Lecture: Use of IT in Comparative Effectiveness

 

Assigned Reading

  1. How to conduct a matched case control comparative effectiveness study  Read► Excel► Jason's Tutorial►
  2. Causal analysis
  3. Measurement of severity of illness from claims data  Read► Slides 2007►  Slides 2003► Video► SWF► Lewis►
  4. Benchmarking clinicians Read►  You Tube►

Narrated slides and videos require Flash.  Download►

What do you know?

Advanced learners like you, often need different ways of understanding a topic. Reading is just one way of understanding. Another way is through writing about what you have read.  The following questions get you to think more about the concepts taught in this session.

  1. Discuss how the paper on impact of Vioxx established the causal link between the medication and mortality.  In particular, what steps did the paper take to check for the counterfactual argument that patients who had died would not have died if they had not taken Vioxx.
  2. Did moderate use of Vioxx lead to higher cardiac events than other pain medications?  Was there a difference in type of patients that received high-dose Vioxx and other medications?  Could these differences explain the association between Vioxx and cardiac events?
  3. Discuss how the paper on impact of Vioxx established risk score for various cardiac risk factors.  Did they adequately account for interaction among the risk factors?  What evidence is there that the adjustment for severity was adequate?
  4. Besides association between two events, what else needs to be verified before it can be inferred that one of the variables is causing the occurrence of the other?
  5. Describe the HCUP data? 
  6. Describe the limitations of Quality Indicators developed by the Agency for Health Care Quality and Research.
  7. What is meant by counterfactual?  In testing if a medication has led to excess mortality, how would the measurement of severity of illness help establish counterfactual claim that patients would have lived if it were not for the medication.
  8. What is APR-DRG?  Describe the data used for creating the APR-DRG. 

  9. Construct a simple Multi-Morbidity Index using the data in the Table below.

    •  Assess the average severity of CHF, MI, Diabetes, Hypertension, Alcohol Use, and ACL surgery (assume that sicker patients have longer stays). 
    •  Assess the overall severity of the 9 cases in the Table as the sum of the severity of each of their diagnoses
    • Plot the patient's length of stay against the patient's severity of illness. 
    •  A new patient with MI, AA, and CHF is discharged in 3 days.  Is this length of stay more, or less, than what would we expect for these types of patients?  
    • Can this procedure be repeated in an electronic health record, where there are thousands of diagnoses and millions of cases?
Case
Type 		 1st Diagnosis 2nd Diagnosis 3rd Diagnosis 4th Diagnosis Length of stay Number of Patients
1 MI CHF DM 5.56 10
2 MI AA 4.10 10
3 CHF DM AA 5.54 10
4 CHF DM 3.56 20
5 MI CHF AA 7.03 30
6 MI CHF 5.02 30
7 CHF AA 5.04 30
8 MI CHF DM AA 7.62 40
9 MI 2.03 40
10 CHF 3.03 40
11 MI DM 2.60 50
12 DM AA 2.57 50
13 DM 0.61 60
14 AA 2.12 70
15 0.01 80
16 MI DM AA 4.57 120
MI = Myocardial Infarction; CHF = Congestive Heart Failure; DM=Diabetes Mellitus; AA=Alcohol abuse

 

Do One Assignment: Complete a Mini-Comparative Effectiveness Study 

  1. Identify which 2 patients in the following table could serve as matched controls for the cases. Cases received the intervention and controls did not.  Blanks indicate patients who did not fall in the time period.  Match on age.  Select the possible controls randomly, using the lowest random number provided.   For the follow-up period in above problem, show a Kaplan Meier survival plot of patients with no falls. Hafsa A► Gabriella C►

    Patient ID

    Received Intervention

    Age

    Months to Fall

    Random Number

    Observation Period

    Follow-up Period

    1

    Yes

    65

     

    3

    0.24

    2

    No

    60

     

    2

    0.85

    3

    Yes

    84

    2

     

    0.64

    4

    No

    82

    4

     

    0.7

    5

    No

    78

     

    0.87

    6

    No

    80

    3

     

    0.72

    7

    No

    79

     

     

    0.86

    8

    No

    64

     

     

    0.16

    9

    No

    70

     

    2

    0.17


  2. In the following questions assume that we have followed two clinicians, Smith and Jones, and constructed the decision trees in Figure 6. Mariam A►Solution►


Figure 6:  Dr. Jone's and Smith's Practice Pattern

  • What is the expected length of stay for each of the clinicians?
  • What is the expected length of stay for Dr. Smith if he were to take care of patients of Dr. Jones?
  • What is the expected length of stay for Dr. Jones if he were to take care of patients of Dr. Smith? 

More

For additional information (not part of the required reading), please see the following links:

  1. Additional reading on how to analyze decision trees and event trees Read►
  2. Steve Short, Tampa General Hospital's Sr. Vice President & Chief Financial Officer, talk on state of industry  Bio► Slides►
  3. Tutorial on structural modeling Read►
  4. Agency for Healthcare Research and Quality's reference guide for effectiveness and comparative effectiveness reviews Read► Tutorial►
  5. AHRQ quality indicators for electronic health record data Slides►

This page is part of the course on Information Systems.   This page was edited 05/16/2013 by Farrokh Alemi, Ph.D.  ©Copyright protected.