Particularly on dairies with hired labor, or where more than one person is responsible for the same job, written protocols are critical to ensuring everyone knows the plan. Written management plans are more commonplace for milking parlor procedures, reproductive management, calving and colostrum management. You likely already have a Health Record Management Plan; it just may not be written down and may have been developed on an ad hoc basis overtime. Follow these steps to determine what data need to be recorded to critically evaluate health data flow and health data recording and evaluation and develop a written Health Record Management Plan.
Assessing Data Needs
Determining the questions you want to ask the cows regarding health management dictates what data needs to be recorded to get the answers. Work with your veterinarian and others on your health management team to come up with a list of questions to which you want the answers.
An example for clinical mastitis:
- Are clinical mastitis prevention measures being effectively implemented?
- Are clinical mastitis treatment protocols effective?
To answer these questions the following definitions and data are needed:
- Definitions for clinical mastitis episodes
- NEW–First episode in that quarter during the current lactation
- RTX-Treatments given within 14 days after the initial treatment protocol
- Ex. Protocol is treatment ‘X’ once a day for 3 days. On day 4 the cow still has clinical mastitis and a second course of treatment ‘X’ is given.
- RECUR–Second or greater clinical episode in that quarter during the current lactation (15-60 days after prior clinical episode).
- Needed data for each clinical mastitis episode to answer those questions:
- Quarter affected
- Treatment given
- Pen cow was in at time of clinical episode (assess pen level prevention measures; hygiene)
Data should flow from the point of action at the cow (data capture) to entry into the health record system (data entry) involving the fewest people and least number of steps possible. Over time unintended complexity and unnecessary data capture and recording can develop with ‘ad hoc’ plans resulting in loss of one of the most valuable resources on a dairy-TIME. Istime being wasted on your dairy? Use the Data Flow Assessment Tool to find out.
Data Capture- Who will capture what, where, when and how?
Cow people should be doing cow work, not excessive paperwork. However, some is required if the dairy is to have “Good Health Records” and optimize the effectiveness of the cow work they do. It is critical to keep data capture as simple and convenient as possible, making use of forms and methods already in place with some modification as needed.
There is a common perception that keeping “Good Health Records” will involve ‘a lot more paperwork’ and time. However, often critical evaluation of data flow on the dairy results in streamlining paperwork and a reduction in the time required.
- Consider the herdsman who would write all treatments on his pocket notepad during treatments. Afterwards he would transfer those data onto one of 3 treatment record sheets: a ‘Mastitis’, ‘Hospital Pen’ and ‘Fresh Pen’ treatment sheet. When asked why 3 sheets were needed, management realized they weren’t; they had come into being over the years, no one had questioned how or why they were being used. Those three sheets were replaced with a single ‘Treatment Record Sheet’ with a DX (diagnosis) column that allowed each identification of cows with mastitis vs. other health events vs. fresh cows. The herdsman recorded treatment and a daily ‘severity score’ directly onto the ‘Treatment Record Sheet’ saving at least 30 minutes each day and capturing more data. You increase the likelihood of successful adoption if you stick with the familiar and make someone’s job easier or more efficient that before. Furthermore, you also increase the likelihood of compliance with recording of some new data that may be necessary.
General recommendations for data capture sheets:
- Do not include items for which the ‘correct answer’ can be provided even if the proper procedure was not followed or the fact that something was done can be filled in at a later time even if it was not.
- Ex. ‘Calving Observation Sheet’ with check boxes for hours of the day maternity pen was observed. Instead ask for the time a cow begins in stage 2 labor and the time delivery occurred and the time assistance was given. These data are more information and facilitate accountability.
- Only capture data that will be used and eliminate capture of data that are not used.
- Ex. Every cow with clinical mastitis had a MAST event recorded with a remark: MIM. According to management, workers were supposed to record the severity of clinical mastitis and MIM was an abbreviation for Mild Mastitis. Turns out the workers thought it just meant mastitis and all cows had the MIM abbreviation and none received the MOM (Moderate Mastitis) or SEM (Severe Mastitis). Clearly these severity data were not being used by the dairy or someone might have noticed the strange fact that cows only had mild clinical mastitis.
- Reduce redundant steps in data capture. Streamline the process, where possible, by capturing data (writing it down) on the same sheet that will be read for data entry.
For herds using dairy management software on a computer, protocols for data entry will be necessary to ensure accurate and consistent health records.
- The fewer the better: the fewer people responsible for data entry the better for keeping consistent records.
- Limit data entry to those:
- Needed for computer generated lists
- To be summarized for the entire herd to evaluate management
- If the data can be just as easily evaluated on paper don’t enter it into the computer.
Health Data Entry Protocol Examples—These documents provide examples of the format of a health data entry protocols for Dairy Comp 305 and DHI-Plus/RX-Plus
A guide to understanding the diagnosis, treatment and recording of the major diseases of dairy cattle on the farm