SchizoCat
BIOSTATS & SOCIAL SCIENCES
OME + UWORLD
Table of Contents
Prevention
2
Screening
3
Vaccinations
7
Diagnostic tests
8
Study design
13
Bias
19
Statistical distribution
27
Hypothesis testing
29
Risk
32
Confidence interval
37
Statistical methods
39
Drug advertisements
43
Ethics
44
Genetics
51
Patient safety
52
1
Prevention
Types of prevention:
• Primary prevention: prevent the onset of disease.
o Aim is to reduce exposure:
 For example:
• Weight loss, smoking, alcohol, eating better.
• Vaccination.
• Secondary prevention: early detection to delay progression.
o Screening tests with high sensitivity.
 If positive  intervene with lifestyle and medications.
• Tertiary prevention: preventing complications.
o Treatment of disease; lifestyle modifications and drugs.
o More responsive than preventive.
2
Screening
Cancer:
Cancer
Colorectal
Start
50 (40 or 10 years
before first
degree relative
was diagnosed)
Breast
50
Cervical
21
Lung
55-80 with a 30pack year history
and they quit <15
years ago
How
Colonoscopy:
every 10 years
Sigmoidoscopy:
every 5 years +
FOBT: every 3
years
FOBT alone: every
year
Mammogram:
every 2 years
Pap smear: every
3 years
Pap smear +HPV
after the age of
30: every 5 years
Low dose CT scan
yearly
Stop
75
75
65: 3 consecutive
normal pap or
TAH
80
3
•
We don’t screen for prostate (due to lead time bias), ovarian (unless
BRCA+), or endometrial cancers.
Medical disease:
Disease
Abdominal aortic
aneurysm
Osteoporosis
Hepatitis C
HIV
HTN
DM
Dyslipidemia
Depression
Mobility
Who
Males; 65 and who have
ever smoked
Females; 65 or older
Or younger if there are
risk factors such as:
steroid use, low BMI <21,
alcohol, smoker,
amenorrhea
Baby boomer (19451965)
Everyone
Everyone; every visit
HTN
Men: 35 and more or
greater than 25 with
CVD risk factors
Women: 45 and more or
greater than 30 with
CVD risk factors
How
US abdomen (CT
abdomen counts)
DEXA scan
>-2.5  bisphosphonates
Hep C Ab
ELISA
If positive  confirm
before telling patient
ABPM
HbA1c
Lipid panel
Treatment: statins
PHQ-9
Get up and go
4
Adolescent screening:
•
MCC death in this age group is suicide  screen for depression.
5
o Depression can present as irritability, failure to gain an expected
amount of weight, and academic decline. Also, abdominal pain
and headache.
o All teenagers above the age of 12 should be screened.
6
Vaccinations
Adult vaccines:
• Contraindications:
o Anaphylaxis.
o Egg allergy.
o Immunodeficiency.
Vaccine
Tdap
Pneumococcal
Zoster
Flu
HPV
Meningococcal
When
Every 10 years for 3
lifetime doses
Once before 60; PCV13
Once after 65; PPSV23
>60
Everyone annually
9-26
Before the age of 15: 2
doses 6 months apart
After the age of 15: 3
doses at 0, 2, and 6
months
Dormitory and army
Contraindication
Anaphylaxis
Never give 13 and 23 at
the same time
Immunodeficiency
IM  eggs
Live attenuated
intranasal 
immunodeficiency
7
Diagnostic tests
•
Sensitivity: SNNOUT
o TP/(TP+FN)
8
•
•
•
•
o High sensitivity means that negative results are less likely to be false
negatives and more likely to be true negatives.
o Screening tests should have high sensitivity.
Specificity: SPPIN
o TN/(TN+FP)
o High specificity means that positive results are less likely to be false
positives and more likely to be true positives.
o Confirmatory tests should have high specificity.
Accuracy:
o Probability that an individual is correctly classified by a test.
o Sum of the true positives and negatives divided by the total number
of individuals tested.
 (TP+TN)/(TP+ FP+TN+FN)
Positive predictive value:
o TP/(TP+FP)
o “How likely that I actually have the disease?”
o Increases with increased disease prevalence.
Negative predictive value:
o TN/(TN+FN)
o Varies with pretest probability (prevalence).
 A patient with a high pretest probability (a lot of risk factors)
has a low NPV.
9
10
•
Interpretation of above graph:
11
•
•
•
•
•
o Moving the cutoff point to the left side increases the sensitivity of
the test because more patients with the disease test positive and
there are fewer FNs.
o Moving the cutoff point to the right side will increase FNs and
decrease FPs thus increasing specificity.
Precision:
o Result repeated consistently or a tight confidence interval.
o A measure of random error in the study.
Accuracy:
o Measures what’s supposed to be measured.
