Should we be measuring mortality in hiv clinical programs september 13 th 2012
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Should We be Measuring Mortality in HIV Clinical Programs? September 13 th , 2012. Steven Johnson MD Director, University of Colorado HIV/AIDS Clinical Program; Professor of Medicine, Division of Infectious Diseases; University of Colorado School of Medicine.

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Should We be Measuring Mortality in HIV Clinical Programs? September 13 th , 2012

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Should we be measuring mortality in hiv clinical programs september 13 th 2012

Should We be Measuring Mortality in HIV Clinical Programs?September 13th, 2012

Steven Johnson MD

Director, University of Colorado HIV/AIDS Clinical Program;

Professor of Medicine, Division of Infectious Diseases;

University of Colorado School of Medicine


How many of you currently track mortality in your hiv clinical program

How many of you currently track mortality in your HIV clinical program?


Outline

Outline

  • Great Improvements over Time

  • Mortality in the Current Era

  • Health Disparities and Mortality

  • Measuring Mortality in Clinical Programs


Great improvements over time

Great Improvements over Time


Effect of art on mortality over time

Effect of ART on Mortality Over Time

% of Patients on ART

Deaths per 100 Person-Years

8

90

80

7

70

6

60

5

50

Patients on ART, %

Deaths per 100 Person-Years

4

40

3

30

2

20

1

10

0

0

1996

1997

1998

1999

2000

2001

2002

2003

2004

Palella FJ et al. J Acquir Immune Defic Syndr. 2006;43(1):27-34.


Should we be measuring mortality in hiv clinical programs september 13 th 2012

University of Colorado HIV Clinical Program: AIDS Class C Deaths, 1995-2011

1554 HIV+

Patients in Care in 2011


3 million years of life saved

3 Million Years of Life Saved

  • Attempt to quantify mortality impact of ART and OI prophylaxis from 1989-2003

  • Defined eras of treatment relative to OI prophylaxis, ART, and prevention of mother-to-child transmission

  • The model estimated the survival benefit of treatment in each era

  • As of 2003 in the U.S., the cumulative survival benefit of HIV treatment estimated at 2,951,371 years of life

Walensky R, et al. JID 2006;194:11-19


2012 unaids report

2012 UNAIDS Report

  • 2011 data for low and middle income countries:

  • 8 million on ART

  • 14 million life-years saved


Life expectancy from age 20 in patients starting antiretroviral therapy

Life Expectancy from Age 20 in Patients Starting Antiretroviral Therapy

  • NA-ACCORD: multicenter study involving 23 cohorts and over 75,000 HIV+ patients.

  • Current study evaluated a subset of patients > 20 years old and starting antiretroviral therapy between 1996 and 2007.

  • Life expectancy estimated for cohort as well as subsets of patients based on sex, race, transmission category, and baseline CD4 count.

  • 1799 deaths occurred during 89,521 person-years of follow up.

Hogg et al, Abstract 137, 19th CROI, Seattle, 2012


Life expectancy in years from age 20 by sex 1996 2007

Life Expectancy in Years from Age 20 by Sex, 1996-2007

General Population

HIV+

Hogg et al, Abstract 137, 19th CROI, Seattle, 2012


Life expectancy from age 20 in patients starting antiretroviral therapy1

Life Expectancy from Age 20 in Patients Starting Antiretroviral Therapy

Hogg et al, Abstract 137, 19th CROI, Seattle, 2012


Mortality in the current era

Mortality in the Current Era


Factors affecting hiv mortality

Factors Affecting HIV Mortality

  • Immunodeficiency

  • HIV viremia

  • When to Start ART

  • Co-morbidities

    • Hepatitis C

    • Tobacco use

    • Substance use

    • Mental illness

    • Non-AIDS CA

    • Cardiovascular disease

  • Undiagnosed HIV

  • Late presentations

  • Linkage to care

  • Retention in care

  • Access to care

  • Health Disparities

  • Health insurance

  • Provider expertise


Patients presenting to the university of colorado hospital with pcp and a new hiv diagnosis

Patients Presenting to the University of Colorado Hospital with PCP and a New HIV Diagnosis


