Public health sciences Flashcards
Cross-sectional study
Frequency of disease and frequency of risk-related factors are assessed in the present. Asks, “What is happening?”
measures
Disease prevalence. Can show risk factor association with disease, but does not establish causality
Case-control study
Compares a group of people with disease to a group without disease. Looks to see if odds of prior exposure or risk factor differs by disease state. Asks, “What happened?”
measures
Odds ratio (OR). Patients with COPD had higher odds of a smoking history than those without COPD.
Cohort study
Compares a group with a given exposure or risk factor to a group without such exposure. Looks to see if exposure or risk factor is associated with later development of disease. Can be prospective (asks, “Who will develop disease?”) or retrospective (asks, “Who developed the disease [exposed vs nonexposed]?”).
measures
Relative risk (RR). Smokers had a higher risk of developing COPD than nonsmokers.
Twin concordance study
Compares the frequency with which both monozygotic twins vs both dizygotic twins develop the same disease.
measues
Measures heritability and influence of environmental factors (“nature vs nurture”).
Adoption study
Compares siblings raised by biological vs adoptive parents.
measures
Measures heritability and influence of environmental factors.
Clinical trial
Experimental study involving humans. Compares therapeutic benefits of 2 or more treatments, or of treatment and placebo. Study quality improves when study is randomized, controlled, and double-blinded (ie, neither patient nor doctor knows whether the patient is in the treatment or control group). Triple-blind refers to the additional blinding of the researchers analyzing the data. Four phases (“Does the drug SWIM?”).
Phase I
Small number of healthy volunteers or patients with disease of interest.
purpose
“Is it Safe?” Assesses safety, toxicity, pharmacokinetics, and pharmacodynamics
Phase II
Moderate number of patients with disease of interest.
purpose
“Does it Work?” Assesses treatment efficacy, optimal dosing, and adverse effects
Phase III
Large number of patients randomly assigned either to the treatment under investigation or to the best available treatment (or placebo)
purpose
“Is it as good or better?” Compares the new treatment to the current standard of care (any Improvement?)
Phase IV
Postmarketing surveillance of patients after treatment is approved.
purpose
Can it stay?” Detects rare or long-term adverse effects. Can result in treatment being withdrawn from Market.
Evaluation of diagnostic tests
Uses 2 × 2 table comparing test results with the actual presence of disease. Sensitivity and specificity are fixed properties of a test. PPV and NPV vary depending on disease prevalence in population being tested.
Sensitivity (true-positive rate)
Proportion of all people with disease who test positive, or the probability that when the disease is present, the test is positive. Value approaching 100% is desirable for ruling out disease and indicates a low false-negative rate. High sensitivity test used for screening in diseases with low prevalence.
= TP / (TP + FN) = 1 – FN rate
SN-N-OUT = highly SeNsitive test, when Negative, rules OUT disease If sensitivity is 100%, then FN is zero. So, all negatives must be TNs.
Specificity (truenegative rate)
Proportion of all people without disease who test negative, or the probability that when the disease is absent, the test is negative. Value approaching 100% is desirable for ruling in disease and indicates a low false-positive rate. High specificity test used for confirmation after a positive screening test.
= TN / (TN + FP) = 1 – FP rate
SP-P-IN = highly SPecific test, when Positive, rules IN disease If specificity is 100%, then FP is zero. So, all positives must be TPs.
Positive predictive value
Probability that a person who has a positive test result actually has the disease.
PPV = TP / (TP + FP)
PPV varies directly with pretest probability (baseline risk, such as prevalence of disease): high pretest probability high PPV
Negative predictive value
Probability that a person with a negative test result actually does not have the disease.
NPV = TN / (TN + FN)
NPV varies inversely with prevalence or pretest probability
Likelihood ratio
Likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without the target disorder.
LR+ > 10 and/or LR– < 0.1 indicate a very useful diagnostic test. LRs can be multiplied with pretest odds of disease to estimate posttest odds.
LR+ = sensitivity / 1 – specificity = TP rate/FP rate
LR– = 1 – sensitivity/ specificity = FN rate/TN rate
Odds ratio
Typically used in case-control studies. OR depicts the odds of a certain exposure given an event (eg, disease; a/c) vs the odds of exposure in the absence of that event (eg, no disease; b/d).
