USC Week 9 Outcomes Measurement and Pharmacoepidemiologic Methods Lecture Summary write a summary about the lecture attached. one page double space. no ref

USC Week 9 Outcomes Measurement and Pharmacoepidemiologic Methods Lecture Summary write a summary about the lecture attached. one page double space. no references Outcomes Measurement and
Pharmacoepidemiologic Methods

The economic, clinical, and humanistic outcomes
(ECHO) model
Characteristic differences between randomized
control trials and observational studies
Rascati (Chapter 11)
Learning objectives
1. Outline the differences/similarities between outcomes research and PE
2. Describe the components of clinical decision making using the
economic, clinical, and humanistic outcomes (ECHO) model
3. Describe how economic, clinical, and humanistic outcomes are
4. Compare and contrast randomized controlled trials (RCTs) and
observational studies
Outcomes Measurement
Differences between PE and Outcomes Research
•Pharmacoeconomics is the identification, measurement,
and comparison of the costs and outcomes of pharmacy
products (e.g., drugs) or services
―Bootman, 2005
• PE is a type of “outcomes research”
―However, not all outcomes research are PE research
What is outcomes research?
• Outcomes research seeks to understand the end results of health
care practices and interventions
• Outcomes research is more broadly defined as “studies that
attempt to identify, measure, and evaluate the end results of
health care services” (Bungay, 2013)
―End results = Outcomes
―Not only clinical outcomes are measured, but also economic and
humanistic outcomes
• End results include effects that people experience and care about
such as improved ability to function (e.g., activities of daily living)
or an increased quality of life
Source: Agency for Healthcare Research and Quality (AHRQ)
Examples of health outcomes
• Health outcomes include
―Physiologic measure (e.g., blood pressure, A1C)
―Clinical events (e.g., stroke, myocardial infarction)
―Mortality (e.g., infant mortality rate)
―Symptoms (e.g., difficulty breathing)
―Quality of life (using health surveys such as SF-36)
―Patient’s experiences with care (evaluated using a health survey such
as Consumer Assessment of Health Plans)
The ECHO Model
The ECHO model
• It has been proposed that the evaluation of drug therapy and
related services should include an assessment of the economic,
clinical, and humanistic outcomes (ECHO) (Kozma, 1993)
―For example, cost-utility analysis encompasses a measurement of the
economic (costs), clinical (e.g., effectiveness, side-effects,
complications), and humanistic (quality of life, QALY) outcomes
Components of clinical decision making
-The ECHO model
Source: Bungay, 2013
The ECHO model
Humanistic Intermediaries
Effects of disease and treatment on
humanistic outcomes (e.g., side effects,
satisfaction with therapy)
Medical events that occur as a
result of disease or treatment (e.g.,
asthma attacks, ER visits, hospitalization
Treatment Modifiers
Factors that alter outcomes
associated with treatment alternatives (e.g.,
compliance with therapy, dosage forms)
Direct medical, direct non-medical,
indirect, and intangible costs
External Controls
Source: Kozma, 1993
Non-clinical factors that affect
availability or use of treatment
alternatives (e.g., formularies, prior
Functional status, QOL (e.g., physical
function, social function, pain, vitality)
Clinical Outcomes
Clinical Indicators
Measurements of a patient’s physical
and biological status used to infer
the severity or risk of disease (e.g.,
FEV, wheezing, breathlessness)
Humanistic Outcomes
Economic Outcomes
Alternatives (e.g., betaagonist vs. theophylline)
Total costs of medical care associated with
treatment alternatives balanced against
clinical or humanistic outcomes(e.g.,
cost/QALY, cost/successful treatment)
The ECHO model
Outcomes resulting from medical care can be classified along
three dimensions:
1. Economic outcomes
― Direct, indirect, and intangible costs resulting from clinical or
humanistic outcomes
2. Clinical outcomes
― Medical events that occur as a result of disease or treatment
3. Humanistic outcomes
― Consequences of disease or treatment on patients’ functional status
or quality of life
Measurement of economic
Measurement of economic outcomes
• Economic outcomes are usually of primary interest to the payer
• Cost component of economic outcomes include direct costs
(medical and non-medical), indirect costs, and intangible costs
• Economic outcomes also include measures of health resource
utilization such as
―number of inpatient or outpatient visits
―total days of hospitalization in a given year
―number of days a patients received a medication
Measurement of clinical
Measurement of clinical outcomes
• Clinical outcomes are usually of primary interest to the health
care professional
• Clinical outcomes include coronary events, osteoporosis, death,
rheumatoid arthritis, cancer, diabetes, psoriasis, Parkinson’s
disease, depression, surgery, etc.