Viremia copy years predicts mortality among treatment na ve hiv patients

Viremia Copy-Years Predicts Mortality Among Treatment-Naïve HIV+ Patients

  • Treatment naïve patients starting ART from 2000-2008

  • Viremia copy-years, a measure of cumulative plasma HIV exposure, determined for each patient

  • Viremia copy-years predicted all cause mortality independent of cross-sectional RNA and CD4 count

Mugavero M, et al. CID 2011:53:927-935


Co morbidities in hiv infection

Depression

Bipolar Disease

Other Mental Illness

Alcohol use

Tobacco use

Other Drug use

Hepatitis B

Hepatitis C

Human Papillomavirus

Coronary Disease

Hyperlipidemia

Diabetes mellitus

Hypertension

Aging

Co-morbidities in HIV Infection


D a d study

D:A:D Study

  • Data Collection of Adverse Events of Anti-HIV Drug Study

  • Collaboration of 11 cohorts following HIV+ individuals in 212 clinics in 21 countries in Europe, U.S., and Australia

  • Data collection at enrollment and at least every 8 months after

AIDS 2010;24:1537-1548


Causes of death in the d a d

Causes of Death in the D:A:D

Other

  • Suicide (3.9%)

  • Drug OD (2.5%)

  • Euthanasia (0.2%)

  • Homicide (0.6%)

  • Accident (1.5%)

  • Invasive bacterial infection (6.7%)

  • Lactic acidosis (0.6%)

  • Pancreatitis (0.7%)

  • Renal dysfunction/disease (1.2%)

  • Other (10%)

  • Unknown (5.3%)

AIDS 2010;24:1537-1548


Causes of death in d a d over two time periods

Causes of Death in D:A:D Over Two Time Periods

Weber R, et al, Abstract THAB0304, XIX IAC, Washington, D.C., 2012


University of colorado hiv aids clinical program mortality 2006 2010

University of Colorado HIV/AIDS Clinical Program Mortality 2006-2010

At least 89 deaths out of 2494 HIV+ patients seen over the last 5 years


Cause of death over three 5 year periods of the art era

Cause of Death Over Three 5-Year Periods of the ART Era

University of Colorado Hospital HIV Program


Incidence of non aids cancers among hiv persons compared to general u s population

Incidence of Non-AIDS Cancers among HIV + Persons Compared to General U.S. Population

Patel P, et al. Ann Intern Med 2008;148:728-736


Cancer as a cause of death among people with aids in the united states

Cancer as a cause of death among people with AIDS in the United States

  • Evaluation of cancer deaths in a U.S. cohort of 83,282 persons with AIDS

  • NHL was the most common cause of cancer death

  • Lung cancer was the most common non-AIDS cancer

Simard E and Engels E. CID 2010;51:957-962


Should we be measuring mortality in hiv clinical programs september 13 th 2012

Non-AIDS Malignancy as a Cause of Death, 2006-2010; 19 cancer deaths out of 89 total deaths, N = 2494 HIV+ patients

University of Colorado Hospital HIV Program


D a d all cause mortality

D:A:D: All-Cause Mortality

Weber R, et al, Abstract THAB0304, XIX IAC, Washington, D.C., 2012


Health disparities and mortality

Health Disparities and Mortality


Life expectancy from age 20 in patients starting antiretroviral therapy 1996 2007

Life Expectancy from Age 20 in Patients Starting Antiretroviral Therapy, 1996-2007

Race/Ethnicity (U.S.)

Transmission Risk

Hogg et al, Abstract 137, 19th CROI, Seattle, 2012


Measuring mortality in clinical programs

Measuring Mortality in Clinical Programs


Potential use of mortality data

Potential Use of Mortality Data

  • Compare performance between HIV programs.

  • Provide individual programs with data for internal analysis and development of local quality improvement initiatives.

  • Analyze aggregate outcomes data to determine the importance of existing measures and aid in the development of new measures.

  • Use aggregate outcomes data as a tool to advocate for ongoing support of RW programs.


Potential issues with using mortality as a measure

Potential Issues with Using Mortality As A Measure

  • Programs will vary based on the patient population and underlying co-morbidities.

  • Defining when a patient is in care and a death is attributable to the program can be difficult.

  • Ascertaining cause of death can be difficult (autopsies are uncommon).

  • Outcomes may be unknown for patients not retained in care (lost to follow up).

