Statistical application and the interpretation of data is important in health care. Review the statistical concepts covered in this topic. In a 750-1,000-word paper, discuss the significance
Statistical application and the interpretation of data is important in health care. Review the statistical concepts covered in this topic. In a 750-1,000-word paper, discuss the significance of statistical application in health care, including the following:
- Describe the application of statistics in health care. Specifically discuss its significance to safety, health promotion, and leadership.
- Provide an example of the application of statistics in health care by finding a journal article that illustrates its application to safety, health promotion, or leadership. Identify at least two statistical terms used within this article and provide definitions. Include the article on your reference page.
- Describe the importance of standardized health care data as it pertains to ensuring integrity of research data.
In addition to your article, use two peer-reviewed, scholarly references other than those listed in the Topic 1 Resources. References should be published within the last 5-7 years.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is located in Class Resources if you need assistance.
American Association of Colleges of Nursing Core Competencies for Professional Nursing Education
This assignment aligns to AACN Core Competency 8.2.
Expert Answer and Explanation
The Use of Statistics in Health Care
In healthcare, data supports decision-making in the sense that it provides insights into the patterns of health outcomes based on specific interventions. The process of generation of this data involves the use of statistical methods including the measure of central tendency, which supports data analysis. The application of statistics, however, goes beyond analyzing data because in organizational setting, it promotes patient health and safety, with leaders utilizing statistics to better make decisions. It is important to examine how statistics impact each of these areas, and conduct an assessment of statistical components in an article.
How Statistics is Crucial to Safety, Health Promotion, and Leadership
One of the applications of statistics in health care is in safety. Safety is one of the areas in which statistics is significant considering that it support the reduction of error, allowing clinicians to determine inconsistencies in clinical interventions like wrong frequency of drug administration. Guided by the information generated using statistics that reveals these inconsistencies, a hospital can develop and adopt more potent interventions that lead to optimization of drug administration (Bensken, Pieracci, & Ho, 2021). For instance, they can examine the impact of the dossing intervals on stabilization of symptoms through event history analysis. This can inform decisions, lessening the risk of medical errors.
Statistics has a potential of optimizing health promotion outcomes by allowing clinicians to collect measurements of population health outcomes, which they rely on to decide whether making changes to the existing interventions is necessary. Considering a healthcare program that seeks to influence the change of a health behavior like smoking, clinical researchers employ statistics to determine the prevalence of the behavior in subjects across various population characteristics like income status (Bensken et al., 2021). They can then develop population-centered interventions that target high-risk groups.
In an organization, leaders allocate resources and provide input into the organization’s budgeting operations. To effectively execute these functions, leaders may need to employ statistical methods which essentially support the analysis of the demand for services in different units or departments, and the rate of use of the resources. They can specifically use the mean to compute the information pertaining to demand for services. This may involve determining the average number of patients that visit a department. In response to this change, a provider may intervene by allocating more resources or reducing resources.
Examples of Use of Statistics in Health Care
The use of statistics in healthcare is widespread with tools like Statistical Process Control (SPC) being applied in evaluation of the effectiveness of the quality improvement methodologies. The SPC’s use for this particular role is seen in the study conducted by Lima de Mendonca et al. (2024), in which they sought to assess SPC’s use in abdominal surgery specialties. The researchers employed a methodology in which they search terminologies related to SPC and abdominal surgery, in Ovid Medline and Embase. They generated a SR flow diagram that integrated Preferred Reporting Items for Systematic Reviews and Meta-Analysis feature.
According to the outcomes of the study, the use of SPC in describing surgical complications is prevalent in various publications, majority of which were published in western countries (Lima de Mendonca et al., 2024). This is an evidence of wider application of the SPC in specialties that deal with surgical care. Guided by these findings, providers can develop quality improvement programs to lessen cases of adverse health events linked to abdominal surgery.
The Statistical Terms Captured in the Article Including their Definitions
The article highlights a number of statistical terms including cumulative summation chart which displays the summation of a series of data that keeps on changing. It also features “control limits” which represent the limits defining the range of variation of a process that lie within the acceptable range. The mean rate is also used in the article, and it denotes a measure of central tendency or the total of the values of items divided by the sum of their values.
The Benefit of Standardized Health Care Data in Regard to Integrity of the Research Data
The idea of standardizing health data in health research is crucial in the sense that it brings aspect of uniformity to data, which enhances the comparison and combination of data. This is particularly important when dealing with large data that is drawn from research-based organizations, clinical facilities, and hospitals. Because the loss of the data integrity, which stems from the misinterpretation of data or entry errors, may compromise data quality, is common with non-standardized data, data standardization promotes data integrity (Zarour et al., 2021). It also supports safe and effective sharing of data, with providers and other professionals collaborating with the agenda of using shared data to develop interventions that can help support patient care.
Conclusion
In conclusion, the significant role that statistics plays in healthcare is seen in how it promotes safety, and affects health promotion including leadership operations. For providers, basing decisions on the data generated through statistics can enhance their decision-making capacity, allowing them to come up with more effective interventions for addressing clinical issues. For their part, leaders can utilize statistics to determine how to adequately allocate resources to meet patients’ demand.
References
Bensken, W. P., Pieracci, F. M., & Ho, V. P. (2021). Basic Introduction to Statistics in Medicine, Part 1: Describing Data. Surgical Infections, 22(6), 590–596. https://doi.org/10.1089/sur.2020.429.
Lima de Mendonca, Y., Sarto, R., Titeca, H., Bethune, R., & Salmon, A. (2024). Use of Statistical Process Control in Quality Improvement Projects in Abdominal Surgery: A PRISMA Systematic Review. BMJ Open Quality, 13(1), e002328. https://doi.org/10.1136/bmjoq-2023-002328.
