Using basic statistics on the individual patient's own numeric data.

Area of Science:

• Chiropractic research
• Biostatistics
• Patient data analysis

Background:

• Assessing individual patient data requires objective analytical methods.
• Coefficient of Variation (CV) and Quartile Analysis (QA) are statistical tools for evaluating data variability and outliers.
• Their application in clinical practice for individual patient numerical data needs practical demonstration.

Purpose of the Study:

• To illustrate the practical application of CV and QA for analyzing individual patient numerical data.
• To assess the potential of these statistical methods to enhance objectivity in clinical practice.
• To explore the correlation between CV of physiological measurements and patient-reported health outcomes.

Main Methods:

• Mastoid fossa temperature differential (MFTD) readings were collected from a patient over 8 visits using infrared instrumentation.
• Coefficient of Variation (CV) and Quartile Analysis (QA) were applied to the MFTD readings to identify outliers and assess variability.
• The Short Form-12 (SF-12) health survey was administered at each visit, and findings were correlated with CV to evaluate clinical significance.

Main Results:

• An outlier MFTD reading was detected on the eighth visit using QA, coinciding with the highest CV value.
• Correlations between SF-12 scores and CV were consistently low, negligible, positive, and not statistically significant.
• The study identified a potential outlier in physiological data but found no significant association with patient-reported health outcomes.

Conclusions:

• Basic statistical analyses like CV and QA can be applied to individual patient numerical data in chiropractic practice.
• These methods may offer increased objectivity when interpreting clinical numerical findings, especially when clinical significance is uncertain.
• Further research is warranted to validate the utility of CV and QA in diverse clinical scenarios and patient populations.