Evaluating the cost-effectiveness of diagnosing and treating phantom cows in seasonal-calving dairy herds

The objective of this study was to explore the cost-effectiveness of using a progesterone-based synchrony program to manage phantom cows on seasonal-calving dairy farms. Phantom cows were defined as cows that had been artificially inseminated ≤14 d after mating start date (MSD), were not subsequently detected in estrus, and were diagnosed nonpregnant at a pregnancy diagnosis conducted approximately 49 d after MSD. Decision-tree analysis was applied to data from a previous randomized controlled trial in which phantom cows (n = 378) from spring-calving dairy farms were randomly allocated to an untreated control group or were immediately treated with a 10-d progesterone-based synchrony program with fixed-time artificial insemination. The net economic return of treating all cows presented by the farmer for pregnancy diagnosis that were diagnosed nonpregnant was compared with no intervention. The net return was calculated per cow present at MSD because the decision trees followed all cows present at MSD through to mating end date to account for farmers inadvertently presenting ineligible cows for pregnancy diagnosis and possible treatment. Probabilities, costs, and benefits of reproductive outcomes were based on published data and expert opinion. The effects of key variables on the economic return were tested by sensitivity analysis. Phantom cow intervention delivered a net return of NZ$4.451 (at the time of the study, NZ$1 = US$0.6629) per cow present at MSD. The sensitivity of pregnancy diagnosis, the proportion of ineligible cows presented by the farmer for pregnancy diagnosis, and the prevalence of phantom cows were highly influential on the net economic return from phantom cow intervention. These findings suggest that treatment of phantom cows in seasonal-calving dairy farms using a progesterone-based synchrony program is economically viable based on the current model assumptions. Accurate cow selection and pregnancy diagnosis are essential to success, and veterinarians and animal health advisors can improve the net economic return of intervention by selecting farms likely to have a higher prevalence of phantom cows based on the presence of observable risk factors.