Dr. John Wenz presented this material for DAIReXNET on Monday, March 4, 2013. For more information, please see our archived webinars page at www.extension.org/pages/15830/archived-dairy-cattle-webinars.

1. “Good Health Records”
The Foundation of Consistent,
Effective Dairy Health Management
John R. Wenz DVM, MS
www.goodhealthrecords.com

2. Despite all our Knowledge
% Cows with Disease is Rising
USDA, 2008 #N481.0308

3. Dairy Health Management
You know what to do…
You don’t always know how well it’s getting done
www.dairymoos.com
“Good” Health Records are the Foundation of
Consistent, Effective Dairy Health Management

4. Good Health Records Program
in WA and ID
• Survey Dairy Producers (243)
• Develop Software to Evaluate Outcomes
• Demonstration Herd Project (43 herds)
Dr. Sarah Giebel
– Impact of Standardized Health Records
• Time for recordkeeping
• Importance of Feedback
• Value

5. Dairy Health Record Quality is Poor
• Lack Accuracy and Consistency needed for
efficient summary and analysis
Kelton et al., 1998; LeBlanc et al., 2006;
Appuhamy et al., 2007; Wenz and Giebel, 2012
• “…many health record entries are focused on
treatment, rather than diagnosis...”
Nordlund and Cook, 2004

6. WA and ID Survey of Health Records
Wenz et al., 2012 J.Dairy Sci. 95 Suppl.2:260
• Only 17% dissatisfied with quality and utility
of their computer health records.

7. Perception of Health Record Quality is
Based on Intended Use
• producers generally utilize individual animal
data, whereas practitioners … are more
concerned with herd summary information”
(Etherington et al., 1995)
• Health Records are USER – DEFINED Why?
• Variable Disease Definitions

8. User-defined Records  Inconsistency
Between and Within Dairies
Metritis
User-defined events used to
record metritis on 50 dairies METR
using Dairy Comp 305® METRITS
Wenz and Giebel, 2012 HOSP
ILL
TEMP
How was health data recording decided? DIRTY
• 52% “Made it up as we went along” TREATED
Wenz et al., 2012 J.Dairy Sci. 95 Suppl.2:260
FLUSHED
INFUSED
PEN

9. The PMO Provides a Standard for
Complete Treatment Records
• Identity of animal(s) treated
• Date(s) of treatment
• Drug(s) administered
• Dosage administered
• Milk discard time; and
• Withdrawal time prior to slaughter
• Disease being treated (Not in PMO)*
• Who administered treatments (Not in PMO)
*But, Ailment treated is determined when a
residue violation is investigated

10. 3+4
Meeting FDA Treatment Records
Requirements
• Can be a combination of Electronic and Written
(Confirm in your area)
• Example:
– Computer:
• ID, Date, Disease, Drug, Withhold times and dates
– Paper/Written:
• Treatment protocol book: Disease, Drug, Route, Dose
• Daily Hospital List: ID, Date, Disease, Drug, WHO treated
10

11. FDA Warning Letter June 2010
• “Our Investigation also found that you hold
animals under conditions that are so
inadequate that medicated animals…are likely
to enter the food supply. For example, you
failed to maintain complete treatment
records.”
11

12. FDA Turning up the Heat on Residues in Milk
Results due any day now

13. USDA Turning up the Heat on Residues in Meat
August 2012

14. New Multi-Residue Method (MRM)
Testing is More Sensitive, More Drugs
DRUG (Partial List) Bovine Kidney Old Test
ug/g ug/g
Ampicillin (Polyflex) 0.02 0.05
Beta-dexamethasone 0.05 -
DCCD (Excenel/Excede) 0.2 -
Enrofloxacin (Baytril) 0.025 -
Florfenicol (Nuflor/Resflor) 0.1 -
Flunixin (Banamine) 0.0125 -
Lincomycin (LS-50) 0.05 1.5
Oxytetracycline 0.5 0.4
Penicillin G 0.1 0.05
Sulfadimethoxine (DI-METHOX) 0.05 -
One of 17 drugs other than intramammary, used to treat mastitis on 102 dairies
No Tolerance for any residue in lactating dairy cattle
ILLEGAL use (not labeled for mastitis, extra-label use not allowed)

15. “Creative” drug use is fostered by
misconceptions of the uninformed

16. Need to Change the Focus of Dairy
Health Management
Perception at the Cow Level
What Drug?
When can milk or the cow be shipped?
Evidence at the Herd Level
Outcomes of Health Management
Good Health Records