Pre-test probability: existing probability of a patient to have the disease in
question even before using a diagnostic test.
o Prevalence is directly related to pre-test probability.
o For example; no risk factors for development of CAD  low pre-test
probability.
Pre-test odds: probability of the event happening to the probability that
the event does not happen.
Post-test probability: dependent on the sensitivity, specificity, and pre-test
probability of having the disease.
o For example; if the patient had a low pre-test probability and his
test was positive  then the possibility of having the disease is low.
Cases and diagnostic tests high yield for the USMLE:
• ECG stress test and CAD.
• Pulmonary embolism and perfusion-ventilation scanning.
• Prostate cancer and serum PSA levels.
12
Study design
Incidence: newly diagnosed with a disease.
Prevalence (pre-test probability): all the people with the disease at a certain
moment of time.
• If a population reached a stable condition (minimal migration and a
negligible growth rate) prevalence can be approximated by considering
the incidence and the duration of disease:
o Prevalence= incidence x duration of disease.
Study designs:
• Experimental (intervention): can establish causal relationships.
o Randomized control trial:
 Can establish causation.
 Intervention group; receives intervention
 Control group; doesn’t receive intervention.
• Placebo or standard of care or nothing.
 Randomization: an ideal randomization process minimizes
selection bias, results in near-equal treatment and control
group sizes and achieves a low probability of having
confounding variables.
• A table of patient baseline characteristics for both
groups would show if the 2 groups included patients
with similar features and would help confirm proper
randomization.
13
Unlike other methods of controlling confounding
(matching, stratified analysis), randomization controls
known as well as unknown confounders.
Blinding: hiding group assignment.
• Open label  no bias.
• Single (patient) or double blinding (patient and
researcher).
Cross over: switching of groups.
Factorial design: involves 2 or more experimental
interventions, each with 2 or more variables that are studied
independently.
•




Cluster analysis: grouping of different data point into similar
categories.
o To establish causality:
14
•
o Dose-response relationship:
 Used to establish causality in epidemiological studies.
 Refers to the presence of a dose-response curve.
• A causal dose-response relationship assumes that the
greater the exposure, the greater the risk of disease.
Observational (the researchers have no control over the independent
variables such as risk factors or treatments): cannot establish causal
relationship.
o Descriptive designs: generate hypothesis.
 Case report: report of disease presentation, treatment, and
outcome in a single subject/event.
 Ecological study: population level association between
exposure and outcome.
• Cannot be used to determine incidence.
• Ecological fallacy: paradox in which the study shows
an association between an exposure and an outcome
while in fact it is the opposite in certain groups within
the population.
 Case series: report of disease course/response to treatment
compiled by aggregating several similar patient cases.
• No comparison group.
 Cross-sectional study:
• To study prevalence and risk factors simultaneously.
• Takes a snapshot.
• Examines association between risk factors and disease.
• Uses prevalence ratio: ratio of 2 prevalence estimates
commonly used in cross-sectional studies to compare
15
the prevalence of disease among exposed and
nonexposed groups of people.
• A major limitation: no clear temporal relationship.
• A major disadvantage is that it is biased in favor of
longer lasting and milder conditions. Since more severe
conditions tend to be rapidly fatal and are therefore
less likely to be found in a snapshot of the population.
This phenomenon is known as late-look or Neymon
bias.
o Analytical designs: test hypothesis,
 Case-control:
• Odds ratio.
o Measure of effect cannot be interpreted as risk
but rather as odds.
• Studies if an exposure is associated with an outcome.
• Useful for diseases with long latency period.
• Two groups (one with and one without disease) are
assessed to compare the presence of risk factors
between the 2.
• If the outcome is uncommon in the population, the
odds ratio is a close proximation of the relative risk
(“rare disease assumption”).

Cohort:
• Study the incidence and whether exposure is
associated with an outcome.
• Retrospective: the protocol is established, and the
study begins AFTER the group develops an outcome of
interest (ex: a study that aims to identify what
16
•
proportion of individuals with lung cancer smoked > 1
pack of cigarettes a day in the past 5 years).
Prospective: the protocol is established and the study
begins BEFORE the group develops an outcome of
interest -- you start with individuals who were exposed
or not then follow them for a period of time (ex: a study
that aims to identify what proportion of individuals who
currently smoke > 1 pack of cigarettes a day develop
lung cancer in the next 5 years).
17
External validity (generalizability):
• Defined as the applicability of the obtained results beyond the cohort
that was studied.
• Review inclusion and exclusion criteria carefully.
Internal validity:
• Bias.
• Reliability.
• Reproducibility.
18
Bias
Subjects:
• Hawthorne: people change their behavior because they know they’re
being observed.
• Recall: sick patients remember more.
• Reduce by blinding.
