UAA HLT 362 Application of Statistics in Health Care Questions
UAA HLT 362 Application of Statistics in Health Care Questions
UAA HLT 362 Application of Statistics in Health Care Questions
Clinical decision is of utmost importance in the provision of quality health outcomes. Contingent upon this premise, the two articles establish decision-making procedures and practice guidelines relevant for clinical practice. The first study assesses the feasibility of decision-making processes by nurses stationed at the emergency department of a care facility (Fisher, Orkin & Frazer, 2010). On the other hand, the work of Tjia et al. (2010) purposes to develop guidelines required to monitor the dispensation of high-risk medications while at the same time establish the prevalence of existing laboratory testing concerning these medications.
In order to draw clinical evidence on a factor in decision making, the article by Fisher, Orkin and Frazer (2010) employed the usage of nonparametric tests comprising Fisher’s exact tests and chi-square. The study relied on conjoint analysis to reflect upon the decision-making patterns. The results of this study provided quality outcomes by demonstrating that nurses depended on the functional status of patients, future health status, and family input to undertake decisions on healthcare delivery for their clients. The article by Tjia et al. (2010) utilized t-test and Likert-type scale to formulate guidelines for the utilization of high-risk drugs and to monitor the frequency of dispensing them. The non-parametric test was instrumental in developing medication dispensing guidelines in terms of drug classes, the frequency of medication, monitoring and laboratory testing for efficacy.
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According to numerous empirical studies, parametric parameters receive useful application in the testing of study group means. Nevertheless, the effectiveness of the methodology remains debatable within the context of the present articles. For instance, the use of t-test and ANOVA requires normal distribution of the applicable data regarding the research. Since data from the two articles were not distributed, it became paramount for the authors to consider skewing of non-normal distribution to produce the results (Gibbons & Chakraborti, 2011). Therefore, the approach remains embedded on assumptions and as such it has a high vulnerability to error. However, the assertion receives higher applicability in the second article. Nonetheless, the application of ANOVA and t-test requires studies that have a broad distribution of sample sizes, a threshold that neither of the two articles met.
Despite providing results on the clinical decision and high-risk drug dispensing techniques, certain strengths and weakness characterized the studies. The first article used conjoint analysis techniques to design a workable mathematics model required for clinical decision-making process for nurses in the emergency department (Fisher, Orkin & Frazer, 2010). However, the technique involving proxy decision-making for this study is complex considering the premise that it does not uniformly address the responses of all nurses. As such, the study could be subject to speculation hence casting doubt on the accuracy of information obtained from the first study.
In the article by Tjia et al. (2010), the selected study design captured a multispecialty population and therefore provided a reflection of clinical practice in the United States of America. However, utilization of the Likert-type scale could subject the study outcomes to errors due to a lack of consensus on the questions administered to participants. Considerably, findings and recommendations in the work of Fisher, Orkin and Frazer (2010) provide the need for aligning clinical decisions as per the patients in the emergency department for purposes of improving the quality of care. Correspondingly, the other article offers guidelines for safe administration of high-risk medications to establish an evidence-based practice in a healthcare setting.
In the entire coursework, the present author discovers nonparametric tests as commonly applied to the processes of analyzing data. Specifically, chi-square dominates most of the literature review in clinical research. Evidently, the adoption of this test has demonstrated effectiveness in the analysis of nominal data. Furthermore, the technique has a high level of accuracy since it has received comparison with observed frequencies obtained from null hypotheses. Nevertheless, the adoption of other nonparametric tests such as the Wilcoxon matched-pairs test, Mann-Whitney U and Kruskal-Wallis tests does not readily occur since they measure rank-ordered data. According to Gibbons and Chakraborti (2011), the application of the above-mentioned non-parametric tests in multifarious clinical studies does not normally occur since outliers have the capacity to obscure the outcomes. Moreover, the outliers have minimal impact on the chi-square tests.
Reference
Fisher, K., Orkin, F., & Frazer, C. (2010). Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study. Applied Nursing Research, 23(1), 30-35.
Gibbons, J. D., & Chakraborti, S. (2011). Nonparametric statistical inference. In International encyclopedia of statistical science (pp. 977-979). Springer, Berlin, Heidelberg.
