Statistics

Question 1

What is sensitivity in diagnostic testing?

Answer 1

TP/(TP+FN)

-Sensitivity (true positive rate): chance that a diseased person will test positive
-Value approaching 100% is desirable for ruling out disease; indicates low false-negative rate
-SN-N-OUT: highly SeNsitive test, when Negative, rules OUT disease
-High sensitivity test used for screening

Question 2

What is specificity in diagnostic testing?

Answer 2

TN/(TN+FP)

-Specificity (true negative rate): chance that a non-diseased person will test negative
-Value approaching 100% desirable for ruling in disease & indicates low false-positive rate
-SP-P-IN= highly SPecific test, when Positive, rules IN disease
-High specificity test use for confirmation after positive screening test

Question 3

PPV

Answer 3

Positive Predictive Value, calculated as TP/(TP+FP). It indicates the likelihood that a positive result means the patient actually has the disease.

Predictive value – Depends on disease prevalence while Sensitivity and specificity does not

Question 4

NPV

Answer 4

Negative Predictive Value, calculated as TN/(TN+FN). It indicates the likelihood that a negative result means the patient does not have the disease.

Question 5

What is relative risk?

Answer 5

Relative risk is calculated as (Incidence of exposed/Incidence of unexposed) = (a/a+b)/(c/c+d). A relative risk < 1 indicates a negative association, > 1 indicates a positive association, and = 1 indicates no association.

Question 6

What is the odds ratio?

Answer 6

The odds ratio is calculated as (a/c)/(b/d) = (AxD)/(BXC).

Question 7

What is a Type I error?

Answer 7

A Type I error is a false positive that rejects the null hypothesis incorrectly, falsely assuming there is a difference when none exists.

Question 8

What is a Type II error?

Answer 8

A Type II error is a false negative that accepts the null hypothesis incorrectly, often caused by a small sample size.

Question 9

What is the power of the test?

Answer 9

The power of the test is the probability of making a correct conclusion, calculated as 1 - probability of Type II error (Beta). Larger sample size increases power

Question 10

What is the null hypothesis?

Answer 10

The null hypothesis states that no difference exists between two groups.

Question 11

What does a p-value < 0.05 indicate?

Answer 11

A p-value < 0.05 indicates rejection of the null hypothesis, suggesting a > 95% likelihood that the difference between populations is true and did not occur by chance.

Question 12

What is variance?

Answer 12

Variance is the spread of data around a mean.

Question 13

What is a cohort study?

Answer 13

A cohort study is a prospective study that compares patients with exposure risk factors to those without, assessing disease occurrence.

Question 14

What is a case-control study?

Answer 14

A case-control study is a retrospective study comparing patients with and without a disease, looking for exposure risk factors.

Question 15

What is Kaplan-Meier analysis?

Answer 15

Kaplan-Meier analysis estimates survival in small groups.

Question 16

What is primary prevention?

Answer 16

Primary prevention aims to avoid disease altogether, such as through vaccination.

Question 17

What is secondary prevention?

Answer 17

Secondary prevention focuses on early detection, such as colonoscopy and mammograms.

Question 18

What is tertiary prevention?

Answer 18

Tertiary prevention aims to decrease morbidity related to established disease, such as controlling blood pressure in hypertensive patients.

Question 19

What are the phases of clinical drug trials?

Answer 19

Phase I studies demonstrate safety on a small group, Phase II assesses effectiveness on a larger group, Phase III compares the new drug to standard care, and Phase IV investigates long-term effects.

Question 20

What is a normal distribution?

Answer 20

A normal distribution (Gaussian) is a symmetric bell-shaped curve. 1 SD includes 68% of samples, 2 SD includes 95%, and 3 SD includes 99.7% around the mean.

Question 21

What is a propensity-score-matched study?

Answer 21

-Propensity-score-matched study: observational study that attempts to reduce confounding and be closer to a randomized controlled trial; cases selected so subjects in both groups similar across multiple factors

Question 22

What is a meta-analysis?

