yvette calderon, m.d., m.s. professor of clinical emergency medicine albert einstein college of...
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Yvette Calderon, M.D., M.S.Yvette Calderon, M.D., M.S. Professor of Clinical Emergency Medicine
Albert Einstein College of MedicineJacobi Medical Center, NY
Project B.R.I.E.F.An innovative multimedia HIV testing system
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Overview• Project BRIEF
• Development of an integrated HIV testing model• Data summary
• Linkage to care• Description of model• Treatment outcomes
• HIV Testing in Special Populations• HIV Testing in Community Pharmacies• Teen-targeted HIV Education and Testing• Tailored HIV Education for African Immigrants
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HIV/AIDS in New YorkHIV/AIDS Prevalence Rates
1.70%
2.40%
1.70%
1.30%
1.90%
0.65%
1.40%
2.20%
1.10%
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
Overall African-American Hispanic
Population Group
New York State
New York City
Bronx Borough
NYSDOH 2010 Surveillance Report, including cases reported and confirmed through 2008
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Bronx Demographics
U.S.A. New York BronxPopulation1 (millions)
307 19.5 1.4
% Hispanic1 15.8 16.8 52.0% Black1 12.9 17.2 43.0Median
Household Income2 $52,029 $55,980 $35,108
% Below Poverty Line2
13.2 13.7 27.3
Data from U.S. Census Bureau1. 2009; 2. 2008
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Region Functionally illiterate Marginally literate
New York State 24% 26%
NYC 36% 27%
Bronx 46% 33%
Brooklyn 41% 32%
Manhattan 31% 19%
Queens 33% 30%
Staten Island 18% 28%
www.casas.org/lit/litcode/search.cfm
Adult Literacy in NYC
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Awareness of HIV Status Among Persons with HIV and Estimates of Transmission - US
AMA Jour of Ethics, Dec 2009, Vol 11, Num 12: 974-979
~21% Unaware of Infection
~79% Aware of Infection
~50-70% of New Infections
~30-50% of New Infections
People living with HIV/AIDS ~1.1 million New infections per year ~56,300
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The Bronx Knows: est. June 2008
• NYC Department of Health Initiative– HIV testing for Bronx residents aged 18-64– Communities engaged in testing
• Colleges• Community-based organizations, • Community health centers• Correctional facilities• NYC Department of Health STD clinics, • Faith-based organizations• Hospitals
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Testing by Agency and Agency Type January 2008 – December 2009
N=175,742 total tests
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Why test in the ED?Why test in the ED?
• Inner city EDs serve disadvantaged patient populations, which continue to bear a disproportionate burden of U.S. health disparities. (Alpert 1996, Kelen 1995, Schoenbaum 1993, et al.)
• These patients utilize the ED for their primary care and have limited or no access to ongoing regular health care.
• The CDC recommends that diagnostic HIV testing and HIV screening be a part of routine clinical care in all health-care settings (CDC 2006 Revised Recommendations)
• As of September 2010, it is New York State law that Emergency Departments, as well as other clinical settings, must offer HIV testing to all patients.
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Educational Videos
Increased Access to HIV Counseling/Testing in the ED
Rapid HIV Testing
Public Health Advocate
Project B.R.I.E.F• Behavior intervention• Rapid HIV test• Innovative video• Efficient cost and health care savings• Facilitated seamless linkage to outpatient HIV care
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• Daytime Hours: Patient are walked to ACS
clinic and seen by a provider
• Evening Hours: Patients are given an
appointment to return on next open visit at
the ACS clinic
Protocol for People Testing Positive
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80,392 patients approached
66,416 pts (92.9%) tested
258 pts (0.4% tested HIV+)
Project BRIEF Results: Oct. 2005- July 2011
71,514 pts (89.0%) eligible
5,098 pts (7.1%) refused
208 pts (81%) linked to care
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Patients tested through Project BRIEF
Demographics (n=63,122)
% Male 42.3%
Mean Age 36.1 ± 14.5 years
Race/Ethnicity Hispanic
Non-Hispanic Black
Non-Hispanic White
Asian
Other
American Indian/ Alaska Native
Native Hawaiian/ Pacific Islander
56.8%
34.2%
5.5%
1.5%
1.4%
0.5%
0.1%
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Risk Factors by GenderRisk Factors by Gender
Malen=24,137
Femalen=32,534
Vaginal sex past 3 mo 86.5% 89.0%
Sex without a condom 86.9% 91.8%
Previous STI dx 12.2% 12.7%
>3 drinks before sex 50.9% 33.8%
Non-IV drugs before sex 25.4% 11.8%
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• 99.2% felt HIV testing in the ED is helpful.
