Test 1 Flashcards
population health
the outcomes of groups of people; socio-ecological framework; geographical; why are some ppl healthy and others not
population management
claims and beneficiary management; clinical integration, analytics, care coordination; reporting and measuring
population medicine
concerned with how care is designed, delivered and paid for to try and reach the triple aim aka high quality, cost effective, accessible health care for a defined patient population
medical model
focuses on individual, explores patho, attempts to find a cure, views risk factors of diseases, considers biology
public health model
focuses on populations, disease prevention and health promotion, views risk factors in terms of an individual social and ecological environment in addition to genetic make up, considers how political, economical, social, ecological and regulatory systems interact, proactive, well or preventative care
population health model
policies and programs; health factors (physical environment, social and economical factors, clinical care, health behaviors), health outcomes (length of life and quality of life)
synergistic approaches that integrate clinical and population models
accountable care organizations, patient centered medical homes, health ppl 2020, leading health indicators
what is healthy ppl 2020
national agenda that communicates a vision for improving health and achieving health equity; grounded in science and data used for developing health budgets and allocating resources to achieving national health priorities
goals of heathy ppl 2020
attain higher-quality, longer lives free of preventable diseases, disability, injury, premature death; achieve health equity, eliminate disparities, and improve the health of all groups, create social and physical environments that promote good health for all, promote quality of life, healthy development, and healthy behaviors across all life stages
leading health indicators
a subset of healthy ppl measures, critical health issues that will dramatically reduce the leading cause of preventable deaths and illnesses, intended to motivate action and improve health of the entire population
practice guidelines
statements that include recommendations intended to optimize patient care that are informed by a systematic review o evidence and an assessment of the benefits with alternative care options; directions of principles presenting current or future rules of policy for assisting health care practitioners in patient care decisions regarding diagnosis therapy or related clinical circumstances
why are practice guidelines needed
to improve quality of healthcare (encouraging appropriate use of therapies), provide direction for disease state treatment based upon available evidence; reduce professional liability, identify alternative treatments, provide consistent treatment across environments, decrease costs
how are practice guidelines developed
a topic is identified for publication (high prevalence, high frequency / severity of associated morbidity or mortality, high quality evidence for the efficacy of treatments that reduce morbidity and mortality, feasibility of implementation of the treatment based on expertise and other resources required, potential cost effectiveness, evidence that current practice is not optimal, availability of personnel, expertise, and resources to develop and implement the practice guideline); solicitation of individual group or organization to draft a guideline, define the clinical question, determine criteria, systematic literature analysis conducted, synthesis of evidence, consensus, grade recommendations, draft and review panels evaluate draft, approval of practice guidelines, revise, create tools for implementation
level 1 practice guideline
systematic review or meta analysis of all randomized controlled trials or evidence based clinical practice guideline based on systematic review of randomized clinical trial
level 2 practice guideline
evidence from at least one well designed randomized clinical trial
level 3 practice guideline
evidence from a well designed controlled trial without randomization
level 4 practice guideline
evidence from a well designed case control and cohort studies
level 5 practice guideline
evidence fro a systematic reviews of descriptive and qualitative studies
grade of practice guidelines
grades of recommendations, assessment, development and evaluation
gold guideline
A, B, C, D
agree practice guideline
the appraisal of guidelines for research and evaluation
how do you locate practice guidelines
pubmed, national guideline clearinghouse, agency for healthcare research and quality, cochrane database of systematic reviews, american college of chest physicians, american heart association, american diabetes association, infectious disease society of america
single payer health insurance
one institution purchases all of the care, but the institution (government) does not pay the providers, own the hospitals, or the technology (ex. France and the US)
socialized medicine
the institution (government) owns the means of providing health care. a government pays the providers, owns the hospitals, or the technology. (UK national health service and US veterans health administration)
what are the two different heath care payment models
single payer health insurance and socialized medicine
why does the US healthcare system need to change
high mortality rate despite huge amount of GDP on healthcare; increasing health costs, medications (adherence, suboptimal prescribing, drug administration and diagnosis)
why are we moving from volume to value based healthcare system
value based programs reward health care providers with incentive payments for the quality of care in medicare; part of the quality strategy to reform how healthcare is delivered and paid for through the triple aim- better care for individuals, better health for populations, lower costs
what are the 7 CMS value based programs
end stage renal disease quality incentive program; hospital value based purchasing program, hospital readmission reduction program, physician value based modifier, hospital acquired conditions reduction program, skilled nursing facility value based program, home health value based program
how can pharmacists engage in value based programs
new value based payment models reward providers for the outcomes of their care instead of for the volume of patients they see
describe PQA’s role in defining pharmacy engagement in value based healthcare
“optimizing health by advancing the quality of medication use”; adherence, appropriate medication use, medication safety, medication therapy management, quality improvement indicators
know the 3 CMS guidelines for comprehensive medication review
