1. WisPQC Data Collection & Reports Webinar for NAS/NOWS Initiative
November 13, :00-1:00 p.m. GoToWebinar®

2. Topics to Cover RE: Data Collection and Reports
Platform used
Collection of data
Data use agreement
Reports and graphics
Data validation

3. Platform Used
PeriData.Net®
Current users
Non-subscribers

4. Data Collection Data elements Collection form on Web site
Opioid data screen in PeriData.Net®
Demonstration by Madison of data screen, data entry, & access to data definitions
Submission of data
Time to collect data
Input from Pilot hospitals

5. Navigation to data collection form on the Web site
Hover over ‘Initiatives’ tab at top of screen and select ‘Women and Infants Affected by Opioids’
Scroll down and select the box labeled ‘Change Package’
Click on box titled ‘General Information and Resources’
Select ‘Data Collection Form’ and can print it

11. Submission of Data No steps to complete
Enter the data and your task is completed!

12. Time to collect data
Input from Pilot Hospitals

13. Data Use Agreement
Purpose
WisPQC will create an agreement
Completion

14. Data Reports and Graphics
Detail Report
Individual hospital report
WisPQC NAS/NOWS Summary Report
Aggregate statewide report
Graphics
Selection of timeframe to include
Run charts and control charts

15. Graphics Available
Number / Percent of infants at risk for NOWS/NAS evaluated with validated tool
Number / Percent of infants treated using standardized protocols
Number of infants with NOWS/NAS

16. Graphics Available
Number of infants transferred/transported for higher level of care
Duration of treatment for NAS/NOWS
Duration of pharmacologic treatment for NAS/NOWS
Length of hospitalization

17. Data Validation What it is Why do it
Domains / Dimensions of data quality
Things to consider

18. What is it?
“Data validation is an activity verifying whether or not a combination of values is a member of a set of acceptable combinations”… it is a “ a decisional procedure ending with an acceptance or refusal of data as acceptable.”
Methodology for Data Validation 1.0 (Handbook), ESSnet Validat Foundation, revised edition June 2016 p. 5 & 6

19. Why bother with data validation?
Data validation ensures that there is “a certain level of quality of the final data”
Quality data enhances the reliability of research findings and is integral to EHR based study findings
Assists with “believability” of the data / information and lessens questioning of what is being reported
Methodology for Data Validation 1.0 (Handbook), ESSnet Validat Foundation, revised edition June 2016

20. Domains / Dimensions of Data Quality
Accuracy – truthfulness of the data
Completeness – degree and nature of missing values
Comparability/consistency – constancy of the data at the desired degree of detail
Data credibility – plausibility or reliability of the data
Timeliness / punctuality
Use of data is the goal & need good data

21. Things to Consider RE: data validation
Is the audit a manual or computer process?
Will you use paper documentation or an electronic report to cross check data accuracy?
How often will you audit data entry; compare to chart (gold standard)? Double-check with second person? What is your sample size?

22. Things to Consider RE: data validation
How will you prevent missing data, reduce possibility of errors?
Confirm common understanding of definitions by data abstractors.
Measure degree of data entry failure, data fall-out, outliers.
Analyze feedback from stakeholders.

23. Learning Collaborative Sessions: Schedule & Format
Upcoming Webinar Meetings: Invite your team of opioid project champions to gather together
Weekday
Date
Time
Topic
Tuesday
Nov 27
12:00– 1:00 pm
Change Package
Thursday
Dec 6
Eat, Sleep, Console
Wednesday
Dec 12
Learning Collaborative Sessions: Schedule & Format
Nursing

24. Questions now: Questions later:
Ask
Questions later:

25. Thank you. For additional information, contact Sue Kannenberg at or ext. 205