• Sample distortion bias: estimate of exposure and outcome association is
biased because the study sample is not representative of the target
population with respect to the joint distribution of exposure and outcome.
• Respondent bias: outcome obtained by the patient’s response and not
by objective methods.
• Selective survival bias: occurs in case-control studies when cases are
selected from the entire disease population instead of just those who are
newly diagnosed.
o For example; a study on cancer survival that is not limited to newly
diagnosed patients will contain a higher proportion of relatively
benign malignancies as these patients generally live longer.
Researchers:
• Selection bias: groups different at baseline.
o Susceptibility bias: a form of selection bias.
 When the treatment regimen selected for a patient depends
on the severity of the condition.
o Loss to follow up: alters the internal validity of a study.
o Reduce by randomization or matching.
• Observer bias: when researcher knows which group the patient is in.
o Reduce by double blinding.
Study:
• Confounding: factor that distorts relationship between exposure and
outcome; related to outcome and exposure.
o Reduce by randomization or matching or restriction or change
study design.
 Randomization: controls known as well as unknown
confounders.
 Restriction: method involves limiting study participation to
individuals with certain characteristics.
 Matching: matching known or suspected confounding
variables between the cases and controls.
o For example: ice cream and drowning. Summer is the factor that
causes ice cream eating and swimming happens during the
summer, so people drown more.
19
•
o Another example; cigarette smoking, alcohol, and low birth weight.
Effect modification (not a bias): exposure and outcome are connected;
factor isn’t related to exposure but related to outcome (it enhances
response to exposure).
o For example: OCPs increase risk of DVT; smoking increases the risk
even more.
o Stratified analysis by the extraneous variable can help distinguish
whether that variable is a confounder or an effect modifier.
20
Problem
Example
Solution
21
Selection bias
The individuals in a sample
group are not
representative of the
population from which the
sample is drawn.
Healthy worker effect: The working
population is healthier on average
than the general population
→ Any sample consisting of only
working individuals does not
represent the general population.
Berkson bias: Sample groups drawn
from a hospital population are
more likely to be ill than the general
population.
Non-response bias: Nonresponder
characteristics differ significantly
from responder characteristics
because nonresponders do not
return information during a study
(e.g., patients do not return a call or
do not respond to a written survey
response).
Volunteer bias: Individuals who
volunteer to participate in a study
have different characteristics than
the general population.
Susceptibility bias: A first disease
present in a patient predisposes to
the second one, and treatment for
the first disease is mistakenly
interpreted as the predisposing
factor for the second disease.
Attrition bias
Selective loss to follow up of
participants; especially in
prospective studies
Risk of over- or underestimating the
association between exposure and
outcome because the remaining
participants differ significantly from
those lost to follow-up.
Survival bias
Also known as prevalenceincidence bias or Neyman bias
A type of selection bias in which
those observed as having a disease
have either more severe or less
severe disease than is true for all
those who truly have the disease. In
comparison to the true population
with disease:
Randomization
Subjects are
randomly
assigned to the
intervention and
control groups
to ensure that
both groups are
roughly equal in
baseline
characteristics (o
ften displayed in
a table, e.g.,
in randomized
controlled trials).
Controls for both
known and
unknown confou
nders
Successful if
possible confoun
ding characteristi
cs (e.g.,
socioeconomic
demographics,
family history)
are
approximately
equally
distributed
between the
groups
Ensure the
sample group is
representative of
the population
of
interest (e.g., in c
asecontrol studies).
Collect as much
data on
characteristics of
the participants
as possible.
Nonresponder
characteristics
22
If those with severe disease die
before the moment of observation,
those with less severe disease are
observed.
If those with less severe disease
have a resolution of their disease
before the moment of observation,
those with more severe disease will
be observed.
Typically occurs in casecontrol and cross-sectional studies
should not be
assumed and
incorrectly
included in data
analysis; instead,
undisclosed
characteristics of
nonresponders
should be
recorded as
unknown.
Intention-totreat
analysis: All
patients who
initially enrolled
in the study
(including dropouts) are
included in the
analysis of study
data regardless
of the eventual
treatment; helps
to
reduce selection
bias; preserves ra
ndomization
Allocation bias
A systematic difference in
the way that participants
are assigned to treatment
or intervention groups
Assigning all female patients to one
group and all male patients to
another group
Randomization
Recall bias
Awareness of
condition by
subjects changes their
recall of related risk
factors; common
in retrospective studies
Subjects recall a certain exposure
after finding out about others with
the same condition
↓
Time to followup in
retrospective
studies
(e.g., retrospectiv
e cohort
studies or casecontrol studies)
23
Information
bias
Incorrectly collected data
Insufficient information about
exposure and disease frequency
among subjects
Information is gathered differently
between the treatment and control
group
Reporting bias: selective disclosure
or suppression of information or
study results, resulting in
underreporting or overreporting of
exposure or outcome
Interviewer bias: Different
interviewing approaches towards
exposed and unexposed groups, or
cases and controls, prompt different
responses between groups and the
conclusion of systematic differences
between groups when there are
none.
