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Interrupted time-series analysis yielded an effect estimate concordant with the cluster-randomized controlled trial
Atle Fretheim1, Stephen B Soumerai, Fang Zhang
1Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA. atle.fretheim@nokc.no
Journal of Clinical Epidemiology
|July 2, 2013
Summary
Interrupted time-series (ITS) analysis of antihypertensive medication prescribing showed results concordant with cluster-randomized controlled trials (C-RCTs). This suggests ITS is a viable method for evaluating quality improvement interventions in healthcare.
Area of Science:
- Health Services Research
- Clinical Trial Methodology
- Pharmacotherapy
Background:
- Quality improvement interventions aim to enhance healthcare delivery.
- Antihypertensive medication prescribing is a key area for quality improvement.
- Cluster-randomized controlled trials (C-RCTs) are a gold standard for evaluating interventions, but can be resource-intensive.
Purpose of the Study:
- To reanalyze data from a C-RCT evaluating a quality improvement intervention for antihypertensive prescribing.
- To estimate intervention effectiveness using both interrupted time-series (ITS) and C-RCT methods.
- To compare the findings from ITS and C-RCT analyses.
Main Methods:
- An interrupted time-series (ITS) analysis was performed on the intervention arm using segmented regression.
- The cluster-randomized controlled trial (C-RCT) data were analyzed using generalized estimating equations.
- A controlled ITS analysis compared slope and level changes between intervention and control groups.
Main Results:
- The ITS analysis estimated an absolute change of 11.5% (95% CI: 9.5, 13.5).
- The C-RCT analysis estimated an absolute change of 9.0% (95% CI: 4.9, 13.1).
- The controlled ITS analysis estimated an absolute change of 14.0% (95% CI: 8.6, 19.4).
Conclusions:
- Interrupted time-series (ITS) analysis can yield effect estimates consistent with cluster-randomized controlled trials (C-RCTs).
- ITS offers a potentially valuable alternative or complementary method for evaluating quality improvement interventions.
- Further research comparing ITS and C-RCTs across diverse settings is needed to confirm generalizability.
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