1. Clinical Effectiveness, Surrogate Outcomes, and Multimorbidity
Chronic HIV Infection as a Model for Optimizing Care in the Era of Electronic Medical Record Systems

2. Learning Objectives Understand how
Focusing on a single health condition can misinform care
Our choice of outcome measurement can drive decision making
A risk index can serve as an outcome and help us individualize care

3. “By 2015, …50% of people living with HIV/AIDS [in the US] will be over 50 years of age.”
Aging Hearing: HIV over fifty, exploring the new threat.
Senate Committee on Aging. Washington, DC

4. The VA is Ahead of the Curve

5. This is Aging with a Twist
Heavy and prolonged substance use
Alcohol>Cigarettes>>Drugs
Hepatitis C and B Infection
“Return to health” with a vengeance
Underweight to overweight
Low cholesterol to high cholesterol
“Chronic inflammation”
ARV and non ARV treatment toxicity

6. The Problem
Multimorbidity is the rule in aging—especially among those with HIV infection
“Primary focus on [individual] disease(s) may …lead to under treatment, over treatment, or mistreatment.”*
The profile of conditions is not identical to those aging without HIV
Goal: apply concepts of syndromes (e.g. falls), multi-morbidity, and tailored care to those aging with HIV
Tinetti ME, Fried T. The End of the Disease Era. Am J Med 2004;116:

7. Our Solution
An integrated outcome that can be used to compare effectiveness across biopyschosocial interventions.

8. Final Common Pathway
Justice AC. HIV and Aging: Time for a New Paradigm. Curr HIV/AIDS Rep May;7(2):69-76

9. VACS Risk Index
An index composed of routinely collected laboratory values that accurately predicts all cause mortality and morbidity among those with HIV infection
Justice, AC. et. al, HIV Med Feb;11(2): Epub 2009 Sep 14.

10. Components of VACS Index
Age
HIV Biomarkers: HIV-1 RNA, and CD4 Count
“non HIV Biomarkers”: Hemoglobin, HCV infection, and Composite markers for liver and renal injury
Correspond to several major organ systems (immune function, liver, renal, bone marrow) and two major infectious processes: HIV and HCV

11. Age HIV Specific Biomarkers Biomarkers of General Organ System Injury
Index Score
Restricted
VACS
Age (years)
<50
50 to 64 23 12
> 65 44 27
CD4
> 500
cells/mm3
350 to 499 10 6
200 to 349
100 to 199 19
50 to 99 40 28
< 50 46 29
HIV-1 RNA
< 500
copies/ml
500 to 1x105 11 7
> 1x105 25 14
Hemoglobin
> 14
g/dL
12 to 13.9
10 to 11.9 22
< 10 38
FIB-4
< 1.45
1.45 to 3.25
> 3.25
eGFR mL/min
> 60
45 to 59.9
30 to 44.9 8
< 30 26
Hepatitis C Infection 5
Age
HIV Specific
Biomarkers
Biomarkers of General
Organ System Injury

12. Predictive Validity

13. VACS Vs. Restricted Index (Discrimination)
5 Year Mortality from cART Initiation

14. MICU Admission Over 6 Years
Akgun K. et al. American Thoracic Society A5199

15. Construct Validity

16. VACS Index More Correlated with Biomarkers of Inflammation

17. Responsiveness

18. VACS Index Response to 1st Year of cART (+/- 80% adherence)
Notice greater discrimination with VACS index
Solid lines indicate >80% adherence

