BACKGROUND:
How accurate is your vaccine forecasting algorithm? Somewhere between the programmer’s ability and CDC certification lies a twisted road fraught with hard work, resource limitations and exasperation. Are you caught paying for changes every time a new vaccine is introduced or a schedule change takes place? Can you visually demonstrate what parts of your algorithm need work? Ohio created a mechanism for editing and viewing all CDC test cases through a web based interface.

OBJECTIVE:
Demonstrate how to; easily display your immunization algorithm’s compliance with CDC test cases, and make changes to the schedule via a web interface.

METHOD:
First all CDC test cases were entered into our web based system ImpactSIIS. Second, we created a layout that would show the results of all test cases simultaneously. Next we compared the CDC test cases to our algorithm, effectively creating a roadmap of what needed to be fixed. After changes were made and outcomes indicated we were ‘compliant’, end users evaluated the system. Then the real work began.

RESULT:
Being compliant with CDC did not mean the algorithm was correct.
Reviewing all test cases simultaneously reduced the time required to isolate problems with the algorithm. As code changed we eliminated the guess work of not knowing if those changes altered the outcome of other records.
CDC status's such as “recommendation”, “up to date”, or “not recommended” did not reveal problems with the algorithm.

CONCLUSION:
CDC test cases did not reveal problems and certification could be misleading. The ability to visually evaluate all cases simultaneously in a web application greatly streamlined the process.

LEARNING OBJECTIVES:
1. How a web based dynamic system can evaluate your algorithm.
2. How to compare accurately CDC test cases to your immunization algorithm.