Zarour, M., Alenezi, M., Ansari, M. T. J., Pandey, A. K., Ahmad, M., Agrawal, A., Kumar, R., & Khan, R. A. (2021). Ensuring Data Integrity of Healthcare Information in the Era Of Digital Health. Healthcare Technology Letters, 8(3), 66–77. https://doi.org/10.1049/htl2.12008.
Topic 1 DQ 1
It has long been a requirement for health care workers to take an Introduction to Statistics class. Why is it important for a person working in health care to understand statistical concepts? To answer this question, please provide two specific examples incorporating two different statistical terms from “Visual Learner Statistics,” located in the Topic 1 Resources. Do not use the same examples as those in a prior post. You may reference other articles in this topic or conduct your own scholarly research if more statistical terms are needed.
Initial discussion question posts should be a minimum of 200 words and include at least two references cited using APA format. Responses to peers or faculty should be 100-150 words and include one reference. Refer to “HLT-362V Discussion Question Rubric” and “HLT-362V Participation Rubric,” located in Class Resources, to understand the expectations for initial discussion question posts and participation posts, respectively.
Expert Answer and Explanation
The knowledge of statistical concepts is crucial for individuals that work in health care in the sense that it enables them to make sense of research, and effectively make decisions based on the available evidence that they can rely on the basis of understanding how these concepts play out in research. An example of these concepts is confounding which denotes the extra effects that a variable introduces into the research, affecting the causal relationship between the dependent and independent variable. To better understand how this how confounding effect occurs, one may need to examine a study that investigates the effectiveness a new medication introduced to manage diabetes (Woltenberg, 2021).
In this study, the independent variable is the new study while the blood glucose levels represent the dependent variable. Because drug reacts with other drugs or alcohol, involving intoxicated persons or those that recently took medications to participate in the study without accounting for these influences, can create confounding effects, compromising the credibility of the research.
For a person working in the healthcare filed, knowing how to avoid the negative influence of the confounding is critical because this knowledge can help them improve the quality of and credibility of their research work. The use of randomization addresses this specific issue because with this method, the person conducting a study use a random approach in which they assign a subject or an experimental unit a treatment.
Considering the research that attempts to examine the effectiveness of a newly introduced diabetes drugs, researchers randomly select subjects to include them in the study (Visual Learner: Statistics, n.d.). Random selection in this case reduces confounding variables like using intoxicated persons or people that have taken a drug that can react with the diabetes medication.
References
Visual Learner: Statistics (n.d.). Terms. https://lc.gcumedia.com/hlt362v/the-visual-learner/the-visual-learner-v2.1.html.
Woltenberg L. N. (2021). Cultivating Statistical Literacy Among Health Professions Students: a Curricular Model. Medical science educator, 31(2), 417–422. https://doi.org/10.1007/s40670-021-01256-4.
Topic 1 DQ 2
Design an experiment with one independent variable (with at least two levels) and one dependent variable. Additionally, what levels of measurement would you use when collecting your data?
Example: XYZ hospital wanted to increase compliance of staff using hand sanitizer after every interaction with a patient. In order to gain compliance, they set up a buzzer when staff exited the patient’s room. For the treatment group, a buzzer would ring for 1 second after exiting the room unless staff had pressed the hand sanitizer lever. The control group did not have the buzzer activated, so no sound would emit when exiting the patient’s room.
Independent Variable: Presence of a buzzer sound or not.
Dependent Variable: Number of times the hand sanitizer lever was pressed.
Level of Measurement: Ratio
In your responses to other students, identify a strength or weakness of another student’s example design.
Initial discussion question posts should be a minimum of 200 words and include at least two references cited using APA format. Responses to peers or faculty should be 100-150 words and include one reference. Refer to “HLT-362V Discussion Question Rubric” and “HLT-362V Participation Rubric,” located in Class Resources, to understand the expectations for initial discussion question posts and participation posts, respectively.
Expert Answer and Explanation
Researchers at ABC healthcare facility sought to determine whether regular physical is associated with lower risk of developing prostate cancer. Using random sampling, they selected 30 participants, assigning half of these subjects into the “Exercise Group”, and the other half into “No Exercise Group.” Subjects in the exercise group were required to spend one hour a day exercising, which included morning runs and stretching exercise. Prior participating in the study, the patients were screened for prostate cancer, and then they were observed for a period of three years. They were later screened for prostrate at the end of the period of study (Andrade, 2021).
For this research, the inclusion criteria included being aged 65 years, non-transgender person, and no prior history of active exercise. The participants were excluded if they were obese, were unable to stick to the presented nutritional plan. To reduce the impact of external influences on the variables, the participants were required to stick to adhere to the recommended nutritional program which was same for those in the experimental and those in the control group (Andersen, Midtgaard, & Bjerre, 2022).
Levels of Measurements
The independent variable: Exercising regularly and not exercising are two non-ordered conditions which show the level of measurement as nominal.
Dependent variable: The diagnosis of the prostate cancer or the absence of the prostate cancer.
Level of measurement: For this variable, the level of measurement nominal considering that they lack specific order of arrangement. This means that the prostate cancer is either present or absence.
References
Andersen, M. F., Midtgaard, J., & Bjerre, E. D. (2022). Do Patients with Prostate Cancer Benefit from Exercise Interventions? A Systematic Review and Meta-Analysis. International journal of environmental research and public health, 19(2), 972. https://doi.org/10.3390/ijerph19020972.
Andrade, C. (2021). A Student’s Guide to the Classification and Operationalization of Variables in the Conceptualization and Design of a Clinical Study: Part 1. Indian journal of psychological medicine, 43(2), 177–179. https://doi.org/10.1177/0253717621994334.
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