Tjia, J., Field, T. S., Garber, L. D., Donovan, J. L., Kanaan, A. O., Raebel, M. A., … & Gurwitz, J. H. (2010). Development and pilot testing of guidelines to monitor high-risk medications in the ambulatory setting. The American journal of managed care, 16(7), 489-496.
Description
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. Include the following:
- Describe the application of statistics in health care. Specifically discuss its significance to quality, safety, health promotion, and leadership.
- Consider your organization or specialty area and how you utilize statistical knowledge. Discuss how you obtain statistical data, how statistical knowledge is used in day-to-day operations and how you apply it or use it in decision making.
Discuss the historical application of statistics in the field of health care. Describe an example, other than Florence Nightingale’s contributions, where statistical application has greatly influenced or changed health care operations or practice.
The application of statistics in health care dates back to the days of Florence Nightingale. While her contributions using statistical analysis was monumental, it was the just beginning of analyzing data to improve patient outcomes (Helbig & Ambrose, 2021). Upon the development of the Communicable Disease Center or what we now know as the Centers for Disease Control and Prevention (CDC) in 1946, the U.S. Public Health service employed the same strategies used by Nightingale and others to develop their own statistical methods. This eventually led to the creation of the Epidemic Intelligence Service (EIS) whose purpose was to respond to and investigate outbreaks and further advance epidemiologic methods.
Through continued research with evolving methods and calculations based on best-evidence available at the time, the CDC was able to identify many hazardous health conditions that significantly contributed to the morbidity and mortality of the population. These advances include banning the use of lead in gasoline after the EPA developed a method in which blood lead levels could be detected and measured. This act alone helped to decrease the rates of lead exposure, and the adverse effects that follow. As the methods and application of statistics continued to improve and become more refined, epidemiologists were able to incorporate technology as seen with the use of the SOCRATES program in 1976, a development that enabled a more efficient way for scientists to address the swine flu crisis of the time (Stroup & Lyerla, 2011). As technology continues to evolve, so too will the application of its uses across health care statistics, allowing for larger sample sizes, more accurate calculations and higher quality of studies. These continued advancements are necessary to address the ongoing threats of disease and serve as pillars for innovating new and creative methods of health promotion and disease prevention.
Reference
Helbig, J. & Ambrose, J. (2021). What are statistics and why are they important to health science? In Grand Canyon University (Ed.), Applied statistics for health care (ch.1). https://bibliu.com/app/#/view/books/1000000000581/epub/Chapter1.html#page_6
Stroup, D.F. & Lyerla, R. (2011). History of statistics in public health at CDC, 1960–2010: The rise of statistical evidence. Morbidity and mortality weekly report 60(04), 35-41. https://www.cdc.gov/mmwr/preview/mmwrhtml/su6004a7.htm
Statistics in healthcare is an important and valuable tool for research, planning, and decision-making. It has been a central component of the healthcare system for centuries, with the earliest example being Florence Nightingale’s pioneering work in the mid-19th century. Nightingale used her knowledge of mathematics and statistics to develop innovative methods for improving patient care, including the use of data visualizations to better comprehend data.
Another example of statistics in healthcare is the utilization of randomized controlled trials (RCTs). RCTs are a type of study that compares the outcomes of one group of subjects receiving a particular treatment, against a control group receiving no treatment or a different treatment. RCTs are often used to measure the efficacy of a drug or treatment, and can help inform decisions about which treatments are most effective.
In the 21st century, statistical applications in healthcare have expanded to include the development of predictive models and machine learning algorithms. These models use large datasets to predict the probability of certain outcomes, such as the likelihood that a patient will respond to a certain treatment. These models can help healthcare providers make more informed decisions, such as which treatments are most likely to be effective for a particular patient.
Another example of the application of statistics in healthcare is the use of big data analytics. Big data analytics is the process of gathering and analyzing large amounts of data to gain insights into trends and patterns in healthcare. This data can be used to improve the delivery of healthcare services and to make decisions about where resources should be allocated. For example, data analytics can be used to identify areas with higher than average rates of certain conditions, enabling healthcare providers to target resources more effectively (Hollander, 2020; Deo, 2019).