Categories of clinical outcomes
• Four categories of clinical outcomes are identified:
1. Objective outcomes
2. Subjective outcomes
3. Composite endpoints/outcomes
4. Intermediate endpoints/outcomes
Source: Agency for Healthcare Research and Quality
Categories of clinical outcomes
Objective outcomes
• Objective outcomes are defined as measures that are not
subject to a large degree of individual interpretation, and are
likely to be reliably measured across patients in a study, by
different health care providers, and over time
― For example, blood and urine test results for glucose, blood test
results for cholesterol, blood pressure measurement, etc.
Source: Agency for Healthcare Research and Quality
Categories of clinical outcomes
Examples of objective clinical outcomes
Clinical outcome
Objective measure
1. Diabetes
2. Hypertension
Blood pressure (mmHg)
3. Myocardial infarction
↑Troponin levels, ST elevation/depression
4. Asthma
Spirometry – Forced Expiratory Volume 1
Source: Agency for Healthcare Research and Quality
Categories of clinical outcomes
Subjective outcomes
• These are outcome measures that are subject to interpretation
by individual health care providers and may not be reliably
measured across patients and by different health care providers
over time
―Examples include assessment of depression, pain, anxiety
• However, instruments have been developed to help standardize
the assessment of some conditions for which a subjective
clinical assessment might introduce unwanted variability
―This help produce a quantifiable measure that should be
reproducible across patients and raters
Source: Agency for Healthcare Research and Quality
Categories of clinical outcomes
Subjective outcomes
• For example, treatment of psoriasis
• Subjective outcome assessment of psoriasis:
―Has the patient’s condition improved a lot, a little, or not at all?
• Objective outcome assessment using a reliable and validated
―Instrument=Psoriasis Area Severity Index (PASI)
―Rating of the severity of target symptoms: erythema, infiltration, and
desquamation (0-4 scale; with 0=none and 4=very severe)
―Rating of the area of psoriatic involvement for each of four main body
areas – head, trunk, upper extremities, and lower extremities (0-6
scale; with 0=0% and 6=90-100%)
―The final calculated score ranges from 0 (no disease) to 72 (severe
Categories of clinical outcomes
Composite endpoints/outcomes
• These are series of individual clinical outcomes which are
grouped together into one outcome measure
―This makes the composite endpoint occur more frequently than any
of the individual components
• Composite endpoints are necessitated when the individual
events included in the score are rare, and/or when it makes
clinical sense to group them
Categories of clinical outcomes
Composite endpoints/outcomes
• For example, a composite endpoint called major adverse
cardiac events (MACE)
―MACE may be defined differently from study to study and hence
interpretation or meaning may not be consistent from study to study
―MACE as an outcome may be compared among patients receiving
different types of antiplatelet drugs (e.g., occurrence of MACE
between patients prescribed ticagrelor or prasugrel)
―A study may define MACE as occurrence of any of: (i) all-cause
mortality, (ii) myocardial infarction, and (iii) coronary revascularization
―Another study may define MACE as occurrence of any of: (i) cardiacrelated mortality, (ii) stent thrombosis, and (iii) coronary
Categories of clinical outcomes
Intermediate endpoints/outcomes
• Intermediate endpoints/outcomes are biological markers for the
condition of interest
• Their use is common in clinical trials
• They are also called surrogate markers (used in lieu of the main
• They may be used to reduce the follow-up period required to obtain
results from a study of treatment effectiveness in RCTs
―For example, RCT of statin efficacy
→Main clinical outcome of interest = reduction in coronary heart disease incidence;
reduction in cardiac mortality
• may take many years of data collection to manifest these outcomes
→Intermediate endpoint = serum lipids (LDL-cholesterol)
• A predetermined percentage reduction of LDL-C can serve as evidence of treatment
Measurement of humanistic
Measurement of humanistic outcomes
• Humanistic outcomes are of primary interest to the patients (
e.g., pain level, degree of functioning, etc.)