• 96.0% felt the video answered their
questions regarding HIV testing.
• 86.5% learned a moderate to large amount of new information
Satisfaction with BRIEF modelBRIEF model
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Linkage to Care Data
October 2005 – July 2011
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Linkage to Care (10/05 – 07/11)
• # of patients diagnosed as HIV-positive• n=258• 214 pts are newly diagnosed
• # of patients linked to outpatient care• n=208 (82%)
• # of pts linked to care @ NBHN• n=191 (92% of all linked patients)
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Male*(n = 168)
Female(n =90)
Total(n=258)
Average Age 40(range: 19-82)
39(range: 13-70)
40(range: 13-82)
# of pts newly dx’d HIV+
142 72 214
# NBHN Visits prior to Dx
5.0 14.2 8.2
# NBHN Visits 1 year prior to Dx
1.6 2.3 1.8
Median Initial CD4 Count (cells/mm3)
282 308 284
Median Initial Viral Load (c/mL)
31,700 40,063 33,118
BRIEF (10/05-07/11)BRIEF (10/05-07/11)HIV dx’d Patient CharacteristicsHIV dx’d Patient Characteristics
* 1 pt is transgender (M -> F)
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HIV Testing on Inpatient Wards
• ED-based HIV testing does not reach all patients– especially those whose disease processes are acute
enough that they require hospital admission.
• When patients become stable enough for transfer to an inpatient ward (IP), they may meet inclusion criteria.– However, HIV testing is oftentimes not offered.
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HIV Testing on Inpatient WardsJune 2010 to June 2011
Inpatients approached for
HIV testing2,819
Refused testing in ED
30.3% (252/831)
Previously approached for testing in ED
46.1% (831/1,804)
Already tested in ED
69.7% (579/831)
Accepted testing in IP
72.5% (705/973)
Refused testingIn IP
27.5% (268/973)
Not previously approached in ED53.9% (973/1,804)
Accepted testingIn IP
48.4% (122/252)
Could not consent to testing in IP
36.0% (1,015/2,819)
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Demographics of Patients tested in IP vs. ED
Patients Tested in IP (n=827)
Patients Tested in ED (n=9210)
p-value
Age52.8 ± 18.3 35.9 ± 14.3 <0.01
Male49.1% (406/827) 43.5% (4003/9210) <0.01
Hispanic48.2% (391/811) 52.4% (4812/9187) 0.02
Black, Non-Hispanic 28.2% (229/811) 35.6% (3294/9187) <0.01
Prior HIV Test 63.8% (526/825) 77.8% (7104/9128) <0.01
June 2010-July 2011
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2
811
18 17 18
23
2118
38
30
42
17
0
5
10
15
20
25
30
35
40
45
50
2005 2006 2007 2008 2009 2010 2011
AIDS @ dx
Total pts
BRIEF Concurrent AIDS dx: Newly dx’d pts
Note: 33 pts with missing baseline CD4 data
67%
38% 61%
47%42%
57%
13%
Tot
al p
atie
nts
test
ed
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HIV Testing in Pharmacies
• Phase 1: testing at one pharmacy site to assess feasibility
• Phase 2: expansion to multiple sites
• Phase 3: addition of multimedia tool for efficient data acquisition and video messaging in different languages
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BRIEF: HIV+ Oct ’07-Oct ’08(all patients except for 1 pt from Philadelphia)
H
H
Congress
Pharmacy
De Franco
Pharmacy
Bioscrip
Pharmacy
Leroy
Pharmacy: E. 204th
Leroy
Pharmacy:
Gun Hill
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HIV Testing in Pharmacies• Evaluated 12 different pharmacies for:
– Location– foot traffic– staff acceptance– private area for testing
• Selected five highest-ranked pharmacies• Obtained a Limited Testing Laboratory certificate
from New York State for each pharmacy site• Established a hospital-based medical record
