Data Sampling

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Population and Sampling

Unless sufficiently small, utilizing sampling is prudent for populations under study. Populations may be static or dynamic, influencing preferred sampling methodology. A population constitutes the entire potential group for examination, be they people, objects, events, etc. Illustrative populations comprise:

  • All cases with a particular diagnosis, treatment, procedure, or complication
  • All physicians/clinicians in a department or discipline
  • All patients receiving care in a clinic during a specified timeframe
  • All cases involving orders for a particular medical device

A sample represents a subset of a population, allowing measurement of a portion to characterize the whole. Sampling aims to achieve accurate representation generalizable to the target population.

Several factors necessitate consideration in sampling. The sample must mirror key population characteristics as well as pertinent location and timeframe. Chosen techniques must engender representative, unbiased samples. For instance, studying pneumonia patients strictly from one season fails to account for weather and seasonal impacts.

Probability vs Nonprobability Sampling

Probability sampling enables stronger generalization to wider populations. Nonprobability sampling reduces generalizability but allows intentionally targeted, potentially biased sampling to uncover suspected issues through qualitative examination of relatively few cases.

Probability Sampling Techniques

Simple random sampling utilizes random number generation to select cases/individuals equitably. Stratified random sampling categorizes the population by homogeneous dimensions then samples appropriate numbers within strata. Systematic random sampling lists the full population, randomly selects the first case, then intermittently selects additional cases at fixed intervals.

Nonprobability Sampling Techniques

Nonprobability purposive sampling selects cases displaying characteristics of interest assessable against predetermined criteria. Initial heart attack studies exclusively utilized male patients because they dominated emergency department admissions, illustrating that symptoms can manifest differently across groups. Quota sampling delineates portions of a stratified population then samples within those. However, small proportions limit conclusions about unsampled segments. Convenience sampling utilizes the most readily available data, but sacrifices breadth.

Survey Design Considerations

Surveys assess large group perceptions, like patient care experiences. Poorly designed surveys risk insufficient or misleading results. Adequate response rates require concerted survey distribution efforts. Additional considerations include delivery method, length, language, scale design enabling nuanced responses, and prompt administration following the experience surveyed.

Focus Groups

Focus groups collect qualitative insights about a topic from representative individuals using open participation. The methodology entails:

  • 6-12 participants with a shared interest
  • Homogenous groups unacquainted with one another
  • Facilitator guiding discussion using scripted questions
  • Recording and transcription
  • Coding responses to identify themes

Benefits include eliciting opinions from gathered participants. Drawbacks include resource intensive analysis and limited generalizability from purposeful sampling.

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