Relative risk
Typically used in cohort studies. Risk of developing disease in the exposed group divided by risk in the unexposed group (eg, if 5/10 people exposed to radiation get cancer, and 1/10 people not exposed to radiation get cancer, the relative risk is 5, indicating a 5 times greater risk of cancer in the exposed than unexposed). For rare diseases (low prevalence), OR approximates RR.
RR = 1 –> no association between exposure and disease.
RR > 1 –> exposure associated with increased disease occurrence.
RR < 1 –> exposure associated with decreased disease occurrence.
Absolute risk reduction
The difference in risk (not the proportion) attributable to the intervention as compared to a control (eg, if 8% of people who receive a placebo vaccine develop the flu vs 2% of people who receive a flu vaccine,
then ARR = 8% − 2% = 6% = .06)
Attributable risk
The difference in risk between exposed and unexposed groups (eg, if risk of lung cancer in smokers is 21% and risk in nonsmokers is 1%,
then the attributable risk is 20%).
Relative risk reduction
The proportion of risk reduction attributable to the intervention as compared to a control (eg, if 2% of patients who receive a flu shot develop the flu, while 8% of unvaccinated patients develop the flu,
then RR = 2/8 = 0.25, and RRR = 0.75).
Number needed to treat
Number of patients who need to be treated for 1 patient to benefit. Lower number = better treatment.
Number needed to harm
Number of patients who need to be exposed to a risk factor for 1 patient to be harmed. Higher number = safer exposure
Incidence = # of new cases/ # of people at risk
(during a specified time period)
Prevalence = # of existing cases/Total # of people
(at a point in time)
Prevalence/ 1 – prevalence = Incidence rate × average duration of disease
Prevalence ≈ incidence for short duration disease (eg, common cold).
Prevalence > incidence for chronic diseases, due to large # of existing cases (eg, diabetes).
Prevalence ∼ pretest probability. increased prevalence –> increased prevalence–> increased PPV and decreased NPV
Precision (reliability)
The consistency and reproducibility of a test. The absence of random variation in a test.
Random error decreased precision in a test.
increased precision –> decresed standard deviation.
increased precision –> increased statistical power (1 − β).
Accuracy (validity)
The trueness of test measurements. The absence of systematic error or bias in a test
Systematic error decreased accuracy in a test.
Selection bias
Recruiting participants
definition
Nonrandom sampling or treatment allocation of subjects such that study population is not representative of target population. Most commonly a sampling bias.
examples
Berkson bias—study population selected from hospital is less healthy than general population
Non-response bias— participating subjects differ from nonrespondents in meaningful ways
strategies
Randomization
Ensure the choice of the right comparison/reference group
Recall bias
definiton: Awareness of disorder alters recall by subjects; common in retrospective studies
examples: Patients with disease recall exposure after learning of similar cases
strategies: Decrease time from exposure to follow-up
Measurement bias
definition: Information is gathered in a systemically distorted manner.
Example: Association between HTN and MI not observed when using faulty automatic sphygmomanometer Hawthorne effect—participants change behavior upon awareness of being observed
strategies: Use objective, standardized, and previously tested methods of data collection that are planned ahead of time Use placebo group
Procedure bias
defintion: Subjects in different groups are not treated the same.
Example: Patients in treatment group spend more time in highly specialized hospital units
Observer-expectancy bias
definition: Researcher’s belief in the efficacy of a treatment changes the outcome of that treatment (aka, Pygmalion effect).
examples: An observer expecting treatment group to show signs of recovery is more likely to document positive outcomes
both strategies for procedure and observer-expectancy: Blinding and use of placebo reduce influence of participants and researchers on procedures and interpretation of outcomes as neither are aware of group allocation
Confounding bias
definition: When a factor is related to both the exposure and outcome, but not on the causal pathway, it distorts or confuses effect of exposure on outcome. Contrast with effect modification.
examples: Pulmonary disease is more common in coal workers than the general population; however, people who work in coal mines also smoke more frequently than the general population
Strategies: Multiple/repeated studies Crossover studies (subjects act as their own controls) Matching (patients with similar characteristics in both treatment and control groups)
Lead-time bias
Definition: Early detection is confused with increased survival.
example: Early detection makes it seem like survival has increased, but the disease’s natural history has not changed
Strategies: Measure “back-end” survival (adjust survival according to the severity of disease at the time of diagnosis)
Length-time bias
Definition: Screening test detects diseases with long latency period, while those with shorter latency period become symptomatic earlier.