documentation protocol
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4,177 patients approached
2,010 pts (73.0%) tested
6 pts(0.3% tested HIV+)
Pharmacy Testing Results
2,755 pts (66.0%) eligible
745 pts (27.0%) refused
-Data from 10/26/09 to 06/07/11
-289 Days of Testing
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Community Pharmacy Testing: Demographics
Bioscrip De Franco Congress Leroy
Mean Age (range)
32.7 (13-86) 31.9 (13-82) 33.7 (15-88) 36.0 (16-75)
Male40.1%(400/998)
42.0%(261/622)
43.3%(101/233)
32.9%(46/140)
Hispanic54.7%(546/998)
63.7%(387/608)
60.3%(147/234)
59.0%(82/139)
Non-Hisp. Black
34.9%(348/998)
33.0%(205/622)
33.8%(79/234)
30.2%(42/139)
Language English Spanish Other
(n=987)
74.0% (730)
24.1% (238)
1.9% (19)
(n=618)
70.7% (441)
25.3% (158)
3.1% (19)
(n=231)
68.8% (159)
26.8% (62)
4.4% (10)
(n=141)
73.0% (103)
27.0% (38)
0% (0)
Uninsured 34.9% (344/985) 33.4% (207/619) 33.2% (79/238) 29.6% (42/142)
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Pharmacy HIV+ ptsPatient Risk factor CD4 VL Comments
61 yo AA F HP 622 1658 DM, HTN, amb care pt
29 yo HM IDU 273 14725 Prev dx’d, never linked prev
34 yo HM MSM 718 89369 RPR 1: 512
33 yo AAM MSM 1180 5453 Mentally challenged, exchanging sex for $
23 yo black HM MSM 494 9648 20 yo M (MR# ) partner tested HIV neg both linked: 1 for HIV care, 1 for nPEP
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Special Populations: Adolescents
Project Control Post-HIV Test Video Intervention Series
Video 1Teens discussing whether or not to use condoms
Video 2A Video 2BSOC: Pre-contemplation, contemplation SOC: Preparation, Action, Maintenance
Negative Consequences of Not Using Condoms Positive Consequences of Using Condoms
Video 3Condom Use Demonstration
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Special Populations: AdolescentsEffects of Video and Counselor on Teenagers’ Intentions for Condom Use
Condom Use measure
VideoMean
improvement
CounselorMean
improvement
Mean difference (video vs. counselor)
p-value 95% CI
Condom Use Intention Score
0.98 -0.04 1.02 0.01 (0.24, 2.30)
Condom Self-Efficacy
0.31 0.05 0.26 0.03 (0.03, 0.50)
Male Condom Outcome Expectancy
0.19 0.04 0.15 0.03 (0.02, 0.28)
Female Condom Outcome Expectancy
0.16 -0.04 0.20 0.06 (-0.01, 0.40)
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Special Populations: Black African Immigrants
We conducted focus groups with black African immigrants to identify:
-barriers to HIV testing
-methods to increase voluntary HIV testing
-receptivity to media/video based interventions
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Special Populations: Black African ImmigrantsKey Messages
Barriers to HIV Testing
StigmaImmigration Status
Hospital SettingConfidentiality
Methods to Increase Testing
Collaborate with Community LeadersProvide Culturally-relevant Education
General Health Approach
Receptivity to Video Messaging
ComprehensionCultural Relevancy
PersuasivenessReceptiveness
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Special Populations: Black African Immigrants
• Preliminary qualitative research revealed 3 key messages:– Culturally-relevant HIV education must be
incorporated into messages of general health and wellness
– HIV testing must exist in venues located outside of traditional medical care facilities
– Use of video to provide tailored messages is acceptable to this community
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"Now this is not the end. It’s not even the beginning of the end. But it is, perhaps, the end of the beginning.”