Overall, statistics in healthcare has played an important role in the field for centuries. From Nightingale’s pioneering work to the development of predictive models and big data analytics, statistical applications have greatly influenced healthcare operations and practice. As the field of healthcare evolves and new technologies are developed, statistics will continue to play a key role in improving patient care.
Application of Statistics in Healthcare
The application of statistics is a critical in every organizational processes. Currently, most firms relies on the data to enhance the operational processes and improve customer relationships. With the emergence of technology, data has a become one of the essential component in the decision-making processes. They in business, analyzed data can be used to show trends in the marketing processes, a scenario that may enhance sale of goods and services. Healthcare system employs a lot of statistics to improve research aimed at establishing effective treatment and medical processes (Ekin, 2019). Historically, statistics have been used in the healthcare system to improve research processes as well as treatment processes.
There are different personalities such as Florence Nightingale who incorporated a lot of statistical in the healthcare system to improve care and to increase efficiency in medical delivery and general care. By identifying statistical trails and trends, healthcare workers are able to monitor local conditions and make comparisons with the national, state and international trends. Health statistics often provide empirical data to aid in allocation of resources to both the private and public facilities in an effort to improve care for the patients. The purpose of the paper is to discuss the application of statistics in the healthcare system.
Application of Statistics
Statistics is important when it comes to the development of models that can be used to predict the future trends including patient flow and the best medication and treatment strategies. In the process of operation, healthcare workers often engages in the collection of data from the time a patient is admitted into the hospital to the time when they are discharged. From the point of admission, biodata is taken to record the identity of the patients and their conditions. Also, in the process of treatment, all the data including time are recorded for future references. All the above processes requires statistical knowledge, which most healthcare workers possess. The statistical concept are mostly used in the analysis of these data to reveal trends and what needs to be done to improve areas of weaknesses. Therefore, the use of statistics is essential in determining the processes that are required to improve medication and treatment processes. Whether considering disease incidences, cure rates, accidents, hospital and physician fees, mortality rates, malpractice, treatments, drugs or medical devices, the application of statistical concepts is important (Kros & Rosenthal, 2016).
Internationally, drug testing is a critical part of the healthcare processes that ensures the establishment of an effective vaccine or drugs to counter certain diseases. The processes of drug test often require the use of statistics to study the effects of placebo and the real drugs. The study objectives in these research requires models based on the available data from the participants. Application of statistics in the healthcare system is essential as it aids in providing guidance to the decision makers and the general healthcare professionals (Pett, 2015). The healthcare institutions to gauge performance as well as the results of the medical performance commonly apply statistical analysis. In most cases, government and human service agencies apply statistical information to define the well-being as well as the overall health of the population.
Pharmaceutical companies and hospitals usually engages in the analysis of the patients in order to identify risks linked to specific disorders, measure the effectiveness of different treatments and assess the symptoms. Healthcare organizations struggle every single day to effectively deliver quality services and medical products to the patients. Application of statistics therefore enable companies to gauge successes and failures in their performance (Kros & Rosenthal, 2016). In the hospitals and other healthcare settings, managers in charge of quality improvements often develop standards of benchmarks and service excellence to determine the future results. Reliable statistical information, i.e., statistics obtained from the analysis of raw data can be used to determine the viability as well as the overall growth in a given medical facility. These data can also be used to plot diminish risks associated with the trade-offs and create innovative approaches in the treatment procedures. The data obtained from the patients during their stay in the hospital can be used in clinical trials for the new technologies in treatments in order to determine the benefits alongside the risks.
With the emergence of the diseases, scientist are always looking for the best treatment and medication approaches. With statistics, mathematicians, computer scientists and medical professionals often analyze the data to identify the best treatment approaches that needs to be undertaken in case there is a diseases outbreak (Kros & Rosenthal, 2016). The use of statistics is also common in the epidemiological research as it helps in determining the study methods to take against a given diseases. Also, the emergence of diseases often lead to the overcrowding in the medical facilities; therefore, with the statistics, the data taken can be used to enhance quality, health promotion, safety and leadership. In general, the use of statistics in healthcare system is meant to enhance quality, safety, and general effective outcome within the healthcare settings.
