1. eHARS to CAREWare Pilot Project Update and Training
6/9/2015

2. Agenda and Objectives
Review background information (purpose, benefits)
Review pilot project timeline
Check-in with Providers
Training:
Where to access the data
Limitations
Reports
Examples
Feedback, Questions, Discussion
Next Steps

3. Background: Purpose
Share Limited Surveillance Data for Clients Who Give Consent:
HIV diagnosis date/AIDS diagnosis date/HIV status
will be viewed by all staff in provider domains that serve the client
All CD4 labs (date, type of test, result)/All viral load labs (date, type of test, result)
will only be viewed by case managers and clinical staff in provider domains that serve the client
Vital status and date of death
Note: HIV/AIDS Surveillance System = eHARS (enhanced HIV/AIDS Reporting System)

4. Background: Benefits More efficient information management
Case managers won’t have to spend time calling clinics for lab results
Clinic staff won’t have to spend time calling case managers back with lab results
Providers will have easy access to diagnosis dates
Improved Client Care
Easy availability of CD4 and viral load values will strengthen case managers’ ability to coordinate HIV medical care and monitor clients’ health status and quality of care
Case manager access to clinical indicators will benefit client health by improving retention in care and treatment adherence support
Increased Understanding
Availability of diagnosis dates, CD4 and VL data will strengthen grantees’ ability to evaluate linkage and retention in care, community viral load, and missing data for those clients served by Ryan White/state funding. This could eventually impact funding for the TGA.

5. Timeline Date Activity November 2014
Pilot sites begin collecting ROIs from MCM clients
Nov/Dec 2014
MDH does match between eHARS and CAREWare
January 2015
MDH tests importing data on test site
First check-in conference call with pilot sites
February 2015
June 2015
Training with pilot sites on how to interpret and use the data
March 2015
MDH does first import of data into MN CAREWare
Second check-in conference call with pilot sites
TBD
MDH does second import of data into MN CAREWare
In-person debrief with pilot sites
July 2015
Rollout of project with all MCM sites

6. Check-In with Providers
How is the pilot going? Struggles, successes, ideas?

7. Surveillance data in careware
Corelle Nakamura
HIV/AIDS Surveillance Student Worker
Minnesota Department of Health

8. Training Overview HIV/AIDS Surveillance Interpreting eHARS data
What is it?
Why do we do it?
Who is included?
Interpreting eHARS data
Limitations
eHARS data in CAREWare
Where to find it?
What it looks like?
Generating Reports in CAREWare

9. Training Overview HIV/AIDS Surveillance Interpreting eHARS data
What is it?
Who is included?
Why do we do it?
Interpreting eHARS data
Limitations
eHARS data in CAREWare
Where to find it?
What it looks like?
Generating Reports in CAREWare

10. What is Epidemiology? Study of health and disease in populations
Describe the patterns of disease occurrence
Person (e.g. gender, age, race/ethnicity, etc.)
Place (e.g. Minneapolis, Greater MN)
Time (e.g. trends between 1990 and 2000)
Analyze data to understand the causes of these disease patterns.

11. What is HIV/AIDS Surveillance?
The on-going and systematic collection, analysis, interpretation, dissemination and evaluation of population-based information about persons infected with HIV or diagnosed with AIDS.

12. HIV/AIDS Surveillance System
AIDS reportable since 1982 (U.S.)
HIV infection reportable since 1985 (MN)
Active and Passive data collection
Attempt to interview all new cases
Continuously updated

13. Who is included in the HIV/AIDS Surveillance System?
All HIV- infected Persons Living in Minnesota
Surveillance
All tested and reported HIV-infected Persons

14. The Surveillance Process
Continuous data collection
Pool of data available for analysis
Analysis
Decisions

15. Why should we care about statistics?
The number of people living with HIV/AIDS (prevalence) impacts prevention.
Higher “pool of infection” among certain communities makes it more likely that transmission will occur.
Looking at new cases (incidence) helps us identify emerging trends in the epidemic.

16. Why do HIV/AIDS Surveillance?
Monitor the incidence and prevalence of HIV/AIDS
Identify changes in trends of HIV occurrence
Target prevention interventions
Allocate funds for health and social services
important changes in
trends to allow investigation and intervention.
 Develop information needed to design and
target prevention and control programs and
policies.
 Develop information needed to support
evaluation of disease prevention and control
programs.
Surveillance plays a role in research and policy by:
 Collecting information about their occurrence (quantify morbidity
and mortality)
 Monitoring for changes (identification of risk factors or evaluation
of prevention efforts)
 Serving as foundation for specific research (hypothesis
generation, providing data)
 Providing data for use in education and health policy decisions
*examples- emerging and re-emerging

17. How is the data used?
Surveillance data is used to create the Epi profile, a yearly update that describes new HIV infections and those living with HIV/AIDS in MN.
The Epi Profile helps to identify who is in need of prevention and care services, and is thus used by both the CCCHAP and the Minnesota HIV Services Planning Council in their consideration of which prevention and care services are needed.
Annual report: slides, tables, narrative & webinar (archive)
The Epi Profile describes the HIV/AIDS epidemic in Minnesota and identifies populations at risk for HIV infection.
The EPI profile is intended to give the
Community Cooperative Council on HIV/AIDS Prevention (CCCHAP)
and the
Minnesota HIV Services Planning Council (Planning Council)
a thorough understanding of the epidemic in our state.
the epi profile helps identify the people: who are in need of prevention and care services, both those who are infected and those at risk. helps to target resources where they are most needed.