-Sir Winston Churchill(Second Battle of El Alamein)
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Bioscrip De Franco Congress Leroy
Start Date 10/26/2009 01/06/2010 09/16/2010 11/15/2010
Days of testing 161 87 52 31
Patients Approached
2123 1299 513 241
Eligible Pts 66.2%(1406/2123)
65.1% (846/1299)
63.5%(326/513)
71.8%(173/241)
Eligible Pts tested
71.0%(998/1406)
73.8% (624/846)
74.2%(242/326)
84.4%(146/173)
Mean tests per day (range)
7.5(3-18)
7.2(1-12)
5.0(2-10)
4.0(1-9)
# Positive Pts 5 0 1 0
Community Pharmacy Testing
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Community Pharmacy Testing: Demographics
Bioscrip De Franco Congress Leroy
Mean Age (range)
32.7 (13-86) 31.9 (13-82) 33.7 (15-88) 36.0 (16-75)
Male40.1%(400/998)
42.0%(261/622)
43.3%(101/233)
32.9%(46/140)
Hispanic54.7%(546/998)
63.7%(387/608)
60.3%(147/234)
59.0%(82/139)
Non-Hisp. Black
34.9%(348/998)
33.0%(205/622)
33.8%(79/234)
30.2%(42/139)
Language English Spanish Other
(n=987)
74.0% (730)
24.1% (238)
1.9% (19)
(n=618)
70.7% (441)
25.3% (158)
3.1% (19)
(n=231)
68.8% (159)
26.8% (62)
4.4% (10)
(n=141)
73.0% (103)
27.0% (38)
0% (0)
Uninsured 34.9% (344/985) 33.4% (207/619) 33.2% (79/238) 29.6% (42/142)
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Community Pharmacy testing: Risk Factors of Patients Tested
Bioscrip De Franco Congress Leroy
Condom use described as never, almost never, or sometimes
47.6%(444//933)
48.5%(283/584)
50.7%(109/215)
62.2%(79/127)
Previously had an STD 10.8%(105/973)
11.8%(73/620)
12.1%(28/231)
14.5%(12/137)
Sex with partner with HIV
2.0%(19/949)
3.8%(23/611)
2.6%(6/231)
1.4%(2/138)
Sex with known MSM 3.1%(29/950)
0.7%(4/613)
3.0%(7/2313)
4.7%(6/127)
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Recruitment Methods
• Participants were recruited using a social network strategy that involved leaders of black African community organizations within the Bronx.
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Data Analysis
• Digital recordings were transcribed • Four researchers coded themes using Nvivo
– Attitudes towards use of video– Barriers to HIV testing– Strategies to improve HIV testing
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0
5
10
15
20
25
30
35
40
ART Meds Other Meds Hospital Physician Total Costs
Cos
t ($,
in th
ousa
nds)
<50 cells/uL50-199 cells/uL200-349 cells/uL>350 cells/uL
CD4 Category
Mean Annual Per-Patient Costby CD4 Strata
Chen RY, et al. Clin Infect Dis. 2006;42:1003-1010.
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Lifetime Per-Person Costsby Initial CD4 Count
Hutchinson, et al. J Acquir Defic Syndr. 2006;43:451-457.
Lifetime Medical Costs ($, in thousands)
Life Expectancy (y)
Initial CD4 Count (cells/μL)
0
5
10
15
20
25
0
50
100
150
200
250
<199 200-349 >500
192.3 195.3
230
8.5
15.4
24.424.4
Life
tim
e M
edic
al C
ost
s ($
, in
thousa
nds)
Life
Exp
ect
an
cy (
y)
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Quinn T et al. N Engl J Med 2000;342:921-929
Mean (+SE) Rate of Heterosexual Transmission of HIV-1 among 415 Couples, According to the Sex and the Serum HIV-1 RNA Level of the HIV-1-Positive Partner
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Cost-Effectiveness of Screening for Other Chronic Diseases
C-E RATIO
Screening program $/QALY Reference
HYPERTENSION
Asymptomatic men >20 y/o
$29,3001 Littenberg. Ann Intern Med. 1990.
BREAST CANCER
Annual mammogram, women 50-69 y/o
$46,5004 Salzmann. Ann Intern Med. 1997
HIV
Routine, rapid testing in health settings
$50,0005 Paltiel. Ann Intern Med. 2006
DIABETES MELLITUS
Type 2 fasting plasma glucose, adults >25 y/o
$57,0002 CDC C-E Study. JAMA. 1998.
COLON CANCER
FOBT + SIG q5y, Adults 50-85 y/o
$92,9003 Frazier. JAMA. 2000.
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Does HIV testing and initiation of HAART impact
COST?
Cost:
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Governor Paterson Signs into Law Landmark HIV Testing Legislation! (July 30, 2010)http://open.nysenate.gov/legislation/bill/S8227
The new legislation (S08227/A11487) will institute significant advances in making
HIV testing routine, such as:
• Requiring the offering of an HIV test in all public (Article 28) and private health
care settings thereby establishing the offer of an HIV test as the standard of
care;
• Extending required offering of HIV screening to individuals ages 13-64 years old;
• Requiring that informed consent be obtained prior to performing an HIV test;
• Facilitating routine testing by permitting flexibility in how informed consent is
documented where rapid technology is used;
• Providing durable consent where written consent is part of the general consent to
medical care with an opt-out for HIV testing. Durable unless patient changes
providers or revokes the consent;
• Requiring that when an HIV test is positive, with the patients’ consent, the person
ordering the test must provide or arrange for follow-up medical care.