• Humanistic outcomes can be measured using patient-reported
outcomes (PRO) instruments
―PRO instrument may include the use of any health-related quality of
life (HRQoL) instruments measured from the patient’s perspective
→Generic HRQoL (e.g., SF-36, QWB scale, Dartmouth COOP)
→Disease-specific HRQoL (e.g., Arthritis Impact Measure Scale [AIMS]
→Preference-based measures (EQ-5D, SF-6D)
• The FDA defines a PRO as “a measurement based on a report
that comes directly from the patient (i.e., study subject) about
the status of a patient’s health condition without amendment
or interpretation of the patient’s response by a clinician or
anyone else”
• A PRO can be measured by self-report or by interview provided
that the interviewer records only the patient’s response
Source: Agency for Healthcare Research and Quality
Outcomes measured by PROs
PROs refer to patient ratings and reports about any of several
outcomes, including:
Health status
Health related quality of life (HRQoL)
Quality of life (QoL), defined more broadly
Satisfaction with care/treatment
Health behaviors, including adherence and health habits
Health care utilization and out-of-pocket costs
Summary-Outcomes Measurement
1. PE is a type of outcomes research; not all outcomes research are PE
2. Evaluation of drug therapy should include an assessment of the
economic, clinical, and humanistic outcomes (ECHO)
3. Economic outcomes include direct, indirect, and intangible costs resulting
from clinical and humanistic outcomes
4. Clinical outcomes refer to medical events that occur as a result of disease
or treatment
5. Humanistic outcomes refer to consequences of disease or treatment on
patients’ functional status or quality of life
6. Categories of clinical outcomes include objective outcomes, subjective
outcomes, composite endpoints/outcomes, and intermediate
Observational studies
Pharmacoepidemiologic methods
• The types of research methods that can help answer the question of
whether a drug ‘works’ include:
1. Meta-analyses of RCTs
― Synthesis of results from several RCTs
― Highest level of evidence
― Helps minimize uncertainty when results differ between two or more RCTs
2. Individual randomized controlled trials (RCTs)
― Answers efficacy question
3. Observational studies (cohort, case-control, surveys)
― Answers effectiveness question
4. Expert opinion
― lowest level of evidence
Randomized Control Trials
• RCTs are the gold standard for proving that a drug ‘works’
―they provide evidence of efficacy
• Proof of efficacy through RCTs are required by the US Food and
Drug Administration (FDA) before a drug can be approved for
use in the general population
• Randomized = Randomization
―Randomization is allocation (through random procedure) of subjects
into groups who will receive the treatment of interest (the treatment
or intervention group), or to another group who will not receive the
treatment of interest (the control group)
―Randomization is used to reduce selection bias (imbalance in
baseline characteristics between treatment and control groups)
―For example, in observational studies where randomization does not
occur, patients with more severe form of a disease may be ‘selected’
to receive the newer medication
→The researcher may not know this ‘selection’ has occurred in the data and
may draw incorrect conclusions about the new drug
• Patients taking the new drug may appear as though they have worse outcomes
• Controlled = controlled or ‘supervised’ environment, and/or use
of a ‘control’ group (standard treatment or placebo)
―subjects must meet study inclusion criteria and are monitored or
supervised over a period of time
• Trial = study or experiment
―RCTs can be used to infer causality whereas causality cannot be
inferred in observational studies
RCT – Process
Source: Schulz, 2010
Advantages of RCTs
1. The randomization process ensures that groups being
compared have similar baseline characteristics
―Thus, efficacy observed is valid and attributable to the drug effects
2. RCTs have good internal validity
―Minimization of known or unknown biases through randomization
―Causality can be inferred
3. RCTs are more scientifically rigorous and needed for FDA drug
Disadvantages of RCTs
1. Time frame for follow-up may be too short
― There is a limitation of extrapolating RCT findings for economic
evaluation of chronic diseases such as diabetes and cardiovascular
diseases (which occurs over the lifetime of the patient)
2. High cost of recruitment and follow-up
3. High adherence rates among patients which is unrealistic in
everyday practice
―Due to monitoring and ‘controlled’ or supervised environment
4. Small sample size compared to observational studies
― Reduced power may lead to non-significant results
Disadvantages of RCTs
5. Due to inclusion and exclusion criteria, RCT patients may not
be representative of the general population
―Subjects cannot have other diseases (comorbidities)