Utilization of Statistics
I am a community registered nurse who majors in the clinical processes within the healthcare system. With the emergence of evidenced-based practices. I will use the statistical knowledge to develop models that can be used to enhance evidenced-based practices. For instance. I will use statistics to determine correct nurse to patient ratio and to enhance diagnostics processes especially when there is increased number of patients in the hospital as a result of disease outbreak. While operating in the hospital, I will obtain data through recording patient’s information including biodata, medical history, disease condition, type of care and the complications or the diseases that each patient is suffering from.
Conclusion
Statistics is used in day to day activities in the healthcare settings to manage the number of patients, determine the most treatment approach to given and to determine the best medication processes to give to the patients. Also, through the formulation of operational models, statistics will be used to enhance decision-making processes. Such a situation can help in promoting public health and well-being of the people in different communities.
References
Ekin, T. (2019). Statistics and health care fraud: How to save billions. Boca Raton, FL: CRC Press.
Kros, J. F., & Rosenthal, D. A. (2016). Statistics for health care management and administration: Working with excel. New York, NY: John Wiley & Sons.
Pett, M. A. (2015). Nonparametric statistics for health care research: Statistics for small samples and unusual distributions. New York, NY: Sage Publications.
Rubric Criteria
|
Criterion |
1. 1: Unsatisfactory |
2. 2: Less Than Satisfactory |
3. 3: Satisfactory |
4. 4: Good |
5. 5: Excellent |
|---|---|---|---|---|---|
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Paper Format Paper Format (use of appropriate style for the major and assignment) |
0 points Template is not used appropriately, or documentation format is rarely followed correctly. |
3.25 points Appropriate template is used, but some elements are missing or mistaken. A lack of control with formatting is apparent. |
3.75 points Appropriate template is used. Formatting is correct, although some minor errors may be present. |
4.25 points Appropriate template is fully used. There are virtually no errors in formatting style. |
5 points All format elements are correct. |
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Argument Logic and Construction Argument Logic and Construction |
0 points Statement of purpose is not justified by the conclusion. The conclusion does not support the claim made. Argument is incoherent and uses noncredible sources. |
5.2 points Sufficient justification of claims is lacking. Argument lacks consistent unity. There are obvious flaws in the logic. Some sources have questionable credibility. |
6 points Argument is orderly but may have a few inconsistencies. The argument presents minimal justification of claims. Argument logically, but not thoroughly, supports the purpose. Sources used are credible. Introduction and conclusion bracket the thesis. |
6.8 points Argument shows logical progression. Techniques of argumentation are evident. There is a smooth progression of claims from introduction to conclusion. Most sources are authoritative. |
8 points Clear and convincing argument presents a persuasive claim in a distinctive and compelling manner. All sources are authoritative. |
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Mechanics of Writing Mechanics of Writing (includes spelling, punctuation, grammar, language use) |
0 points Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice or sentence construction is used. |
3.25 points Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) or word choice are present. Sentence structure is correct but not varied. |
3.75 points Some mechanical errors or typos are present, but they are not overly distracting to the reader. Correct and varied sentence structure and audience-appropriate language are employed. |
4.25 points Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech. |
5 points Writer is clearly in command of standard, written, academic English. |
|
Application of Statistical Knowledge to Organization or Specialty Area Application of Statistical Knowledge to Organization or Specialty Area |
0 points Application of statistical knowledge to organization or specialty area is omitted. More than one criterion regarding how statistical data are obtained, used in day-to-day operations, or applied in decision making are omitted. |
19.5 points Application of statistical knowledge to organization or specialty area is summarized. How statistical data are obtained, used in day-to-day operations, and applied in decision is unclear; one criterion is missing. More information is needed. |
22.5 points Application of statistical knowledge to organization or specialty area is generally discussed. How statistical data are obtained, used in day-to-day operations, or applied in decision making is summarized. . |
25.5 points Application of statistical knowledge to organization or specialty area is discussed. How statistical data are obtained, used in day-to-day operations, or applied in decision making is described. Some information or detail is needed for clarity. |
30 points Application of statistical knowledge to organization or specialty area is thoroughly discussed. How statistical data are obtained, used in day-to-day operations, or applied in decision making is described in detail. The ability to understand and apply statistical data is clearly demonstrated. |