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Governor Paterson Signs into Law Landmark HIV Testing Legislation! (July 30, 2010)Responsiblity
• Requiring the offering of an HIV test in all public (Article
28) and private health care settings thereby establishing
the offer of an HIV test as the standard of care;
– including hospitals, emergency rooms, hospital
outpatient departments, and primary care settings
including physician, physician assistant, nurse
practitioner and midwife offices
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NY HIV Testing Legislation!Counseling
The new legislation (S08227/A11487) will institute significant advances in making
HIV testing routine, such as:
• Section 1 also provides that HIV counseling messages shall be tailored based
on whether the HIV test indicates infection.
• Counseling with respect to positive tests will remain consistent with existing law.
• In the case of negative results, counseling will emphasize risks associated with
participating in high risk behavior and may be accomplished by oral or written
reference to information previously provided.
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Informed Consent vs Assent
• Informed consent: Explanation of the risks, benefits and alternatives to testing, and some attempt to ensure that these are understood
• Opt-out assent: “The patient will be notified that the test will be performed, and consent is inferred unless the patient declines.”
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Revised RecommendationsAdults and Adolescents
• Routine, voluntary HIV screening for all persons 13-64 years in healthcare settings
• Opt-out HIV screening with the opportunity to ask questions and the option to decline testing
• Separate signed informed consent should not be required
• Prevention counseling in conjunction with HIV screening in healthcare settings should not be required
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Qualitative Research
• The videos were made with input from focus groups and semi-structured individual interviews
• The material was tailored to meet the needs of urban youth
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Adolescent-Specific Multimedia Program
• Project Control is a theory-based program designed for teens by teens
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Adolescent-Specific Multimedia Program
• This study compared a youth-friendly HIV education video to in-person HIV counseling to determine the most effective way to convey HIV knowledge and improve HIV testing rates
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Adolescent-Specific Multimedia ProgramResults
• Of 333 eligible patients, 200 (60%) agreed to participate and were randomized
Counselor (n=100)
Video(n=100)
p-value
Age 17.5 ± 1.9 18.1 ± 2.0 0.04
Male 53% 52% 0.89
Hispanic 52% 41% 0.12
Prior HIV test 40% 30% 0.14
Avg pre-test score 57.6% 58.5% 0.18
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Adolescent-Specific Multimedia Program - Results
Video Counselor
Average score 78.5% 66.3%
p-value <0.01 <0.01
95% C.I. 76.2 to 80.1 63.6 to 69.0
Post-test HIV knowledge scores
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Adolescent-Specific Multimedia Program Conclusions
• 51% of adolescents who watched the video consented for HIV testing – only 22% of adolescents who received in-
person counseling consented (p<0.01)
• A youth-friendly HIV education video improved HIV knowledge and increased rates of testing
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RCT 2: Effect of a theory-based, post-HIV test counseling video designed with feedback from
adolescents
• Goal of the investigation– determine if focused, teen-specific videos
change intended risk behavior compared to standard HIV testing and counseling
• Participant eligibility– Between 15 and 21 years old– Sexually active
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Stages of Change Model• Behavior change is the result of change
that occurs in smaller stages.– Precontemplation: not thinking seriously about
changing behavior– Contemplation: aware of the problems caused
by a specific behavior– Preparation: make a commitment to change– Action: take steps to change behavior– Maintenance: take steps to avoid relapse in
behavior
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Stages of Change for Condom UseItem content PC C PR A M
When you had sex, how often did you use condoms in the past 30 days?
Never; Almost
never; Sometimes; Almost every
time
Never; Almost
never; Sometimes; Almost every
time
Never; Almost
never; Sometimes;
Almost
every time
Every time
Every time
For how long have you been using condoms every time?
- - - -
Less than 6 months
6 months or more
Are you considering starting to use condoms every time within the next 6 months?
No
Yes
Yes
Yes
- -
Are you planning to start using condoms every time within the next 30 days?
