Effect of automated health monitoring based on rumination, activity, and milk yield alerts versus visual observation on herd health monitoring and performance outcomes

A primary objective of this randomized trial was to compare the percentage of cows that underwent clinical examination and were diagnosed with clinical health disorders (CHD) with a health monitoring program that relied only on automated monitoring system alerts vs a program that relied only on visual observation of clinical signs of disease to select cows for clinical examination. Another objective was to compare the effects of these health monitoring programs on milk yield, the herd exit dynamics (i.e., cows sold and dead), and first service reproductive outcomes. Lactating Holstein cows (n = 1,204) enrolled in the experiment were fitted with a neck-attached sensor of an automated monitoring system (HR Tags; Merck & Co., Inc.) that generated health alerts based on rumination time and activity. Milk yield was monitored 3 times per day by automated milk meters (MM27BC, DeLaval). Cows were blocked by parity, close-up period diet, and stratified by previous lactation milk yield, and then were randomly assigned within block to different programs for monitoring health from 3 to 21 d in milk (DIM). Cows in the visual observation group (VO; n = 597) were selected for clinical examination exclusively based on visual observation of clinical signs of disease, whereas cows in the automated health monitoring group (AHM; n = 607) were selected for clinical examination based on health alerts consisting of the following: a Health Index Score < 86 arbitrary units, daily rumination < 250 min, or a reduction of > 20% in daily milk yield. Once selected for examination, the clinical exam was the same for both treatment groups. Binary data such as the occurrence of CHD, herd exit, and pregnancies per AI were analyzed with logistic regression. Daily and weekly milk yield were analyzed using ANOVA with repeated measurements. More cows underwent a clinical examination, more cows were diagnosed with at least one CHD, and more cows received treatment in the AHM than the VO treatment group. Cows in the AHM treatment had more accumulated milk than cows in the VO treatment from 2 to 21 DIM. Cows in the AHM treatment diagnosed with at least one CHD produced more milk from 3 to 18 and 20 to 21 DIM than cows diagnosed with a CHD in the VO treatment. Fewer cows left the herd up to 21 DIM for the AHM than the VO treatment. Pregnancies per AI at first service were greater for the VO than the AHM treatment at 30 d but not at 50 d after AI and no difference in pregnancy loss was detected. In conclusion, a health monitoring strategy that used automated health alerts increased the risk of undergoing clinical examination and having CHD diagnosed compared with a program that selected cows for clinical examination based exclusively on visual observation. Cows monitored with the program that relied on automated alerts also had greater milk yield in the first 21 DIM. Thus, monitoring cow health based on automated behavior and milk yield alerts might be a more effective alternative for health monitoring than exclusive use of visual observation of clinical signs of disease.