Introduction on Quasi experimental design which was presented at the PharmCare Symposium by the USM PCRG Group.

1. Understanding Research Design
in Hospital Pharmacy
Intervention Research
Balamurugan Tangiisuran, PhD
School of Pharmaceutical Sciences
Universiti Sains Malaysia
bala@usm.my

2. ◎Observational Studies
 Descriptive studies
 Cross-sectional
 Case-Control
 Cohort
◎Experimental / Interventional Studies
 As per control: RCT / NRCT
 As per Blinding: Single/Double Blind
 As per Design: Simple/Cross-over
STUDY DESIGN

3.  Aquasi-experiment is simply defined
as not a true experiment
 Since the main component of a true
experiment is randomly assigned
groups, this means a quasi-experiment
does not have randomly assigned
groups.
DEFINITION
Shadish, William R., et al., Experimental and Quasi-Experimental Designs for
Generalized Causal Inference, Houghton Mifflin Company, Boston, 2002, p. 14.

4.  Quasi-experimental research designs,
like experimental designs, test causal
hypotheses
DEFINITION
Shadish, William R., et al., Experimental and Quasi-Experimental Designs for
Generalized Causal Inference, Houghton Mifflin Company, Boston, 2002, p. 14.

5. Categories of Quasi
Experimental Design
Quasi-
experimental
design without
control groups
Quasi-
experimental
design that use
control groups
with no pre-test
Quasi-experimental
design that use
control groups and
pre-tests
Interrupted
time series
Stepped
wedge
designs
Ines Krass. Quasi experimental designs in pharmacists
intervention research. Int J Clin Pharm (2016) 38:647-654

6. (a) Design with no control group and post-
test only (X01)
Example:
- Pharmaceutical care intervention(X) to
diabetes patients in clinic settingand
measure of their HbA1C (O1)at the end
of the study
1. Quasi experimental without
control group

7. (a) X01
- Weakest design
- Without any pre-test value for HbA1c
there are many threats to internal
validity
- Difficult to conclude that the PC was
responsible to any observed changes in
glycaemic control
1. Quasi experimental without
control group
Ines Krass. Quasi experimental designs in pharmacists
intervention research. Int J Clin Pharm (2016) 38:647-654

8. (a) Design with no control group and post-
test only (X01)
Example:
- Impact of medication reconciliation post
hospital discharge on readmission rates
and patient satisfaction
1. Quasi experimental without
control group
Luder HR et al. J Am Pharm Assoc. 2003:2015(55):246-254

9. (b) One group pre-post-test design (01 X02)
Example:
• HbA1c (O1) is obtained before the intervention (X)
is commenced and the post-test measurement of
HbA1c (O2) obtained after the PC intervention was
completed
• Does not control other potential influences that
may contribute to any observed improvement
1. Quasi experimental without
control group

10. (b) The one group pre-post-test design
(01 X02)
Example:
• Impact of pharmacist interventions in
smokingcessation therapy
1. Quasi experimental without
control group
Marin Armero et al., Pharmaceutical care in Smoking Cessation.
Patient Prefer Adherence. 2015; 9: 209-215.

11. (c) The one group pre-post-test design usinga
double pre- test (01 02 X03)
Example:
• Involve obtaining two previous measures of HbA1c
(i.e. 3 and 6 month prior to the intervention)
• If they were both high this would suggest that a
lower HbA1c post intervention is not due to
confounding
1. Quasi experimental without
control group

12. (d) The removed treatment design
(01 X02 03 remove X04)
• Athird post-test measurement (O3) is added to the
single group pre-post-test design and then the
intervention is removed and a fourth measurement
(O4) is taken
1. Quasi experimental without
control group

13. (d) The removed treatment design
(01 X02 03 remove X04)
• Allow for an assessment of what happens
once the intervention is withdrawn
• Answer questions around sustainability
1. Quasi experimental without
control group

14. (d) The removed treatment design
(01 X02 03 remove X04)
• Example
• At the end of a period after the intervention had
ceased another HbA1c measurement would be
obtained
1. Quasi experimental without
control group
Ines Krass. Quasi experimental designs in pharmacists
intervention research. Int J Clin Pharm (2016) 38:647-654

15. (d) The removed treatment design
(01 X02 03 remove X04)
• Example
• Maintenance of the threefold improvement in
the ratio of preventer to reliever medication 12
months after the original intervention
1. Quasi experimental without
control group
Bereznicki B. The sustainability of a community pharmacy
intervention to improve the quality use of asthma medication. J
Clin Pharm Ther. 2011; 36:144-151.

16. ◎ Involve obtaining a measurement of HbA1c (O1)
after the intervention (X) and comparing it to
HbA1c (O2) in a group of patients who did not
receive the intervention
◎ Control group allows for statistical adjustment of
potentially confounding variables that could
contribute to causality but…
2. Quasi experimental design that use
a control group but no pre-test
Ines Krass. Quasi experimental designs in pharmacists
intervention research. Int J Clin Pharm (2016) 38:647-654

17. (a) Untreated control group with dependent pre-tests
and post-tests
(b) Untreated control group design with dependent
pre-test and post-test samples using a double pre-
test
(c) Untreated control group design with dependent
pre-test and post-test samples with switching
replications
2. Quasi experimental design that use
a control group but no pre-test

18. ◎Aseriesof consecutiveobservationsis
interrupted by the delivery of a treatment or
intervention
◎Represents stronger category of quasi
experimental design
3. Interrupted time series designs
Ines Krass. Quasi experimental designs in pharmacists
intervention research. Int J Clin Pharm (2016) 38:647-654

19. Example
• collecting several previous measurements of
HbA1c prior to implementation of the PC
intervention
Advantages
• Multiple measurements of both pre and post
intervention makes it easier to control for
confounding
• Enables more robust statistical analysis
3. Interrupted time series designs

20. ◎ Examplein Pharmacy literature
• Studies examiningthe impact of intervention
or policies on medication use over time
3. Interrupted time series designs
Roughead EE et al. Bridging evidence-practice gaps: Improving
use of medicines in elderly Australian veterans. BMC Health Serv
Res. 2013; 13:514.

21. • Cluster based design suited to interventionsin
health settingswherenot ethically justified to
withhold theintervention
• Enablesall sitesto receivetheintervention in a
staggered order
• Avoidssomeof themethodological pit-falls
associated with beforeand after designs
4. Stepped wedge design
Bereznicki B. The sustainability of a community pharmacy
intervention to improve the quality use of asthma medication. J
Clin Pharm Ther. 2011; 36:144-151.

22. 4. Stepped wedge design

23. Threats in Quasi Experimental design
Maturation
Lack of blinding
Instrumentation
Selection bias
Drop out

24. THANK YOU!