Healthcare Epidemiology

Healthcare: Epidemiology
Epidemiology is the study of the distribution and determinants of the events related to
health in a particular population as well as the application of the study in the control of the arising
health issues (Last, 2001). During the study, there are various methods used to achieve a productive
study. It is important to note that epidemiology is not theoretic but based on data which is collected
in a manner that is systematic and unbiased. The information gathered is then critically analyzed
and interpreted. In other cases, observation is used following by recording of the findings and
interpretation. In other cases, scientific methods are also used. Some of these methods include
statistics and bioinformatics. Epidemiology involves more than just is an important
component in the field of public health in which information gathered during the study form a
foundation which directs the most practical and appropriate public health actions which are based
on facts and figure rather than mere reasoning (Cates, 1982).
Epidemiological Study Designs
There are different study designs used in the field of epidemiology. They are mainly
divided into several sub-categories under two main categories, i.e. core knowledge and nice to
know. Under core knowledge, research is based on evidence. The evidence can be obtained from
different sources and therefore it is important to consider the best possible study design which is
practicable and follows the laws of ethics in a manner that does not cause harm to people. As a
result, there is a need to establish the strengths and limitations of each study design. While doing
so, one should always keep in mind the purpose of the study. Such purposes include describing the
extensiveness of certain health issues; identifying the source or foundation of the health issues; or
evaluating therapeutic methods that either includes treatment, prevention or both.
The main subgroups in study designs include both observational and experimental;
however, it is important to distinguish between the two. In observational studies, the researcher is
involved by primarily observing and collecting data without altering what occurs e.g. observing
drinking habits in a particular society. However, in experimental, the researcher can make changes
while observing what consequently happens after the change is made e.g. warning a group of
people on the effects of drinking excessive alcohol, taking the blood samples after some time and
comparing the finding with a different group that was not warned (Study Designs, 2017).
Strengths and Weakness of Observational Study Designs
1. Cross-sectional survey
Strength: it is a fast study design in that one can cover a large population and it provides
information regardless of whether or not people are looking for health care.
Weakness: it may be biased as it is based on self-report. As a result, the diagnostic information
might be inaccurate.
2. Cohort or Longitudinal studies.
Strength: the study designs prospective and it can, therefore, be used to estimate incidence
Weakness: it is costly and time-consuming to perform it.
3. Case-control study
Strength: it is economic when focusing on informal factors.
Weakness: the study is inaccurate because there is a need for a recall of previous events. The
controls used in the study are also not equivalent to the cases.
Strengths and Weakness of Experimental Study Designs
Experimental study designs include the Randomized Controlled Trials (RCT) and the
Quasi-Experimental Designs which are included in the Nice-to-Know category.
1. RCT
Strength: it is recommended because it controls for biases and it is widely used in etiological and
evaluative forms of research.
Weakness: there are several ethical concerns that arise from etiological applications.
2. Quasi-Experimental Designs
Strength: it is more practical as compared to the RCT.
Weakness: there are often cases concerning allocation biases.
Epidemiological Studies
Epidemiological studies are important to the society in many ways. This is because they
not only study the origin and the causes of certain diseases, but they also contribute their treatment
as well as solving health-related problems (Dawood, Ambrose, Russell, Hawksworth, Winchell,
Glass, & Weston, 2011).. In the past, epidemiological studies have helped control serious disease
outbreaks all over the world and as a result, save lives. Further studies prevent future outbreaks
from occurring which save on the cost of treatment in the event of an outbreak.
Epidemiology studies are carried out on the basis of facts and data finds. However, the
interpretation of these findings is up for debate because they are subjected to errors such as bias,
chance (random error), and confounding. Such errors are termed as measurement errors which are
likely to influence the final results and conclusions. Such errors are common in observational
studies and therefore, when designing an observational study, it is important to consider such errors
before proceeding with the study.