Standardize data
collection
Cognitive bias
Tendency to favor
something because
of personal
beliefs or ideas
Response bias: study participants
do not respond truthfully or
accurately because of the manner in
which questions are phrased (e.g.,
leading questions) and/or the
possibility of more socially
acceptable answer options;
especially common in surveys
Observer bias (Experimenterexpectancy effect or Pygmalion
effect): measurement of a variable
or classification of subjects is
influenced by the experimenter's
knowledge or expectations
Confirmation bias: the tendency of
the investigator to include only
those results which support his/her
hypothesis and ignore the rest
Hawthorne effect: subject's change
their behavior once they
are aware that they are being
observed; especially relevant for
psychiatric research; difficult bias to
eliminate
Placebo and nocebo effects: effect
of the subject's
preconceptions/beliefs on the
outcome
Use of placebo
Researchers are
discrete about
their
observations
Prolong the time
of observation to
monitor longterm effects
Blinding
24
Lead-time bias
Lead time: the average
length of time
between detection of a
disease and the
predetermined outcome
Early detection of disease
is misinterpreted as incre
ased survival
Often discussed in the context of
cancer screening (USMLE tip: think
of this bias when you see “a new
screening test” for poor prognosis
diseases like lung or pancreatic
cancer).
Lead-time bias occurs when survival
times are chosen as an endpoint
of screening tests
Measure
the backend survival
Gold standard of
measuring scree
ning
test effectiveness
is to
use mortality
rates instead of
survival times
Length-time
bias
An apparent
improvement in the
duration of survival when
a terminal disease with
a long clinical course
(e.g., slow-growing tumor)
is screened.
Often discussed in the context of
cancer screening
Arrange patients
according
to severity of
disease
Surveillance
bias
An outcome (e.g., disease) Subjects who receive the trial
is diagnosed more
treatment are monitored more
frequently in a sample
frequently
group than in the general
population because of
increased testing and
monitoring.
Leads to falsely
high incidence and preval
ence rates
•
Comparing to an
unexposed contr
ol group with a
similar likelihood
of screening
Selecting an
outcome that is
possible in both
the exposed and
unexposed
group
Per-protocol vs intention-to-treat vs as-treated analysis:
25
o Per-protocol analysis compares treatment groups in a RCT by
including the analysis of those who were strictly adherent and
completed the protocol.
 Provides an estimate of the true effect of an intervention
assuming a perfect scenario. However, it overestimates the
effect of the intervention in a realistic clinical setting.
o Intention-to-treat analysis:
 Leads to a more conservative estimate of the effect of the
intervention; however, it closely mirrors the expected number
of dropouts in a real-life-situation, ITT analysis reflects the
expected effect of the intervention in a realistic clinical
setting.
o As-treated analysis:
 Compares the groups based on the actual treatment
received.
 Gauge the effectiveness of the treatment itself, with less
regard to potential confounders.
Latency period:
• Applied to both disease pathogenesis and exposure to risk modifiers.
• Exposure to risk factors and the initial steps in disease pathogenesis
sometimes occur years before clinical manifestations are evident.
• Exposure to risk modifiers may need to be continuous over a certain
period before influencing the outcome.
26
Statistical distribution
27
•
Outlier is defined as an extreme and unusual value observed in a dataset.
o Can affect the measures of central tendency. As well as the
measures of dispersion.
o Mean is sensitive to outliers and easily shifts towards them, especially
with a small sample size.
28
Hypothesis testing
•
•
•
•
•
Null hypothesis (H0): no difference between groups.
Alternative hypothesis (Ha): there is a difference between groups.
P value: compared to alpha to determine significance.
o When p is less than alpha  significant.
o It is the probability of the result being of chance alone.
Alpha: significance level (0.05).
The probability of a type II error (B) is the complement of statistical power
(1-B).
o Statistical power is the probability of rejecting a false null hypothesis.
29

Influenced by 4 interrelated factors:
• Sample size; larger sample size  greater power.
• Variability (standard deviation) of study outcome;
outcomes with a smaller variability  greater power.
• Effect size (difference between treatment groups;
larger effect size  greater power.
• Significance level (alpha; a); higher significance level
gives a study greater power.
30
•
Type I error and type II errors are inversely related to each other; one
increases and the other decreases.
31
Risk
•
Odds ratio:
o Interpretation:
32
•
•
•
•
 OR = 1  0% change in odds.
 OR = 2  increases odds by 100% and so on.
