CARE COORDINATION IN NEW YORK CITY

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1 CARE COORDINATION IN NEW YORK CITY Department of Health and Mental Hygiene Bureau of HIV/AIDS Prevention and Control Care and Treatment Unit 1

2 Funded Programs 28 agencies providing CCP in New York City (NYC) 16 hospital-based agencies 12 community-based agencies Caseloads: Agency caseloads: 52 to 230 active clients 9 small programs 12 medium programs 7 large programs ~3,300 PLWH in the active portfolio caseload at any given time 4,986 unique PLWH served from March 2012 February

clients 9 small programs 12 medium programs 7 large programs ~3,300 PLWH in the active

3 THERE ARE 28 CCP AGENCIES IN NYC 3

4 BACKGROUND: Target Population Persons at high risk for suboptimal health care outcomes: newly diagnosed previously lost to care/never in care irregularly in care with recent adherence issues (e.g., viral rebound, resistance) 4

previously lost to care/never in care irregularly in

5 CLIENT DEMOGRAPHICS: GRANT YEAR (GY) 2013, CARE COORDINATION PROGRAM (ALL AGENCIES),N = 4,752 AGE GROUP GENDER 5% 6% 39% 50% < Female Male Transgender 62% 2% 36% 65+ RACE/ETHNICITY 10% Hispanic 37% Black 53% Other Manhattan Brooklyn Bronx Queens Staten Island 32% 9% BOROUGH 21% 33% Other/Unknown 5

Male Transgender 62% 2% 36% 65+ RACE/ETHNICITY 10% Hispanic 37% Black 53%

6 Background: The CCP Model Benefits and Services Coordinatio n Treatment Adherence Navigation Client Health Promotion Outreach 6

7 BACKGROUND: Service Delivery Tracks TRACK A No Antiretroviral Therapy (ART) Quarterly Health Promotion TRACK B ART with quarterly adherence assessments Quarterly Health Promotion TRACK C1 ART with monthly adherence assessments Monthly Health Promotion TRACK C2 ART with weekly adherence assessments Weekly Health Promotion TRACK D ART with daily adherence assessments (modified Directly Observed Therapy) Weekly Health Promotion Clients may transition between tracks based on their needs. *Home visits are an integral component of all tracks in the model

with weekly adherence assessments Weekly Health Promotion TRACK D ART with daily adherence assessments (modified Directly Observed

8 BACKGROUND: INTERVENTION DESCRIPTION CCP model provides: Outreach and re-engagement case management: assessment and planning case conferencing patient navigation, including accompaniment adherence support, including directly observed therapy (DOT) health promotion in home visits assistance with medical/social services 8

navigation, including accompaniment adherence support, including directly

9 HEALTH HOMES VS. CARE COORDINATION CCP Complete Full CCP Services Full RW Reimbursement Health Homes ONLY No CCP Services No RW Reimbursement Health Homes PLUS CCP Care Completion Partial CCP Services Treatment Adherence Support and Readiness DOT HIV-Specific Health Promotion Partial RW Reimbursement (COBRA Rate) 9

Homes ONLY No CCP Services No RW Reimbursement Health Homes PLUS CCP Care

10 HEALTH HOMES VS. CARE COORDINATION All contracting agencies were given guidance regarding how to enroll and serve clients who are also enrolled in Health Homes. 10

11 ENROLLMENT From FY11 to Present, Care Coordination enrollment has remained relatively stable, with a reduction of 65 clients from a high of 3,244 in FY CC Enrollment FY10-FY FY10 FY11 FY12 FY13 FY14 CC Enrollment

12 EXPENDITURES From FY11 to present, Care Coordination expenditures have decreased by $502, ,000,000 CC Expenditure FY11-FY13 25,000,000 20,000,000 15,000,000 10,000,000 5,000,000 0 FY11 FY12 FY13 Spending Plan Allocation 25,302,448 24,891,206 20,412,885 CC Expenditure $21,559,884 $21,466,646 $21,057,647 12

30,000,000 CC Expenditure FY11-FY13 25,000,000 20,000,000 15,000,000

13 SHORT-TERM OUTCOMES IN THE NYC RW PART A CARE COORDINATION PROGRAM 13

14 SHORT-TERM OUTCOMES IN THE NYC RW PART A CARE COORDINATION PROGRAM Mary Irvine 1 Stephanie Chamberlin 1 Rebekkah Robbins 1 Julie Myers 1 Graham Harriman 1 Sarah Braunstein 1 Beau Mitts 1 Sarah Gorrell Kulkarni 2 Denis Nash 2 1 New York City Department of Health and Mental Hygiene, New York, NY 2 CUNY School of Public Health at Hunter College, New York, NY Acknowledgements: Data shared with gratitude to the Care Coordination Program Service Providers Effectiveness analysis funded under an NIMH grant: NIH R01 MH A1 14

and Mental Hygiene, New York, NY 2 CUNY School of Public Health at Hunter College, New York, NY Acknowledgements: Data shared with