  • Small programs may have variations in mortality from year to year that may not be related to quality.


Retention in care project at uch in 2010 seen in last 18 months but not last 6 months

Retention in Care Project at UCH in 2010 (Seen in last 18 months but not last 6 months)


Should we be measuring mortality in hiv clinical programs september 13 th 2012

Patient migration significantly impacts estimates of engagement in HIV care and attainment of undetectable HIV-RNA levels in a cohort of newly HIV-diagnosed individuals

Rowan S, et al. World AIDS Conference 2012


Comparing d a d to our local qi project

Comparing D:A:D to our Local QI Project

1999-2008, N = 2482

2006-2010, N = 89


Hivqual survey 2011

HIVQUAL Survey-2011

  • Do you currently measure mortality in your HIV program? 11 yes, 7 no

  • Methodology

    • Review of Death Records = 3

    • Phone calls to patients who are LTF = 9

    • Check with death registries = 4

    • Medical record audits = 6

    • Autopsies infrequent

  • Concerns about accuracy and feasibility


Should we be measuring mortality in hiv clinical programs september 13 th 2012

Deaths Among Persons Living with HIV and AIDS in Colorado, 1982-2009

Combination ART Era

1982

1995

2009

Source: Colorado Department of Public Health and the Environment


Disparities among states in hiv related mortality

Disparities Among States in HIV-Related Mortality

  • Cross-sectional analysis of deaths due to HIV in the National Vital Statistics System in relationship to reported HIV/AIDS cases in 37 states, 2001-2007

  • HIV Case-Fatality rates calculated and compared across states

Hanna et al. AIDS 2011; epub ahead of print.


Should we be measuring mortality in hiv clinical programs september 13 th 2012

Hanna et al. AIDS 2011; epub ahead of print.


Linkage access art use and viral suppression in four large cities in the united states 2009

Linkage, Access, ART Use and Viral Suppression in Four Large Cities in the United States, 2009

Benbow N, et al, World AIDS Conference, Washington, D.C. 2012


Potential strategies to reduce mortality community level

Potential Strategies to Reduce Mortality: Community Level

  • Expanded HIV testing efforts

  • Improved linkage to care

  • Reengagement in care

  • Access to expert care (HIV workforce issues)

  • Address health disparities

  • Health care reform

  • Other funding and resource issues


Should we be measuring mortality in hiv clinical programs september 13 th 2012

University of Colorado HIV/AIDS Clinical Program Mortality, 1999-2011

1554 patients in care in 2011


Potential strategies to reduce mortality clinic level

Potential Strategies to Reduce Mortality: Clinic Level

  • Earlier use of antiretroviral therapy

  • Integration of HIV and primary care (medical home)

  • Aggressive programs for co-morbidities:

    • HIV-HCV co-infection programs

    • Tobacco cessation projects

    • Cancer screening

    • Mental health/substance abuse programs

  • Retention in care and engagement in care projects

  • Medication adherence programs

  • Medical case management


Potential clinic mortality indicator

Potential Clinic Mortality Indicator

  • DRAFT Mortality Indicator (1): Percentage of active patients who died during the measurement year.

    • Denominator: All active patients.

    • Numerator: Number of patients who died during the measurement year.

    • Exclusion(s): None.

  • DRAFT Mortality Indicator (2): Percentage of active patients who died during the measurement year and for whom a non-HIV/AIDS-related cause of death was noted within the clinic's records..

  • DRAFT Mortality Indicator (3): Percentage of active patients who died during the measurement year and for whom an HIV/AIDS-related cause of death was noted within the clinic's records.


Should we be measuring mortality in hiv clinical programs

Should We be Measuring Mortality in HIV Clinical Programs?

  • Is the rate of mortality in this era too low to discriminate differences between programs?

  • Do the varying rates of co-morbidities among programs make it too difficult to track and compare mortality rates?

  • Given factors such as lost to follow up and low autopsy rates, can the cause and frequency of death be accurately measured?

  • Are there local factors external to the program (e.g. late presentations, access to care) that affect mortality independent of program quality?

  • Should individual programs track mortality or can they learn enough from published data?

  • Are aggregate data from multiple programs useful for research, quality improvement, and advocacy?


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