“…An interrupted time-series analysis for multiple groups was employed to compare healthcare resource utilization trends before and after coinsurance rate reduction at 70 years. …”
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“…Data on web-based searches on common cold were retrieved from Google Trends (GT) using the pseudo-influenza syndrome topic and local language search terms for common cold for the same countries and periods. We applied time series analysis methods to estimate the correlation between GT and hospitalization data. …”
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“…Quantitative data were analysed using an interrupted time series analysis (using March 2020 as the intervention period). …”
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“…The average treatment effect in the treated for MAb therapy was estimated using inverse probability of treatment weighting and the impact of MAb implementation using propensity-weighted interrupted time series analysis. RESULTS: Pre-implementation (July–November 2020), 7404 qualifying patients were identified. …”
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“…The seasonality was checked using time series analysis. RESULTS: Six of the consumer goods (dairy, ready-made meals, salty snacks, meats, beer, and cigarettes) were most commonly purchased in summer months, four (processed fish, food fats, wine, and alcohol 30%+) in December, and two (bread and sweets) in October. …”
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“…DESIGN: Population-based time series analysis. SETTING AND PARTICIPANTS: Community-dwelling adults with dementia in Ontario, Canada, from January 2019 to September 2020. …”
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“…PATIENTS AND METHODS: An interrupted time-series analysis of RV surveillance data in Alberta, Canada, from May 2017 to July 2020 was conducted. …”
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“…BACKGROUND: We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014–2018. …”
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“…This facilitates gathering of time-synchronized location and physiological vitals data, which allows artificial intelligence and machine learning (AI/ML)-based time series analysis. The study gives a brief overview of wearable sensor technology, RTLS, and provides use cases of AI/ML algorithms in the field of sensor fusion. …”
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“…An interrupted time series analysis was performed for both AZ and CA. After correcting for pre-intervention trends, AZ days of therapy (DOT) decreased by 6.2 DOT per 1000 patient days within 1 month post intervention (23%, p< 0.0001); the model predicted a further drop of 0.6 DOT per 1000 patient days per month over the 6 months post intervention. …”
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“…MAIN OUTCOMES AND MEASURES: Interrupted time series analysis measured changes in health care utilization over time, stratified by residential flood exposure, race, and income. …”
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“…METHOD: We performed an interrupted time series analysis using negative binomial regression to estimate the change in the monthly admissions for paediatric cancer patients (Age 0-17) associated with the COVID-19 pandemic and subsequent lockdown policies. …”
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“…LEVEL OF EVIDENCE: Level IV: Evidence obtained from multiple time series analysis such as case studies. (NB: Dramatic results in uncontrolled trials might also be regarded as this type of evidence). …”
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“…Descriptive statistics, multivariate regression, interrupted time series analysis were used as indicated. MAIN OUTCOME MEASURES: Impact of ERAS process measure adherence on length of stay. …”
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“…An interrupted time-series analysis was employed to compare changes and trends in hospital admissions and disease spectra before and after the period of nonpharmaceutical interventions (NPIs). …”
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“…METHOD: A summer-specific (June–September), time-series analysis was performed, using daily HSAD and meteorological data from 47 Japanese prefectures from 2017 to 2020. …”
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“…METHODS: We conducted a time-series analysis with a nationally representative Disease Surveillance Points System database during the cool seasons spanning from 2013 to 2015 in 272 Chinese cities. …”
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“…We use a multimethod design combining qualitative and quantitative approaches, involving: (1) in-depth interviews with health workers and decision-makers to explore experiences of delivering PIC4C; (2) a cross-sectional survey of patients with diabetes or hypertension and in-depth interviews to understand how well PIC4C meets patients’ needs; (3) a cohort study with an interrupted time series analysis to evaluate the degree to which PIC4C leads to health benefits such as improved management of hypertension or diabetes; and (4) a cohort study of households to examine the extent to which the national hospital insurance chronic care package provides financial risk protection to people with hypertension or diabetes within PIC4C. …”
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“…Next, we used time series analysis methods to investigate how voluntary and policy-induced social distancing behaviors shifted over time across demographic groups. …”
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“…To explore the molecular mechanism of soybean responses to salt stress, we performed a comparative transcriptome time-series analysis of root samples collected from two soybean cultivars with contrasting salt sensitivity. …”
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