Universidad Central del Caribe Determinants of Health Care Use Among Puerto Rican Drug Users in Puerto Rico and New York City.

Slides:

Advertisements

Similar presentations

Hector Colón, Ph.D., Rafaela Robles, Ed.D. Centro de Estudios en Adicción Universidad Central del Caribe Bayamón, Puerto Rico HIV/AIDS Among Drug Users.

Advertisements

Aftercare Attendance Partially Moderated by History of Physical Abuse and Gender Louise F. Haynes 1 ; Amy E. Herrin 1 ; Rickey E. Carter 1 ; Sudie E. Back.

Predictors of Change in HIV Risk Factors for Adolescents Admitted to Substance Abuse Treatment Passetti, L. L., Garner, B. R., Funk, R., Godley, S. H.,

A Randomized Controlled Trial of Two Treatment Programs for Homeless Adults with Latent Tuberculosis Infection Adeline Nyamathi, ANP, PhD, FAAN Audrienne.

Chronically Medically Ill Homeless Women: Characteristics at Baseline Romina Kee MD, MPH Collaborative Research Unit John H. Stroger Hospital CRU.

Influences of Marijuana Use on Adolescent HIV/STI Acquisition and Care Jonathan M. Ellen, MD Johns Hopkins School of Medicine.

Delay from Testing HIV Positive until First HIV Care for Drug Users: Adverse Consequences and Possible Solutions Barbara J Turner MD, MSEd* John Fleishman.

After the Rapid Policy Assessment (RPAR): Drug Policy Change and Advocacy in Szczecin, Poland Sobeyko J (1), Leszczyszyn-Pynka M (2), Duklas T (7), Parczewski.

Risky Behavior: Perceived Risk of Infectious Disease in Youth Entering Alcohol/Drug Treatment Risky Behavior: Perceived Risk of Infectious Disease in Youth.

Journal Club Alcohol, Other Drugs, and Health: Current Evidence July–August 2013.

Nationals HIV/AIDS Strategy and how the mission of Women Accepting Responsibility, Inc. is helping to meet this goal. By She’kell Hutchinson Program Director,

Correlates of polydrug use among injection drug users: The role of socioeconomic stress and quality of life Marrero CA, Robles RR, Reyes JC, Matos TD,

HIV Risk Behaviors and Alcohol Intoxication among Injection Drug Users in Puerto Rico Tomás D. Matos, MS Center for Addiction Studies Universidad Central.

William F. Ryan Community Health Center 110 West 97 th street New York, NY Eishelle Tillery, MSW Nancy Andino, LCSW www. Ryancenter.org.

SOUTH CAROLINA EPIDEMIOLOGIC PROFILE Data available in an Integrated Epidemiologic Profile Core Epi Section Socio-demographic characteristics of.

Background: Medical and correctional professionals are increasingly realizing the extent to which chronic and infectious disease, mental illness, and substance.

Killing the Pain: Prescription Drug Abuse and Other Risky Behaviors in Rural Appalachia Jennifer R. Havens, PhD, MPH Department of Behavioral Science Center.

Factors Related to Adolescent Alcohol Use Progression Matos TD, Robles RR, Reyes JC, Calderón J, Colón HM, Negrón-Ayala JL CENTER FOR ADDICTION STUDIES,

Risk factors for Incident Trichomonas vaginalis among Women Recruited in RESPECT-2, an HIV Prevention Trial D Helms 1, D Mosure 1, T Peterman 1, C Metcalf.

Emerging Trends of HIV/AIDS in New York City Chris Williams, MPH NYC DOHMH.

NIDA Grants: U10DA015831, K24DA022288, U10DA020024, K23DA022297, U10DA Predictors of Outcome in the Multi-Site CTN Prescription Opioid Addiction.

Characteristics of Patients Using Extreme Opioid Dosages in the Treatment of Chronic Low Back Pain In this sample of 204 participants, 70% were female,

Need and Unmet Need of Mental Health among Community Dwelling Seniors In New York City Shijian Li, Ph.D. SUNY at Old Westbury William Gallo, Ph.D. CUNY.

Prevalence of Chronic Disease & Comorbid Conditions in the CHAIN Cohort CHAIN Report Peter Messeri, Gunjeong Lee, Sara Berk Mailman School of Public.

Universidad Central del Caribe Comorbidity and HIV Risk Behaviors among Hispanic Drug Users Residing in Puerto Rico Oral Presentation.

Nonadherence to HAART: A cross-sectional two-site hospital-based study Vivek Lal 1 ; Shashi Kant 2 ; Richa Dewan 3 ; Sanjay K. Rai 2 ; Ashutosh Biswas.

RESULTS Individual characteristics % (N) unless otherwise specified Gender Male 65% (255) Female 35% (136) Race/Ethnicity African American 35% (137) White-not.

