1. Measurement Wu Gong, MS, MD Wu.gong@Vanderbilt.edu
Department of Biostatistics
Vanderbilt University Medical Center

2. Summary Considerations in selecting outcome measurements
Type of outcome measurements

3. Why Measurement? Measurement supplies numbers used in analysis.
Outcome variable, response variable, dependent variable
Experimental variable, predictor, descriptor variable, independent variable
Adjustment variable, confounder

4. Conceptual Models of Health Outcomes
Health outcomes: medical conditions, impact on health-related or general quality of life, and resource utilization
People of interest: patients, health care providers, and other decision- makers.
Wilson and Cleary Conceptual Model: biomedical patient outcomes and measures of health-related quality of life.
Economic, Clinical, Humanistic Outcomes Model: incorporating costs and economic outcomes.

5. Wilson and Cleary Conceptual Models
Level
Health Concepts
Biological and physiological factors
Genetic and molecular factors
Symptoms
Physical, psychosocial, emotional, and psychological symptoms
Functional Status
Physical, social, role, psychological, etc.
General health perceptions
Subjective rating of general health
Overall quality of life
Summary measure of quality of life

6. Economic, Clinical, Humanistic Outcomes Model

7. Properties of Outcome Measurement
Reliability: the measure remains unchanged upon test and retest or across different interviewers or assessors
Validity: the degree to which a measure assesses what it is intended to measure.
Variability: the distribution of values associated with an outcome measure in the population of interest, with a broader distribution or range of values meaning more variability.
Responsiveness: the ability of a measure to detect change in an individual over time.

8. Clinical Outcomes Prevent the occurrence of undesirable outcomes
Delay disease progression
Accelerate recovery or improve survival from disease
Reduce the burden of chronic diseases

9. Temporal Aspects of Clinical Outcomes
Incident: a first or new diagnosis of the condition of interest
Prevalent: existing disease
Recurrent: new occurrence of disease in a patient who has a previous diagnosis.

10. Subjective Versus Objective Assessment
Laboratory tests: are not subject to individual interpretation, and are likely to be reliable measured across patients by different health care providers and over time.
All-cause mortality: not subject to interpretation by individual health care providers.
Depression: subject to interpretation.
Type of Clinical Outcome Assessments: Patient-reported outcome assessment, observer-reported outcome assessment, and clinician-reported outcome assessment.

11. Humanistic Outcomes
Health-related quality of life measures the impact of disease and treatment on the lives of patients and is defined as the capacity to perform the usual daily activities for a person’s age and major social life.
It commonly includes physical functioning, psychological wellbeing, and social role functioning.
Patient-reported outcomes are measurements based on reports that come directly from the patient about the status of the patient’s health condition without amendment or interpretation of the patient’s response by a clinician or anyone else.

12. Economic and Utilization Outcomes
It measures health recourse utilization and represents the payer and societal perspective.
Monetary Costs: direct cost of the medical treatment, and indirect cost caused by disability.
Health resource utilization: number of inpatient or outpatient visits, total days of hospitalization, number of days treated with IV antibiotics, etc.

13. Measurement Scales
How well the variable is designed to measure the phenomena of intereste?
The goal is to minimize the measurement error
Precise: free of random error
Accurate: free of systematic error

14. Type of Measurement Numerical variables Categorical Vairables
Continuous
Discrete
Categorical Vairables
Dichotomous
Nominal
Ordinal

15. Continuous Variable
It quantifies how much on an infinite scale. It has an unit and can take on any value on a range of same values.
The precision in measuring the continuous variable is often limited by the instrument.
Body weight in pound
Height in inches
Number of days to recover
CD+ cell count
Descriptive statistics: mean, standard deviation.

16. Discrete Variable
It quantifies how many on a scale with fixed units, usually integers. It takes on a countable number of values.
How many times a woman has been pregnant?
Number of children
Number of asthma attacks per week
Number of antiretroviral therapy medicine pickups per year
Number of outpatient visits per year

17. Dichotomous Variable
It is also called binary variable and has only two possible values.
It is often coded as zero and one.
Dead or alive
Improved or not improved
Completed or failed
Descriptive statistics: count, proportion.

18. Ordinal Variable
The ordinal variable has an order such as severe, moderate, and mild pain.
It does not specify a numerical difference between one category and the next, and has less information than that of discrete or continuous numeric variable.
The quantitative differences between the categories are uneven.
Likert Scale: Like, Like Somewhat, Neutral, Dislike Somewhat, Dislike
Educational Level: None, Elementary, High School, College, etc.

19. Nominal Variable There is no natural ordering among the categories.
There is no distance measure between two values.
Gender: male and female
Marital status: single, married, divorced, widowed
Blood Type: A, B, O, AB

20. Repeated Measure Single time point
Two time points for each patient before and after treatment
Measured repeatedly at regular or varying time points

21. References
Hulley, Stephen B., et al. Designing Clinical Research pdf
Velentgas, Priscilla, et al. Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide