in + care campaign webinar december 7, 2011

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 MaintenanceAnne 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


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?


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


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 SuppressionData 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 SuppressionTheresa 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)


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)


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)


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)


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

in + care campaign webinar december 7, 2011

Documents