NPTE Non-systems

JACHO

Joint Commission on Accreditation of Healthcare Organizations

-Hospitals, SNF, Home Health, PPO, HMO, Mental institutions

-The FBI of healthcare

CARF

Commission on Accreditation of Rehabilitation Facilities

-Free standing rehab programs/facilities

CMS

Centers for Medicare and Medicaid Services

OSHA

Occupational Safety and Health Administration

-keeps us safe at work

Documentation mistakes

-Strike out with single line and initialed and dated by PT

-Never use white out

PPE: MRSA, VISA, C-diff, Lice Scabies, Hep-B, Dermatitis, Rota Virus

Contact Precautions: Gloves and Gown

PPE: Mumps, Meningitidis Pneumonia, Flu, Strep

Droplet: Mask

PPE: Measles, Tuberculosis, Chicken Pox, Herpes Zoster, SmallPox, SARS

Airborne: N95

May add Contact if infection is severe (gown and gloves)

- must use (-) air flor room and keep door closed

MTV= airbone

Measles, Tuberculosis and Varicella

CPR basics

-chest compressions at least 5cm (2 in) deep

-30:2

-Allow full recoil

-minimize pauses in compressions

Levels of Evidence

Meta-analysis

Systematic reviews of multiple well-designed controlled studies

Randomized controlled trials

Cohort Studies

Case Control Studies

Cross sectional studies

Case series/case reports

What is the difference between meta-analysis and systematic review?

Meta has a statistical analysis but a systematic review does not (its just synthesizing information out there)

Levels of Measurement for Qualitative Data: Non-parametric

Qualitative data: no numbers

Used for Non-parametric data

NOn= Nominal and Ordinal

Nominal: data that is mutually exclusive categories (Gender and blood type)

Ordinal: data that is ranked and no quantifiable differences between ranks (MMT)

Levels of Measurement for Quantitative Data: Parametric

Quantatiative: Numbers

Interval: Hold no true zero and can be below zero (Temperature)

Ratio: Highest level of measurement and can have True 0, ROM measurements

Rati0= True 0

Define reliability

Will you get the same results every time when used in the same situation

Types of Reliability

Intra-rater: Can 1 PT get the same outcome each time with several attempts

Inter-rater: Can 2 or more PTs get the same result

Test-retest: 1 test on 1 person on 2+ occasions get the same result (look for key words of new equipment, same test different week)

Define Validity

does the test measure what you want

Types of validity

Content: Measure specifically what the pt problem is (Fall risk-> use TUG)

Construct: Measure what is it supposed to measure (Goniometer measures ROM)

Concurrent: Comparing GOLD standard to other test (HHD vs MMT)

Face: the outcome measure should measure what is looks like it will measure related to patient problem (appears to measure; surveys?)

Types of Errors

Type 1: False Positive

1 can be turned into a P

ex: Telling a male he is pregnant

*Type 2: False Negative

II can be turned into a N

ex: Telling a pregnant woman she is not pregnant

Sensitivity and SNOut

-Someone will get (+) if they have the condition

-A (-) result = better able to rule OUT the diagnosis

-has few false negatives

-Very low likelihood ratio

Specificity and SPIn

-Identifies pt who DON'T have the condition

-Someone will get (-) if they DON'T have the diagnosis

-A (+) result = better able to rule IN the diagnosis

-high likelihood ratio

T-Test

-Determines if there is a difference BETWEEN 2 groups

-Can be done when 2 diff groups are matched and tested

OR

-if one group is tested (pretest/posttest)

-ONLY used if there is one dependent and one independent variable in the study

Analysis of Variance (ANOVA)

-statistical test used to determine whether there are differences among 3 or more groups

-Can analyze 2 or more independent variables and any interaction between the variables

-Ex: looking to determine difference btwn 3 exercise protocols that increase ROM following shoulder immobilization

Chi Square Test

-tells whether the observed pattern, trait or distribution is different that what would have been expected by chance alone

-often in genetics or with population statistics

-chi square test is commonly used to test relationships and differences btw categorical variables

Effect Size

-the magnitude of the difference btw groups

-Absolute effect size provides the difference btw the average outcomes in 2 diff intervention groups

-P values tells us whether an effect exits but does not share the size of the effect

-Effect Size btw groups is shared as Cohen's D, Odds or Risk ratio

-Effect size for associations is shared as Pearson's Coefficient

Statistical Significance

-The probability of level of confidence as to whether or not the results of the experiment happened by chance

- P values often set to 0.5 or 0.01

-p=0.05 there is probability that the results obtained would occur by chance 5% of the time and would occur from tx 95% of the time

-p=0.01 there is probability that the results obtained would occur by chance 1% of the time