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Compliance (adherence)
the extent to which a patients begavior coincides with a prescribed medical regimen in either a curative or preventive situation. This includes medications, diet, exercise, and any other therapy involved in treatment.
Non-compliance due to communication (patient)
lack of: comprehension of importance, effectiveness, or instructions, little medical supervision, low satisfaction with health care professional, perception of health care professional as unfriendly or overbearing
Non-compliance due to patient difficulties
physical disabilites, pschological difficulties, fear, concurrent self-administration of other medications(OTCs, herbs, street drugs, alcohol, prescriptions)
Non-compliance due to therapy
multiple drugs, frequency of administration, duration of therapy, adverse effects, administration difficulties, asymptomatic, cost
Non-compliance due to health care system
poor relationship with patient, provides prescription without confidence in effectiveness, unwillingness to educate
Steps to prevent non-compliance DDDA
detection: persistent therapeutic problem, refulls missed, missed clinic appts., ask questions, determine the reason, develop a plan, assess a success DDDA
Improving compliance
educate, simplify the medication regimen, labeling, explicit directions, packaging, dosage forms, compliance aids
Past Medication History PMH
disease, sugeriees, medical procedures
Family History FH
1rst degree relatives, disease states, cause of death
Social History SH
tobacco use, alcohol use, recreational drug use, living status
offending agents, type or response or reaction
prescription: current (name, Rx number, physician, pharmacy name and #), Past Meds: just list, Compliance Issues: shows basic understanding of current meds, length of therapy, does, quantity, etc.
may have to prompt patient, ask what they take for headache, constipation, pain/fever, cough/cold, GI upset, etc
Other info needed
ADR's other than allergies, home rememdies, herbal products, diet restrictions/deficiencies, fluid intake
Basic Patient Data Required for Patient Profile by OH Law
-full patient name and gender
-complete address and #
-birth date
-drug allergies
-disease state / chronic?
-OTC's, devices
Basic Prescription Date Required for Patient Profile by OH Law
-date filled
-Rx number
-drug, strength, dosage form
-price dispensing RPh initials
Profile Utilization
-source of 3rd party info
-tax/insurance info
-aids in ident. script by patient name
-accounting/filing info
-aids in delivery instruct.
-inventory control
-simulataneous script, label, profile info
Disadvantages/Limitations of Profiles
-limited to the patients knowledge of diagnosis
-must be updated continuously
-not all OTC's on record
the study of the distribution and determinants of disease frequency in human populations
1. identify etiology
2. determine the extent of dx in community
3. study history and prognosis of dx
4. evaluate new preventitive and therapeutic measures
5. provide foundation for developing public policy and reg. decisions
Primary Prevention
someone who is healthy and well and keep them from getting sick ex. vaccine ULTIMATE GOAL
Secondary Prevention
denotes the id of people who have already developed a disease and caught it at an early stage ex. figure out diabetes early
Population base approach for prevention
look for groups of people prone to certain disease
ex. older:heart disease, stroke, cancer younger: accidents, suicide, homicide
High-risk approach for prevention
look for people who are at high risk for certain diseases ex. obese; heart disease
how sensitive the test is at detecting the disease (true positives) #disease w/ + test / # with disease
if the test is negative and the person does not have the disease # w/o disease (-) / # w/o disease

# of NEW cases per unit of time / # of people in population at risk
*used for screening purposes, new case impact, change in disease pattern

# of people w/ disease per unit of time / # of people in population at risk
*used for provision of service, treatment allocations, hospital bed usage, planning facilities
Human Disease
results from an interaction of hose, agent, and enviroment
habitual presence of a disease within a given geographic region (usual occurance)
occurrence of an illness of similar nature in a community or region tha tis in excess of what is expected
world wide epidemic
Incubation Period
the intercal from receipt of infection to the time of onset of clinical illness
Attack Rate
# of people at risk who develop illness / # of people at risk
Cohort Study Design
BEST WAY, start with healthy subjects-follow to determine risk of disease with exposure or nonexposure ADV. determines true risk, multiple disease with multiple risk factors can be assessed DISADV. expensive, time consuming, problem w/ rare diseases
Relative Risk
likelihood of occurrence of the target event in those exposed and those not exposed incidence in exposed group / incidence in unexposed group
Attributable Risk
portion of risk that can be attributed to the exposed factor incidence of exposed-incidence of unexposed
Case-Control Study Design
NOT NEARLY AS GOOD AS COHORT, know the outcome in the beginning, use case and controls and determine exposure to risk factors ADV. less expensive, easier, can look at rare disease DISADV. estimate of risk, can not observe multiple disease/risk factors
Odds Ratio
an estimate of relative risk using a case-control method for study design
odds of exposure for cases / odds of exposure for controls
Cross-Sectional Design
prevalence study (point in time study)
Experimental Study Design
classic controlled clinical trial ex. drug A versus drug B for treatment of a particular disease
Medicare Part D costs
-monthly premium - $33
-yearly deductable $250
-25% copay for next $2000
-if exceed this you pay all for the next $2850
-after this you only pay %5 copay
*break even pt about $850
Can have additional financial assistance if:
1. income is less the $14,255 for single, or $19,245 couple
2. ur assets cannot exceed $11,500 single, or $23,00 couple
5 purposes for stat. analysis
1. describe gen. characteristics of groups
2. test cause-effect relationship between two or more variables
3. determine the correlation between two or more variables
4. compare differences between means of different groups or factors
5. compare differences in distribution or frequency of occurence
descriptive stats.
describe, summarize, and reduce to a manageable form the properties of a mass of data, these are usually descriptors of properties or populations ex. mean, median, mode, etc
inferential stats.
statistics that are used to make judgements about a population from data obtained through a sample. They are used to make ESTIMATES about true population parameters or characteristics. *has to be intervel or ratio level data
ex. ANOVA, t-test
Nominal scale of measurement
-#'s used to identify groups
-categorization, labels
-count obects / people in categories
-catergories are not ordered
Ordinal scale of measurement
-assign #'s to objects that are rank ordered
-# indicate order only
-researcher does no know the distance between numbers
Interval scale of measurement
-actual defined units of measurement
-research knows order and distance between #'s
-distance between #'s is equal
-NO absolute zero
Ratio scale of measurement
-actual defined limits of measurement
-researcher knows order and distance between #'s
-distance between #'s is equal
-there IS an absolute zero
-measuring what it is supposed to be measuring
*internal validity-extent to which results are true for sample studied
*external validity-extent to which results are true for population, generalizability
refers to dependability, stability, consistency, predictability, and accuracy of study results ex. instrument is reliable if it produces same results over and over
Measure of central tendency
mode, median, mean
-nominal: MODE
-ordinal:mode and MEDIAN
-interval:mode, median, MEAN
-ratio:mode, median, MEAN
how scattered data is
range, standard deviation, variance, standard error of mean
Central Limit Theorem
regardless of the shape of the parent population, the distribution of the sample means will approach a normal distribution if the sample size is large enough, if sample is greater than 30 can assume it is normally distributed
-association between two variables
-values range from -1 to 1
-magnitude is indicated by #
-direction indicated by +-
-when nominal direction indicated in words
Strength of Correlation
.7 + = very strong
.5-.69 = strong
.3-.49 = mod. strong
.1-.29 = weak
0-.9 = almost no association

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