NR 503 DeVry Week 3 Discussion Paper NR 503 DeVry Week 3 Discussion Paper ? NR 503 DeVry Week 3 Discussion 1 Latest Discussion Part One (graded) Risk and Cohort Study Design As an Advanced Practice Nurse, you will care for patients who are at risk for specific diseases. Please pick one chronic or infectious disease specific to a population in your geographic area and provide evidence of risk, relative risk, and odds ratio in relation to that disease, and specific risks in the population you identified. NR 503 DeVry Week 3 Discussion 2 Latest Discussion Part Two (graded) Now that you have identified the disease and risk, what is one evidence-based action that you could take within your local community or patient population to prevent this risk? NR 503 DeVry Week 3 Discussion 3 Latest Discussion Part Three (graded) Please provide a summary of the case or information you have discussed this week. CLICK HERE TO ORDER YOUR NR 503 DeVry Week 3 Discussion Paper NR 503 DeVry Week 3 Relative Risk Calculation Worksheet Latest Purpose The purpose of this assignment is to help you to begin to understand and apply the important counts, ratios, and statistics presented in healthcare and epidemiological research. Remember to use the list of formulas presented prior to the problems and to carefully consider the purpose of each calculation and how it is interpreted. Course Outcomes Through this assignment, the student will demonstrate the ability to: (CO #3) Identify appropriate outcome measures and study designs applicable to epidemiological subfields such as infectious disease, chronic disease, environmental exposures, reproductive health, and genetics. (CO #4) Apply commonly used measures of health risk. (CO #6) Identify important sources of epidemiological data. Due Date: Sunday 11:59 p.m. (MT) at the end of Week 3 Total Points Possible: 50 Requirements: 1. Complete the Risk Calculation Worksheet located in Course Resources. 2. For each question identify the correct answer. 3. Submit the worksheet to the DropBox by 11:59 p.m. MT Sunday of Week 3 Epidemiological Formulas and Statistics Incidence (exposed) Definition Incidence of new cases of disease in persons who were exposed Formula number (exposed with disease)/Total number of exposed Incidence (unexposed) Definition Incidence of new cases of disease in persons who were not exposed Formula number (unexposed with disease)/Total number of unexposed Incidence of Disease Definition Measure of risk. Total number in a population with a disease divided by the total number of the population. Formula Number with the disease/ Total population number Relative Risk Definition Risk of disease in one group versus another. Risk of developing a disease after exposure. If this number is one, it means there is no risk. R (exposed)/Risk (unexposed) Formula (# exposed with disease (divided by)/total of all exposed) (# of non-exposed with disease/(divided by)total of all non-exposed) Odds Ratio Definition A measure of exposure and disease outcome commonly used in case control studies. Formula R (exposed)/ R (unexposed) 1- R (exposed) 1-R (unexposed) Prevalence Definition The number of cases of a disease in a given time regardless of when it began. (new and old cases) Formula (Persons with the disease/ Total population) X 1000 Attributable Risk Definition The difference in disease in those exposed and unexposed and is calculated from prospective data. Directly attributed to exposure (if exposure gone, disease would be gone) Formula R(exposed) ? R(unexposed) Crude Birth Rate Definition The number of live births per 1,000 people in the population Formula (# of births/estimated mid-year population) X 1000 Crude Death Rate Definition The number of deaths per 1,000 people in the population Formula (# of deaths/estimated mid-year population) X 1000 Fetal Death Rate Definition The number of fetal deaths (20 weeks or more gestation) per 1,000 live births. Formula (# of fetal deaths/ # of live births + fetal deaths) X 1000 Annual Mortality Rate Definition Usually an expression of a specific disease or can be all causes per 1,000 people for a year. Formula (# of deaths of all causes (or a specific disease)/Mid-year population) X 1000 Case Fatality Rate Definition The parentage of individuals who have a specific disease and die within a specific time after diagnosis. Formula (# of persons dying from a disease after diagnosis or set period/ # of persons with the disease) X 100 Relative Risk Calculation Worksheet Prior to completing this worksheet, review the lessons, reading and course text up to this point. Also review the tables of calculations. Each question is worth five (5) points. There is only one right answer for each of the ten problems. 1. The population in the city of Springfield, Missouri in March, 2014 was 200,000. The number of new cases of HIV was 28 between January 1 and June 30th 2014. The number of current HIV cases was 130 between January 1 and June 30th 2014. The incidence rate of HIV cases for this 6 month period was: A. 7 per 100,000 population B. 14 per 100,000 population C. 28 per 100,000 population D. 85 per 100,000 population 2. The prevalence rate of HIV cases in Springfield, Missouri as of June 30, 2014 was: A. 14 per 100,000 population B. 28 per 100,000 population C. 79 per 100,000 population D. 130 per 100,000 population 3. In a North African country with a population of 5 million people, 50,000 deaths occurred during 2014. These deaths included 5,000 people from malaria out of 10,000 persons who had Malaria. What was the total Annual Mortality Rate for 2014 for this country? (Please show your work) 4. What was the cause-specific mortality rate from malaria? (Please show your work) 5. What was the case-fatality percent from malaria? 6. Fill in and total the 4 X 4 table for the following disease parameters: Total number of people with lung cancer in a given population = 120 Total number of people with lung cancer who smoked = 90 Total number of people with lung cancer who did not smoke = 30 Total number of people who smoked = 150 Total number of people in the population = 350 Fill in the missing parameters based on the above. YES LUNG CANCER NO LUNG CANCER TOTALS YES SMOKING NO SMOKING TOTALS 7. From Question 6, what is the total number of people with no lung cancer? 8. From question 6, what is the total number of people who smoked, but did not have lung cancer? 9. Set up the problem for relative risk based on the table in #6. 10. Calculate the relative risk. 