Example: A slowly progressive cancer is more likely detected by a screening test than a rapidly progressive cancer
Strategies: A randomized controlled trial assigning subjects to the screening program or to no screening
Statistical distribution
Measures of central tendency
Mean = (sum of values)/(total number of values). Most affected by outliers (extreme values).
Median = middle value of a list of data sorted from least to greatest. If there is an even number of values, the median will be the average of the middle two values.
Mode = most common value. Least affected by outliers.
Measures of dispersion
Standard deviation = how much variability exists in a set of values, around the mean of these values.
Standard error = an estimate of how much variability exists in a (theoretical) set of sample means around the true population mean.
Normal distribution
Gaussian, also called bell-shaped. Mean = median = mode.
Nonnormal distributions
Bimodal-Suggests two different populations (eg, metabolic polymorphism such as fast vs slow acetylators; age at onset of Hodgkin lymphoma; suicide rate by age).
Positive skew-Typically, mean > median > mode. Asymmetry with longer tail on right.
Negative skew-Typically, mean < median < mode. Asymmetry with longer tail on left
Statistical hypotheses
Null (H0)-Hypothesis of no difference or relationship (eg, there is no association between the disease and the risk factor in the population).
Alternative (H1)-Hypothesis of some difference or relationship (eg, there is some association between the disease and the risk factor in the population).
Type I error (α)
Stating that there is an effect or difference when none exists (null hypothesis incorrectly rejected in favor of alternative hypothesis). α is the probability of making a type I error. p is judged against a preset α level of significance (usually 0.05). If p < 0.05, then there is less than a 5% chance that the data will show something that is not really there
Also known as false-positive error.
α = you accused an innocent man. You can never “prove” the alternate hypothesis, but you can reject the null hypothesis as being very unlikely.
Type II error (β)
Stating that there is not an effect or difference when one exists (null hypothesis is not rejected when it is in fact false). β is the probability of making a type II error. β is related to statistical power (1 – β), which is the probability of rejecting the null hypothesis when it is false.
incresaed power and decreased β by:
increased sample size
increased expected effect size
increased precision of measurement
Also known as false-negative error.
β = you blindly let the guilty man go free. If you increased sample size, you increased power. There is power in numbers.
Confidence interval
Range of values within which the true mean of the population is expected to fall, with a specified probability.
CI for sample mean = x¯ ± Z(SE)
The 95% CI (corresponding to α = .05) is often used.
For the 95% CI, Z = 1.96.
For the 99% CI, Z = 2.58.
If the 95% CI for a mean difference between 2 variables includes 0, then there is no significant difference and H0 is not rejected. If the 95% CI for odds ratio or relative risk includes 1, H0 is not rejected. If the CIs between 2 groups do not overlap –> statistically significant difference exists. If the CIs between 2 groups overlap –> usually no significant difference exists.
Meta-analysis
A method of statistical analysis that pools summary data (eg, means, RRs) from multiple studies for a more precise estimate of the size of an effect. Also estimates heterogeneity of effect sizes between studies.
Improves strength of evidence and generalizability of study findings. Limited by quality of individual studies and bias in study selection.
t-test-Checks differences between means of 2 groups
Example: comparing the mean blood pressure between men and women
ANOVA-Checks differences between means of 3 or more groups.
Example: comparing the mean blood pressure between members of 3 different ethnic groups
Chi-square (χ²)-Checks differences between 2 or more percentages or proportions of categorical outcomes (not mean values).
Example: comparing the percentage of members of 3 different ethnic groups who have essential hypertension.
Core ethical principles
Autonomy-Obligation to respect patients as individuals (truth-telling, confidentiality), to create conditions necessary for autonomous choice (informed consent), and to honor their preference in accepting or not accepting medical care.
Beneficence-Physicians have a special ethical (fiduciary) duty to act in the patient’s best interest. May conflict with autonomy (an informed patient has the right to decide) or what is best for society (eg, mandatory TB treatment). Traditionally, patient interest supersedes.