-
No
Yes
Yes - -
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Theory-based videos
• Stages of Change Model for Condom Use5 Stages of Change
1. Pre-contemplator
2. Contemplator
3. Preparation for action
4. Action
5. Maintenance
“Negative consequences” video
“Positive consequences” video
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Theory of Reasoned Action
• A person’s attitude toward a behavior, combined with subjective norms, forms one’s behavioral intentions.
• Validated measures to determine behavioral intention– Self-Efficacy: attitude of one’s ability to
perform a behavior– Outcome Expectancy: beliefs on the likely
consequences for a behavior
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Measures
• Self-Efficacy: 12 QuestionsEx: On a scale of 1 (not sure at all) to
7 (completely sure): You can put a condom on yourself so that it will not slip or break?
• Outcome Expectancy: 9 questionsEx: On a scale of 1 (strongly disagree)
to 5 (strongly agree): If you use condoms, your relationship with your partner will be better
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RCT 2: Design and Demographics
Counselor (n=101)
Video(n=102)
p-value
Age 18.7 ± 1.6 18.8 ± 1.5 0.58
Male 45% 39% 0.44
Hispanic 57% 60% 0.73
Prior HIV test 69% 66% 0.69
- 2 study arms: counselor group (control) and video group (experimental)- Participants completed pre- and post-intervention measures on: condom intention,
condom outcome expectancy, and condom self-efficacy. Both arms offered HIV testing.
- 203 (94%) agreed to participate and were randomized.
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Pre-intervention measures
“Consent for HIV Test” Teen Pre-test video
Decline to test Agree to test
Obtain consent/Perform HIV test
Should I use a Condom Video
Randomization
Counselor Group(Control)
Video Intervention GroupPC/Contemplation Neg. Consequences
Prep./Action/Maintenance Positive Consequences
Condom DemonstrationVideo
Condom DemonstrationVideo
Post-intervention measuresSatisfaction Questionnaire
Post-intervention measuresSatisfaction Questionnaire
HIV Test Results Delivered(if applicable)
Participant Flow Diagram
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RCT 2: Results• Stages of Change for Condom Intention
Measure– Mean difference in both arms for change over
time: 1.02, CI(.24,1.80) SD=2.87.
• Through immediate change in condom intention score, the intervention:1. helped people progress to the next level of
readiness
2. maintained participants’ positive behavior
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B.R.I.E.F. validation study
Validate the effectiveness of B.R.I.E.F. in a community hospital ED
• acceptability
• patient satisfaction
• linkage to care
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Validation study- results
8793
999995
7685
979996
0
20
40
60
80
100
120
Accepted testing* Found ED testinghelpful
Video answered HIVquestions
Learned new HIVinformation
Plan to change sexpractices
Urban (n=8924) Community (n=3544) *n=11565;5350
5123 patients were tested in the community ED
% o
f P
atie
nts
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Conclusions• This model’s effectiveness in two distinct venues
suggest more widespread applicability
Community Urban Difference;95% CI
HIV+ 0.35% (18/5123) 0.35% (39/11038) 0%; [-0.2 to 0.2]
Linked to care 77.8% (14/18) 84.6% (33/39) -6.8%; [ -31 to 13]
Newly dx’d 77.8% (14/18) 79.5% (31/39) -1.7%; [-27 to 18]
AIDS at dx 35.7% (5/14) 51.4% (18/35) -16%; [-41 to 14]
Initial CD4 (mean) 419 ± 316 342 ± 369 77; [-156 to 309]
Outcomes for Positive Patients
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Analysis of patients who refuse testing
Characteristics and risk factors of patients who decline HIV testing
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Refusal Analysis - Results
• 44% of patients refused testing because they felt they were “not at risk for HIV infection.”
59.2% had vaginal sex in the past 3 months
49.2% described condom use as “never”
10.9% had a previous STI diagnosis
37.1% had more than one current sexual partner
Accepted Refused
Male 46.5% (6919/14849) 47.2% (515/1090)
Hispanic 50.4% (7492/14860) 13.5% (147/1090)
Black 34.5% (5128/14860) 40.2% (438/1090)
Married 14.6% (2175/14860) 18.1% (197/1090)
Age ≤ 29 45.9% (6810/14843) 27.6% (300/1087)
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Cost:
Chen et al, CID 2006;42-1003-1010
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HIV Testing Expansion: Earlier Diagnosis, Higher CD4 Counts
• Program to expand testing in medical and jail settings in Washington, DC began in 2006
• Since program began, patients diagnosed with higher CD4 counts at initial testing
• During first 18 months of program, increase in median CD4+ count at diagnosis to 332 cells/mm3
Median CD4+ Countat Time of Testing
215
187 198220
262
332
183
0
50
100
150
200
250
300
350
2001 2002 2003 2004 2005 2006 2007
Year of HIV Diagnosis
Me
dia
n C
D4
Co
un
t
Hader S, et al. 16th CROI; 2009; Montreal. Abstract 57.