The University of Georgia The Treatment of Oxycodone Abuse: Organizational Predictors of Admissions Hannah K. Knudsen Lori J. Ducharme J. Aaron Johnson.

Experience of a NYC hospital with non- occupational post-exposure prophylaxis (nPEP) Antonio Urbina 1, Georgina Osorio 1, Daniel Egan 2, Paul Galatowitsch.

Obtaining housing associated with achieving abstinence after detoxification in adults with addiction Tae Woo Park, Christine Maynié-François, Richard Saitz.

Gonorrhea Increases In Washington State: Gonorrhea Increases In Washington State: Analyses for intervention planning May 2011 Mark R. Stenger Infectious.

Motivational Interviewing (MI) is effective and efficient for fostering health behavior change, and the elicitation of “change talk” (CT: i.e., any expression.

CARIBBEAN BASIN AND HISPANIC ADDICTION TECHNOLOGY TRANSFER CENTER Effects of a Two-facet Intervention to Reduce HIV Risk Behaviors Among Hispanic Drug.

HIV/AIDS Education Impact on Risky Adolescent Sexual Behaviors across Racial Groups Seventh National Conference on Quality Health Care for Culturally Diverse.

Increased exposure to an HIV risk reduction protocol associated with a reduction in drug abuse severity Louise F. Haynes 1 ; Rickey E. Carter 1 ; Amy E.

Factors Associated with Methadone Maintenance Enrollment among Opioid Injecting Users and in Vietnam: A Case-Control Study Nguyen Nguyen 1, Onyebuchi Arah.

Arnold School of Public Health Health Services, Policy, and Management 1 Drug Treatment Disparities Among African Americans Living with HIV/AIDS Carleen.

Methods Data for this NIDA-funded HIV prevention trial (Project WORTH) were drawn from 337 women offenders under community supervision, who reported using.

Results Compliance with Breast Cancer Screening Guidelines in the HIV Clinic: A Quality Improvement Tool E. Patrozou M.D., E. Christaki M.D., L. Hicks.

1 The impact of ongoing illicit drug use on virologic suppression in HIV-infected injection drug users receiving HAART Authors: Harout Tossonian, Jesse.

The Impact of Integrated HIV Care on Patient Health Outcomes Tuyen Hoang, PhD Matthew B. Goetz, MD, Elizabeth Yano, PhD, Barbara Rossman, PhD, Henry D.

Chapter 6 Subset of Overview by Gender GAIN Coordinating Center (11/21/2012). Normal, IL: Chestnut Health Systems. November Available from

The Relationship Between Psychotropic Medication Use and STI Infections Among Detained Youth Dexter R. Voisin Professor.

Barriers to HIV care and Antiretroviral Treatment (ART) among HIV-infected Crack Users in the United States Christine Bell 1 Gabriel Cardenas 2 Tanisha.

BASELINE PREDICTORS OF THREE TYPES OF ANTIRETROVIRAL THERAPY (ART) ADHERENCE: A 2-YEAR FOLLOW-UP Nilsson Schönnesson L. 1 Diamond P. 2 Ross MW. 2 Williams.

CEACEA CENTROCENTRO DE ESTUDIOS EN ADICCION Testing an Intervention Model to Reduce HIV/AIDS Among Hispanic Drug Users Residing in Puerto Rico Robles RR,

Richard Wolitski, PhD Division of HIV/AIDS Prevention Housing and Health : A CDC Perspective July 21, 2012 AIDS 2012 International Housing Summit World.

HIV Testing Strategies and Linkage to Care for Criminal Justice Populations Timothy P. Flanigan, MD Professor of Medicine Brown Medical School.

Sexually Transmitted Disease Surveillance 2013 Division of STD Prevention.

Bringing Hepatitis C Treatment into the Medical Home A Pilot Program for Drug Users Dr. Joanna Eveland MS, MD, Clinical Chief for Special Populations Mission.

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Division of Sexually Transmitted Disease Prevention.

Housing Status and HIV Risk Behaviors Among Homeless and Housed Persons with HIV in the United States The findings and conclusions in this presentation.

A Survival Comparison between HIV+ U.S.-born Latinos and Foreign-born Latinos in Houston, Texas Raouf Arafat, MD, MPH, Adebowale Awosika- Olumo.

Estimating the population impact of homelessness on HIV viral suppression among people who use drugs Brandon DL Marshall, 1 Beth Elson, 1 Sabina Dobrer,

Background  Substance abusers are at risk for HIV and other STIs.  Anal intercourse (AI) is riskier than vaginal intercourse.  Studies of AI have focused.

