HLT-362V Application of Statistics in Health Care

Grand Canyon University HLT-362V Application of Statistics in Health Care– Step-By-Step Guide

This guide will demonstrate how to complete the Grand Canyon University  HLT-362V Application of Statistics in Health Care assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for HLT-362V Application of Statistics in Health Care                                

Whether one passes or fails an academic assignment such as the Grand Canyon University  HLT-362V Application of Statistics in Health Care depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for HLT-362V Application of Statistics in Health Care                                

The introduction for the Grand Canyon University  HLT-362V Application of Statistics in Health Care  is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for HLT-362V Application of Statistics in Health Care                                

After the introduction, move into the main part of the HLT-362V Application of Statistics in Health Care       assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for HLT-362V Application of Statistics in Health Care                                

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for HLT-362V Application of Statistics in Health Care                                

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for HLT-362V Application of Statistics in Health Care

Statistics refers to the science concerned with studying and developing procedures or methods gathering, analyzing, interpreting, and presenting empirical data for decision-making purposes. Statistics is applied in different sectors to determine trends and predict the future performance of different processes. In healthcare, statistics serve different purposes, including measurement of quality improvement processes, measuring performance, predicting the future trends in the healthcare delivery processes, enhancing research and evidence-based practices. Statistics has become a cornerstone of healthcare companies in measuring the failures and success of different processes. Therefore, the purpose of this assignment is to discuss the application of statistics in healthcare.  

Application of Statistics in Healthcare 

The information drawn from the studies involving statistics is often used to guide decision-making processes in healthcare organizations. Today, healthcare organizations widely apply statistics to determine the level of performance and the outcomes of different processes. Governmental institutions, particularly those involved in the development of healthcare policies, rely on statistical data to determine the population’s overall well-being (McGee et al., 2018). To enhance the delivery of quality care, healthcare institutions and pharmaceutical companies ought to understand patients to evaluate the risks associated with them and institute the best treatments for effective outcomes. Statistical information is therefore essential in the assessment or evaluation processes for better treatment procedures to be conducted.  

Due to increased competition in the healthcare sector and the increased number of patients, healthcare companies continue to struggle to efficiently quality healthcare services. As a result, research processes are always needed to determine successes and failures. The research processes often rely on the data/information collected and stored in the healthcare databases. The application of statistical knowledge to analyze, interpret and present data is necessary to determine possible areas of weaknesses in healthcare systems. Valid and applicable statistical information can be applied to determine future outcomes in healthcare delivery processes as a scenario that may inform possible changes required to ensure continuous quality performance. Most healthcare institutions are involved in the collection and storage of data at every stage of treatment processes. Capture and storage of these data require the application of statistical knowledge (Marques et al., 2018). Besides, the data gathered can be applied in clinical trials to determine quality treatment approaches that can be applied to reduce errors and increasing problems such as healthcare-acquired infections. Through clinical trials, medical researchers have been able to identify the adverse effects of drugs and some procedures used in the treatment of patients.        

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HLT-362V Application of Statistics in Health Care

HLT-362V Topic 5 ASSIGNMENT 2 Summary and Descriptive Statistics

The understanding of the prevalence of diseases requires statistical methods. Healthcare institutions require advanced information on how to manage different forms of diseases. For instance, when there is an outbreak of infectious diseases, healthcare institutions often engage inadequate preparations for the management of possible patient influx; they mostly utilize the knowledge of statistics to determine trends or the levels of infections. Further, epidemiology, which is a major area of medical research, entirely relies on statistical knowledge. Epidemiology, also referred to as biostatistics, is an integration of statistics and microbiology to facilitate studies of diseases among populations.   

The knowledge of statistics is significant to quality improvement, the safety of healthcare delivery, health promotion, and leadership. Quality improvement processes rely on statistical knowledge to determine the evaluation of the outcomes and the procedures that can be undertaken (Ekin, 2019). Setting safety standards in healthcare facilities rely on the data analysis outcomes and the interpretation of possible procedures that may lead to unsafe delivery of healthcare services. Finally, the knowledge of statistics in healthcare has great significance in leadership and management. To make correct decisions, leaders and healthcare managers rely on the outcomes of the statistical research outcomes. Leaders also apply statistical knowledge to predict results, address complex or technical issues, and provide an elaborate solution to general problems impacting healthcare institutions. 

How Statistical Knowledge Is Utilized in My Healthcare Organization 

In my organization, statistical knowledge is applied to determine trends in patient admission and nurse-to-patient ratio. The trends are always determined after careful analysis of medical information or data that have been collected for a given period. For my organization, the presence of statisticians who are continuously involved in the research processes has been a blessing to the organization, particularly setting operational standards and recruiting enough nurses for better services amidst the increasing number of patients. 

