Secondary analyses are based on the use of pre-existing data sets and usually the researcher conducting the statistical analysis has not had any contact with the participants whose data are being examined. A systematic review is, on the other hand, the thorough compilation and summary of all publications relevant to a particular research topic.

1. PHC215
By Dr. Khaled Ouanes Ph.D.
E-mail: k.ouanes@seu.edu.sa
Twitter: @khaled_ouanes
INTRODUCTION TO
HEALTHCARE RESEARCH
METHODS

2. Secondary Studies:
Existing Data Sets

3. Overview
Secondary analysis: the researcher
conducting the statistical analysis has not had
(and does not have) any contact with the
individuals whose data are being examined.
Sources:
 publicly available individual-level or population-level data
 privately held survey data
 clinical records

4. Publicly Available Data
Sharing data is a cost-efficient way to
extract as much information as possible out
of data sets.
For example, the U.S. Centers for Disease
Control and Prevention (CDC) provides, on
its website, data from several nationwide
cross-sectional studies:
 National Health and Nutrition Examination Survey (NHANES)
 National Health Interview Survey (NHIS)
 Behavioral Risk Factor Surveillance System (BRFSS)

5. Advantages
 Researchers may be able to download an entire
cleaned data set (and supporting documentation)
immediately and at no cost directly from the
website of the sponsoring organization.
 Secondary analysis is an excellent option for
researchers with strong statistical skills but limited
time and/or data collection resources.

6. Limitations
 The analyst is limited to exploring only the topics
included in the original survey.
 The analyst has to trust that the data were collected
using valid and standardized methods.
 It may be difficult to find someone who can answer
questions about the data collection process.
 There is a risk of duplicating the analysis that
someone else has done or is doing.

7. Private Data
 Individual researchers and research teams, such as
those at universities or university hospitals, may have
data available that have not yet been analyzed.
 The original researcher – the one who collected the
data – may be open to a new researcher taking the
lead on analyzing that portion of the data set and
writing up the results for possible publication.
 Limitation: Patient records are often incomplete.

8. Clinical Records
 Clinical records are a common source of data for
case series.
 Individuals working in clinical settings commonly
have access to patient records for research
purposes, provided that the research project
receives all required approvals and will not violate
any law (such as HIPAA) or policy.

9. Ethics Committee Review
 Additional approval by an ethics committee at
the institution where the secondary analysis will be
conducted is usually not required for anonymized
publicly available data.
 Secondary analysis of private data or hospital
records almost always requires review by a
research ethics committee.

10. Tertiary Studies:
Systematic Reviews &
Meta-Analyses

11. Overview
 A systematic review is the careful compilation and
summary of all publications relevant to a particular
research topic.
 A meta-analysis creates a summary statistic (a pooled
statistic) for the results of systematically identified
articles.

12. Systematic Review Process

13. Search Strategy
 After identifying a well-defined study question, the
next critical step in a systematic review or meta-
analysis is to select appropriate databases, search
terms, and search limiters.
 Once a system for identifying eligible articles is in
place, abstract databases are systematically
searched for articles that meet all the inclusion
criteria.

14. Systematic Search
Strategy & Counts
to Report

15. Data Extraction
Once all eligible articles are identified, the content of
these articles is extracted into data extraction tables
that list descriptive characteristics like:
 The study location and study years
 The study design
 The study population and sample size
 The key findings of interest
 The strengths and limitations of the study

16. Data Extraction
 A data extraction table allows for easy compilation
and comparison of observations relevant to the
study question.
 Studies that find no statistically significant results for
an item of interest are just as valuable as those that
find a significant association.
 Publication bias occurs when articles with
statistically significant results are more likely to be
published that those with null results.

17. Meta-Analysis
 A meta-analysis pools the results of several studies
identified during a systematic review to create one
summary statistic.
 Only similar statistics from similar studies can be
pooled.
 Before pooling the data, the researcher must show
that the results of the studies are comparable.

18.  A specialized computer software program can be
used to estimate the value of the pooled statistic and
its confidence interval.
 The contribution of each study to the pooled estimate
is usually weighted based on the sample size of the
included studies.
 The contributing studies and the summary measure are
often displayed using a forest plot.
Meta-Analysis

19. Example of a Forest Plot graphical
display

20. Threats to the validity of a meta-analysis:
 Poor quality of included studies: The selection criteria
used during the systematic review process can
eliminate any studies of questionable validity.
 Publication bias: The possibility of publication bias can
be examined using a funnel plot.
Meta-Analysis

21. Example of a Funnel Plot graphical
display

22. PHC215
By Dr. Khaled Ouanes Ph.D.
E-mail: k.ouanes@seu.edu.sa
Twitter: @khaled_ouanes
HEALTHCARE RESEARCH METHODS
Based on the textbook of introduction to health research methods – K.H. Jacobsen