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.

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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. Anaya, PhD, Herschel Knapp, PhD, Steven M. Asch, MD MPH

Background The key factor to control HIV is adherence to HIV medicationsThe key factor to control HIV is adherence to HIV medications Co-morbidities impede adherenceCo-morbidities impede adherence Mental disorders Substance abuse Hepatitis C

Integrated HIV Care in the VA PHARMACIST HIV SPECIALIST PSYCHIATRIST SOCIAL WORKER PSYCHOLOGIST

Research Questions Would integrated HIV care enable providers to manage co-morbidities more effectively?Would integrated HIV care enable providers to manage co-morbidities more effectively? Would access to more comprehensive integrated care lead to better control of HIV?Would access to more comprehensive integrated care lead to better control of HIV?

Study Design Study population –Retrospective cohort of HIV-infected veterans –Five VA facilities in western U.S. –Oct 2000 to April 2006 Eligibility criteria –Receiving HIV treatment in the VA –Sufficient baseline severity –3+ months of follow-up

Data Sources Quantitative –VA regional data warehouse: demographics, visits, lab tests, diagnoses, pharmacy prescriptions and refills Qualitative –Interviews with chiefs of the HIV clinics to obtain descriptions of integrated services

Four Levels of Comprehensiveness Components of HIV clinics Comprehensive Level 4321 Physician assistant, nurse practitioners xxxx Clinical coordinator xxxx HIV physician specialist xxx Dedicated pharmacist xxx Psychiatristxx Social worker xx Psychologistx

Distribution of Integrated HIV Care Users (N=1,069) 3% I only Multi-level users II only III only IV only 27% 5% 8% 57% Single-level users

Utilization Index PatientComprehensivenessScore Level 4 Level 3 Level 2 Level 1 A00113 B01014 C02028

Survival Analyses First analysis (N=459 single-level users) Time to viral suppression  comprehensive levels Second analysis (N=610 multi-level users) Time to viral suppression  utilization index

Demographics of Study Patients CharacteristicsStatistics Eligible patients, N 1,069 Age, mean (SD) Age, mean (SD) 51 (9.4) Caucasian, African A. (%) Caucasian, African A. (%) 34, 24 Never married (%) Never married (%)57 Low income (%) Low income (%)76 Homeless (%) Homeless (%)18

Clinical characteristics of Patients CharacteristicsStatistics Had co-morbidities (%) 93 No. of co-morbidities per patient 3 Mental disorders (%) Mental disorders (%)56 Hepatitis B (%) Hepatitis B (%)49 Hepatitis C (%) Hepatitis C (%)33 Drug use (%) Drug use (%)31

Factors Adjusted Hazard ratios Multi-level users (n=610) Single-level users (n=459) Age Marital status (Single)  Married  Widow/divorced/separated Low income Homeless STD Number of co-morbidities Baseline HIV viral load Baseline CD4 + counts Factors Associated with Viral Suppression

Factors Adjusted Hazard ratios Multi-level users (n=610) Single-level users (n=459) Access to medication Utilization index 1.12n/a Compared to Level 2 Level 1 Level 1 Level 3 Level 3 Level 4 Level 4n/a Visit frequency n/a1.43

Conclusions HepatitisPsychiatricPsychological Social services HIVprimarycareViralsuppression 2.6 times more likely +

Implications Resources should be allocated to channel patients toward comprehensive integrated HIV care clinicsResources should be allocated to channel patients toward comprehensive integrated HIV care clinics Findings may be relevant for other chronic conditions that require principle care in subspecialty clinicsFindings may be relevant for other chronic conditions that require principle care in subspecialty clinics