Confounding is the possibility that a difference between study groups might develop totally
or partially during observation; which could affect the final results. Confounding is usually as a
result of the difference in exposure. Therefore, the consequences of confounding include the fact
that the estimated association may be different from the true effect. As a result, there might be an
overestimation or underestimation of the effect.
Bias is a systematic error which occurs when there is an incorrect estimation of the
exposure and the risk of disease. As a result, researchers require a larger scope during the analysis
stage in order to reduce the effects on the validity of the information acquired. There are three
types of bias, observer bias, recall bias, and selection bias; all of which affect the validity of the
study findings (Role of chance, bias, and confounding in epidemiological studies, 2017).
Statistical Terms
Descriptive Statistics is a branch of statistics concerned with the describing the population under
study by collecting, organizing, analyzing and presenting data in an organized manner.
Probability is the measure of the likelihood that a health-related event will occur in a given
population while probability distributions are functions that can provide the probabilities of
different outcomes from events occurring.
Sampling and Inference; inference in statistics is based on the law of probability which allows
researchers to come up with conclusions on a given population based on the observations made by
means of random sampling.
Hypothesis testing: this is the process statistical inference which involves comparing data collected
against synthetic data which acts as the control.
T- and F-test; T-test is used to estimate the population parameters using population meanwhile
the F-test is also used to estimate the population parameters but with the inclusion of population
Correlation and Linear Regression; correlation is used to show the magnitude to which two
different variables are related while linear regression indicates the relationship between an
independent variable and a dependent one showing how a change in one affects the other.
Correctly interpret the statistical results of epidemiological studies; the following refers to the
process through which the data collected is carefully analyzed while drawing conclusions from the
same. The first step involves the identification of whether or not the data is distributed normally
followed by the application of a null hypothesis, the concept of clinical v statistical significance,
the types of errors, and finally drawing inferences (McCluskey & Lalkhen, 2007).
Epidemiological Study and Analysis Plan
The first step during any epidemiological study is having an idea for the study. This is
usually obtained from either emerging issues or one’s experience. The idea is important because
it lays the foundation for research. One the idea is identified, the relevant information is gathered
which is followed by stating a hypothesis, one which the study will prove right or wrong. Other
factors that should be kept in mind include possible outcomes, the degree of the anticipated effects,
as well as the target population.
The next step involves the preparation of protocol through which funds shall be obtained.
Some of these research methods are costly and therefore it is important for one to conduct a
financial analysis on the required resources as well as substantial amount of funding. Therefore,
the reach team should write a protocol which will be used to obtain funds. It should include, the
study hypothesis, the background, and justification, the study population, the methods of
recruitment, the study design to be used, the sample size, methods of collecting data, statistical
analysis, possible ethics, a timetable, references, budget, and dissemination of results. However,
different bodies require having different protocols. It is always important to identify what a
particular body requires.
Once the study is approved and finances are provided, the next step involves the
recruitment of staff members while gathering the necessary equipment. One should always look
for competent personnel to cut down on issues of incompetence. In the modern age,
computerization of equipment has been largely advocated where data is stored and analyzed using
computer software. This is the followed by recruiting study subjects and the collection of samples.
The study material which may be in the form of biological specimens is then processed depending
on the purpose of the study. This is an important stage of the study. If the samples are interfered
with in any way, it may lead to errors which affect the final results. Quality control should be
advocated in the event of laboratory procedures.
The next step is critical in any study; data processing and editing. In the following step,
data is collected and recorded in either form or in computer software via data entry. The data is
then stored and backed up for analysis. Disseminating the results is the final step which involves
writing a paper. The paper should include a title page, an abstract, an introduction followed by the
methodology, the results and the discussion.
Research Questions
Research questions are vital in research because the quality of answers is only as good as
the quality of questions asked. For this reason, they should be good structured, clear, and straight
to the point. The first step involves choosing what type of research question one would like to
create; is it a descriptive, comparative or related research question. The next step involves
identifying the different types of variables one aims at measuring, manipulating or controlling. At
this step, it is important to identify the target population. The third step involves selecting the
appropriate structure for the research question based on the current variable or target population.