Relative risk is the risk of an outcome in an exposed group divided by the
risk of that outcome in the unexposed group.
o Used in cohort and experimental studies.
o Interpretation:
 If the RR is 1.0 (null value)  there is no association between
exposure and outcome (or disease).
 RR >1.0  increased risk of disease.
 RR <1.0  decreased risk of disease.
o Unadjusted (bivariate) RR: estimates association between a risk
factor and an outcome but does not account for the effect of
other variables, known as potential confounders on the outcome of
interest.
o Adjusted (multivariate): accounts for the potential confounders and
provides a better estimate of associations.
Attributable risk percentage:
o Percentage of disease in an exposed group that can be attributed
to the exposure.
o Also described as the percentage of disease in an exposed group
that could be prevented by eliminating the risk factor.
o Difference in risk of disease between an exposed group and a
nonexposed group divided by the risk of disease in the exposed
group.
Absolute risk is equivalent to the incidence rate (number of new cases per
population at risk in a given time period).
o Calculated as incidence/time.
 (number of new cases/number of people at risk)/follow-up
period.
Number needed to treat:
o Number of patients who need to be exposed to a treatment to
prevent 1 additional adverse outcome in a particular time period
compared with a different treatment or control, assuming the
treatment is beneficial.
o Consider the following questions when interpreting NNT:
 What is the baseline risk of patients in the study?
 What is the comparison group?
 What is the outcome?
 How long does the study last?
33
•
Number needed to harm:
o Number of people who must be exposed to a treatment to cause
harm to 1 person who otherwise would not have been harmed is
known as NNH.
o Calculated same as NNT but using ARI instead of ARR.
Receiver operating characteristic curve (ROC):
• Generated by plotting true-positive rate (sensitivity) against the falsepositive rate (1-specificity).
o Sensitivity: how well a test can screen for a disease. (SNNOUT)
o Specificity: how well a test can confirm the diagnosis. (SPPIN)
o Changing the cutoff point to increase the number of patients with
the disease who test positive will increase the true positive rate
(directly proportional to sensitivity) but it will also increase the
number of patients without the disease who test positive (increasing
FP, inversely proportional to specificity).
o Accuracy: proportion of true results out of all the results of a given
diagnostic test.
 Measured by the total area under the ROC curve.
 The closer the plotted curve approaches the left and top
borders, the more accurate the test.
o Ideal diagnostic test: 100% sensitive and specific  square line.
o A useless diagnostic test: inverse linear relationship between
sensitivity and specificity  straight line.
34
Hazard ratio:
• The measure of an effect of an intervention on an outcome (death/cure)
over a period of time. (time-to event survival outcome)
• Used in survival analysis.
• Formula:
o (a/(a+b))/(c/(c+d).
35
•
o Incident of outcome in exposed group/incidence of outcome in
unexposed group.
Interpretation:
o Hazard ratio <1  more likely to occur in control group.
o Hazard ratio >1  more likely to occur in treatment group.
o Close to 1  no relationship.
o Example:
 If a medication’s hazard ratio for an adverse event is 0.75;
since it is less than 1 then it is more likely to occur in the
control group, and the medication reduces the risk of event
by 1.0 – 0.75 = 0.25 (or 25%)
36
Confidence interval
C% confidence interval (CI) is a range of plausible values calculated from
sample data that captures the true population value with a C% confidence
level.
• A 90% confidence interval has a 90% confidence level and captures the
central 90% of the distribution.
• A 95% confidence interval has a 95% confidence level and captures the
central 95% of the distribution.
• A CI with a greater confidence level is always wider than CI with a lower
confidence level.
The null value of a CI for a difference in rates (proportions or percentages) is
always 0; CI that includes 0 is not statistically significant.
37
Increasing sample size would increase the study’s power and makes the CI
narrower.
38
Statistical methods
•
•
Qualitative variables: represent categories or groups.
o Type of treatment or blood type.
Quantitative variables: represent numerical values.
o Temperature or glucose level.
T test:
• Two sample t test:
o Employed to compare 2 means.
o The t statistic is obtained to calculate the p value.
ANOVA:
• Analysis of variance.
• Compares 3 or more means.
• A statistically significant anova indicates only that at least 1 group is
different from the rest.
39
Chi-square test:
• Appropriate for categorical ((high or normal) or (yes or no)) data and
proportions.
• Test is used when 2 groups are independent.
Z test:
• Used to compare 2 means, but population variances are employed in the
calculations.
• Limited capability.
Correlation coefficient:
• Assesses linear relationship between 2 variables.
o R <0  one variable increase, the other decreases.
o R >0  both variables increase or decrease together.
40
Linear regression analysis:
• Used to describe the association between:
o 1 quantitative dependent (outcome) variable.
o 1 or more quantitative independent (explanatory) variables.
