Interrupted Time Series Analysis
Cross-source consensus on Interrupted Time Series Analysis from 1 sources and 6 claims.
1 sources · 6 claims
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Highlighted claims
- The study used a retrospective interrupted time series design to compare ED outcomes before and after MNCVC started. — Evaluating the impact of an Australian Virtual Care service on low-acuity presentations to district emergency departments: an interrupted time series analysis
- The main outcome was the monthly proportion of total ED presentations that were category 4 and 5 low-acuity presentations. — Evaluating the impact of an Australian Virtual Care service on low-acuity presentations to district emergency departments: an interrupted time series analysis
- ARIMA was chosen because it could account for seasonality and autocorrelation that segmented regression did not adequately address. — Evaluating the impact of an Australian Virtual Care service on low-acuity presentations to district emergency departments: an interrupted time series analysis
- The study reported no missing data in the aggregate monthly dataset. — Evaluating the impact of an Australian Virtual Care service on low-acuity presentations to district emergency departments: an interrupted time series analysis
- The model estimated both an immediate level change and an ongoing monthly trend change after July 2022. — Evaluating the impact of an Australian Virtual Care service on low-acuity presentations to district emergency departments: an interrupted time series analysis
- Researchers used a proportional outcome because population growth and rising ED activity made it more robust for assessing case-mix change. — Evaluating the impact of an Australian Virtual Care service on low-acuity presentations to district emergency departments: an interrupted time series analysis