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Background: While farm animal veterinarians receive extensive training in the diagnosis and treatment of individual animals, population medicine or ‘herd health’ has also become commonplace in modern production animal veterinary medicine. Clinicians are increasingly using routinely collected farm data to identify epidemiological patterns in order to implement preventive health management changes on farm. As such, data handling and statistical analysis techniques are becoming more important in farm practice. While data handling and statistical techniques can initially be challenging to learn, a relatively small investment in time spent learning can dramatically reduce the time spent analysing farm outcomes, and provide a useful evidence base on which to base on-farm management decisions. Aim of the article: This article provides a practical guide to data skills for the production animal vet, briefly covering basic descriptive statistics and graphical representations of data. It also includes further examples of more advanced data analysis techniques, such as statistical modelling and the use of coding language.

This article, the second in a two-part series providing practical advice for practitioners on carrying out clinical audits in farm animal practice, focuses on the data collection, analysis and discussion steps of clinical audit. Part 1, which was published in the October issue of In Practice, discussed preparing for and initiating clinical audit in farm animal practice. Both articles are based on findings from a three-year research project looking at the use of clinical audit in farm animal practice. The research included conducting audits using information already in existence in the practice setting, and audits focused on actively collecting information over a period of time in three farm animal practices, and a nationwide survey on the experiences and attitudes of farm animal veterinary surgeons towards clinical audit in the UK. The findings from this work demonstrate that clinical audit is achievable in farm animal practice, with strategic planning, selection of relevant topics and the setting of realistic goals.

The main aim of calf rearing is to produce a healthy calf that is achieving the target growth rate. Calf mortality rate and daily liveweight gain represent appropriate bottom-line ‘output’ measures for evaluating the success of a calf-rearing programme, and they are affected by various ‘inputs’ or aspects of the calf-rearing process. This article summarises how these outputs can be monitored, and highlights how some key input areas can be assessed when output targets are not met.