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Introduction to Interrupted Time Series Analysis

Interrupted Time Series Analysis for Single Series and Comparative Designs:Using Administrative Data for Healthcare Impact AssessmentJoseph M. Caswell, AnalystInstitute for Clinical Evaluative Sciences (ICES) North and Epidemiology, Outcomes & Evaluation ResearchHealth Sciences North Research Institute (HSNRI)Northeast Cancer CentrePresentation Overview quasi - experimental research Interrupted time Series (ITS) ITS single Series with example ITS comparative with example Autocorrelation Adjusting standard errors (SE) in SAS Guide and macroQuasi- experimental Research experimental research: Gold-standard is randomized controlled trial (RCT) , drug trials (random assignment to treatment and placebo groups) Treatment and control groups balanced on baseline measures Can be time-consuming, expensive, and even unethical ( , withholding care) quasi - experimental research: Alternative(s) available when RCT is not an option Quickly implemented, cost-efficient Often times, observational data are already available Various statistical methodologies for observational studies ( , propensity scores, ITS, instrumental variables, etc)Observational Studies Administrative data: Routinely collected by hospitals and other healthcare facilities Great source for conducting observational health studies ICES data holdings: Examples: Ontario Cancer Registry (OCR) Registered Persons Database (RPDB) Discharge Abstract Database (DAD) Ontario Health Insurance Plan (OHIP) Many, many more We can use admi

Quasi-Experimental Research •Experimental research: – ^Gold-standard is randomized controlled trial R T –i.e., drug trials (random assignment to treatment and placebo groups) –Treatment and control groups balanced on baseline measures –Can be time-consuming, expensive, and even unethical (i.e., withholding care) • Quasi-experimental ...

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