• If the outcome is going to be measured by 2 different variables (for e.g.,
brain atrophy via ventricular volume and total brain volume)  2 different
regression models can be used.
Scatter plots:
• Useful for crude analysis of data.
• It can demonstrate the type of association.
Kaplan-Meier statistical method:
• Used in survival analysis to analyze time-to-event data (time from entry
into a study until an event of interest).
• This method takes into account that any potential event may occur at
different points in time for different study participants  thus it compares
the rate at which these events occur during the entire study period rather
than at the end of the study only.
41
•
•
KM curve depicts the probability of survival at various time points during
the study, calculated based on the proportion of subjects who are alive
at different times.
Long-rank test is the statistical test that compares KM survival curves.
42
Drug advertisements
What to review:
• Hazard rate: chance of an event occurring in one of the study groups
during a set period.
• Hazard ratio: chance of an event occurring in the treatment group
compared to the chance of that event occurring in the control group
during a set period.
o Hazard ratio <1  more likely to occur in control group.
o Hazard ratio >1  more likely to occur in treatment group.
o Close to 1  little difference between groups.
43
Ethics
Informed consent:
•
•
There should be no conflict of interest when recommending a certain
management.
Presumed not obtained in emergency situations.
44
•
•
•
•
•
•
o Informed refusal is the negative corollary of informed consent; if
appropriately informed, patients with decision-making capacity
can refuse life-saving treatment.
No informed consent is required in the setting of extension of procedure if
an unexpected complication arises that requires immediate treatment.
Assent agreement with treatment; is obtained from a minor. Not
informed consent.
If there is only 1 medically reasonable treatment option  directive
counseling (single treatment option is recommended to the patient).
If parents refused nonurgent life-saving treatment for a child (e.g.,
treatment of ALL) seek a court order.
Two-physician consent is used only when a patient is incapacitated and
there is no living will or surrogate available to make decisions for the
patient.
For divorced parents  only parents with custody may give consent for
medical care.
o If joint custody  only one parent is necessary.
Decision making capacity:
•
Psychiatry patients who have severe delusions related to the medical
condition, disorganization, or cognitive impairment may lack capacity
and require a surrogate decision maker.
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Surrogate decision making:
• The hierarchy of decision making:
o The mentally competent patient.
o Advance directives:
 Durable medical power of attorney.
 Living will:
• Form of written advanced directive.
• Specifies a patient’s wishes for healthcare in advance
of losing the ability to communicate or of becoming
incapable of making his or her own decisions.
• Protects the patient’s autonomy and overrules the
wishes of any family members.
• If no living will  family meeting  they don’t agree 
ethics committee.
 POA can override living will if it is more consistent with the
patient’s recent wishes.
o Next of kin:
1. Spouse.
2. Adult child.
3. Parents.
4. Adult sibling.
o Ethics committee or legal consult.
Substituted judgement:
• In the absence of advance directives.
• Surrogate decision-maker to make medical decisions based on his or her
understanding of what the patient would have wanted if she had
capacity and was faced with the specific decision.
Against medical advice:
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Gifts:
• Case-by-case basis.
• No absolute prohibition on accepting gifts.
• Consider multiple factors: cost, type, and timing of the gift; the apparent
motivation behind giving it; and the nature and longevity of the physicianpatient relationship.
o Gifts that are clearly extravagant, inappropriately intimate, or given
to secure preferential treatment should not be accepted.
• Pharmaceutical and medical device companies:
o Gifts can influence a physician’s prescriptions or practices, even on
a subconscious level.
o AMA guidelines suggest accepting nonmonetary gifts from
interested parties only if the gifts directly benefit patient care and
are of small monetary value (educational materials, drug samples)
Conscientious refusal:
• When a provider refuses to provide care because doing so would conflict
with the provider’s beliefs.
• Provider conscience does not take precedence over other ethical
principles.
• Obligated to refer patients in a timely manner if they are unable to
provide care.
Medical records:
• Patients have the legal right to obtain a copy (not the original) of their
medical records.
• Cannot be released to anyone else without the patient’s authorization;
except when directed by a written court order.
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•
•
Under HIPAA, a facility or physician has 30 days to provide the patients or
the patient’s representative with a copy of the requested medical
records.
If physician should disclose information  only the minimum amount to
respond to specific request “minimum necessary disclosure”.
Physician-patient relationship:
• Respond politely but firmly to inappropriate patient requests; set limits and
establish clear professional boundaries.
Refusing treatment:
• Health Care Consent Act has been applied to Jehovah’s witnesses to
allow transfusion to preserve a patient’s life in an emergency when no
blood refusal card is present.
• Contagious disease  isolation until the patient no longer poses a risk on
others.
• Patients admitted under the involuntary status have the right to refuse
treatment for a non-life-threatening injury.
