Kelly A. Gebo MD MPH for the HIV Research Network
June 8, 2004

 Focus on health services delivery to persons with HIV infection
 Key issues concern:
 Frequency of use of inpatient and outpatient care, and the costs of providing these services
 Use of and adherence to antiretroviral medications
 Access to care and socioeconomic disparities in utilization
 Quality of care and patient safety

 HIV Costs and Services Utilization Study
 Preceded HIVRN
 Collected data in 1996-1998
 Obtained nationally representative sample of
2,864 HIV+ patients in care
 Probability sample permits strong inferences to national population
 Unique data on utilization, clinical symptoms, outcomes in HIV patients

 Recruiting a nationally representative sample is extremely expensive and time-consuming
 Over 1 year to accrue baseline sample
 Sample becomes unrepresentative of population over time, unless refreshed.
 Difficult to obtain medical records from providers not linked to study

 Trade-off representativeness for efficiency and large sample size.
 From HCSUS: Most HIV+ seen by providers with relatively large HIV caseloads.
 Recruit providers of HIV care and extract information from medical records.
 Supplement records data with personal interviews.

 Network of HIV care providers who can collect and transmit clinical and health services utilization for aggregate analyses to a coordinating center
 Provide up-to-date data on:
 Resource use and costs of care
 Clinical outcomes of care
 Linked clinical/resource use outcomes

21 HIV primary and specialty care sites CY 2004

 13 Adult, 2 Pediatric only, 3 Adult and Pediatric
<500 500-1000 >1000
Alameda, Oakland*
Alliance, Boston *
Nemecheck, Kansas
City*
CHOP-Peds
St. Judes-Peds
St. Lukes-Peds
UCSD-Peds
CORE-Peds
Phoenix, AZ *
Drexel
Henry Ford
Montefiore*
OHSU
Rochester *
CORE-Chicago
Johns Hopkins
Montefiore
Parkland
St. Lukes-
Roosevelt
UCSD
Wayne State
*Community-based

1999 2000 2001
10,852 19,410 17,582
7,887
12,345
4,342

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Sites individually collect information electronically and by chart abstraction
De-identified information sent to Central Data
Coordinating Center (DCC)
Data cleaned, quality assured
Reports sent back to sites for confirmation of data
Compatible, multisite database created
Preliminary data analysis at DCC
Data Dissemination
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Data disseminated to investigators after research question proposed, data analysis approved by data subcommittee
Interactive data querying system on the internet
Public use data available

 Feedback
 Project officers meeting monthly
 Data Subcommittee calls 6x per year
 Full Committee calls quarterly
 Intranet website
 Abstracts, posters, papers
 Submission of research ideas, ideas for new variables
 Interview questions
 All contact information

 Acute/chronic hospital care
 Admission/Discharge dates
 Diagnoses
 Outpatient Visits
 Dates of service
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Diagnoses
CPT Coding
 Emergency Department
 Substance Abuse/Mental Health Visits
 Insurance

Median Age (Range) 40 (18 – 89)
Male
Race
African-American
Caucasian
Hispanic
Other/Unknown
HIV Risk Factor
MSM
Heterosexual
IDU
MSM IDU
Heterosexual IDU
Other/UK
7,571 (71.7%)
5,070 (48.0%)
3,282 (31.1%)
2,017 (19.1%)
187 (1.8%)
4,021 (38.1%)
3,432 (32.5%)
1,383 (13.1%)
344 (3.3%)
544 (5.2%)
832 (7.9%)

CD4 Median
<50 cells/mm 3
51-200
201-500
>500
327
1,076 (10.2%)
2,076 (19.7%)
4,370 (41.4%)
3,034 (28.8%)
Viral Load
Median
<10K
10-100,000K
>100K
1,311 copies/ml
6,774 (64.2%)
2,386 (22.6%)
1,396 (13.2%)

Medicaid
Uninsured
Medicare
Private/HMO
Other
31.9%
31.4%
16.3%
11.4%
9.1%

Overall
Blacks
Whites
Women
Men
Age>40
Age<40
OP Utilization
(Visits/year)
5.15
4.58
5.37
IP Utilization
(Admissions/100 PY)
35.8
40.5
28.8
4.80
5.28
5.57
4.64
42.5
33.1
38.4
32.6

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“We are currently utilizing data from E.R. visits to ascertain various modes which patients use to access care:
(1) those who use E.R. and
(2) those who use the [urgent care] clinic for primary care.
With this data we will be able to identify clients who need help in obtaining primary care in our clinic”
Kathleen Clanon, M.D., Alameda County Medical Center
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“ Our monthly collection of CD4 count, viral load values, and missing values has encouraged clinicians to more closely track both the patients in the clinic, and patients who have missed appointments and are late for quarterly clinical and lab monitoring. This has resulted in additional efforts to track patients who have missed visits.”
James Hellinger, M.D.
– Community Medical Alliance, Boston, MA

HAART Usage (CD4<350)
PI Backbone
NNRTI Backbone
 PCP (2 or more CD4<200):
 MAC (2 or more CD4<50)
91%
68%
63%
88%
87%