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Qualitative Research Study:African-born Immigrants Population Data
• African immigrants to the USA increased
from 109,733 between 1961 and 1980 to
531,832 between 1981 and 2000.
• The Bronx’s sub-Saharan African
population ballooned from 12,063 in 1990,
to 36,361 in 2000, to 54,932 in 2007.
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African-born Immigrants: HIV data• African-born individuals in the USA had a disproportionately high prevalence
of HIV – although they comprised only 0.6% of the study population, almost
4% of HIV diagnoses were amongst African-born individuals.
– up to 41% of diagnoses in F’s (mean: 8.4%, range: 4%-41%) & up to
50% of diagnoses in blacks (mean: 8.0%, range: 2%-50%) occurred
among African-born individuals.
– Data collated and analyzed aggregate data on persons dx’d with HIV in
2003-2004 and reported to HIV surveillance units in California, Georgia,
Massachusetts, Minnesota, and NJ and in King County, Washington;
NYC; and the portion of Virginia included in the DC, metropolitan area
• There is a “hidden epidemic” of HIV amongst African migrants living
in the USA.
JAIDS Journal of Acquired Immune Deficiency Syndromes . 49(1):102-106, 1 September 2008.
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Qualitative Research Study:African-born Immigrants
• Community-based Participatory Research– Engage African-born immigrant community
• Small, gender-divided focus groups
– Produce culturally-sensitive educational media
• Tailor HIV educational messages to a specific community
– Modify videos according to community feedback
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Adolescent Cohort
• CDC estimates indicate that HIV seroincidence rates among individuals 13-29 are increasing
• B.R.I.E.F. patients under 21 were analyzed to assess the efficacy of the intervention on this high risk group
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Conclusions
Despite the challenges to engage and test teens:
• High acceptability of an integrated, ED-based HIV testing program
• The computer program helped to elicit a behavior profile which showed significant HIV risk
• This model could be an important way to expose a hard-to-reach and high risk population to HIV prevention messages
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Conclusions- RCT2
• Young people are engaging in behavior which puts them at high risk for contracting HIV
• Innovations in HIV prevention need to be utilized to influence those most at risk
• Interventions should be tailored to meet the needs of the community and formulated with input from teens
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Qualitative Research Study:African-born Immigrants
• Community-based Participatory Research– Work with African-born immigrant
communities to share videos in key community settings
• Expansion to other sites across the world– Dublin, Ireland
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Total: 33 million (30 – 36 million)
Western & Central Europe
730 000730 000[580 000 – 1.0 million][580 000 – 1.0 million]
Middle East & North Africa
380 000380 000[280 000 – 510 000][280 000 – 510 000]Sub-Saharan Africa
22.0 million22.0 million[20.5 – 23.6 million][20.5 – 23.6 million]
Eastern Europe & Central Asia
1.5 million 1.5 million [1.1 – 1.9 million][1.1 – 1.9 million]
South & South-East Asia
4.2 million4.2 million[3.5 – 5.3 million][3.5 – 5.3 million]Oceania
74 00074 000[66 000 – 93 000][66 000 – 93 000]
North America1.2 million
[760 000 – 2.0 million]
Latin America1.7 million1.7 million
[1.5 – 2.1 million][1.5 – 2.1 million]
East Asia740 000740 000
[480 000 – 1.1 million][480 000 – 1.1 million]Caribbean230 000
[210 000 – 270 000]
Adults and children estimated to be living with HIV, 2007
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USA Statistics
• At the end of 2003, an estimated 1.1 million persons in the United States were living with HIV/AIDS
• 21% are undiagnosed and unaware of their HIV infection