―Subjects cannot take other drugs except those under investigation
―Other exclusion criteria based on age, race, sex, education
―Higher medication adherence rates than obtained normally due to
higher monitoring
―Thus, RCTs have poor external validity but good internal validity
Observational Studies
Observational studies
• In contrast to RCTs, observational studies are not conducted in
controlled or supervised environments
―Subjects are ‘observed’ either directly (prospective methods) or
indirectly (retrospective methods)
―Subjects are already taking the treatment or intervention in the ‘real
world’ and are just being observed for outcomes
―Subjects are not under supervised or “controlled” conditions
―There is no randomization of subjects into groups
―The outcome of interest is effectiveness rather than efficacy
→Effectiveness evaluate if the drug ‘does work’ in the real-world environment
Types of observational studies
There are two main types of observational studies:
1. Prospective observational studies
― These record treatments and outcomes as they occur
― Exposed and unexposed groups are identified (exposure occurs before
outcome), then subject are followed up over time for manifestation of the
― For example, prospective cohort study
2. Retrospective observational studies
― These analyze treatments and outcomes that have already occurred in the past
― Treatment was given in the past, outcomes had occurred in the past, data and
results are then analyzed in the present
― For example, retrospective database analysis (retrospective cohort study,
retrospective case-control study)
Advantages of observational retrospective
database analysis
1. Less expensive to conduct than RCTs
2. Less time-consuming to conduct than RCTs
―No need to enroll patients into study
3. Many years’ worth of patient data can be examined in a short
period of time at low cost
― Larger sample size
4. Data from observational studies are more representative of
the ‘real’ clinical practice world (hence, they have good
external validity)
― More realistic adherence rates and treatment patterns
Advantages of observational retrospective
database analysis
5. Data is more inclusive and include patients from different
socio-demographic background
―Age, sex, race, ethnicity, religion, income level
6. Easier to recalculate with different criteria (sensitivity
―Age range, diagnoses, medication adherence rates can be changed to
determine if results are robust (i.e., insensitive) to initial study results
Disadvantages of observational retrospective
database analysis
1. Information may be incomplete
― Most retrospective databases are not primarily collected for
research purpose but for reimbursement (payments for services)
―Information may be incomplete if:
→Patient switches insurance company
→Patient pays out-of-pocket for some health expenses rather than through
→Patient have more than one insurance type (Medicare + Medicaid; insurance
from employer and another from spouse)
Disadvantages of observational retrospective
database analysis
2. Data may be inaccurate or incomplete
―ICD-9-CM diagnosis and procedure codes and cost of medication may
be entered wrongly into the electronic health record
―Data may not be measured, recorded, or available
→Smoking information
→Family history of disease
→Past rates of medication adherence
→Cholesterol information
Disadvantages of observational retrospective
database analysis
3. Selection bias
― This occurs when patients with certain characteristics are more
likely to receive one treatment compared to another treatment

Due to lack of randomization of patients to treatment groups
― For example, patients with a more severe form of a disease who
have been resistant to standard therapy may be receiving (or be
‘selected’ to receive) a newer, more effective medication
→ Thus, the risk of an undesirable outcome of interest may be higher among
patients receiving the newer medication because they are sicker from the
→ Hence, higher risk of the undesirable outcome may be wrongly attributed to
the newer medication
Disadvantages of observational retrospective
database analysis
• Example:
• Channeling bias (this is a type of selection bias)
―Channeling occurs when drug therapies with similar indications are
preferentially prescribed to groups of patients with varying baseline
→For example, Medications A and B are used for the treatment of diabetes
→However, Medication A is found to cause weight gain more often than
Medication B
→A doctor might prescribe more of Medication B for his/her overweight
→Therefore, comparing health outcomes among patients using Medications A
and B may be problematic due to this intrinsic channeling bias which may be
unknown to the researcher using the retrospective database
Methods to minimize biases in
observational retrospective
database analysis
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