18. Overview HIV/AIDS Surveillance Interpreting eHARS data
What is it?
Why do we do it?
Who is included?
Interpreting eHARS data
Limitations
eHARS data in CAREWare
Where to find it?
What it looks like?
Generating Reports in CAREWare

19. Limitations of Surveillance Data
Incomplete data
Differences in reporting among providers
Delays of up to 3 months
Reported to surveillance and entered into eHARS
Potential inaccuracies in diagnosis and laboratory dates
Prior to 2007
Outside of MN
Manual entry
Key stroke errors
Delaysreporting to surveillance, getting into eHARS
-Differences in reporting among providers
-Labs less accurate prior to 2011 because CD4s and Viral Loads were not reported, only confirmatory labs
-Labs prior to 2007 may have estimated dates (only month and year reported) and may be less accurate
-Those diagnosed outside of MN may have less reliable dates of diagnosis. MN has had HIV name based reporting since 1983, but other states do not or may not have started using name based reporting until more recently.
-Recent labs have more electronic reporting and less manual data entryless data entry errors

20. How to interpret eHARS data
There is a ROI, but no labs
Haven’t had labs
Labs have not been entered yet
Labs were not reported to surveillance
ROI was not processed before the quarterly match
Slight discrepancies
Name and birth date
Lab date and Diagnosis date
Given these limitations, how should we interpret the data? There may be slight discrepancies (DOB, lab dates, diagnosis dates)
-If you do not see labs, could mean they have not been reported to surveillance. Could also mean that they have not been entered yet or the individual hasn’t had a lab in that time period.
-CAREWare diagnosis date is inputed by providers based on self-reported diagnosis dates from providers.

21. Training Overview HIV/AIDS Surveillance Interpreting eHARS data
What is it?
Why do we do it?
Who is included?
Interpreting eHARS data
Limitations
eHARS data in CAREWare
Where to find it?
What it looks like?
Generating Reports in CAREWare

22. Where to find eHARS lab data in CAREWare?

23. What it looks like when there is eHARS data in CAREWare?

24. Training Overview HIV/AIDS Surveillance Interpreting eHARS data
What is it?
Why do we do it?
Who is included?
Interpreting eHARS data
Limitations
eHARS data in CAREWare
Where to find it?
What it looks like?
Generating Reports in CAREWare

25. Generating an Active ROI report

26. Generating an Active ROI report

27. Generating an Active ROI report

28. Generating an Active ROI report

29. Generating an Active ROI report

30. Generating a “No Clinical Encounter Report” for those with Active ROIs

31. Generating a “No Clinical Encounter Report” for those with Active ROIs

32. Generating a “No Clinical Encounter Report” for those with Active ROIs

33. Generating a “No Clinical Encounter Report” for those with Active ROIs

34. Generating a “No Clinical Encounter Report” for those with Active ROIs
Double click

35. Generating a “No Clinical Encounter Report” for those with Active ROIs

36. Generating a “No Clinical Encounter Report” for those with Active ROIs

37. Generating a “No Clinical Encounter Report” for those with Active ROIs

38. Generating a “No Clinical Encounter Report” for those with Active ROIs

39. Generating a “No Clinical Encounter Report” for those with Active ROIs

40. Generating a “No Clinical Encounter Report” for those with Active ROIs

41. Generating a “No Clinical Encounter Report” for those with Active ROIs

42. Generating a “No Clinical Encounter Report” for those with Active ROIs

43. Generating a “No Clinical Encounter Report” for those with Active ROIs

44. Summary
HIV Surveillance is the ongoing, systematic collection, analysis, interpretation and dissemination of HIV related data.
It is important to inform public health action to reduce HIV related morbidity and mortality and to improve health.
HIV Surveillance data needs to be interpreted carefully based on limitations.

45. For more information… Surveillance CAREWare:
Corelle Nakamura:
Jessica Brehmer:
Allison LaPointe:
CAREWare:
Dennis London:

46. Thank you

47. Feedback, Questions, Discussion
Questions about the training or demonstration? Overall feedback, questions?

48. Next Steps In order to move ahead, goal: 90% of clients to sign ROI
How can we reach 90%? What strategies will increase participation?