Management of Data for Health Performance Measurement in the Industrialized Dairy Herd

Abstract

One part of dairy herd management is to handle disease occurrence by means of health promotion, disease prevention, timely medical treatments, or eradication of disease. Supporting this part of herd management is an essential task for the cattle veterinarian. The study objective was to identify principles and tools for analysis of herd health data in industrialized dairy herds. The analysis takes into account the additional complexity caused by changes in behavior among herd managers and herd personnel due to, for instance, legislative changes to promote animal welfare or food safety. Methods from herd management science were combined with context-specific information about social mechanisms. The results were synthesized into a concrete 7-step plan of action, as follows: (1) As the foundation, use continuously process behavior charts primarily based on animal-level data. (2) Assure strict definition of the measurements considering purpose, collector and meaning in terms of biology and management. (3) Interpret the patterns in the process behavior charts and search for and remove causes of exceptional variation in a dialogue with the herd manager. (4) Search for options to reduce routine variation. Multivariable or multivariate statistical models can give additional information because of their ability to reveal hidden sources of variation. (5) Set targets at the tactical and strategic levels while accounting for costs and benefits with appropriate methods suggested in the study. Issues related to non-financial effects are addressed. (6) Adjust measurement and intervention theory. The previous five steps should initiate an iterative process in which the intervention is evaluated and updated based on the results achieved thus far. (7) Develop a framework in the veterinary practice unit to support the health performance measurement process. The activities in step 7 will almost certainly require expert statistical assistance.