TREAT – A Decision Support System TREAT – A Decision Support System for Antibiotic Treatmentfor Antibiotic Treatment

S. Andreassen1, L.E Kristensen2,

L. Leibovici3, U. Frank4,

J. H. Jensen1, H. C. Schønheyder5 1Aalborg University, Denmark

2Judex Datasystems A/S, Denmark3Rabin Med. Ctr., Petah-Tiqva, Israel

4Freiburg Univ. Hosp., Germany

5Aalborg Hospital, Denmark

Supported by an EU 5th Framework grant

(TREAT, IST 1999-11459)

Operational project goals

1. Build TREAT - a model of infections and their therapy, based on Causal Probabilistic Nets and on Decision Theory

2. Implement TREAT as a system integrated into the hospital information infrastructure (TREAT-LAB and TREAT-WARD)

3. Test TREAT in 3 countries to show that it can improve diagnosis and treatment of severe infections by

• reducing the percentage (30-40%) of inappropriate antibiotic treatments to half, thereby reducing the infection related mortality

• reducing cost of therapy

• restricting the use of broad-spectrum antibiotics

• stemming the rise of antibiotic resistance

4. Achieve scientific and commercial dissemination

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

2. to demonstrate the value of morphology, Gram stain and motility

Two urinary tract pathogens

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

Likelihood E. Coli * 2

Treatment = Gentamicin

The value of morphology, Gram stain and motility

Gram negative rods isolated from blood culture

Urinary tract = Yes,Motility = Peritrichous

Databases for local calibrations

To adapt the TREAT system to a given hospital,

databases are needed for:

• Infection related mortality

• Cost of treatments

• Antibiotics

• Resistance and cross-resistance

• Pathogen prevalences (influenced by risk factors,

ICD diagnoses)

Database for crude mortality

Mortality per site of infection dependent on coverage of empirical and semi-empirical treatment

Database for costs of treatments considered by TREAT

Database for antibiotics

Resistance and cross-resistance (Nosocomial E. coli infection)

Balance for each antibiotic drug:

• Benefits:– reduced mortality,

morbidity and hospital stay related to coverage, activity at the site of infection, and synergism.

• Detriments:– cost of drug,

administration and monitoring.

– side-effects.– ecological costs.

Non-interventional study in 813 Danish bacteraemic patients:

N=813

Age>65 yrs. 61%

ICU 11%

Source: Urinary 28%

Source: Abdominal 23%

Source: Lungs 13%

30-day fatality 20%

Non-interventional study in 813 Danish bacteraemic patients:

Physician - empirical

Physician-semi

DSS

Coverage 59% 78% 87%

Mean cost, $ 187.5 223.5 201.0

Mean, side-effects, $

100.0 115.0 117.5

Mean, resistance, $

1626.5 1874.5 1511

Physician - empirical

Physician-semi DSS

AbdAbd: No. of regimens

17 21 7

AbdAbd:% of pts. prescribed broad spectrum

2.1% 3.1% 0%

UTIUTI: No. of regimens

18 20 6

UTIUTI:% of pts. prescribed broad spectrum

2.3% 3.2% 1.6%

Non-interventional study in 813 Danish bacteraemic patients:

Conclusions:

• TREAT – a computerised DSS – prescribed appropriate antibiotic treatment more often than the attending physician, while using less broad-spectrum antibiotics at a lesser cost.

• The use of a causal probabilistic net as the basic model allowed us to combine data from several sources with knowledge; and to calibrate the system to different sites, in different countries.

• A randomised, controlled trial of the system in 3 countries is due to start in 6 months.