ArticleJournal of evaluation in clinical practice2020
Design, analysis, power, and sample size calculation for three-phase interrupted time series analysis in evaluation of health policy interventions.
Article in Journal of evaluation in clinical practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Optimizing drug inventory management with a web-based information system: The TBTC Study 31/ACTG A5349 experience.Contemporary clinical trials · 2021Trial
- Evaluating PEACHES: Pleasure-Inclusive Implementation Strategies to Enable Healthcare Workers to Address Anal Sex Stigma During HIV Service Encounters.Archives of sexual behavior · 2026Article
- Trends in migraine-specific medication consumption: a multinational analysis of 73 countries based on IQVIA-MIDAS database, 2015 to 2024.The journal of headache and pain · 2026Article
- Sample size requirements to evaluate policies in addiction research using interrupted time series analysis (ITS): Tools and guidance.Addiction (Abingdon, England) · 2026Article
- Trends in overweight prevalence among university freshmen and the impact of the COVID-19 pandemic: a repeated cross-sectional study.Frontiers in public health · 2026Article
- Fish Oil-Containing Lipid Emulsion and Retinopathy of Prematurity: Signal, Selection, or Secular Trend.Indian journal of pediatrics · 2026Article
- Outcome Evaluation of a Multimodal Suicide Prevention Program Designed Through International Collaboration: Protocol for a Controlled Interrupted Time Series Study.JMIR research protocols · 2025Article
- Electronic health record interventions to reduce postoperative pregabalin prescribing: a quality improvement initiative.Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2025Observational
- Impact of Health All-in-One Machines on access to healthcare of rural areas in China: an interrupted time series analysis.BMC health services research · 2025Article
- Impact of Enhanced Outpatient Pooling Level on Healthcare Utilization, Costs and Fund Expenditures in China: An Interrupted Time Series Analysis.Risk management and healthcare policy · 2025Article
- The total number of patients with any of four major fragility fractures decreased during the first wave of the COVID-19 epidemic in Japan, commencing before the state of emergency declaration, which was not as enforceable as lockdown.Archives of osteoporosis · 2023Article
- Combined effect of early diagnosis and treatment on the case fatality risk of COVID-19 in Japan, 2020.Scientific reports · 2023Article
- Outcomes after Acute Malnutrition Program Adaptations to COVID-19, Uganda, Ethiopia, and Somalia.Emerging infectious diseases · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
objectiveTo discuss the study design and data analysis for three-phase interrupted time series (ITS) studies to evaluate the impact of health policy, systems, or environmental interventions. Simulation methods are used to conduct power and sample size calculation for these studies.
methodsWe consider the design and analysis of three-phase ITS studies using a study funded by National Institutes of Health as an exemplar. The design and analysis of both one-arm and two-arm three-phase ITS studies are introduced.
resultsA simulation-based approach, with ready-to-use computer programs, was developed to determine the power for two types of three-phase ITS studies. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from -0.9 to 0.9 with various effect sizes. The power increased as the sample size or the effect size increased. The power to detect the same effect sizes varied largely, depending on testing level change, trend changes, or both.
conclusionThis article provides a convenient tool for investigators to generate sample sizes to ensure sufficient statistical power when three-phase ITS study design is implemented.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.