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. 45 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: 46 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. 47 • • 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: 48 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. 49 • 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. 50 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). 51 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. 52 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. 53 Adverse event: • Unintended consequences of medical management that are not related to the patient’s underlying disease. • Can be preventable or nonpreventable. 54 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. 55 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. 57 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) 58 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. 60 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. 61 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: 62 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: 63 Reducing antibiotic use in URI & acute bronchitis: Hand hygiene: 64 • • 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. 65 o This intervention improves patient engagement, identification of new symptoms, enabling early management before sequelae develop, care coordination. 66