yvette calderon, m.d., m.s. professor of clinical emergency medicine albert einstein college of...

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

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

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

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

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

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

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

http://www.nyc.gov/html/doh/images/hiv/bronx-knows-mta-large.jpg

http://www.nyc.gov/html/doh/images/hiv/bronx-knows-mta-large-sp.jpg

Testing by Agency and Agency Type January 2008 – December 2009

N=175,742 total tests

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.

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

• 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

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

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%

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%

• 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

Linkage to Care Data

October 2005 – July 2011

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)

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)

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.

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)

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

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

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

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

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


2,010 pts (73.0%) tested

6 pts(0.3% tested HIV+)

Pharmacy Testing Results


745 pts (27.0%) refused

-Data from 10/26/09 to 06/07/11

-289 Days of Testing

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)

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

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

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)

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

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


• 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

"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)


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



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)


(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)

Community Pharmacy testing: Risk Factors of Patients Tested


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)

Recruitment Methods

• Participants were recruited using a social network strategy that involved leaders of black African community organizations within the Bronx.

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

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.

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)

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

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.

Does HIV testing and initiation of HAART impact

COST?

Cost:

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.

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

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.

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.”

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

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

Adolescent-Specific Multimedia Program

• Project Control is a theory-based program designed for teens by teens

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

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

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

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

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

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

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 - -

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

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

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

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.

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

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

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

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

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

Analysis of patients who refuse testing

Characteristics and risk factors of patients who decline HIV testing

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)

Cost:

Chen et al, CID 2006;42-1003-1010

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.

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.

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.

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

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

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

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

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

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

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


1,940 pts (73.8%) tested

6 pts(0.3% tested HIV+)

Pharmacy Testing Results


687 pts (26.2%) refused

-Data from 10/26/09 to 05/01/11

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



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)


(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)

Community Pharmacy testing: Risk Factors of Patients Tested


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)


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

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


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


yvette calderon, m.d., m.s. professor of clinical emergency medicine albert einstein college of...

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