Pediatric Asthma Hospitalizations: Impact of Managed Care in the Patterns of Outpatient Healthcare Utilization Capriles, JA., Rodríguez, MH., Rios, R.,

Behavioral Health and HIV/HCV Risk Behavior Among Young African American IDUs Patricia M Morse, LCSW, PhD, Edward V, Morse, PhD, Samuel Burgess, MA, MPH.

Non-Medical Staff Knowledge, Beliefs and Practices about HIV and Hepatitis for Injection Drug Users Rowe, KA 1, Tesoriero, JM 1, Heavner, KK 1, Rothman,

Therese Fitzgerald, LCSW, MSW

Pengjun Lu, PhD, MPH;1 Kathy Byrd, MD, MPH;2

Daniulaityte, R., Falck, R., & Carlson, R. Introduction

Kristen Williams, Jonathan J.K. Stoltman, and Mark K. Greenwald

Health Care for the Homeless and Hepatitis National Hepatitis Coordinators' Conference January 27, 2003 Presented by: Amy M. Taylor, MD, MHS Deputy Chief,

Sherry Deren, Sung-Yeon Kang, Milton Mino & Honoria Guarino

Believed discrimination occurred because of their:

Rowe, KA1, Tesoriero, JM1, Davis, SJ1, Heavner, KK1, Rothman, J2,

DO NOW: Please describe

Receipt of medication-assisted treatment halves the risk of HIV-1 RNA viral load rebound for HIV-positive women who use illicit drugs Joëlla W. Adams,

© The Author(s) Published by Science and Education Publishing.

Twice daily regimen N=45 MDI regimen N=28 P Value

Presentation transcript:

Universidad Central del Caribe Determinants of Health Care Use Among Puerto Rican Drug Users in Puerto Rico and New York City To be published in: Clinical Infectious Diseases Journal To be published in: Clinical Infectious Diseases Journal

Authors Rafaela R. Robles Tomás D. Matos Héctor M. Colón Sherry Deren Juan Carlos Reyes Jonny Andía C. Amalia Marrero Hardeo Sahai Rafaela R. Robles Tomás D. Matos Héctor M. Colón Sherry Deren Juan Carlos Reyes Jonny Andía C. Amalia Marrero Hardeo Sahai

Center for Addiction Studies, Universidad Central del Caribe School of Medicine, Bayamón, PR Institute for AIDS Research, National Development and Research Institutes, Inc., New York, NY Center for Addiction Studies, Universidad Central del Caribe School of Medicine, Bayamón, PR Institute for AIDS Research, National Development and Research Institutes, Inc., New York, NY

Support for this study was provided by a grant from the National Institute on Drug Abuse at the National Institutes of Health (Grant #R01 DA10425)

Table 1. Sociodemographic, health-related, and drug-use behavior characteristics at baseline, by study site. Puerto Rico (n=334) NY City (n=617) Number (%) p value Sociodemographic Characteristics Gender Male261 (78.1)428 (69.4) Female73 (21.9)189 (30.6)0.002 Age years47 (14.1)11 (1.8) years136 (40.8)175 (28.4) 35 or more years150 (45.0)431 (69.9)<0.001 Mean / SD * 33.5 / / * Standard Deviation

Table 1. Sociodemographic, health-related, and drug-use behavior characteristics at baseline, by study site. Puerto Rico (n=334) NY City (n=617) Number (%) p value Sociodemographic Characteristics Education Less than high school182 (54.5)390 (63.1) High school or more152 (45.5)228 (36.9)0.006 Living with sex partner (yes)53 (15.9)175 (28.3)<0.001 Living with children (yes)74 (22.2)155 (25.1)0.177 Living with parents (yes)145 (43.4)84 (13.6)<0.001 Homeless (yes)59 (17.7)114 (18.4)0.419 Employed (yes)34 (10.2)81 (13.1)0.111

Table 1. Sociodemographic, health-related, and drug-use behavior characteristics at baseline, by study site. Puerto Rico (n=334) NY City (n=617) Number (%) p value Health-Related Characteristics Health insurance (yes)127 (38.0)444 (71.8)<0.001 Perception of health Excellent/good161 (48.3)367 (59.7) Fair/poor172 (51.7)248 (40.3)<0.001 Chronic physical health problems (yes)80 (24.0)308 (50.2)<0.001 HIV positive (test results)65 (20.8)143 (25.6)0.064 Previously diagnosed HIV/AIDS (yes)44 (13.2)108 (17.5)0.050 Previously diagnosed tuberculosis (yes)6 (1.8)77 (12.5)<0.001 Previously diagnosed hepatitis B/C (yes)78 (23.4)137 (22.2)0.367 Previously diagnosed STD (yes)46 (13.8)182 (29.4)<0.001 Probable case of depression-last 2 weeks (yes)199 (59.6)341 (55.5)0.129 Physical health services-last year (yes)29 (8.7)423 (68.4)<0.001 Mental health services-last year (yes)16 (4.8)106 (17.2)<0.001 Drug treatment - last year (yes)186 (55.7)490 (79.3)<0.001

