1 in+care Campaign Webinar December 7, 2011
Jan 19, 2016
1
in+care CampaignWebinar
December 7, 2011
2
Ground Rules for Webinar Participation
• Actively participate and write your questions into the chat area during the presentation(s)
• Do not put us on hold• Mute your line if you are not speaking
(press *6, to unmute your line press #6)• Slides and other resources are available
on our website at incareCampaign.org• All webinars are being recorded
3
Agenda
• Welcome & Introductions, 5min• Stories from the Field, 10min• Data Integrity Maintenance, 15min• Review of December Campaign Data,
15min• Stories from the Field, 10min• Q & A Session, 5min
4
Project CONNECTJames Raper, DSN, CRNP, JD, FAANP, FAAN
Associate Professor of Medicine & NursingUniversity of Alabama at Birmingham
5
UAB 1917 Clinic: Linkage to careUAB 1917 Clinic: Linkage to care
• Problem identified: Scheduled new patient visits often not attended (“no show”)
• Study of patients calling to establish HIV care at UAB 1917 Clinic, 2004-2006
• 31% of patients (160 of 522) failed to attend a clinic visit within 6 mos. of initial call
Mugavero et al. Clin Infect Dis 2007;45:127-130
7
Project CONNECTProject CONNECT• Program launched January 1, 2007• New patients have orientation visit within 5 days of their
initial call to the clinic• Semi-structured interview, psychosocial questionnaires &
baseline labs • Uninsured patients meet with clinic SW• Prophylactic antibiotics initiated more quickly• Expedited referral for SA / MH services
• Interview• Predisposing factors: Education, Income• Enabling factors: Insurance, Transportation, Housing,
Social support, Spirituality, Stigma• Contextual factors: Dependant care, Recent
incarceration, Intimate partner violence• Perceived barriers to HIV care
8
CONNECT: Program EvaluationCONNECT: Program Evaluation
Time Period “No Show”
Unadjusted OR (95%CI)
Adjusted OR (95%CI)a
Pre-CONNECT (n=522)
Post-CONNECT (n=361)
30.7%
17.7%
1.0
0.48 (0.35-0.68)
1.0
0.54 (0.38-0.76)
a Multivariable model controls for age, race, sex, insurance, location of residence and time from call to scheduled visit.
9
Data Integrity Maintenance
Anne RhodesServices Analyst, HIV Care ServicesVirginia Department of Health
Terri Fox, MSWResearch AnalystRutgers University, School of Social Work
10
Anne RhodesServices Analyst, HIV Care ServicesVirginia Department of Health
11
Quality Management Tools
12
Barriers to Use
13
Measures
14
Retention Global Issues
15
Current Retention Measure: 2 or more visits at least 3 months apart
* Source: Virginia Client Reporting System (VACRS)
16
Current Work in Virginia
• Discussion with DIS and CBOs funded for testing to set up consent process
• Programming all retention measures into VACRS
• Matching with state surveillance/ obtain other sources of care markers (Medicaid, Medicare, labs)
17
Terri Fox, MSWResearch AnalystRutgers University, School of Social
Work
18
1. Make the data a priority by using it2. Infuse data expectations in contract language,
regular reporting, and outcome evaluation3. Work with a diverse group of
staff/providers/consumers (depending on your ‘program’ unit) to ensure common understanding of definitions of services, units and realistic outcomes
4. Get the input from all parties involved about what goals for service should be
5. Commit to working towards the stated goals
NJ Data Integrity Maintenance
19
6. Ensure that the scope isn’t too broad; the focus and amount of data should be narrow—(what do we fix first? ); where there are too many variables, each one gets a little lost to someone, diluting the potential for impact
7. When there is a question of the integrity of the data, there MUST be a follow up to address the data issue. Do NOT accept ‘there is a problem with the data’ as the end of the discussion. Next steps should always be to address said ‘data’ problem
NJ Data Integrity Maintenance
20
8. Identify data champions at each site; a data champion understands the local service system and how service information is translated into data points in whatever software/form/chart that you are using
9. Include the data champions in any and all discussions about data, especially where the program manager may not be as data savvy as the nurse, case manager, etc.
10. Check the data on a regular basis- does it look like the levels of service are being met- how are the outcome variables? What is the quality of care as expressed by the data?