17. You need Health Records
more like Repro Records
Standardized
Fast and Easy Evaluation of Outcomes
Repro Records Health Records
• System defined • User-defined
– Standard data entry – Whatever you want
– Consistent remarks – However you want
• Outcomes evaluation • Count keeper
– Conception rate – # of Events
– Pregnancy rate
• Accurate and Consistent • Variable accuracy and
consistency

18. To be “Good”, Health Records Should
Support:
• Individual cow management decisions
• Residue avoidance/Regulatory compliance
• Outcomes-based health management
decisions

19. 3 Simple Rules for Good Health Records*
1. Record ALL Disease Episodes
– Regardless of severity or therapy
– Each Quarter or Foot as separate episode
2. Use a SINGLE, SPECIFIC Event for Each Disease
– Record Diseases not Treatments
– Differentiate Clinical from Subclinical/Screening
3. Record CONSISTENT Event Remarks
– Same INFO (Treatment, Quarter, Severity)in the
– Same ORDER using the
– Same ABBREVIATIONS
*http://extension.wsu.edu/gdhr/information/how/pages/default.aspx

20. Good Records are achieved through Standard
Protocol Implementation*
Protocols must Balance 3 Key Functions of Health Records
NT – No treatment intend to keep
BF – No treatment will be sold
*Until dairy management software companies make disease entry
the same as entry of breedings (standardized)

21. Keeping Good Health Records
Doesn’t Take Longer
Time Budget Analysis
Time to Capture and Enter Data
Before and After Standard Protocol Implementation…
Capture Entry
Increase 4.5% (1/22) 22.2% (4/18)
Decrease or
95.5% (21/22) 77.8% (14/18)
No Change
Giebel et al., 2012 JDS 95 Suppl. 2:9

22. Veterinarians Need to be More Involved in
Health (Records) Management
• WA and ID Health Records Survey Respondents
– 80% - Vet Valuable Resource for Health Records
– 30% - Vet helps decide how to record health data
– 35% - Vet evaluates health record summaries
www.goodhealthrecords.com
http://extension.wsu.edu/gdhr/tools/Pages/VetGuide.aspx

23. HEALTHSUM Dairy Health Database
A tool available through veterinarians to
Evaluate the Outcomes of
YOUR Management, YOUR Cows on YOUR Dairy
• Is Your Prevention Program Effective?
– Disease incidence Monitoring and Alerts
• By risk group (Pen, Lactation…)
• Is Your Treatment Program Effective?
– Retreatment
– Recurrence
– Removal

24. Prevention Efficacy Example:
Clinical Mastitis Incidence
• New vs. Recurrent*, ALL Clinical Mastitis (% Milking Herd)
*
*Cow had mastitis episode 15-60 days prior

25. Pen Level Incidence Example:
A Story of Two Identical Open Lot Pens
Pen 56 (Avg.) – 120 cows, Lact – 2.9, DIM – 191, CM* – 10%
Pen 58 (Avg.) – 123 cows, Lact – 2.8, DIM – 200, CM* – 5.2%
* CM – Clinical Mastitis

26. Treatment Efficacy Example:
OUTCOMES of Clinical Mastitis Episodes that Occur in a Month
• Evaluated by Risk Groups
– Lactation group
– Initial treatment
– Culture Result
• Retreatments
24 WA+ID herds Median (5.8%)

27. Treatment Efficacy Example
OUTCOMES of Clinical Mastitis (CM) Episodes that Occur in a Month
RECURRENCE –
CM Same Quarter 15-60 days later
24 herd Median (7.4%)
LOST QUARTER –
Dried or Killed quarter
17 herd Median (1.8%)
REMOVAL –
Sold or Died within 14 days of CM
24 herd Median (12%)

28. Clinical Mastitis Treatment Efficacy
• Recurrence by Culture Result Example
Coliforms No Growth Coag. Neg. Staph. Env. Strep.

29. Take Homes
• Need Dairy Health Management more like
Repro Management
– Change from Perception at the cow-level to
Evidence (Outcomes) at the herd-level
• “Good” Health Records Support:
– Individual cow management decisions
– Residue avoidance/Regulatory compliance
– Outcomes-based health management decisions

30. Take Homes
• Don’t need standard disease definitions to
Standardize Health Records
• Each dairy needs Standard Data Recording
Protocols
– Guided by the 3 Simple Rules of Good Records
• Resources at www.goodhealthrecords.com

31. Questions?
• Acknowledgements
– USDA NIFA for Funding
– WA and ID Dairies and Veterinarians
– Dr. Sarah Giebel and Sandy Poisson
– Drs. Dale Moore, Chris Schneider, David
Galligan, Ray Jussuame
www.goodhealthrecords.com