Answer 22

A meta-analysis pools data from multiple studies using quantitative statistical methods.

Question 23

What is the receiver-operating curve (ROC)?

Answer 23

The ROC analyzes the effect on sensitivity and specificity when adjusting the cut-off value of a test.

Question 24

Comparing variables

Answer 24

Question 25

Selection bias

Answer 25

Nonrandom sampling or treatment allocation of subjects such that study population is not representative of target population Berkson bias—cases and/ or controls selected from hospitals (bedside bias) are less healthy and have different exposures Attrition bias—participants lost to follow up have a different prognosis than those who complete the study Reduce bias: Randomization

Question 26

Recall bias

Answer 26

Awareness of disorder alters recall by subjects; common in retrospective studies Patients with disease recall exposure after learning of similar cases Reduce: Decrease time from exposure to follow-up

Question 27

Hawthorne effect

Answer 27

Participants change behavior upon awareness of being observed

Question 28

Observer-expectancy bias

Answer 28

Researcher’s belief in the efficacy of a treatment changes the outcome of that treatment (aka, Pygmalion effect) An observer expecting treatment group to show signs of recovery is more likely to document positive outcomes Reduce: blinding (masking) and use of placebo

Question 29

Confounding bias

Answer 29

Factor related to both exposure and outcome (but not on causal path) distorts effect of exposure on outcome (vs effect modification, in which the exposure leads to different outcomes in subgroups stratified by the factor) An uncontrolled study shows an association between drinking coffee and lung cancer; however, people who drink coffee may smoke more, which could account for the association Reduce: matching, crossover study

Question 30

Lead-time bias

Answer 30

Early detection interpreted as 􏰀survival, but the disease course has not changed Breast cancer diagnosed early by mammography may appear to exaggerate survival time because patients are known to have the cancer for longer Reduce: adjust survival according to the severity of disease at the time of diagnosis

Question 31

Length-time bias

Answer 31

Screening test detects diseases with long latency period, while those with shorter latency period become symptomatic earlier

Question 32

Quaternary disease prevention

Answer 32

Quit (avoid) unnecessary medical interventions to minimize incidental harm (eg, imaging studies, optimizing medications to reduce polypharmacy)

Question 33

NSQIP

Answer 33

Collects outcome data to measure and improve surgical quality; outcomes are reported as observed/ expected ratios

Question 34

JCAHO

Answer 34

Prevention of wrong site/ procedure/ patient protocol Preop verification of patient and procedure Operative site and side marking Time out: before incision is made: verifying patient, procedure, position site + side, availability of implants or special requirements

Question 35

RFs for retained object after surgery

Answer 35

MC= sponge emergency procedure, unplanned change in procedure, obesity, towel used for closure

Question 36

Sentinel event

Answer 36

Unexpected occurrence involving death or serious injury or the risk thereof; hospital undergoes root cause analysis to prevent and minimize future occurrences (e.g. wrong site surgery)

Question 37

Gap protection technique

Answer 37

gaps in care (change in caregiver, divisions of labor, shift changes, transfers) can lead to loss of information and error Prevention: structured handoffs, checklists (face to face best), standardized orders; reading back orders if verbal

Question 38

Patient safety errors

Answer 38

Question 39

Plan-Do-Study-Act

Answer 39

-Plan-Do-Study-Act: -Develops and implents a quality initiative, and analyzes the results, and adjusts the iniative based on the results -Plan: develop the initiative -Do: implement the plan -Study: analyze the results -Act: adjust the process based on the results

Question 40

-Six Sigma:

Answer 40

DMAIC, Define, Measure, Analyze, Improve, Control -Focus on improving existing processes

Question 41

-Situation-Background-Assessment-Recommendation:

Answer 41

Provides framework for communication between members of the health care team about a patient's condition

Question 42

-Root Cause Analysis:

Answer 42

-Identifies the factors that caused a failure and should be eliminated through the process

Question 43

-Failure Mode and Effects Analysis:

Answer 43

-Prospectively uses a step-by-step approach for identifying all possible failures in a design or process