713 Bioinformatics & Stats

bioinformatics

the application of computational and statistical methods to analyze biological data, particularly in genomics, proteomics, and molecular biology. It focuses on understanding biological processes by interpreting large datasets such as DNA sequences and protein structures.

health informatics

the application of information technology and data analysis to healthcare settings, focusing on managing, analyzing, and using health data to improve patient care, clinical processes, and decision-making

electronic health records

provides a centralized accessible database where therapists can review patient histories, track progress, and even collaborate with other healthcare providers in real time.

data driven treatment plans

allows for more personalized and effective treatment plans. By analyzing large datasets, researchers can uncover trends that help predict outcomes for specific injuries or conditions

wearable technology

opened new possibilities for real time monitoring outside the clinic giving PTs a continuous stream of data on their patients’ progress and allows them to adjust exercises in real time based on actual performance

internal consistency

the degree to which different items within a test measure the same construct

test-retest relaibility

the consistency of a measure when the same test is repeated under identical conditions

inter-rater reliability

the degree of agreement among different rates evaluating the same outcome

Intra-rater reliability

the consistency of a single rater’s measurements across multiple occasions

standard error of measurement (SEM)

an estimate of the amount of error in a test score, reflecting the precision of an individual’s score

criterion validity

the extent to which a measure is related to an outcome (often compared with a gold standard)

construct validity

the extent to which a test measures the theoretical construct it’s intended to measure

minimal clinically important difference (MCID)

the smallest change in an outcome that a patient perceives as beneficial, which would warrant a change in patient management

minimal detectable change (MDC)

the smallest change in a score that reflects a real change beyond measurement error

specificity

the proportion of true negatives correctly identified. High specificity is important to avoid unnecessary treatment for those without the condition

negative predictive value

the likelihood that a person who tests negative truly does not have the condition

clinical relevance

In physical therapy, diagnostic accuracy measures help determine the utility of special tests