Table 1. Sociodemographic, health-related, and drug-use behavior characteristics at baseline, by study site. Puerto Rico (n=334) NY City (n=617) Number (%) p value Drug-Use Behavior Characteristics Number of non injected drugs used (last 30 days) 065 (19.5)39 (6.3) 175 (22.5)91 (14.7) 276 (22.8)137 (22.2) 3 or more118 (35.3)351 (56.8)<0.001 Mean / SD2.0 / /

Table 1. Sociodemographic, health-related, and drug-use behavior characteristics at baseline, by study site. Puerto Rico (n=334) NY City (n=617) Number (%) p value Drug-Use Behavior Characteristics Number of injected drugs used (last 30 days) 081 (24.3)205 (33.2) 153 (15.9)182 (29.4) 289 (26.6)102 (16.5) 3 or more111 (33.2)129 (20.9)<0.001 Mean / SD1.7 / / Number of injections (last 30 days) Mean / SD / / 95.2<0.001 * Standard Deviation

Table 2. Health services utilization during six months prior to follow-up, by study site. Physical health services Inpatient medical services (yes) 10 (3.0)115 (18.6)0.14 (0.07, 0.26) <0.001 Outpatient medical services (yes) 18 (5.4)401 (65.0) 0.03 (0.02, 0.05)<0.001 HIV medications * (yes) 14 (21.5)74 (51.7)0.26(0.13, 0.50)<0.001 Puerto Rico (n=334) NY City (n=617) Number (%) OR(95% CI)p

Table 2. Health services utilization during six months prior to follow-up, by study site. Puerto Rico (n=334) NY City (n=617) Number (%) OR(95% CI)p Mental health services (yes) 9 (2.7)110 (17.8)0.13(0.06, 0.26)<0.001 Drug use related services Methadone (yes) 15 (4.5)391 (63.3)0.03(0.02, 0.05)<0.001 Outpatient (yes) 7 (2.1)13 (2.1)1.00(0.39, 2.52)0.599 Inpatient (yes) 60 (18.0)23 (3.7)5.67(3.43, 9.35)<0.001 Drug treatment in jail (yes) 17 (5.1)76 (12.3)0.38(0.22, 0.66)<0.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 1 * Model 2 Study Site East Harlem, NY1.00 Bayamón, PR0.20(0.15, 0.26)< (0.14, 0.26)<.001 Predisposing Factors Gender Male 1.00 Female 1.11(0.81, 1.53).516 OR(95% CI)pOR(95% CI)p * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 3Model 4 Study Site East Harlem, NY1.00 Bayamón, PR0.19(0.13, 0.27)< (0.17, 0.40)<.001 Predisposing Factors Gender Male 1.00 Female 1.34 (0.95, 1.90) 1.11(0.86, 1.87).237 OR(95% CI)pOR(95% CI)p.096 * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 1Model 2 Predisposing Factors Age Education Less than high school High school or more OR(95% CI)pOR(95% CI)p or more (0.54, 1.86) (0.86, 1.60) (0.75, 1.34).992 * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 3Model 4 Predisposing Factors Age Education Less than high school High school or more OR(95% CI)pOR(95% CI)p or more (0.51, 1.83) (0.79, 1.52) (0.68, 1.25) (0.43, 1.68) (0.78, 1.58) (0.67, 1.29).680 * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 3Model 4 Need Factors Probable case of depression – CESD (yes) Injection Frequency OR(95% CI)pOR(95% CI)p 1.28(0.94, 1.73) (0.28, 0.64) (0.77, 1.88) (0.76, 1.87) daily 2- 3 daily 4 or more daily 1.31(0.94, 1.73) (0.32, 0.80) (0.65, 1.70) (0.70, 1.84).598 * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 3Model 4 Enabling Factors Health Insurance (yes) Employed (yes) OR(95% CI)pOR(95% CI)p 1.52(1.08, 2.14) (0.61, 1.60) (0.71, 1.61) (0.83, 1.81) (0.71, 1.66) , 1.66).831 Living w/ sex partner (yes) Living w/ children (yes) Living w/ parents (yes) Homeless (yes) * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001

Table 4. Factors associated with utilization of drug treatment services during last six months using hierarchical multiple logistic regression. Model 3Model 4 Enabling Factors Physical health services – last year (yes) Mental health services – last year (yes) OR(95% CI)pOR(95% CI)p 1.14(0.77, 1.70) (0.51, 1.34) (3.50, 7.05)< (0.46, 2.27).952 Drug treatment – last year (yes) HIV medications (yes) * Deviance (D): Model 1: D=155.33, p=<.001. Model 2: D=153.84, p=.828. Model 3: D=109.48, p=<.001