Finally, one should write out the issues to be addressed in the form of a question. It is advisable to
include any words that would help provide a greater context to the questions (How to structure
quantitative research questions | Laerd Dissertation, 2012).
Grant Proposal
The grant proposal is document provided to fund providers asking for funds ("Grant
Proposal Writing: Epidemiology and Preventive Medicine SER", 2015). The structure of the
grant proposal includes the following:
1. Proposal Summary:
This section introduces the proposal in a summarized manner including the number of finances
been requested and a summary of how the funds would be used.
2. Organization Description and History
This section offers information on the office locations and what the organization does. It also
includes the major accomplishments that have been achieved by the organization. Established
partners and other relationships would also be included in this section.
3. Background
This section provides the reader with an in-depth explanation of the problem the project hopes to
address. It should also provide evidence of the problem.
4. Program Description
This section shows how the funds will be distributed and the goals the project hopes to accomplish.
Each goal should be clearly indicated.
5. Program Timetable
This includes a chronological timeline that shows how long the project would take as well as the
time to be spent on each activity.
6. Budget
This is a clearly indicated table with columns showing expenditures showing how the funds would
be executed.
Survey Instrument (Questionnaire)
Survey instruments such as questionnaires are important to any research. In an
epidemiological study, questionnaires are used to identify determinants of health and disease.
When designing a questionnaire, it is important to establish what exactly the study is all about and
the information one would wish to obtain from the target population. The following is an example
of such a questionnaire aimed determining chronic inflammation in the body.
Patient Location:
Tick ‘YES’ or ‘NO’
Do you have elevated cholesterol or triglycerides?
Do you have numbness or tingling in your arms or legs?
Do you eat meat, commercially baked sweets, fried foods,
or use vegetable oil daily?
Do you consume fish less than two times per week?
Do you have high blood pressure, asthma, or colitis?
Do you smoke?
Do you drink alcohol?
Analysis of Epidemiological Data
Analysis of data is dependent on the nature of the data. Some of the main features to analyze
include frequency and effect. However, analysis methods are classified as follows;
1. Estimating population parameters: under the following category, population mean is
conducted. Other methods such as estimation of population proportion from either a
random sample or a cluster sample are also used.
2. Formulating and testing statistical hypotheses in large or small-sized samples (Statistical
methods in the analysis of epidemiological data. (2016).
Cates, W. (1982). Epidemiology: Applying principles to clinical practice. Contemp Ob/Gyn, 20,
Dawood, F. S., Ambrose, J. F., Russell, B. P., Hawksworth, A. W., Winchell, J. M., Glass, N., ...
& Weston, E. (2011). Outbreak of pneumonia in the setting of fatal pneumococcal meningitis
among US Army trainees: potential role of Chlamydia pneumoniae infection. BMC infectious
diseases, 11(1), 157.
Grant Proposal Writing: Epidemiology and Preventive Medicine SER. (2015). Retrieved 25 February 2018, from
How to structure quantitative research questions | Laerd Dissertation. (2012). Retrieved 25 February 2018, from
Last J.M, (2001). Dictionary of epidemiology. 4th ed. New York: Oxford University Press; p. 61.
McCluskey, A., & Lalkhen, A. G. (2007). Statistics IV: Interpreting the results of statistical tests.
Continuing Education in Anaesthesia, Critical Care & Pain, 7(6), 208-212.
Ressing, M., Blettner, M., & Klug, S. J. (2010). Data Analysis of Epidemiological Studies: Part
11 of a Series on Evaluation of Scientific Publications. Deutsches Arzteblatt International,
107(11), 187192.
Role of chance, bias, and confounding in epidemiological studies. (2017). Health Knowledge.
Retrieved 25 February 2018, from
Statistical methods in the analysis of epidemiological data. (2016). Retrieved 25
February 2018, from
Study Designs. (2017). Society, the Individual, and Medicine. Retrieved 25 February 2018, from

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