Leaders
F-test - ✔️✔️The F-test is designed to test if two population variances are equal. The
ratio of the two variances is compared. If they are equal, the ratio of the variances will
be 1.
Frequency - ✔️✔️Frequencies measure how often a particular value occurs to assess
the importance of a value or check the variation of the values in a study.
Hypothesis - ✔️✔️A proposed explanation for an observation that leads to a prediction.
Through investigation and the use of statistical data, those doing the study will either
confirm or reject the hypothesis. Testing the hypothesis will show if there is a link (or
not) between two or more variables.
Integrity - ✔️✔️Research always makes some assumptions, depending on the type of
method used. Research assumptions must be identified to determine possible breaches
of integrity.
Interval data - ✔️✔️Interval data includes units of equal size, such as IQ results. There
is no zero point. An example of interval scale is time: Time is measured in 24 hours in
each day; the time between each hour is the same, 60 minutes.
Mean - ✔️✔️Mean is the arithmetic average. Divide the sum of all scores by the total
number of scores.
ANOVA test - ✔️✔️Analysis of variance (ANOVA) may be used in research studies
where there are two or more groups to compare.
Chi-square tests - ✔️✔️Chi-square tests determine if an association exists between
two categorical variables.
Control group - ✔️✔️In a healthcare environment, this group of patients does not
receive the treatment that is being studied.
Experimental group - ✔️✔️This group of patients receives the treatment being studied
with follow-up observation to determine the effect of the treatment.
Median - ✔️✔️Median is the midpoint of the distribution of values, or the point above or
below which 50 percent of the values fall.
,Methods section components - ✔️✔️When analyzing the quality of a study, a careful
evaluation of the research methods can reveal critical details about population and
sample, covariables and hypothesis, data presentation, statistical analysis, and study
limitations.
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Parametric and nonparametric tests - ✔️✔️Parametric tests are based on probability
distributions. Nonparametric tests are used when data are not normally distributed.
Pearson's correlation - ✔️✔️Pearson's correlation is used with interval and ordinal
scale data and determines the extent to which a change in one variable tends to be
associated with a change in another.
Qualitative research methods - ✔️✔️Qualitative research is aimed at understanding
perceptions, perspectives, interpretations, and opinions. Qualitative research methods
often include questionnaires, interviews, written documents, observations, and focus
groups.
Ratio data - ✔️✔️Divide one quantity by another, and you have a value. You will have
a proportion, a percentage or a rate.
Reliability, validity, and analysis of questionnaires - ✔️✔️Questionnaires can be
evaluated for reliability based on their consistency (stability) or repeatability over time;
questionnaires are valid if they measure or record what they purport to measure. Data
from questionnaires may then be grouped according to nominal, ordinal, or interval or
ratio data.
Research - ✔️✔️Research can inform decisions regarding the development and
efficacy of new processes, systems, technologies, environments, and organizational
structures to support operations.
Research platform - ✔️✔️Research is built on a platform of previous knowledge, the
scientific method.
Risk adjustment - ✔️✔️Risk adjustment is essential for comparing data across
systems, especially among patients with varying comorbid diseases and complex
treatment modalities. Multivariate regression analyses can be used to analyze and
adjust risk. This analysis model looks at each measured factor to the patient's risk of a
particular outcome.
Risk of error and harm - ✔️✔️Studies should include an analysis of any sources of
error as well as a thorough explanation of the consequences associated with a
particular study treatment.
, Sample size - ✔️✔️The design of the study provides insight into an appropriate number
and volume of each variable. The calculation of statistical confidence factors informs the
validity testing of the study sample size.
Standard Deviation - ✔️✔️Standard deviation determines the amount of variance in a
set of data and evaluates the degree to which each case deviates from the average, or
mean.
Statistical significance - ✔️✔️The observation is statistically significant if the null
hypothesis is rejected. In a research study, the null hypothesis states there is no
association between the independent and dependent variables in a study.
t-test - ✔️✔️The t-test helps the researcher to compare whether two groups have
different average values. A paired t-test is used when each observation in one group is
paired with a related observation in another.
Variables - ✔️✔️The independent variable is the factor that is directly manipulated by
the researchers. The dependent variable is the measurable variable that depends on
the independent variable.
Master Population/Patient Index (MPI) - ✔️✔️Assigns specific medical record number
to avoid duplicate patient records. Includes patient's demographic information and dates
of encounters.
Disease Registries - ✔️✔️Secondary data gathered on patient diagnosis, condition,
and procedure. Used for public health purposes and documenting disease prevalence.
Length of Stay/Average Length of Stay (ALOS) - ✔️✔️Average number of days a
patient spends in the hospital. Tracked to gauge the efficiency of a healthcare facility.
Center for Medicare and Medicaid Services (CMS) - ✔️✔️Responsible for developing
U.S. healthcare policy; administers the Medicare program and federal portion of
Medicaid program.
HRRP - ✔️✔️Affordable Care Act (ACA) added a section to Social Security Act in
2012, requiring CMS to reduce payments to hospitals with excessive readmissions.
Data gathered is response to the Hospital Readmissions Reduction Program (HRRP),
which is a Medicare value-based purchasing program.
Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS)
Scores - ✔️✔️An effective indicator that measures quality provided, communication
from providers, and other aspects of care delivery. It affects clinical outcomes, patient
retention, and medical malpractice claims.