1. Quality of HIV Care and Mortality in HIV-Infected Patients Who Use Drugs and Alcohol
PT Korthuis, KL Kraemer, KA McGinnis, M Skanderson, AJ Gordon, AC Justice, DA Fiellin for the Veteran’s Aging Cohort Study
College on Problems of Drug Dependence June 19, 2013
Funded by U24-AA020794, U01-AA020790, & K23-DA19809

2. Disclosures
No conflicts of interest

3. Background
Substance abuse is common among HIV-infected patients and decreases survival1-3
Previous studies demonstrate lower quality of care for HIV-infected patients with alcohol or drug use4
No studies assess whether higher quality of HIV care improves survival for patients with and without drug or alcohol use
1 Korthuis AIDS Pt Care STD 2008
2 Lucas Am J Epi 2006
3 Braithwaite AIDS Care 2007
4 Korthuis JAIDS 2012

4. Objective & Hypothesis
Objective: To assess whether receipt of HIV care quality indicators (QIs) is associated with mortality in HIV-infected patients who use drugs and/or alcohol.
Hypothesis: Higher quality of HIV care (QOC) is associated with lower mortality in patients with illicit drug and unhealthy alcohol use.

5. Methods Design: Prospective cohort study
Setting: Veteran’s Aging Cohort Study (VACS)
8 geographically diverse VA infectious disease clinics
Participants: 3,408 HIV-infected patients enrolling between June 2002 and July 2008

6. Measures
Independent Variable: Percent of HIV quality indicators (QI) received, if eligible, in first 12 months after enrollment
9 HIV QIs abstracted from administrative data
Dichotomized as “≥ 80% QIs” vs. “< 80% QIs” received
1 Justice AC JAIDS 2013
2 Tate JP AIDS 2013

7. 9 HIV Quality Indicators
Pass Criteria
Eligibility Criteria
Medications
ART
Receipt of ART in past 12 months
CD4 nadir ≤ 350 cells/mL3 ever
PCP proph
Receipt of dapsone, tmp/smx, atovaquone, pentamidine in past 12 months
CD4 count ≤ 200 cells/mL3 in past 12 months
MAC proph
Receipt of clarithromycin, azithromycin, or rifabutin in past 12 months
CD4 count ≤ 50 cells/mL3
Screening
Hyperlipidemia
Lipid test in past 12 months
On ART
Hepatitis C
Hepatitis C antibody test, ever
All
Prevention
Pneumovax
Pneumococcal vaccine, ever
Influenza
Influenza vaccine in past 12 months
Monitoring
CD4
≥ 2 CD4 counts performed in past 12 months
HIV Visits
≥ 2 HIV clinic visits in 12 months

8. Measures (cont.) Covariates:
Illicit drug use (past year stimulants, opioids, or IDU)
Unhealthy alcohol use (AUDIT-C score ≥ 4)
Gender
VACS Index1,2, validated measure of HIV disease severity based on:
Age
CD4
HIV-1 RNA
Hemoglobin
Liver injury
Renal injury
Hepatitis C
Liver injury = FIB-4
1 Justice AC JAIDS 2013
2 Tate JP AIDS 2013

9. Measures (cont.)
Outcome variable: Deaths per 100 person-years, determined by:
Patient Treatment File
Death in VA hospital
Beneficiary Identification Records Locating System
VA death benefits
Medicare Vital Status file
Social Security National Death Index
Cause of death used to assess HIV-related, Non-HIV-related mortality

10. Analysis
Associations between the percent QIs received and overall, HIV-related, and non-HIV-related mortality assessed using
Kaplan Meier survival analysis
Cox proportional hazards models adjusted for gender and VACS index
Analyses stratified by past year illicit drug and unhealthy alcohol use

11. Patient Characteristics
740 deaths (21.7%)
15,013 patient-years follow-up
Mean 4.40 (SD 1.45) years
Mean Age (SD)
49.1 (8.8)
Male Gender (%)
97.4
Race/ethnicity (%)
White
Black
Latino
Other
19.6
67.0
9.4
4.0
CD4 > 200 (%)
75.9
HIV RNA < 500 (%)
49.1
On Antiretrovirals (%)
83.2
> High School/GED (%)
58.7
Ever Homeless (%)
42.1
HCV Positive (%)
53.6
Depression (%)
22.2
Unhealthy Alcohol Use (%)
25.8
Drug Use (%)
Opiates
Cocaine
Stimulants
22.0
9.5
21.9
4.3
Injection Drug Use (%)
7.1