• CDC estimated that approximately 56,300 people were newly infected with HIV in 2006
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3,948 patients approached
1,940 pts (73.8%) tested
6 pts(0.3% tested HIV+)
Pharmacy Testing Results
2,627 pts (66.5%) eligible
687 pts (26.2%) refused
-Data from 10/26/09 to 05/01/11
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Bioscrip De Franco Congress
Start Date 10/26/2009 01/06/2010 09/16/2010
Days of testing 102 87 22
Patients Approached 1520 1299 266
Eligible patients68.0%
(1033/1520)65.1%
(846/1299)64.7%
(172/266)
Eligible Patients tested74.4%
(769/1033)73.8%
(624/846)76.7%
(132/172)
Mean tests per day (range)
7.5(3-18)
7.2(1-12)
6.0(2-10)
Community Pharmacy Testing
Two patients have tested positive
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Community Pharmacy Testing: Demographics
Bioscrip De Franco Congress
Mean Age (range) 33.6 (13-86) 31.9 (13-82) 32.9 (15-74)
Male39.6%
(305/769)42.0%
(261/622)44.3%(58/131)
Hispanic55.4%
(426/769)63.7%
(387/608)60.3%(79/131)
Non-Hisp. Black33.9%
(261/769)33.0%
(205/622)34.4%(45/131)
Language English Spanish Other
(n=764)71.3% (545)26.7% (204)2.0% (15)
(n=618)70.7% (441)25.3% (158)3.1% (19)
(n=130)71.5% (93)23.8% (31)4.6% (6)
Uninsured 38.5% (294/764) 33.4% (207/619) 35.9% (47/131)
Prior HIV Test74.3%
(567/763)76.4%
(476/623)86.3%
(113/131)
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Community Pharmacy Testing: Demographics
Bioscrip De Franco Congress
Mean Age (range) 33.6 (13-86) 31.9 (13-82) 32.9 (15-74)
Male39.6%
(305/769)42.0%
(261/622)44.3%(58/131)
Hispanic55.4%
(426/769)63.7%
(387/608)60.3%(79/131)
Non-Hisp. Black33.9%
(261/769)33.0%
(205/622)34.4%(45/131)
Language English Spanish Other
(n=764)71.3% (545)26.7% (204)2.0% (15)
(n=618)70.7% (441)25.3% (158)3.1% (19)
(n=130)71.5% (93)23.8% (31)4.6% (6)
Uninsured 38.5% (294/764) 33.4% (207/619) 35.9% (47/131)
Prior HIV Test74.3%
(567/763)76.4%
(476/623)86.3%
(113/131)
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Community Pharmacy testing: Risk Factors of Patients Tested
Bioscrip De Franco Congress
Condom use described as never, almost never, or sometimes
46.5%(342/718)
48.5%(283/584)
51.6%(64/124)
Sex with multiple partners40.2%
(309/769)38.0%
(237/624)43.2%
(57/132)
Previously had an STD9.4%
(72/761)11.8%(73/620)
14.5%(19/131)
Sex with partner with HIV1.8%
(13/737)3.8%
(23/611)3.1%
(4/131)
Sex with known MSM3.0%
(22/738)0.7%
(4/613)1.5%
(2/131)
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Special Populations: Black African Immigrants
Female (n=6)
Male(n=8)
Age Range (years) 25-50 25-45
Country of OriginNigeria
(6/6)Côte d'Ivoire (6/8)
Mali (2/8)
Length of stay in U.S. > 1year 100% 100%
Regularly engaged in health care 2/6 0/8
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Building Linkage:Coordination of ED/hosp testing with HIV clinical care
Pt tests HIV+ in UCA/ED
Pt stable & d/c’dPt admitted to inpt
Pt admitted to inpt ACS HIV team
Communication from PHA to HIV care team about pt
Pt stabilized & d/c’d
Pt d/c’d to NH (etc)
Pt d/c’d home w/ f/u at ACS clinic
Pt escorted to ACS clinic
Open access ACS HIV clinic
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Special Populations: Black African Immigrants
Collaborate with Community Leaders“You can also…try to contact the imam, try to contact the head of the different communities. Try those people to involve those people, probably they're going to help.”
Cultural Relevance“I think it's going to be important to have an African—somebody from Africa (physician)… and he's working over here, I think that is very important. That [is] going to encourage people to come get tested.
General Health Approach“In order to make more Africans engage in testing, I think you don't have to focus only on HIV, but focus on other diseases like high blood pressure, many things.”
“[If you are testing] for just HIV you won't see nobody.”
Strategies to Increase HIV Testing
Special Populations: Black African Immigrants