20. All current /past drinkers at BL (Referent group NH to NH)
sqrtscore
Coef. t
P>t
[95% Conf.
Interval]
sqrtscorebl
0.76
44.95
0.73
0.79
NH to Haz
-0.03
-0.16
0.872
-0.38
0.32
NH to Dx
0.57
1.94
0.052
-0.01
1.14
Haz to Haz
0.26
2.13
0.033
0.02
0.50
Haz to Dx
0.66
2.74
0.006
0.19
Haz to NH
-0.15
-0.86
0.392
-0.49
Dx to Dx
0.15
0.94
0.346
0.45
Dx to Haz
1.06
0.291
-0.28
0.92
Dx to NH
-0.11
-0.31
0.757
-0.80
0.58
NH to past
1.62
0.106
-0.06
Haz to past
0.06
0.29
0.772
-0.34
Dx to past
2.14
0.032
0.04
0.87
Past to NH
0.30
1.8
0.072
0.63
Past to Haz
0.83
2.49
0.013
0.18
1.48
Past to DX
0.979
-0.64
0.62
Past to Past
0.09 1
0.319
-0.09
0.27
_cons
1.16
11.15
0.95
1.36
Average Score is 27 at BL and FU. The average hazardous person who continued to drink hazardously, VACS Index score increased by 2.7 points. If they increase to Dx levels, their score increased by 7 points.

21. Also Plan to Analyze Smoking cessation HCV treatment
ARV Medication changes
Statins and other “anti inflammatory” medications
Major issue: sick quitters

22. Sick Quitters
Checking for an interaction between quitting and having a high score at baseline

23. VACS Index Summary
Is accurate among patients with access to cART in the US, Canada and Europe
Offers substantially more information than CD4, HIV RNA, and age alone
Predicts mortality, MICU admissions, functional status and inflammation
Is responsive to therapeutic and behavioral changes

24. VACS Index Calculator
Direct to Patient Marketing to Provide Information about Prognosis and Motivate Behavior Change

25. Risk Assessment (Decision Support) Tools
Many computerized tools
Available for many health risks including:
Diabetes
Heart disease, MI
Breast Cancer
Colorectal Cancer
HIV Transmission
The concept of developing a web-based risk assessment tool is certainly not new.
If you ‘google’: health risk assessment tools, you get over 20 million hits
The spectrum of what you might find is very broad.
As a sampling, this list includes a number of these.
Many of which are from large organizations: American Diabetes Association, American Heart Association, National Cancer Institute, etc.
There are also many tools to assess risk of HIV transmission

26. Framingham Risk Assessment
Results View:
Risk score results:
Age: 60
Gender:
male
Total Cholesterol:
280 mg/dL
HDL Cholesterol:
100 mg/dL
Smoker:
Yes
Systolic Blood Pressure:
120 mm/Hg
On medication for HBP:      No
Risk Score*
10%
* The risk score shown was derived on the basis of an equation. Other NCEP materials, such as ATP III print products, use a point-based system to calculate a risk score that approximates the equation-based one.
To interpret the risk score and for specific information about CHD risk assessment as part of detection, evaluation, and treatment of high blood cholesterol, see ATP III Executive Summary and ATP III At-a-Glance.
Tool based on the Framingham Heart Study
It assesses for “hard” coronary heart disease outcomes like MI and coronary death

27. Tool Based on Framingham Study
National Heart Lung and Blood Institute
National Institutes of Health
Calculates 10 year risk of “hard” coronary heart disease outcomes like MI
Result is a score with link to explanation

28. Cleveland Clinic
Wells BJ, Jain A, Arrigain S, Yu C, Rosenkrans JR WA, Kattan MW. Predicting Six-year Mortality Risk in Patients with Type 2 Diabetes. Diabetes Care 2008;31:

29. Cleveland Clinic
6-year mortality risk for patients with Type 2 Diabetes
Input demographic and clinical data
Result is a probability

30. Survival Probability http://www.mayoclinic.org/gi-rst/mayomodel1.html
This give the survival probability of a patient with untreated biliary cirrhosis

31. Mayo Clinic Risk Tools Mayo Clinic mortality risk models
This tool is for risk of mortality in patients with untreated primary biliary cirrhosis
Computes a risk score and gives an estimated probability of survival up to 7 years

