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関連する概念動画

Sampling Methods: Overview01:06

Sampling Methods: Overview

2.0K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
2.0K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

376
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
376
Quality Assurance01:19

Quality Assurance

926
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
926
Sampling Plans01:23

Sampling Plans

855
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
855
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

579
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
579
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

8.4K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
8.4K

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Updated: Jan 8, 2026

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品質改善におけるサンプリング方法と考慮事項：スコープレビュー

Lucylynn Lizarondo1, Vanesa Bochkezanian1, Alexa McArthur1

  • 1JBI, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia.

JBI evidence implementation
|December 24, 2025
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まとめ

品質改善（QI）のサンプリングは、タイムリーな意思決定のために実用的で非確率的な方法を優先します。ヘルスケアにおける透明で文脈に応じたサンプリングのためのより明確なガイダンスが必要です。

キーワード:
PDSA評価改善科学品質改善サンプルサイズサンプリング

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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
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科学分野:

  • ヘルスケアの品質改善
  • 実装科学
  • 研究方法論

背景:

  • 品質改善（QI）は、ヘルスケアを強化するためにデータ駆動型の方法を使用します。
  • 効果的なサンプリングは、実現可能で関連性のあるQIデータ収集に不可欠です。
  • 現在のQIサンプリング方法は、しばしば実用的で、一貫性がなく、正当化が欠けています。

研究 の 目的:

  • QIイニシアチブのためのサンプリング戦略を特定し、統合すること。
  • QIにおけるサンプリングフレームワークとサンプルサイズの考慮事項を検討すること。
  • QIサンプリングをエビデンス実装と実装科学のより広範な文脈の中に位置づけること。

主な方法:

  • JBI方法論に従ったスコープレビュー。
  • 複数のデータベースおよび組織ウェブサイトにわたる査読済みおよびグレー文献（2000年から2024年）を検索しました。
  • QIサンプリングに関する概念的/方法論的洞察を提供するソースを含み、経験的なQI研究を除外しました。

主要な成果:

  • 10件のソースが対象となり、統計的推論ではなく意思決定のためのサンプリングに焦点を当てました。
  • 文脈への適合性と実現可能性から、非確率的（判断、意図的、便宜的）方法が支配的でした。
  • バイアスや不明瞭なサンプルサイズガイダンスなどの限界が指摘され、実用的なフレームワークはほとんどありませんでした。

結論:

  • QIサンプリングは、実用性と統計的厳密さのバランスをとります。
  • QIサンプリングのための、より明確で目的に適合したガイダンスが必要です。
  • ガイダンスの改善は、透明で、文脈に応じた、方法論的に健全なサンプリング決定をサポートできます。