12. All-Cause Mortality (Deaths/100 Person-Years, n=3408)
< 80% QIs Received
≥ 80% QIs Received
P-value
aHR (95% CI)*
Overall
6.40
4.35
<.001
0.73 (0.62, 0.85)
Unhealthy Alcohol Use No
Yes
6.27
6.66
4.27
.001
0.72 (0.60, 0.87)
0.73 (0.54, 0.97)
Illicit Drug Use
5.99
6.96
4.15
4.94
.006
0.68 (0.56, 0.82)
0.82 (0.63, 1.06)
*Adjusted for gender and VACS Index

13. HIV-Related Mortality (Deaths/100 Person-Years, n=3408)
< 80% QIs Received
≥ 80% QIs Received
P-value
aHR (95% CI)*
Overall
3.21
1.91
<.001
0.66 (0.53, 0.82)
Unhealthy Alcohol Use No
Yes
3.40
2.89
2.00
1.49
.003
0.65 (0.50, 0.84)
0.57 (0.36, 0.90)
Illicit Drug Use
3.05
3.48
1.78
2.29
.025
0.58 (0.44, 0.77)
0.79 (0.54, 1.15)
*Adjusted for gender and VACS Index

14. Non-HIV-Related Mortality (Deaths/100 Person-Years, n=3408)
< 80% QIs Received
≥ 80% QIs Received
P-value
aHR (95% CI)*
Overall
3.19
2.44
.004
0.79 (0.64, 0.98)
Unhealthy Alcohol Use No
Yes
2.87
3.77
2.35
2.77
.075
.058
0.80 (0.61, 1.04)
0.85 (0.58, 1.25)
Illicit Drug Use
2.94
3.48
2.36
2.65
.055
.097
0.78 (0.59, 1.03)
0.84 (0.58, 1.21)
*Adjusted for gender and VACS Index

15. Survival by QOC and Drug Use Kaplan-Meier Survival Estimates
For drug use: Receiving > 80% of QIs improves survival overall, and narrows the gaps in mortality between patients with (yellow) vs. without (green) drug use.

16. Survival by QOC and Alcohol Use Kaplan-Meier Survival Estimates
For alcohol:  Receiving > 80% of QIs both improves survival overall, and closes the gap in mortality between patients with (yellow) vs. without (green) Unhealthy drinking.

17. Limitations Limited number of quality indicators
Does not account for out-of-VA care
Lack of detailed cause of death for non-HIV-related mortality

18. Conclusions
Overall, higher QOC is associated with decreased All-Cause, HIV-related, and Non-HIV-related mortality.
For HIV-infected patients with unhealthy alcohol or illicit drug use, higher QOC is associated with decreased all-cause and HIV-related mortality
Similar associations were observed between QOC and non-HIV-related mortality, did not meet the statistical threshold for significance.

19. Implications & Significance
Interventions to improve HIV QOC may improve survival for HIV-infected patients
Improved quality of HIV care may help close gaps in mortality for those with substance use disorders
Improving non-HIV-related mortality may require greater attention to treatment of comorbid conditions and substance abuse

20. VACS Acknowledgements
Consortium PI : AC Justice*
Scientific Collaborator (NIAAA): K Bryant
Affiliated PIs: S Braithwaite, K Crothers*, R Dubrow *, DA Fiellin*, M Freiberg*, V LoRe*
Participating VA Medical Centers: Atlanta (D. Rimland*, V Marconi), Baltimore (KA Oursler*, R Titanji), Bronx (S Brown, Y Ponomarenko), Dallas (R Bedimo), Houston (M Rodriguez-Barradas, N Masozera), Los Angeles (M Goetz, D Leaf), Manhattan-Brooklyn (M Simberkoff, D Blumenthal, H Leaf, J Leung), Pittsburgh (A Butt, K Kraemer, M Freiberg, E Hoffman), and Washington DC (C Gibert, R Peck)
Core and Workgroup Chairs: C Brandt, J Edelman, N Gandhi, J Lim, K McGinnis, C Parikh, J Tate, E Wang, J Womack
Staff: H Bathulapalli, T Bohan, J Ciarleglio, A Consorte, P Cunningham, L Erickson, C Frank, K Gordon, J Huston, F Kidwai-Khan, G Koerbel, F Levin, L Piscitelli, C Rogina, S Shahrir, M Skanderson
Major Collaborators: VA Public Health Strategic Healthcare Group, VA Pharmacy Benefits Management, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Yale Center for Interdisciplinary Research on AIDS (CIRA), Center for Health Equity Research and Promotion (CHERP), ART-CC, NA-ACCORD, HIV-Causal
Cross Cohort Collaborators: Richard Moore (NA-ACCORD), Jonathan Sterne (ART-CC), Brian Agan (DoD)
Major Funding by: National Institutes of Health: AHRQ (R01-HS018372), NIAAA (U24- AA020794, U01-AA020790, U01-AA020795, U01-AA020799, U24-AA022001, U24 AA022007), NHLBI (R01-HL095136; R01-HL090342) , NIAID (U01-A ), NIMH (P30-MH062294), NIDA (R01DA035616), NCI (R01 CA173754) and the Veterans Health Administration Office of Research and Development (VA REA , VA IRR Merit Award) and Office of Academic Affiliations (Medical Informatics Fellowship)
*Indicates individual is also the Chair of a Core or Workgroup