Nonmaleficence-“Do no harm.” Must be balanced against beneficence; if the benefits outweigh the risks, a patient may make an informed decision to proceed (most surgeries and medications fall into this category).
Justice-To treat persons fairly and equitably. This does not always imply equally (eg, triage).
Informed consent
A process (not just a document/signature) that requires:
Disclosure: discussion of pertinent information
Understanding: ability to comprehend
Capacity: ability to reason and make one’s own decisions (distinct from competence, a legal determination)
Voluntariness: freedom from coercion and manipulation
Patients must have an intelligent understanding of their diagnosis and the risks/benefits of proposed treatment and alternative options, including no treatment.
Patient must be informed that he or she can revoke written consent at any time, even orally
Exceptions to informed consent (WIPE it away):
Waiver—patient explicitly waives the right of informed consent
Legally Incompetent—patient lacks decisionmaking capacity (obtain consent from legal surrogate)
Therapeutic Privilege—withholding information when disclosure would severely harm the patient or undermine informed decision-making capacity
Emergency situation—implied consent may apply
Consent for minors
A minor is generally any person < 18 years old. Parental consent laws in relation to healthcare vary by state. In general, parental consent should be obtained, but exceptions exist for emergency treatment (eg, blood transfusions) or if minor is legally emancipated (eg, married, self supporting, or in the military).
Situations in which parental consent is usually not required:
Sex (contraception, STIs, pregnancy)
Drugs (substance abuse)
Rock and roll (emergency/trauma)
Physicians should always encourage healthy minor-guardian communication.
Physician should seek a minor’s assent even if their consent is not required.
Decision-making capacity
Physician must determine whether the patient is psychologically and legally capable of making a particular healthcare decision. Note that decisions made with capacity cannot be revoked simply if the patient later loses capacity.
Capacity is determined by a physician for a specific healthcare-related decision (eg, to refuse medical care). Competency is determined by a judge and usually refers to more global categories of decision making (eg, legally unable to make any healthcare-related decision).
Components (think GIEMSA):
Decision is consistent with patient’s values and Goals Patient is Informed (knows and understands)
Patient Expresses a choice
Decision is not a result of altered Mental status (eg, delirium, psychosis, intoxication), Mood disorder
Decision remains Stable over time
Patient is ≥ 18 years of Age or otherwise legally emancipated
Advance directives
Oral advance directive-Incapacitated patient’s prior oral statements commonly used as guide. Problems arise from variance in interpretation. If patient was informed, directive was specific, patient made a choice, and decision was repeated over time to multiple people, then the oral directive is more valid.
Written advance directive-Specifies specific healthcare interventions that a patient anticipates he or she would accept or reject during treatment for a critical or life-threatening illness. A living will is an example.
Medical power of attorney-Patient designates an agent to make medical decisions in the event that he/she loses decisionmaking capacity. Patient may also specify decisions in clinical situations. Can be revoked by patient if decision-making capacity is intact. More flexible than a living will.
Do not resuscitate order-DNR order prohibits cardiopulmonary resuscitation (CPR). Other resuscitative measures that may follow (eg, intubation) are also typically avoided.
Confidentiality
Confidentiality respects patient privacy and autonomy. If the patient is incapacitated or the situation is emergent, disclosing information to family and friends should be guided by professional judgment of patient’s best interest. The patient may voluntarily waive the right to confidentiality (eg, insurance company request).
General principles for exceptions to confidentiality:
Potential physical harm to others is serious and imminent
Likelihood of harm to self is great
No alternative means exist to warn or to protect those at risk
Physicians can take steps to prevent harm
Examples of exceptions to patient confidentiality (many are state-specific) include the following (“The physician’s good judgment SAVED the day”):
Suicidal/homicidal patients
Abuse (children, elderly, and/or prisoners)
Duty to protect—State-specific laws that sometimes allow physician to inform or somehow protect potential Victim from harm.
Epileptic patients and other impaired automobile drivers.
Reportable Diseases (eg, STIs, hepatitis, food poisoning); physicians may have a duty to warn public officials, who will then notify people at risk. Dangerous communicable diseases, such as TB or Ebola, may require involuntary treatment.
Car seats for children
Children should ride in rear-facing car seats until they are 2 years old and in car seats with a harness until they are 4 years. Older children should use a booster seat until they are 8 years old or until the seat belt fits properly. Children < 12 years old should not ride in a seat with a frontfacing airbag.