32. Acute Coronary Syndrome
Global Registry of Acute Coronary Events
UMASS Medical School
Center for Outcomes Research

33. GRACE Center for Outcomes Research, UMASS Medical School
International database
30 countries
247 hospitals
102, 341 patients
Gives probability of death or death/MI at admission or discharge

34. Diabetes Risk Test
This is the first of several screen shots of risk assessment tools. They cover a number of common, health conditions. A few deal with very serious health problems (ie: MI, coronary death, Cancer), which I think is critical to point out. It may help those that are a bit squeamish about the content of this site. Also, they are from ‘high profile’ organizations.
American Diabetes Association
This is a tool to assess risk of Type-2 diabetes

35. Heart Attack Risk Calculator
American Heart Association
Full Name of Tool: Heart Attack-Coronary Heart Disease-Metabolic Syndrome Risk Assessment
Some of this repetition is to reinforce the notion that there are many tools out there and some of them address very serious health outcomes. This may enlighten some of the those concerned about the content of our site.

36. Colorectal Cancer Risk Assessment
National Cancer Institute
Yet another example….

37. HIV Risk http://www.thebody.com/surveys/sexsurvey.html
Risk of HIV transmission

38. VACS Index Calculator
Brief overview of the development of the prototype
Brief overview of the project.
What we developed
It is a portal through which people may get their VACS Index score
Built as a prototype
This allows for incremental building with feedback and revision
The main features
It is developed around functional requirements

39. Prototype Development
Goals:
Identify the basic requirements
Development of a user interface
Gather feedback from users
Revise and enhance the tool
Explain the development process for a prototype:
What the goals are and where we stand
You find out what the functional requirements are, then build a prototype. It may or may not be close to the final product, but you test it, get feedback, and enhance the next generation.
Sit in between 1 and 2

40. Functional Requirements: What it Should Do
Calculate the VACS Index
Provide unique patient-specific feedback based on an individual score
Provide a risk estimate
Be used for online research recruitment
The functional requirements define the function(s) of the site.
Specifically, what the tool or site must be able to do
This input is essential for the development of the tool

41. Workflow Patients/Providers access the site Information entered
Score calculated
Explanation of tests and score
Option to register for online research
Evaluate end-user experience through survey
This slide highlights the use or flow of the site.
Who can access it
How it will be used
Allows you to develop the navigational features, ie links, the various pages and how they should interact
Helps the developer maximize the user experience

42. This is an overview of the various pages and how they might interact.
For example:
From the calculator tool itself, you should be able to access the results and a description of the lab values associated with calculating the score.

43. Technical Specifications
Website will be ASP.NET pages
Database will be SQL Server relational database
Secure VA Intranet Environment
Behind the firewall
Must obtain informed consent, HIPAA, patient de-identification
Possibility of hosting outside of VA
This is technical information. It also briefly mentions the security issues.
According to Mike R., the site may be hosted behind the VA firewall, or an outside source. The latter is something we have to find out more about, as there is a group in Boston that has a patient-accessible home care portal hosted on the outside that communicates with VistA.

44. The Calculator
This is a screen shot of the calculator. Users can enter information and calculate their risk index score.

45. Results
Your score is XX. Among 100 veterans in VA care with HIV infection with this score, we would expect that YY would be alive at five years and ZZ would have died. The figures in grey represent those expected to live 5 years and the figures in black represent those expected to have died.
This is how results will be displayed. There will be an explanation as well as a 100 faces diagram, depicting the results

46. Issues to Address #1 Discrepancies in internet access
Concerns have been voiced. One of those being discrepancies in internet access. This is a table highlighting the data gathered on variation in Veteran’s access to the internet.
Variation in Veterans’ Access to Internet and . Kirsha S. Gordon, et al. 3/2010. (under review)
Discrepancies in internet access
Solution: Provide training and internet access