Physician-assisted suicide:
• Physician helps competent patients voluntarily end their lives when faced
with end-of-life suffering.
• Providing medication, a prescription, or information to a patient with the
understanding that the patient intends to use it to a commit suicide,
• Euthanasia: physician administers lethal medication. ILLEGAL.
• Approach to patient:
o Explore the reasons for the request.
o Discuss palliative care options.
 Adequate pain control, psychologic support, comfort care,
and appropriate MDT referrals.
Counseling patients in clinical uncertainty:
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Delivering bad information: (SPIKES protocol)
• Face-to-face visit in a comfortable private setting.
• Provide empathy and emotional support.
• Assess the patient’s understanding of the condition and how much the
patient wants to know.
• Gaining an understanding of cultural/educational/religious issues.
• Making medical information understandable.
• Formulating a collaborative treatment plan.
Newly deceased patients used for training purposes:
• Obtain permission from the family (or the patient prior to death) before
the student performs the procedures.
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•
Performed under close supervision as part of a structured training
sequence.
Toxicology:
• Involuntary toxicology screening is reserved for emergency care or for
those who lack decision-making capacity.
• Approach to parents wanting an involuntary screen:
o Acknowledge the parents’ concern.
o Ask for more detailed descriptions of behavioral changes or any
other evidence of substance use.
o Explaining that substance use problems can usually be detected by
establishing a trusting relationship with the patient and taking a
careful history.
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Genetics
Inheritance:
• X-linked recessive:
o Possibility of child getting the disease:
 0.5(chance of male) x 0.5(chance of getting faulty X).
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Patient safety
Medical error:
• Sources:
o Transition of care between inpatient and outpatient and between
units within inpatient facilities.
 Specifically, continuity of care for medications.
• Medication reconciliation (process of reviewing and
updating a patient’s medication regimen);
o Errors due to medication reconciliation: omitting
active medications, including outdated
prescriptions, and recording incorrect
medication data.
o Solutions:
 Multiple care team members should verify
medications independently with the
patient (redundancy).
• Active direct conversation with the
patient (when cognitively intact);
address both prescription and
nonprescription medications +
inspection of medication bottles.
• Interprofessional review: physicians,
nurses, pharmacists; independently.
 Brief review by the ordering physician prior
to placing or renewing medication orders.
 Loss to follow-up after hospital discharge when an unrelated
finding is found incidentally such as a lung or adrenal nodule.
• Solution: timely (<4 weeks) primary care follow-up
promotes completion of necessary studies. Patients
should receive high-quality provider communication
and counseling explaining the importance of follow up.
o Failed communication:
 Poor communication between medical personnel.
 Failure to review medical records.
 Failure to adequately communicate with the patient/and or
patient family.
• High-quality communication:
o Face-to-face discourse, allowing response to
nonverbal cues.
o Patient-centered interaction tailored to the
patient’s current motivations, goals, and ability.
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o Interactive approaches for verifying patient
understanding.
 Lack of standardized terminology or the use of jargon.
o Patient handoff: process of transferring responsibility for medical
care.
o Signout: process of transmitting information about the patient and
needed follow-up care.
 Both handoff and signout are sources of adverse clinical
events; such as near misses, escalation in care, inefficiencies
in care, and delays in diagnosis or treatment.
 Solution:
• Implement a systemic signout process that includes
checklists to improve efficacy and accuracy.
o Includes: DNR/DNI status, hospital course, recent
events, current condition, and anticipatory
information.
o Protocols requiring separate documentation of
cross-coverage patient events can prevent errors
related to omitted information during signout.
 This approach introduces redundancy to
verbal signout.
o Specific action plans in lieu of vague directions
(don’t just write “follow up potassium”).
o Quiet environment to minimize distractions.
o Closed-loop communications.
o Paper-based systems:
 Medication orders are handwritten.
 Do not use trailing zeros.
 Solution: computerized provider order entry systems (CPOE)
systems which are combined with clinical decision support
system.
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Adverse event:
• Unintended consequences of medical management that are not related
to the patient’s underlying disease.
• Can be preventable or nonpreventable.
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Medical error:
• Systems error: medical errors resulting from a series of actions and/or
factors rather than human error.
• Individual error: medical error resulting from the failure of a single
healthcare professional due to negligence.
• Accidental failure: perform an action as intended or accidently
performing the incorrect action.
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56
•
Cognitive bias:
o Up to 70% of diagnostic errors.
o Due to overdependence on heuristics (mental shortcuts).
o Anchoring bias minimized by:
 Enhancing clinician awareness (morbidity and mortality
review).
 Providing training (simulated cases illustrating biased thinking).
 Optimizing organization and workplace factors (limiting
distractions).
o Solution:
 Metacognition: process of understanding and self-monitoring
potentially flawed cognitive pattern and biases.
