Economic evaluation of risks to producers who use milk residue testing programs

Barrett Durand Slenning From the Population Medicine Program, Department of Food Animal and Equine Medicine, College of Veterinary Medicine, North Carolina State University, Raleigh, NC 27606 (Slenning), and the Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, CA 95616 (Gardner).

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 DVM, MPVM
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Ian Andrew Gardner From the Population Medicine Program, Department of Food Animal and Equine Medicine, College of Veterinary Medicine, North Carolina State University, Raleigh, NC 27606 (Slenning), and the Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, CA 95616 (Gardner).

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 BVSc, PhD

Objective—

To evaluate the decision to test for milk antimicrobial residues in milk from dairy cows treated with procaine penicillin G (PPG).

Design—

Economic-decision analysis after stochastic simulation.

Sample Population—

1,000 computer-simulated cows/model.

Procedure—

Meta-analysis of the Food Animal Residue Avoidance Databank was used to generate PPG disappearance curves for cows given single PPG treatments, IM, of 6,600 U/kg (3,000 U/Ib) of body weight or 26,400 U/kg (12,000 U/lb), and multiple treatments at 26,400 U/kg (12,000 U/lb), IM. These curves were entered into 1,000-replication stochastic pharmacokinetic models, generating population-level milk PPG profiles for each treatment group for each day after treatment, which were subjected to economic-decision analyses of feasibility of residue testing. The model was evaluated for changes in herd size, proportion of herd available for testing, milk production, test price, test sensitivity/specificity, and withdrawal periods.

Results—

For both single-treatment groups, a 2-day withdrawal period avoided violative residues. However, nearly two thirds of the cows risked false identification for violative residues. For the multiple-treated group, nearly 40% had violative residues after a 5-day withdrawal period, and an additional 10 to 15% risked false identification for violative residues. Economic analysis yielded a decision against testing; mean cost was $2 (ie, 5% more than the mean cost of not testing).

Clinical Implications—

Complex dynamics of current milk residue tests discourage practitioners from recommending procedures to clients. In general, increases in herd size, milk production, proportion of a herd available for testing, or milk price will increase the value of testing. Increasing test sensitivity decreases its desirability to producers. (J Am Vet Med Assoc 1997;211:419–427)

Objective—

To evaluate the decision to test for milk antimicrobial residues in milk from dairy cows treated with procaine penicillin G (PPG).

Design—

Economic-decision analysis after stochastic simulation.

Sample Population—

1,000 computer-simulated cows/model.

Procedure—

Meta-analysis of the Food Animal Residue Avoidance Databank was used to generate PPG disappearance curves for cows given single PPG treatments, IM, of 6,600 U/kg (3,000 U/Ib) of body weight or 26,400 U/kg (12,000 U/lb), and multiple treatments at 26,400 U/kg (12,000 U/lb), IM. These curves were entered into 1,000-replication stochastic pharmacokinetic models, generating population-level milk PPG profiles for each treatment group for each day after treatment, which were subjected to economic-decision analyses of feasibility of residue testing. The model was evaluated for changes in herd size, proportion of herd available for testing, milk production, test price, test sensitivity/specificity, and withdrawal periods.

Results—

For both single-treatment groups, a 2-day withdrawal period avoided violative residues. However, nearly two thirds of the cows risked false identification for violative residues. For the multiple-treated group, nearly 40% had violative residues after a 5-day withdrawal period, and an additional 10 to 15% risked false identification for violative residues. Economic analysis yielded a decision against testing; mean cost was $2 (ie, 5% more than the mean cost of not testing).

Clinical Implications—

Complex dynamics of current milk residue tests discourage practitioners from recommending procedures to clients. In general, increases in herd size, milk production, proportion of a herd available for testing, or milk price will increase the value of testing. Increasing test sensitivity decreases its desirability to producers. (J Am Vet Med Assoc 1997;211:419–427)

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