Changes in the elderly
Sexual changes:
Men—slower erection/ejaculation, longer refractory period.
Women—vaginal shortening, thinning, and dryness.
Sleep patterns: decreased REM and slow-wave sleep; increased sleep onset latency;
increased early awakenings.
increased suicide rate.
decreased vision and hearing.
decreased immune response.
decreased renal, pulmonary, and GI function.
decreased muscle mass,
increased fat.
Intelligence does not decrease.
Disease prevention
Primary disease prevention-Prevent disease before it occurs (eg, HPV vaccination)
Secondary disease prevention-Screen early for and manage existing but asymptomatic disease (eg, Pap smear for cervical cancer)
Tertiary disease prevention-Treatment to reduce complications from disease that is ongoing or has long-term effects (eg, chemotherapy)
Quaternary disease prevention-Identifying patients at risk of unnecessary treatment, protecting from the harm of new interventions (eg, electronic sharing of patient records to avoid duplicating recent imaging studies)
Healthcare payment models
Bundled payment-Healthcare organization receives a set amount per service, regardless of ultimate cost, to be divided among all providers and facilities involved.
Capitation-Physicians receive a set amount per patient assigned to them per period of time, regardless of how much the patient uses the healthcare system. Used by some HMOs.
Discounted fee-for-service-Patient pays for each individual service at a discounted rate predetermined by providers and payers (eg, PPOs).
Fee-for-service-Patient pays for each individual service.
Global payment-Patient pays for all expenses associated with a single incident of care with a single payment. Most commonly used during elective surgeries, as it covers the cost of surgery as well as the necessary pre- and postoperative visits.
Medicare and Medicaid
Medicare and Medicaid—federal social healthcare programs that originated from amendments to the Social Security Act.
Medicare is available to patients ≥ 65 years old, < 65 with certain disabilities, and those with end-stage renal disease.
Medicaid is joint federal and state health assistance for people with limited income and/ or resources.
The 4 parts of Medicare:
Part A: HospitAl insurance, home hospice care
Part B: Basic medical bills (eg, doctor’s fees, diagnostic testing)
Part C: (parts A + B = Combo) delivered by approved private companies
Part D: Prescription Drugs
Hospice care
Medical care focused on providing comfort and palliation instead of definitive cure. Available to patients on Medicare or Medicaid and in most private insurance plans whose life expectancy is < 6 months
During end-of-life care, priority is given to improving the patient’s comfort and relieving pain (often includes opioid, sedative, or anxiolytic medications). Facilitating comfort is prioritized over potential side effects (eg, respiratory depression). This prioritization of positive effects over negative effects is known as the principle of double effect.
1: <1yo: Congenital malformations 1-14yo: Unintentional injury 15-34 yo: Unintentional injury 35-44 yo: Unintentional injury 45-64 yo: Cancer 65+: Heart disease
common causes of death (US) by age
1 medicare: Congestive HF Medicaid: Mood disorders private insurance: Maintenance of chemotherapy or radiotherapy uninsured: Mood disorders
Hospitalized conditions with frequent readmissions
Swiss cheese model
Focuses on systems and conditions rather than an individual’s error. The risk of a threat becoming a reality is mitigated by differing layers and types of defenses. Patient harm can occur despite multiple safeguards when “the holes in the cheese line up.”
types of medical errors
May involve patient identification, diagnosis, monitoring, nosocomial infection, medications, procedures, devices, documentation, handoffs. Medical errors should be disclosed to patients, independent of immediate outcome (harmful or not).
Active error
Occurs at level of frontline operator (eg, wrong IV pump dose programmed).
Immediate impact.
Latent error
Occurs in processes indirect from operator but impacts patient care (eg, different types of IV pumps used within same hospital).
Accident waiting to happen.
Medical error analysis
Root cause analysis
design: Retrospective approach. Applied after failure event to prevent recurrence.
Method: Uses records and participant interviews to identify all the underlying problems (eg, process, people, environment, equipment, materials, management) that led to an error
Failure mode and effects analysis
Design: Forward-looking approach. Applied before process implementation to prevent failure occurrence.
Methods: Uses inductive reasoning to identify all the ways a process might fail and prioritizes them by their probability of occurrence and impact on patients.