Male
Age ≥ 40
Blacks
Hispanics
IDU’s
> 4 OP visits
AOR (95% CI)*
(N=2,533)
1.35 (1.00, 1.83)
1.28 (0.89, 1.85)
0.99 (0.71, 1.39)
1.03 (0.70, 1.52)
1.28 (0.89, 1.85)
2.39 (1.76, 3.24)
*Adjusted for site of care, insurance

Male
Age ≥ 40
Blacks
Hispanics
IDU’s
> 4 OP visits
AOR (95% CI)
(N=754)
1.10 (0.63, 1.92)
0.85 (0.54, 1.36)
0.90 (0.49, 1.63)
1.44 (0.69, 3.03)
0.68 (0.37, 1.23)
1.85 (1.02, 3.35)
*Adjusted for site of care, insurance

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“ Projects in the works now include a red flag letter that notifies docs of particular deficiencies (such as lack of PCP or MAI prophylaxis, patients on triple nuke therapy and regimens that have incorrect dosing or contains meds that shouldn't be used together).”
Robert Beil, MD- Montefiore Medical Center
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“ 'The data obtained.…has been helpful in identifying other opportunities to improve and comply with HIV/AIDS national guidelines. Tracking the
CD4 and meds listed on the same page is a reminder to start the patient on prophylaxis as needed.”
John Jovanovitch, MD - Henry Ford Hospital System, Detroit, MI
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“ Participation in the HIV Research Network has been a major stimulus driving our data collection into the clinical realm. It is incredibly productive to reflect upon our own experience, as measured against our peers and national guidelines, as we strive to improve the care we deliver both at systemic and individual levels”
Peter Sklar, MD - Drexel University, Philadelphia, PA

 950 adult and 300 pediatric
 Topics assessed include
 HIV related symptoms and quality of life
 Adherence to ART
 Mental Health and Substance Abuse treatment
 Adverse Drug Events
 More detailed utilization data:
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Case management, home care, pharmacy
 Insurance Coverage

 Drug Interactions
 Variations in care across sites
 Intranet error reporting system

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2002 JAIDS Manuscript on Utilization
2004 JAIDS Disparities in Access to HAART
(in press)
Under Review
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2000/2001 IP/OP Utilization
2001 IP Diagnoses
High rates of OI prophylaxis
Variations in Quality of Care
Pediatric IP/OP Utilization
Pediatric VL suppression

 Near real time data collection with quick feedback to sites
 Addresses disparities in care and safety issues
 Data from the HIVRN may be useful for:
 Allocation of healthcare resources
 Improvement of HIV prevention and treatment strategies

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Longitudinal Data Analysis
 Link treatment to clinical outcomes
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Evaluate complications of HAART
Impact of hepatitis co-infection
Impact of SA/MH diagnoses
Pediatric Issues
 Growth and development
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Reproduction
Disclosure
Interview Data
 Evaluate QOL, HIV symptoms
 Assess adherence

Adult Sites
 Victoria Sharp-
St. Luke’s Roosevelt, NY
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W. Christopher Mathews- UCSD, San Diego
Philip Keiser- Parkland Hospital, Dallas
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James Hellinger- Community Medical Alliance, Boston
Patrick Nemecheck- Nemecheck Health Renewal,
Kansas City
P. Todd Korthuis- OHSU, Portland
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Jeff Nadler- Tampa General Health Care, Tampa
Robert Beil- Montefiore Medical Center, NY
Lawrence Hanau- Montefiore Medical Center, NY
John Post- McDowell Health Care Center, Phoenix
Lawrence Crane- Wayne State University, Detroit
John Jovanovitch- Henry Ford Hospital, Detroit
Kathlen Clanon- Alameda County Consortium, Oakland
Kathye Gorosh- CORE Foundation Chicago
Steven Fine- Community Health Network, Rochester
Peter Sklar- Drexel University, Philadelphia
Pediatric Sites
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Stephen Spector-UCSD,
San Diego
Patricia Flynn-
St. Jude’s,
Memphis
Richard Rutstein- CHOP,
Philadelphia
Data Coordinating Center
 Richard Moore
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Jeanne Keruly
Haya Rubin
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Kelly Gebo
Erin Reilly
Liming Zhou
George Siberry
Funding Sources
 AHRQ
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SAMHSA
HRSA
OAR

6
5
8
7
4
3
2
1
0
A
ID
S-R e la te d
AIDS-Related: Pneumonia, PCP
GI: Pancreatic diseases, liver diseases
Mental Health: Substance-related, affective disorders
Circulatory: Carditis, hypertension
GI
M e n ta l
C irc u la to ry
In fe c ti o u s to ry
R e s p ira
N e rv o u s
Sy s t.
In ju ry
G e n it o u ri n a ry
Bl o o d
Sk in
O th e
H
IV
d r ia g n o s is
N e o p la s m in g
M is s
M u s c u lo s ke l.
Pre g n a n c y

6
5
8
7
4
3
2
1
0
A
ID
S-R e la te d
GI
M e n ta l
C irc u la to ry
In fe c ti o u s to ry
R e s p ira
N e rv o u s
Sy s t.
In ju ry
G e n it o u ri n a ry
Bl o o d
Sk in
O th e
H
IV
d r ia g n o s is
N e o p la s m in g
M is s
M u s c u lo s ke l.
Pre g n a n c y