1. Using Ohio’s Impact SIIS Data in Assessing Immunization Rates
Carolyn A. Parry, MPH
Public Health Advisor
Ohio Department of Health
Immunization Program

2. Objectives
Determine when a practice is ready to use registry data for an assessment.
Determine the methods to use for conducting assessments using Impact SIIS data.
Number of records that matched the list of “active” patients
What type of additional information in located in the charts
Data quality

3. Methods Two sites were selected
Site A began using the registry in January 2003 with pre-loaded historical information
Site B began using the registry in March 2003 without pre-loaded historical information
Three methods of extraction were researched
Impact SIIS’s CASA Report function
Electronic name and date of birth matching
Random selection of 100 names and manually entering into CASA
Two age ranges assessed
Assessment conducted September 2003
Assessed as of January 1, 2003

4. Impact SIIS’s CASA Report function
Currently utilized by some local health department
How a practice is set up in Impact SIIS determines whether this function can be utilized
File size and time limits do not allow this function to be used for all practices
Not available for Site A or Site B

5. Electronic Name Matching
An electronic list of names and dates of birth is used to electronically search for matches in the registry
In this case, patient ID numbers were utilized to facilitate the matching process
Conducted by computer staff, not an automated process within the registry

6. Results - Electronic Name Matching
Records Found
% Match
MOGE
Records Reviewed
UTD from Name Match
UTD from 100 Sample
Site A
24-35 months
1614/1881
85.8%
204
1410
51.06%
62.63%
12-23 months
1483/1800
82.3% 61
1422
72.29%
67.00%
Site B
205/380
53.9% 18
187
45.45%
42.42%
186/352
52.8% 41
145
60.00%
57.14%

7. Electronic Name Matching
Questions/Issues to be resolved
Names of those who did not match were excluded from the Impact SIIS extract
Moved or Going Elsewhere (MOGE)
When modified it will be a valuable way to pull assessment data for larger practices and possibly HMO groups

8. Random Selection of 100 Names Manually Entered into CASA
100 records randomly selected from each age group
Records manually retrieved from Impact SIIS and entered into CASA
Pulled charts of those records with missing immunizations, entered missing chart data into CASA

9. Site A Results – Before and After Chart Pull
UTD
Late UTD
Missed Opps
Last Imm > 12 months
UTD with varicella
UTD at 12 months
24-35 months
Original
62.63%
16.16%
7.07%
12.12%
52.53%
75.76%
After chart pull
66.67%
15.15%
9.09%
56.57%
77.78%
12-23 months
67.00%
17.00%
1.00%
73.40%
15.96%
1.06%
4.37 and 6.40 percentage point increases in UTD rate, respectively

10. Site B Results – Before and After Chart Pull
UTD
Late UTD
Missed Opps
Last Imm > 12 months
UTD with varicella
UTD at 12 months
24-35 months
Original
42.42%
15.15%
12.12%
28.28%
36.36%
51.52%
After chart pull
68.80%
18.48%
2.17%
10.87%
59.78%
73.33%
12-23 months
57.14%
13.27%
8.16%
78.82%
14.12%
0.00%
26.38 and percentage point increases in UTD rate, respectively

11. Site A Results – Status in Registry and Additional Information Found in Charts
24-35 month age group
Imms
Phil/
Religious Exempt
History of Disease
MOGE
Not found (2) 2
Found – no shots (2) 1
Found – not complete (26)
-Missing varicella only (8)
-Missing charts (2)
*7 of 30 charts had additional information

12. Site B Results – Status in Registry and Additional Information Found in Charts
24-35 month age group
Imms
Phil/
Religious Exempt
History of Disease
MOGE
Not found (7) 4 3
Found – no shots (12) 9 1 2
Found – not complete (33)
-Missing varicella only (4)
-Deleted (1) 17
*39 of 52 charts had additional information

13. Conclusions
Flexibility in the choice of available methods of data extraction is crucial
How sites are set up and utilize the registry impacts the ability to use certain methods
All assessment methods still need to obtain a list of “active” patients
In the beginning, sites using the registry real-time with pre-load historical information will have more complete assessments using registry only data

14. Conclusions continued…
Conducting assessments with registry data serves as a quality check
Limitations of the data being reviewed must be taken into consideration
Electronic data does not necessarily eliminate the need to pull charts

15. Recommendations
Site B would benefit from having more information in the registry
Impact SIIS should review the algorithm for accuracy
Documentation of history of disease and its effect on forecasting
Replicate the study in 2004
Look more closely at data quality

16. Questions? Contact: Carolyn A. Parry, MPH Public Health Advisor
Ohio Department of Health
Immunization Program
(614)