ADDITIONAL INFORMATION;

Discuss how to apply important counts, ratios, and statistics presented in healthcare and epidemiological research

Introduction

Medical research is a complex process, and it can be easy to get lost in the details. But when you understand how important counts, ratios, and statistics are used in medical research papers, it makes reading research papers easier and more fun! Here are five quick tips for reading medical research papers:

Read the study carefully.

Before you start reading, it’s important to understand what the study is about. You can do this by reading the abstract of the article and then going through it in full. If you have any questions, feel free to ask your instructor or other classmates.

Once you’ve read through all of your assigned articles, go ahead and answer these questions:

• What kind of information is being presented? How does this compare with previous research on this topic?

• How does this affect healthcare policy and practice?

Pay attention to the words.

• Pay attention to the words.

• Find words like “significant”, “p < 0.05”, “significant difference”

• Find words like “no difference”, “trend”, or increase in number of patients treated with a drug over time (e.g., increased number of hospital admissions per year).

• Look for words that may be used interchangeably with other terms such as mean or median value when referring to different types of data sets (e.g., first quartile mean and median; total population mean and median).

In addition, pay attention to:

• Clinical practice guidelines – these are guidelines developed by experts who review all evidence available on a topic before writing up recommendations based on this evidence; they often contain recommendations for clinical practice based on research findings

Pay attention to how the numbers are presented.

In addition to the information you provide, it’s important to be aware of how the numbers are presented. For example, if you are comparing two different populations and one has more total cases than the other, this could affect your conclusions about whether or not there is an association between your factor and disease incidence.

It may also be helpful to know how often a particular event occurred in each group (for example: did they have any deaths?). This will help ensure that your results are valid.

Know what statistical test was used.

You should know what statistical test was used. Statistical tests are used to determine if the data supports a hypothesis. They do not make a statement about whether or not the data supports or rejects the hypothesis, but they can provide insight into how robust (or weak) your results are.

Statistical tests are not scientific research; however, they can be used in conjunction with scientific research and may help you interpret it better.

Find out if p < 0.05 was reported.

If you see a p value of 0.05, then this means that there is no difference between groups in your study after adjusting for multiple comparisons (i.e., if there were two groups and one group had an average score higher than the other, then their results would be statistically significant).

Consider the sample size and sample characteristics

Consider the sample size and sample characteristics.

• Sample size: The number of people in your sample is important for determining statistical power. The larger your sample size, the more likely you are to get accurate results from a study.

• Sample characteristics: For example, if you’re studying anorexia nervosa (AN), take into account any differences between those with AN who are severely underweight compared with those who are just slightly underweight or normal weight for their height and age; these factors can affect how accurately your results reflect what’s happening in real life—and thus how valuable they might be for healthcare professionals working with patients at risk of developing ANs later down the road! The same goes for other variables such as gender/gender identity, race/ethnicity, socioeconomic status (SES), etc.—the list goes on!

Understand what measure of performance is being reported.

To understand what is being reported, it’s important to know the measure of performance that’s being used.

• Effect size: The effect size is a measure of how much one variable changed as another variable changed. It can be thought of as a ratio or percent difference between two numbers (like 1X2/3X2=1). For example, if you have three groups: Group A (the control group), Group B (a comparison group), and Group C (another comparison group) with an overall mean score of 60% in each group and then you give them all new sets of questions on their knowledge about disease symptoms that they aren’t familiar with before—the average score would be reduced by 10% across all three groups because each person knows less about this topic than someone else does! This is called an “effect size” because it refers specifically only to how much one thing influences another thing; for example: “The decrease in obesity rates caused by increased exercise has been shown statistically significant at 95% confidence level.”

Know how the study will affect practice.

Now that you’ve read the study, it’s time to think about how it will affect practice. Be sure to consider the following:

• What are the implications for practice?

• How strong is this study and what limitations does it have?

• Will this information be used in practice? If yes, how might you use it? If no, why not?

A quick way to understand a research paper is to read it with the above checklist in mind.

A quick way to understand a research paper is to read it with the above checklist in mind. If you find that your understanding of the topic and its implications has been impacted by any of these points, then you should consider reading more about the research and how it relates to other topics.

Conclusion

As you learned in this tutorial, understanding research papers is not difficult. The most important thing is to read them with the above checklist in mind and make sure that you understand what they say. If you have time to read more about a topic, then by all means do so!