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Documentation of Sources Documentation of Sources (citations, footnotes, references, bibliography, etc., as appropriate to assignment and style) |
0 points Sources are not documented. |
3.25 points Documentation of sources is inconsistent or incorrect, as appropriate to assignment and style, with numerous formatting errors. |
3.75 points Sources are documented, as appropriate to assignment and style, although some formatting errors may be present. |
4.25 points Sources are documented, as appropriate to assignment and style, and format is mostly correct. |
5 points Sources are completely and correctly documented, as appropriate to assignment and style, and format is free of error. |
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Thesis Development and Purpose Thesis Development and Purpose |
0 points Paper lacks any discernible overall purpose or organizing claim. |
4.55 points Thesis is insufficiently developed or vague. Purpose is not clear. |
5.25 points Thesis is apparent and appropriate to purpose. |
5.95 points Thesis is clear and forecasts the development of the paper. Thesis is descriptive and reflective of the arguments and appropriate to the purpose. |
7 points Thesis is comprehensive and contains the essence of the paper. Thesis statement makes the purpose of the paper clear. |
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Application of Statistics in Health Care (quality, safety, health promotion, leadership) Application of Statistics in Health Care (quality, safety, health promotion, leadership) |
0 points Application of statistics in health care is omitted or incomplete. The significance to quality safety, health promotion, and leadership is omitted. |
26 points Application of statistics in health care is summarized. The significance to quality, safety, health promotion, and leadership is partially presented. One or more criteria are missing. There are inaccuracies. Significant information or rationale is needed. |
30 points Application of statistics in health care is generally described. The significance to quality, safety, health promotion, and leadership is generally described for all criteria. There are minor inaccuracies. More information or rationale is needed to fully illustrate the application of statistics overall. |
34 points Application of statistics in health care is described. The significance to quality, safety, health promotion, and leadership is described for all criteria. Some minor information or rationale is needed to fully illustrate the application of statistics to health care and the specific areas. |
40 points Application of statistics in health care is described in detail. The significance to quality, safety, health promotion, and leadership is described thoroughly for all criteria. Strong information and rationale is provided to fully illustrate the application of statistics, and its significance, to health care and the specific areas. |
APA Writing Checklist
Use this document as a checklist for each paper you will write throughout your GCU graduate program. Follow specific instructions indicated in the assignment and use this checklist to help ensure correct grammar and APA formatting. Refer to the APA resources available in the GCU Library and Student Success Center.
☐ APA paper template (located in the Student Success Center/Writing Center) is utilized for the correct format of the paper.
APA style is applied, and format is correct throughout.
☐ The title page is present. APA format is applied correctly. There are no errors.
☐ The introduction is present. APA format is applied correctly. There are no errors.
☐ Topic is well defined.
☐ Strong thesis statement is included in the introduction of the paper.
☐ The thesis statement is consistently threaded throughout the paper and included in the conclusion.
☐ Paragraph development: Each paragraph has an introductory statement, two or three sentences as the body of the paragraph, and a transition sentence to facilitate the flow of information. The sections of the main body are organized to reflect the main points of the author. APA format is applied correctly. There are no errors.
☐ All sources are cited. APA style and format are correctly applied and are free from error.
☐ Sources are completely and correctly documented on a References page, as appropriate to assignment and APA style, and format is free of error.
Scholarly Resources: Scholarly resources are written with a focus on a specific subject discipline and usually written by an expert in the same subject field. Scholarly resources are written for an academic audience.
Examples of Scholarly Resources include: Academic journals, books written by experts in a field, and formally published encyclopedias and dictionaries.
Peer-Reviewed Journals: Peer-reviewed journals are evaluated prior to publication by experts in the journal’s subject discipline. This process ensures that the articles published within the journal are academically rigorous and meet the required expectations of an article in that subject discipline.
Empirical Journal Article: This type of scholarly resource is a subset of scholarly articles that reports the original finding of an observational or experimental research study. Common aspects found within an empirical article include: literature review, methodology, results, and discussion.
Adapted from “Evaluating Resources: Defining Scholarly Resources,” located in Research Guides in the GCU Library.
☐ The writer is clearly in command of standard, written, academic English. Utilize writing resources such as Grammarly, LopesWrite report, and ThinkingStorm to check your writing.
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