47. Issues to Address #2: Calibration
Tool is VERY accurate at ranking within a sample of individuals with HIV infection in every sample studied (discrimination)
Tool is VERY accurate at estimating mortality rates within VA (calibration)
But…

48. Calibration (continued)
Observed vs. predicted mortality for a given score depends upon
Overall mortality within the sample (may be artifact due to incomplete death ascertainment in Non North American cohorts
Interval over which the mortality is predicted (short term is more accurate than long term)
Solution: Test index in SMART, NA-ACCORD, and ACTG (groups with good mortality ascertainment)

49. Research Recruitment We are planning a link for online recruitment
Idea is to create a “virtual laboratory” of VA and non-VA patients willing to help us develop the tool
This slide is incomplete. We were also discussing dissemination….[I wasn’t sure what else to put here]

50. Groups Who Might Disseminate Tool
Gay Men’s Health Crisis
ACRIA (NYC)
VA Public Health Strategic Health Care Group?
NIAAA?
NHLBI?
NA-ACCORD
ART-CC

51. Future Work Quality of decision support for Research screening
Patient education
Doctor/Patient communication
Research screening
As a template for other risk assessment tools
The possibilities are endless…
As the prototype evolves, data will be collected
Usability of the site
Research recruitment

52. Organ Systems Not Included (Candidates)
Cardiovascular (HDL, LDL)
Respiratory (FEV1)
Cognitive (MMS)
Neuromuscular (6 minute Walk Test)
Digestive (BMI)
Bone/Endocrine (BMD, Testosterone, Vitamin D)
Genitourinary/reproductive (Sexual function)
Rationale: not routinely ordered and/or not measured in a consistent manner

53. Behaviors Not Included, But of Interest
Smoking
Alcohol
Prescription Drugs
Exercise
Adherence

54. Diagnoses That May Have Impact
Metastatic Solid Tumor and Liquid Cancers
Myocardial Infarction, Congestive Heart Failure
Cirrhosis
Stroke
Peripheral neuropathy
Fragility fracture (especially hip fracture)

55. Future Plans Test responsiveness to behavior change and treatment
Alcohol and smoking cessation
HCV treatment
Conduct randomized trial using Index
To motivate behavior change (decrease alcohol use)
As a secondary outcome
Implementation
Collaborate with others who want to use the Index
Post calculator and interpretation on website
Encourage clinical laboratories to report Index

56. National VACS Project Team 2010

57. Veterans Aging Cohort Study
PI and Co-PI: AC Justice, DA Fiellin
Scientific Officer (NIAAA): K Bryant
Participating VA Medical Centers: Atlanta (D. Rimland), Baltimore (KA Oursler, R Titanji), Bronx (S Brown, S Garrison), 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, E Hoffman), and Washington DC (C Gibert, R Peck)
Core Faculty: K Akgun, S Braithwaite, C Brandt, K Bryant, R Cook, K Crothers, J Chang, S Crystal, N Day, R Dubrow, M Duggal, J Erdos, M Freiberg, M Gaziano, M Gerschenson, A Gordon, J Goulet, N Kim, M Kozal, K Kraemer, V LoRe, S Maisto, K Mattocks, P Miller, P O’Connor, C Parikh, C Rinaldo, J Samet
Staff: H Bathulapalli, T Bohan, D Cohen, A Consorte, P Cunningham, A Dinh, C Frank, K Gordon, J Huston, F Kidwai, F Levin, K McGinnis, L Park, C Rogina, J Rogers, L Sacchetti, M Skanderson, J Tate, E Williams
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
Major Funding by: National Institutes of Health: NIAAA (U10-AA13566), NIA (R01-AG029154), NHLBI (R01-HL095136; R01-HL090342; RCI-HL100347) , NIAID (U01-A ), NIMH (P30-MH062294), and the Veterans Health Administration Office of Research and Development (VA REA ) and Office of Academic Affiliations (Medical Informatics Fellowship).