and remind you to use TREAT… Be nice to us – we will come and remind you to use TREAT…

43. Ethical considerations Use of the system approved by the local ethics committee Use of the system approved by the local ethics committee Approval based upon testing of the system and local observational trial results Approval based upon testing of the system and local observational trial results Ultimately, choice of treatment determined by physician Ultimately, choice of treatment determined by physician Patient informed consent is not necessary Patient informed consent is not necessary

44. TREAT Observational trial 6-12/2002

45. Methods and objectives All patients fulfilling inclusion criteria were entered into an observational database All patients fulfilling inclusion criteria were entered into an observational database Entry, bacteriological, and 30-day outcome data collected prospectively Entry, bacteriological, and 30-day outcome data collected prospectively Each case presented to TREAT Each case presented to TREAT TREAT advice compared to physician performance TREAT advice compared to physician performance Primary outcome: antibiotic treatment matching in-vitro susceptibility of clinically relevant isolates (‘appropriate treatment’) Primary outcome: antibiotic treatment matching in-vitro susceptibility of clinically relevant isolates (‘appropriate treatment’)

46. Participants FreiburgIsraelRomeOverall Departments65314 Beds12020060380 Patients3486122431203

47. Inappropriate antibiotic treatment

48. Primary outcome Appropriate antibiotic treatment was prescribed to 58% of patients. Appropriate antibiotic treatment was prescribed to 58% of patients. TREAT’s advice was appropriate in 70% of cases (p=0.0001) TREAT’s advice was appropriate in 70% of cases (p=0.0001) Increment in the rate of coverage: relative increase of 21% and an absolute increase of 12% Increment in the rate of coverage: relative increase of 21% and an absolute increase of 12% The improvement reached statistical significance in Rabin, Freiburg, and overall. The improvement reached statistical significance in Rabin, Freiburg, and overall.

49. Secondary outcomes TREAT used a lower number of antibiotic regimens than the physician TREAT used a lower number of antibiotic regimens than the physician TREAT preferred narrow spectrum antibiotics to broad spectrum ones. TREAT preferred narrow spectrum antibiotics to broad spectrum ones. Overall cost, the overall cost at each site and the costs related by the model to future resistance were significantly reduced by TREAT Overall cost, the overall cost at each site and the costs related by the model to future resistance were significantly reduced by TREAT

50. Euros P=0.0001 P=0.03 P=0.0001 TREAT/Physician = 0.5 Treatment costs

51. Conclusions – observational trial TREAT has the potential of improving significantly on the percentage of appropriate empirical antibiotic treatment while at the same time reducing all components of costs, but mainly the costs assigned by the model to future resistance.

52. TREAT Intervention

53. Which patients should be entered to TREAT? Patients for whom antibiotic treatment is, or should be, considered

54. Primary outcome - appropriate antibiotic treatment Analysis by intention to treat, stratified by location, showed a significant improvement in appropriate antibiotic treatment in intervention vs. control, Mantel-Haenzel OR 1.48 (95% CI 1.03-2.11), p=0.033. NControlsIntervention Intention to treat pIntervention Per protocol p Israel409131/ 206 (63.6%)140/ 203 (69.0%)0.2574/87 (85.1%)<0.001 Italy7413/ 24 (54.2%)38/ 50 (76.0%)0.0622/28 (78.6%)0.06 Germany7732/ 43 (74.4%)38/ 44 (86.4%)0.1618/19 (85.1%)0.06 Total560176/273 (64.5%)216/297 (72.7%)0.03114/134 (85.1%)<0.001

55. Table 2: secondary outcomes * general linear model, comparing intervention to control and adjusting for location N patientsControlInterventionP-value * Direct costs, Euro, mean (sd) Israel167825.5 (30.9)25.2 (33.2) 0.47 Italy26384.9 (83.9)79.1 (87.7) Germany37973.5 (85.4)68.9 (75.6) Side effect costs, Euro, mean (sd) Israel167888.5 (1046.9)98.3 (1048.6) 0.96 Italy26324.4 (159.2)74.6 (992.2) Germany379189.8 (1765.5)129.2 (1294.4) Ecological costs, Euro, mean (sd) Israel1678511.7 (439.9)445.9 (404.7) 0.002 Italy263372.2 (248.3)317.2 (282.2) Germany379503.8 (336.7)517.8 (374.6) Total antibiotic costs, Euro, mean (sd) Israel1678612.5 (507.7)546.0 (476.7) 0.007 Italy263540.0 (371.5)487.5 (419.5) Germany379716.1 (522.1)712.1 (532.6) Duration of hospital stay, all patients, median/ mean (sd) Israel14625/ 6.91 (7.7)4/ 6.31 (8.3) 0.03 Italy2196/ 9.5 (9.4)7/ 9.6 (7.5) Germany30514/ 16.3 (12.0)10/ 13.6 (11.2)

56. Thank you