5. ConclusionThe development of the DD Check App successfully standard-izes the recording of M-stages of DD, and the app automated thedescriptive and predictive analyses of such longitudinal data. Theapp is flexible enough to be used at different levels of record detailand in different situations to discover statistically significant trendsin the observed or predicted prevalence of M-stages to help makeinformed decisions to prevent and control DD on-farm. The appassigns Cow Types, creates treatment lists, and produces data setsfor distribution between herd managers. It can be utilized by userswho do not have a statistical background to predict near futuretrends of DD in endemically affected farms. Cattle can be scoredduring pen walks, at the milking parlor or using a cattle chute, andthe app can be used to compare different subsets of cows. Sim-ilar apps aimed at standardizing field data sets will increase theawareness and understanding in the industry resulting in improvedprevention and control of endemic production diseases. Futureapplications will include economic models to estimate cost andreturn of treating certain DD lesions or implementing preventionand control methods. Prevalence and cow characteristics from farmmanagement programs could be linked to the model to visualize theassociation of cow and farm level risk factors with DD.