Moreover, data collection processes in my healthcare organization involve the use of technology. There are well-established EMR systems and databases that facilitate the capture and storage of clinical data. Patient information/data are always taken from the point of admission, treatment processes, and discharge. Healthcare professionals are well trained on how to apply the EMR systems to capture patient data. At the moment, the organization has a wide array of data that can be analyzed and the outcomes used in the decision-making processes.   

Conclusion 

Statistics refers to the science concerned with studying and developing procedures or methods gathering, analyzing, interpreting, and presenting empirical data for decision-making purposes. The knowledge of statistics is important in different sectors. Today’s operational processes rely on data that can only be generated and analyzed by those with knowledge of statistics. Today, statistics is widely applied by healthcare organizations to determine the level of performance and the outcomes of different processes. Governmental institutions, particularly those involved in the development of healthcare policies, rely on statistical data to determine the population’s overall well-being. 

References 

Ekin, T. (2019). Health care systems and fraud. Statistics and Health Care Fraud, 1-30. 

Marques, C. S., Santos, G., Marques, V., & Ramos, E. (2018, September). The impact of knowledge creation, acquisition, and transfer on innovation in the healthcare sector. In European Conference on Knowledge Management (pp. 494-502). Academic Conferences International Limited. https://www.proquest.com/openview/56146799514cd6f30fadfe7f6739975b/1?pq-origsite=gscholar&cbl=1796412 

McGee, D., Lorencatto, F., Matvienko-Sikar, K., & Toomey, E. (2018). Surveying knowledge, practice, and attitudes towards intervention fidelity within trials of complex healthcare interventions. Trials, 19(1), 1-14. https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-018-2838-6 

HLT-362V Summary and Descriptive Statistics Sample Answer

Summary and Descriptive Statistics 

Descriptive statistics include measures of variability and measures of central tendency. Both measures of variability and central tendency are used to determine the normality of data. Common measures of central tendency include mean, median, and mode. These measures can also be used to determine the distribution of the dataset used in a study. Other measures of central tendency include kurtosis, Skewness, maximum, and minimum. Measures of variability determine the spread or dispersion of data for a given data set. The purpose of this assignment is to determine measures of central tendency and variability for the National Cancer Institute data set.   

Measures of Central Tendency 

Measures of central tendency are used to determine different attributes of data. Alternatively, measures of central tendency can be defined as the single value that is applied in describing a set of data by identifying the central point within a given set of data. Before undertaking data analysis, there is always the need to determine measures of central tendencies to understand the distribution of a given set of data (Amrhein et al., 2019). Measures of central tendencies include mode, median, mean, maximum, minimum, standard deviation, range, and frequencies. Descriptive statistics are always applied by data analysts to determine the normality of data before deciding on the type of statistical test to use. For instance, both the mean and median can be used to determine the distribution of data and thereafter types of inferential statistics to utilize in the process of data analysis (Kaliyadan & Kulkarni, 2019). Before engaging in the analysis of any type of data set, there is the need for the determination of the descriptive statistics so as to inform the entire process.   

The tables presented below indicate the descriptive statistics for the National Cancer Institute. The process of data collection was undertaken through the application of a Microsoft Excel spreadsheet. Excel formulas were mainly applied in the determination of measures of central tendencies, including mean, median, and mode.  

Table 1 

Table 2 

Table 3 

Table 4 

Table 5 

From table 1 to table 5, there is the presentation of the descriptive statistics for the races included in the study. The values of data were recorded for every 100,000 individuals. Going by the mean of the data, the black community had the highest rate of cancer complications, with Whites coming second. The mean of the black race suffering from cancer complications exceeded the mean for all other races. Mode and media from the analysis also indicate a continuous and normally distributed dataset used in the analysis. Hispanics showed the lowest rates of cancer infections going by the mean and median presented. The dataset used in the study was gathered for a period of five years, starting from the year 2000 to 2016. The lowest rate of cancer infection was recorded as 32, while the highest rate was 51.7.     

Table 6: Measures of Variation 

Figure 6 indicates measures of variation for the descriptive statistics given in tables 1 to 5 above. The highest variation was recorded among the participants from the black race. The highest mean recorded by the black race also indicated the highest variation. The measures of variation were also recorded for every 100,000 persons. From the table, maximum and minimum measures were also used in determining the variation of the data presented in the dataset.    

Conclusion 

The epidemiological study point to race as a major factor in cancer susceptibility. Individuals of African origin have an increased risk of cancer compared to other races, Asian Americans and Caucasians. The measures of central tendency and variability from the data clearly show the differences in the rates of susceptibility to risks of cancer for different races involved in the study. The mean of the black race suffering from cancer complications exceeded the mean for all other races. Mode and media from the analysis also indicate a continuous and normally distributed dataset used in the analysis. 

References 

Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician, 73(sup1), 262-270. Retrieved from: https://doi.org/10.1080/00031305.2018.1543137 

Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian dermatology online journal, 10(1), 82. Retrieved from: 10.4103/idoj.IDOJ_468_18