NJ Data Integrity Maintenance
21
11. Train annually. This never hurts anyone. You can even let your champions participate in training new/newer staff
12. Do NOT make data entry overly complicated. There should be no translation/interpretation needed from contact sheet to database
13. Make realistic goals for care. Do not set providers up to fail. (Meet providers where they are- take steps towards achievable goals)
14. Communicate that data are part of care; not an addition to care
NJ Data Integrity Maintenance
22
23
24
Review of December Campaign Data
Michael Hager, MPH MANQC Manager
25
Data Review – Measure 1: Gap
Data Points: • 85 organizations submitted
data• 54,256 patients in sampleData Results: • 16.16% patients experienced
gap in care• Top 10%: 2.85%; Top 25%:
4.60%
26
Data Review – Measure 2: Visit Frequency
Data Points: • 59 organizations submitted data• 34,508 patients in sampleData Results: • 60.43% patients retained in care for
2 yrs• Top 10%: 88.60%; Top 25%: 85.93%
27
Data Review – Measure 3: New Patients
Data Points: • 76 organizations submitted data• 5,021 patients in sampleData Results: • 61.5% new patients retained in care
for yr• Top 10%: 99.98%; Top 25%: 89.96%
28
Data Review – Measure 4: Viral Suppression
Data Points: • 77 organizations submitted data• 56,094 patients in sampleData Results: • 70.33% patients virally
suppressed at last viral load test• Top 10%: 86.90%; Top 25%:
82.58%
29
December Campaign Data
What have you learned?
30
Retention and Viral Suppression
Theresa Rubin, MA, MPhilQuality Coordinator, AIDS Care UnitNorth Carolina Department of Health & Human Services[[email protected]]
31
• NC has 95 counties in Part B Program• 8,201 Part B Clients for April 1, 2010 to
March 31, 2011• All subgrantees and their contractors
required to use CAREWare• Viral Load data are for all HIV+ clients• 91% had at least 1 Viral Load test• Suppression was defined as VL ≤ 100• We will be using VL ≤ 200 for the future
Looking at Viral Load
32
Viral Load by Gender
63% 57%68%
0%
20%
40%
60%
80%
100%
male (n=5397) female (n=2747) transgender(n=57)
Detectable Missing Undetectable
33
Viral Load by Age
58%44%
56% 63% 66% 73%
0%
20%
40%
60%
80%
100%
13-19(n=92)
20-29(n=758)
30-39 (n=1510)
40-49 (n=2898)
50-59 (n=2203)
60+(n=657)
Detectable Missing Undetectable
34
Viral Load by Race/Ethnicity
57%72% 70%
46%
0%
20%
40%
60%
80%
100%
Black(n=4970)
White(n=2273)
Hispanic(n=527)
Other(n=431)
Detectable Missing Undetectable
35
Viral Load by HIV Risk Factor
60% 66% 62% 51%
0%
20%
40%
60%
80%
100%
HETERO(n=3865)
MSM +MSM/IDU(N=3033)
IDU (n=563) Other(n=740)
Detectable Missing Undetectable
36
Viral Load for MSM+MSM/IDU by Race/Ethnicity
57%75% 69% 72%
0%
20%
40%
60%
80%
100%
BLACK(n=1393)
WHITE(n=1342)
HISPANIC(n=166)
Am.Ind/Other
(n=37)
Detectable Missing Undetectable
37
Time for Questions and Answers
38
Introducing Campaign Office Hours
• Purpose: directly communicate with NQC staff and consultants• ask general questions• request technical assistance• engage in dialogue about the Campaign.
• Details: Mondays and Wednesdays from 4pm-5pm ET• Conference Call #: 866-394-2346• Participant Code #: 4182576142#
39
• First Data Collection Submission Deadline: December 15, 2011 (Deadline Extended)
• First Improvement Update Submission Deadline: December 15, 2011
• Office Hours: December 7/12/14/19/21 4pm-5pm ET
• January Webinar: TBA• Meet the Author – Dr. Thomas
Giordano: January 12, 2012 at 12pm ET
Next Steps
40
Campaign Headquarters:National Quality Center (NQC)90 Church Street, 13th floorNew York, NY 10007Phone [email protected]
incareCampaign.orgyoutube.com/incareCampaign