patient has multiple chronic diseases with choices set by sponsor; patient is taking multiple part D drugs with choices set by the sponsor; patient is likely to incur annual drug costs above defined threshold
describe electronic quality management system (eQMS)
a way to track product, patients, and outcomes in a single non-paper environment; there are many vendors and room to develop your own system based on systems by common databases like Access and Sharepoint
statistics
the science concerned with developing and studying methods for collecting, organizing, summarizing, and interpreting empirical data
biostatistics
statistics of biology and health science
population
all observations or all theoretically conceivable observations concerning a phenomenon of interest
sample
a subset of the population or universe of interest and conveys information that is of administrative usefulness
descriptive statistics
summarize the information in a collection of data; frequency, graphs, central tendency, dispersion, distribution, tells you numbers
inferential statistics
provide predictions about a population, based on data from a sample of that population; parametric and non-parametric tests
parameter
value that describes a population
variable
attribute, characteristics, or measures property that can vary fro observation to another
qualitative
data in which the classification of objects is based on attributes and properties (gender, ethnicity, race)
quantitative
type of data which can be measured and expressed numerically (age, height, weight, BMI)
nominal
data that doesn’t represent an amount or quality - names, no numbers
ordinal
represents and order or series - high school vs college, disease severity
interval
measured on an interval scale having equal units but an arbitrary zero point - temperature in F
ratio
variables such as weight for which we can compare meaningfully one weight vs another - height, weight, Kelvin
absolute frequency
number of times a value appears
relative frequency
the result of dividing the absolute frequency of a certain value by the total number of data
cumulative frequency
calculated by adding each frequency from a frequency distribution table of the sum of its predecssors
pie charts
distributions of nominal data
bar graphs
distributions of ordinal or nominal data
histograms
frequency distributions of discrete or continuous data; no natural separation between rectangles of adjacent classes
scatter plot
typically used to display the relationship between two different continuous measurements
box and whisker plot
summarizes data using the median, upper and lower quartiles, and extreme values
line graphs
display info that changes overtime; points connecting the data to show a continuous change
purpose of central tendency and measures of dispersion
determines a single value that accurately describes the center of the distribution and represents the entire distribution of scores; goal is to determine the single value that is best representative for the entire set of data
mean
average of all values; denoted by X bar
weighted mean
grades
median
middle
mode
frequency
if the data is symmetrical and normally distributed
the mean and median are about the same; pick the one that fits the need
skewed data to the left is negative
skewedness pulls the mean in the direction of the tail
mean < median
median should be used to describe the center
skewed data to the right is positive
skewedness pulls mean in direction of the tail
mean > median
median should be used to describe the center
outliers pull the mean in their direction
large outlier: mean > median
small outlier: mean < median
variation
measures of variation give information on the spread or variability or dispersion of the data values
range
simplest measure of dispersion; difference between the largest and smallest values
quartiles
determining the value in the appropriate position in the ranked data
first quartitle position =
(n + 1)/4
second quartile position =
(n + 2)/2
third quartile position =
3(n + 1)/4
interquartile range
Q3 - Q1
measures the spread of the middle 50% of the data
not influenced by outliers and extremes
resistant measures
measures that are not influenced by outliers and extremes (Q1, Q3, IQR)
sample variance
average (approximately) of squared deviations of values from the mean
standard deviation for a sample
most commonly used measure of variation; shows variation about the mean; square root; same units as original data
standard deviation for a population
most commonly used measure of variation; shows variation about the mean; the square root of the population variance
coefficient of variation
measure of relative variation; always a percentage; shows variation relative to mean; used to compare variability of 2 or more groups
statistical inference
drawing conclusions about a population parameter using information from a sample; 2 ways to make an inference: estimation of parameters (point estimation and interval estimation) and hypothesis testing
confidence interval
reports a range of numbers in which we hope the true population parameter will lie; the probability that this procedure produces an interval that contains the actual true parameter value is known as the confidence level
point estimate
the sample statistic estimating the population; parameter of interest
critical value
the table value based on the sampling distribution of the point estimate and the desired confidence level; this is controlled by the z or t score
standard error
standard deviation of the point estimate
confidence interval for mu (sigma known)
assumptions: population is normally distributed
confidence interval estimate
construct a confidence interval
point estimate of the population; level of confidence; standard deviation of the sample mean
confidence interval for mu (sigma unknown)
if the population standard deviation is unknown, we can substitute the sample standard deviation S
this introduces extra uncertainty since S is variable from sample to sample
use the t distribution instead of the normal distribution
describe the components of hypothesis testing
can be used to determine whether a statement about the value of a population parameter should or should not be rejected
two types of hypothesis testing
null hypothesis and alternative hypothesis
together both cover all possible values of mu
one of the statements must be true
null hypothesis
the claim you are trying to test; hypothesize that the population parameter mu is equal to some value mu sub zero
alternative hypothesis
the claim we are gathering evidence; this is a statment that contradicts the null hypothesis
process
develop the null and alternative hypothesis
specify the level of significance (alpha)
compute the value of the test statistic
compare p values with alpha values
reject or fail to reject null hypothesis
type 1 error