• Promoted using morbidity and mortality conferences
and practicing diagnostic time-out.
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Medical malpractice:
• Negligence: failure to perform an action with the skill, care, and
knowledge expected of a healthcare provider under reasonable
circumstances.
Never event:
•
•
•
JCI developed the term sentinel event while the term never event was developed by the
Agency for Healthcare Research & Quality.
Adverse events that are unambiguous, serious, and usually preventable.
o Examples:
 Unintentionally leaving a foreign object in a patient’s body
following surgical intervention.
 Wrong-site surgery.
 Wrong-patient error.
 Patient death/serious injury due to contaminated
drugs/device/biologics supplied by a healthcare facility.
 Patient suicide during hospitalization.
 Patient death/serious injury due to the administration of the
wrong medication.
Hospital should perform a root cause analysis.
o Suboptimal teamwork is a leading cause.
Near miss:
• Unintended medical error that could have resulted in an adverse event.
Latent error:
• Error due to a system design that predisposes people working in the
system to make mistakes. (i.e., inefficient protocols)
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Violation:
• Deliberate deviation from standards, law, or rules, which could potentially
result in harm to the patient.
Hospice care:
•
Goal of patient care in terminal illness include preserving patient
autonomy and prioritizing patient comfort.
o Voluntarily stopping of eating & drinking (VSED):
 Confirm that the patient is cognitively intact and that the
request is voluntary and not influenced by mental illness.
 Counsel the patients about possible consequences, including
severe thirst and associated discomfort.
 Discuss alternatives to VSED.
 Discuss and clearly record the patient’s preferences for
managing discomfort (e.g., small sips of fluid, oral swabbing,
ice chips) because delirium and cognitive impairment may
occur.
Aftermath of a mistake:
59
•
Admit the mistake, especially under the following circumstances:
o Actual patient harm.
o Clear or potential clinical significance.
o An unwanted treatment, device, or substance reaching the
patient.
o An unanticipated outcome.
o An unexpected safety event.
Complementary and alternative medicine (CAM):
• Initial response to a patient requesting an alternative approach is to
explore the reasons for requesting a different treatment.
• Afterwards, discuss risk and benefits of proposed CAM.
PDSA (study) and PDCA (check) paradigms:
Medical error analysis:
• Failure mode and effects analysis:
o Prospective process.
o First step: assemble a multidisciplinary team, define the topic,
describe the processes within each topic.
o Failure modes: all the things that could go wrong in each process.
o Hazard analysis to identify and document:
 Any possible effects of each of the failure modes.
 Any potential causes of each of the failure modes.
o For each failure mode, an action plan should be developed to
address it if it occurs.
• Control charts:
o Plot the data of a variable over time along with upper and lower
control limits within which the variable should be located. Variables
that consistently fall outside the upper control limit  a potential
problem that should be addressed.
• Root cause analysis:
o Retrospective approach.
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Human factors engineering strategies:
•
Transgenders:
o Addressing the incorrect pronoun or name can be corrected by
redesigning physical systems to improve visibility of key patient
information.
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Effective teams:
•
Suboptimal team dynamics can be improved through teamwork training,
including communication and mentorship, and promotion of safety
culture.
o Teamwork simulation with teams practicing communication skills
during simulated patient scenarios.
o Safety debriefings consisting of collaborative, team-based
discussion of patient safety risks and concerns.
o Development of evaluation metrics rewarding members who
identify errors and safety risks.
Healthcare quality:
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Run charts:
• Longitudinal graph that tracks a process performance outcome over
time.
• Frequently used to:
o Visually identify performance variations, including trends, defined as
consistent directional change (increase or decrease) for 5 or more
consecutive points.
o Assess effectiveness of a quality improvement intervention by
comparing changes in process outcomes pre- and postintervention.
Major insurance plans:
Behavioral interventions for weight loss:
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Reducing antibiotic use in URI & acute bronchitis:
Hand hygiene:
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•
•
According to the CDC, preferred hand hygiene method in most clinical
settings is antiseptic hand rub.
o All hand surfaces should be covered and rubbed until dry.
if hands are visibly soiled or exposure to spores (C. diff) is suspected, hand
should be washed with soap and water for 20 seconds.
Patient safety procedures in the surgical setting:
Home health care:
Readmissions:
• Used as a quality-of-care metric because they are often preventable and
increase costs and patient morbidity.
• Patients with chronic conditions are at highest readmission risk, given their
vulnerability to rapid deterioration and complex medication regimens
that often necessitate frequent monitoring.
• Solution: improve follow-up & communication with patients, including
telephone follow-up shortly after discharge.
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o This intervention improves patient engagement, identification of
new symptoms, enabling early management before sequelae
develop, care coordination.
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