15 METHODS: ELIGIBLE SAMPLE AND CARE STATUS GROUPS Clients Eligible for Analysis (N=3,641) Eligibility: enrolled by 3/31/11, matched to Registry, and alive for 1 year of follow-up. Key Terms: Newly Diagnosed: HIV diagnosis date in 12 months before enrollment Current to Care (Baseline): Any CD4 or VL test date in 6 months before enrollment* Out of Care (Baseline): No CD4 or VL test date in 6 months before enrollment* *Among the previously diagnosed 15

Key Terms: Newly Diagnosed: HIV diagnosis date in 12 months before enrollment Current to Care (Baseline): Any

16 METHODS: PRE- VS. POST- ENROLLMENT COMPARISON Matched programmatic (eshare) data with NYC HIV Registry data Estimated relative risks (RRs) using GEE, a method for handling correlated data Outcome Measures: Engagement in Care (EiC EiC): 2 CD4 or VL tests 90 days apart, with 1 in each half of 12-month period Viral Load Suppression (VLS): VL 200 copies/µl on most recent test in second half of 12-month period* * Missing VL in 2nd half of 12-month period was considered evidence of lack of care and treated as=to unsuppressed VL. 16

a method for handling correlated data Outcome Measures: Engagement in Care (EiC EiC): 2 CD4 or VL tests 90 days apart, with 1 in

17 PRELIMINARY RESULTS: ENGAGEMENT PRE- & POST-CCP RR=1.24 ( 95% CI ) RR=1.06 ( 95% CI ) 100% % with EiC 80% 60% 40% 91% 91% 74% 83% 87% 93% 20% 0% N/A Newly diagnosed ALL previously diagnosed 0% Out of care Current to care Among previously diagnosed 12 months prior to CCP enrollment 12 months post CCP enrollment 17

08) 100% % with EiC 80% 60% 40% 91% 91% 74% 83% 87% 93% 20% 0% N/A Newly diagnosed

18 PRELIMINARY RESULTS: VL SUPPRESSION PRE- & POST-CCP 100% 80% RR=1.58 ( 95% CI ) RR=1.34 ( 95% CI ) % with VLS 60% 40% 20% 0% N/A 66% Newly diagnosed 32% ALL previously diagnosed 51% 50% 51% 0% Out of care 38% Current to care Among previously diagnosed 12 months prior to CCP enrollment 12 months post CCP enrollment 18

4) % with VLS 60% 40% 20% 0% N/A 66% Newly diagnosed 32% ALL previously diagnosed

19 PRELIMINARY RESULTS: SIGNIFICANCE OF FINDINGS, BY SUBGROUP Significant improvements held across subgroups Sex Race/Ethnicity Age Primary Language Insurance Status Housing Status Household Income ART Status Year of HIV Diagnosis Viral Load Suppression CD4 Count with two exceptions: other/unknown race (VLS only) 500 (EiC only) 19

Insurance Status Housing Status Household Income ART Status Year of HIV Diagnosis

20 PRELIMINARY RESULTS: RELATIVE IMPROVEMENTS, BY SUBGROUP = Greatest improvement in the subgroup breakdown, as determined by Relative Risk Subgroup Improvement in EiC: Sex Male Race/Ethnicity Age <45 Primary Language Insurance Status Uninsured Housing Status Homeless Household Income <$9,000 ART Status No ARV prescription Year of HIV Diagnosis Dx after 2004 Viral Load Suppression Unsuppressed CD4 Count Subgroup Improvement in VLS: Sex Race/Ethnicity Age <45 Primary Language Insurance Status Housing Status Household Income ART Status No ARV prescription Year of HIV Diagnosis Dx after 2004 Viral Load Suppression CD4 Count <200 20

prescription Year of HIV Diagnosis Dx after 2004 Viral Load Suppression Unsuppressed CD4 Count Subgroup Improvement in VLS: Sex Race/Ethnicity Age <45 Primary

21 KEY FINDINGS Short-term EiC and VLS improvements were robust across most subgroups examined, among the previously diagnosed. Newly diagnosed clients also fared well. Improvements were observed for EiC at 25 (89%) and VLS at 21 (75%) of 28 agencies. Results not just driven by a few large programs 21

22 LIMITATIONS AND CONSIDERATIONS Labs are an imperfect proxy for primary care May overstate care engagement to the extent that some labs reflect acute care vs. primary care visits Not all primary care visits produce lab data Ceiling effects may explain some subgroup findings Certain groups have very little room for improvement Contribution vs. attribution can t credit all to CCP Next analyses to include contemporaneous comparison groups Evolving HIV service and policy landscape 22

FOR MORE INFORMATION NYC DOHMH Care Coordination website http://www.nyc.gov/html/doh/html/living/hiv-care-coord.

23 FOR MORE INFORMATION NYC DOHMH Care Coordination website Graham Harriman, Director of Care and Treatment Stephanie Chamberlin, Specialist Mary Irvine, Director of Research and Evaluation 23

WISCONSIN AIDS/HIV PROGRAM NOTES

WISCONSIN AIDS/HIV PROGRAM NOTES Wisconsin 2014 HIV Care Continuum: Statewide and Select Population Groups Casey Schumann, MS, AIDS/HIV Program Epidemiologist, AIDS/HIV Program, Wisconsin Division of Public Health Background The HIV care