occurs when the null hypothesis is rejected when it is in fact true (denoted by alpha)
type 2 error
occurs when the null hypothesis is not rejected when it is in fact false (denoted by beta)
p-value
the probability computed using the test statistic that measures the support or lack of support provided by the sample for the null hypothesis
p > .1
non significant evidence against H0
.05 < p < or equal to .1
marginally significant evidence
.01 < p < or equal to .05
significant evidence against H0
P < or equal to .01
highly significant evidence against H0
if p-value is less than alpha we can say
there is enough evidence against the null hypothesis to reject it
if p-value is more than alpha we can say
there is not enough evidence against the null hypothesis to reject it
relative risk
ratio of risk of an event occurring in the exposed group vs the unexposed group; the number of times higher or lower the risk is among exposed as compared with risk among unexposed population
RR =
risk(exposed) / risk(unexposed)
RR<1
suggest exposure being considered is associated with a reduction in risk in the exposed group to the unexposed group (protective effect)
RR=1
suggest no or little difference in the risk between exposed and unexposed groups (no effect)
RR>1
suggests an increased risk of the outcome in the exposed group compared to the unexposed group (harmful effect)
odds ratio
ratio of odds of the disease in the group exposed to the factor, to the odds of the disease in the unexposed group; when the risk of disease in the unexposed is low, the OR approximates to the risk ratio
OR
odds (exposed) / odds (unexposed)
OR=1
no association
OR > 1
odds of disease in exposed are greater than in unexposed, possibly casual
OR < 1
odds of disease in exposed are lower than in unexposed, possibly protective
hazard ratio
measure of the effect of an exposure on an outcome of interest in two population samples over time; commonly reported in time-to-event or survival analysis; outcome could be positive (cure) or negative (death), ratio of risk in group 1 to risk in group 2
HR =
Hazard (exposed) / Hazard (unexposed)
HR = .5
half as many patients in the exposed group are experiencing an event proportionally to the unexposed group
HR = 1
event rates are the same in both groups
HR = 2
twice as many ppl in the exposed group are experiencing an event proportionally to the unexposed group
epidemiology
the science of public health and examines the distribution and frequency of disease in populations, as opposed to studying disease at the individual level
descriptive epidemiology
determining the distribution of disease; identifying what populations or subpopulations do or don’t develop disease; what geographic areas are most or least common to have outcome of interest; frequency of disease occurrence and how it varies over time, develop hypothesis
analytical epidemiology
identify determinants of disease/health by testing hypothesis; determine whether exposure causes or prevents disease, examine associations, identifying or measuring effects of risk factors
descriptive examines disease occurrence
counts, prevalence, cumulative incidence, odds, risk, incidence rate
analytical examines exposure of diease
ratios, differences, attributable risk
counts
tells us how many events/cases; provides absolute number or the burden of disease
limitations: burden of disease is relative to population size; need to know those at risk and the pop size
prevalence
number of existing cases of disease / total population; number of existing cases in the population; focuses on the disease state and measures the proportion of the population who has the disease of interest; provides a single snapshot of the population at one point in time; period prevalence provides a series of snapshots of population within a specified period of time
measures of association / risk
risk difference, risk ratio, risk rate ratio, odds ratio
indicidence proportion
number of new cases of disease / total number at risk for developing disease measures the proportion of the population at risk that develops the disease of interest over a specified period of time; usually reported as 1 year time period; measure of risk in group of people, used in fixed populations, also referred to as cumulative incidence or risk
incidence rate
number of new cases during a specific period of time / total person-time of observation in population at risk during that period; used when different individuals are followed for different lengths of time; numerator is the same as that of cumulative incidence; person time
clinical trial
to evaluate novel treatments for a disease or condition; carried out in hospital clinics among ppl who have already developed the disease; disadvantages: very expensive; not appropriate to answer certain types of questions; it may be unethical to assign certain persons to certain treatment or comparison groups
case reports
detailed presentation of a single case or hand full of cases; generally report a new or unique finding
case series
experience of a group of patients with a similar diagnosis, assess prevalent disease, cases may be identified from a single source or multiple sources, generally report a new/unique condition; may be only realistic design for rare disorders
cross sectional study
a sample of individual is selected from a defined population at .a particular point in time; simultaneously collect information on both the exposures and outcomes of interest; used to determine the distribution and determinants of know or potential risk factors; good for descriptive purposes, not appropriate for inference
cohort study
to investigate the association between an exposure and an outcome / disease; to learn abut the natural history of a disease to calculate measures of association; retrospective and prospective
case control study
an observational study; identify cases and identify controls, compare the groups to determine any differences in past exposures, comparing the frequency of exposure among cases vs controls, cannot estimate disease rates
pharmacoepidemiology
study of the use and effects of drugs in populations; combine pharmacology with epidemiology, postmarketing surveillance
strengths and weaknesses of US drug approval process
based on clinical trails, may exclude important groups of patients, small sample sizes, short duration, postmarketing surveillance, adverse event reporting, spontaneous event reporting limitations, outcomes of postmarket ADE reporting
how do pharmacists or other healthcare professionals contribute to pharmacoepidemiology
drug experts, help identify issues or problems, perform ADE reporting, interpret PE studies and make recommendations to various committees, contract drug use evaluations, develop guidelines, medication adherence proponents, conduct pharmacoepidemiological research
