1. Retention in Care Among Adults Infected with HIV Katherine A. Marx, MS, MPH, Rebecca M. Schwartz, PhD, Edmond S. Malka, MPH, CPH, Jayashree Ravishankar, MD, MPH SUNY Downstate Medical Center, Brooklyn, NY

2. Presenter Disclosures Katherine A. Marx (1)The following personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months: No relationships to disclose

3. East Flatbush Brooklyn

4. HIV Care Retention and Survival Retention in medical care associated with decreased mortality Antiretroviral use associated with longer life Giordano TP, et al. Clin Infect Dis 2007;44(11):1493-1499. Walensky RP, et al. J Infec Dis 2006;194(1):11-19.

5. Retention Deficits ½ of adults medically eligible for HIV care in United States not receiving treatment Missed appointments associated with treatment failure Clinic retention rates 38% - 77% Teshale E, et al., 12th Conference on Retroviruses and Opportunistic Infections.2005 Feb 22-25;Boston. Meyerson BE,et al. Am J Pub Health 2007;97(4):744-749. Rastegar DA,et al, AIDS Care 2003;15(2):231-237 Berg MB,et al., AIDS Care 2005;17(7):902-907. Sherer R, et al. AIDS Care 2002;14(Suppl 1):S31-S44. Lo W. et al., AIDS Care 2002;14(Suppl 1): S45-S57. Gardner LI, et al. AIDS 2005:19(4):423-431. Horstmann E, et al., International Conference on AIDS.2006 Aug 13-18; Toronto

6. Predicting Retention: Individual Characteristics AIDS Diagnosis (CD4<200 or symptomatic) Substance use (active or past) Giordano TP, et al. AIDS Care 2005;17(6):773-783. Giordano TP, et al. Clin Infect Dis 2007;44(11):1493-1499. Naar-King S, et al. AIDS Patient Care STDS 2007;21(Suppl 1):S40-S48. Rumptz MH, et al. AIDS Patient Care STD 2007;21(Suppl 1):S30-S39. Ashman JJ,et al. AIDS Care 2002;14(Suppl 1):S109-118. Cunningham WE,et al. Med Care 2006;44(11):1038-1047.

7. Predicting Retention: Individual Characteristics Age Employment Housing Giordano TP, et al. AIDS Care 2005;17(6):773-783. Giordano TP, et al. Clin Infect Dis 2007;44(11):1493-1499. Naar-King S, et al. AIDS Patient Care STDS 2007;21(Suppl 1):S40-S48. Rumptz MH, et al. AIDS Patient Care STD 2007;21(Suppl 1):S30-S39. Ashman JJ,et al. AIDS Care 2002;14(Suppl 1):S109-118. Cunningham WE,et al. Med Care 2006;44(11):1038-1047. Insurance Language Mental illness Race Sex Time

8. Goals Compare retention definitions Examine associations between individual characteristics and retention in care

9. Methods Retrospective cohort: chart review –Approved by Institutional Review Board Sample (N=212) –Active adult clients on 12/31/05 –Exclusion for death (N=3), incomplete data (N=3) –All eligible 18-29 included, random selection for 30-49 and 50 and over age groups Study period: 1/1/06 - 12/31/06 Analysis: –De-identified database –SPSS version 16.0 –Logistic Regression – binary vs. ordinal

10. Retention Status Retention : attended 1 or more primary care visits in each 6 month period of a 12 month year No retention

11. Retention Score Low High 01234 Quarters with primary care visits

12. Demographic and health characteristics VariableN% Female12659 Black Hispanic White 176 29 7 83 14 3 Substance use7837 Alcohol use8741 Marijuana use3818 Mental illness8942 AIDS diagnosis7837 Homelessness10 5 English18587

13. Adjusted odds ratios - comparison of predictors for retention status and retention score

14. Retention Status - Binary Model 3 variables 2 significant predictors ↑ AIDS diagnosis (OR = 2.18, 95% CI 1.17 - 4.10) ↓ History of substance use (OR =.52, 95% CI.29 -.94) –Primary language English (OR =.57, 95% CI.23 - 1.46)

15. Retention Score - Ordinal Model 3 significant predictors ↑ AIDS diagnosis (OR 1.81, 95% CI 1.09-3.01) ↓ Substance use (OR.58, 95% CI.35-.96) ↓ Primary language English (OR.40, 95% CI.19-.84)

16. Model Comparison Retention variables highly correlated (R=0.82, p<.001) Model findings consistent Ordinal model sensitive to association between language and retention

17. Predicted probabilities for English as a primary language by retention score 0 2341

18. Language and Retention Linguistic resources at the study site –Provider language concurrence –Professional telephone interpretation –Ad hoc interpretation by staff

19. Retention Interventions Substance use history –Treatment and harm reduction –Mental health and ancillary services AIDS diagnosis –Peer programming –Health literacy

20. Limitations Individual determinants of retention One clinic Existing dataset Exclusion of walk-in visits

21. Conclusions Ordinal measure identified additional predictor Binary measure simple to interpret Language status predicts retention in care

22. Thank you! SUNY Downstate Medical Center School of Public Health STAR Health Center Nicholas A Rango HIV Clinical Scholars Program Rebecca Schwartz Edmond Malka Jayashree Ravishankar Karen Benker Tracey Wilson David Odegaard Alexa Kazim Mikhail Zlotin Susan Holman Jack DeHovitz Cassandra Raphael Genevieve Jeanbart Marie Martial Magna Robinson