Sampling methods and considerations in quality improvement: a scoping review.

Introduction: Quality improvement (QI) in health care involves systematic, data-driven approaches to enhance service quality, safety, and efficiency. Sampling is critical to ensure that data collection is feasible, contextually appropriate, and aligned with improvement goals. However, sampling metho...

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Publicado en:JBI Evidence Implementation Vol. 24; no. 1; pp. 163 - 176
Autores principales: Lizarondo, Lucylynn, Bochkezanian, Vanesa, McArthur, Alexa, Królikowska, Aleksandra, Prill, Robert, Lockwood, Craig
Formato: research systematic review tables/charts Journal Article
Publicado: Lippincott Williams & Wilkins Jan2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan2026
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      pub: Lippincott Williams & Wilkins
      place: Baltimore, Maryland
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        atl: Sampling methods and considerations in quality improvement: a scoping review.
      aug:
        au:
          Lizarondo, Lucylynn
          Bochkezanian, Vanesa
          McArthur, Alexa
          Królikowska, Aleksandra
          Prill, Robert
          Lockwood, Craig
        affil: JBI, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia
      sug:
        subj:
          Health Services Research
          Quality Improvement
          Sampling Methods
          Implementation Science
          Scoping Review
          PubMed
          CINAHL Database
          Gray Literature
          Probability Sample
          Nonprobability Sample
          Thematic Analysis
          Benchmarking
          Accreditation
          Purposive Sample
          Convenience Sample
          Random Sample
          Stratified Random Sample
          Sample Size
          Decision Making
      ab: Introduction: Quality improvement (QI) in health care involves systematic, data-driven approaches to enhance service quality, safety, and efficiency. Sampling is critical to ensure that data collection is feasible, contextually appropriate, and aligned with improvement goals. However, sampling methods in QI—often pragmatic and non-probability based—are inconsistently reported and poorly justified. Aim: This scoping review, the first to address this topic, aimed to identify and synthesize sampling strategies, frameworks, and sample size considerations for QI initiatives, situating them within the broader evidence implementation and implementation science context. Methods: This review followed the JBI methodology for scoping reviews and was registered in the Open Science Framework (osf.io/rs83a). Peer-reviewed and gray literature from 2000 to 2024 was searched for in PubMed, Web of Science Core Collection, and CINAHL Ultimate (EBSCOhost), as well as organizational websites (e.g., Institute for Healthcare Improvement, Agency for Healthcare Research and Quality, National Institute for Health and Care Excellence, and the World Health Organization). Sources offering conceptual, methodological, or theoretical insights into sampling in QI were included, while empirical QI studies were excluded. Two reviewers independently screened and extracted data, with findings synthesized narratively and in tables. Results: Ten sources were included. Sampling in QI was primarily intended to support timely, relevant, and credible decision-making rather than statistical inference. Non-probability methods—particularly judgment, purposive, and convenience sampling—were dominant, valued for contextual fit and feasibility. Decisions were shaped by local constraints, perceived risks, and implementation stage. While limitations such as bias, generalizability, and unclear sample size guidance were acknowledged, few sources provided actionable frameworks. Conclusion: The results indicate that QI sampling reflects a balance between pragmatism and statistical rigor. This highlights the need for clearer, fit-for-purpose guidance to support transparent, context-sensitive, and methodologically sound sampling decisions.
      pubtype: Academic Journal
      doctype:
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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