21. Questions

22. Supplemental Slides

23. How Much Quality is Enough?
% QIs Received
Deaths per 100 PY
(95% CI)
100%
4.3 (3.8, 4.9)
80-89%
4.4 (3.9, 5.0)
70-79%
7.2 (5.9, 8.8)
60-69%
4.9 (3.9, 6.1)
50-59%
6.4 (4.8, 8.9)
<50%
8.5 (6.5, 11.1)
Mortality rates were similar for those patients receiving 80% or more of quality indicators, if eligible, and began to increase for patients receiving less than 80%. We therefore, decided to dichotomize the % of quality indicators received as >= 80% vs. < 80%.
Mortality began to increase for those with < 80% of QIs
QI dichotomized at ≥80% vs. < 80%

24. Associations Between Individual QIs and Mortality
Quality Indicator
aHR (95% CI)
ART
0.67 (0.50, 0.89)
PCP proph
0.80 (0.49, 1.30)
MAC proph
0.77 (0.39, 1.51)
Hyperlipidemia screening
0.99 (0.82, 1.20)
Hepatitis C screening
0.60 (0.41, 0.86)
Pneumovax
0.55 (0.45, 0.67)
Influenza
1.05 (0.90, 1.21)
≥ 2 CD4 counts in 12 mo
0.63 (0.53, 0.75)
≥ 2 HIV clinic visits
0.58 (0.48, 0.72)
*Adjusted for gender and VACS Index

25. Subject Characteristics (n=3,410)
Overall
Current Unhealthy Alcohol Use
Current Illicit Drug Use
(n=3410)
Yes
(n=864) No
(n=2483)
P value
(n=967)
(n=2355)
Mean Age (SD)
49.1 (8.8)
48.1
49.5
<.001
48.6
49.2
.065
Male Gender (%)
97.4
98.4
97.1
.046
97.2
97.5
.689
Race/ethnicity
White
Black
Latino
Other
19.6
67.0
9.4
4.0
19.1
67.9
9.5
3.5
20.0
66.7
3.9
.845
12.8
75.6
7.5
4.1
22.8
63.1
23.2
CD4 > 200
75.9
74.6
76.5
.258
70.0
78.1
HIV RNA < 500
49.1
42.9
51.5
41.4
51.9
On Antiretrovirals
83.2
79.2
84.6
80.3
84.4
.004
> High School/GED
58.7
54.0
60.8
.001
52.5
61.9
Ever Homeless
42.1
47.6
40.1
8.0
HCV Positive
53.6
58.2
52.1
.002
66.8
Diabetes
19.9
10.1
21.5
14.3
Depression
22.2
27.6
20.5
31.3
18.6
Unhealthy Alcohol Use
25.8 -
39.7
20.6
Drug Use
Opiates
Cocaine
Stimulants
Marijuana
21.9
4.3
27.7
13.0
38.1
6.4
38.8
8.4
16.0
3.7
23.6
33.6
77.0
15.3
49.6
Injection Drug Use
7.1
10.5
6.1
25.1
The majority of the 3,410 patients were male (97%) and african-american (67%) with mean age of 49.1 (SD 8.8) years at baseline. Overall, 22% reported past year illicit drug use and 26% had unhealthy alcohol use.
PT Korthuis JAIDS 2012