Describe the application of statistics in health care. Specifically discuss its significance to quality, safety, health promotion, and leadership
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.
Three peer-reviewed, scholarly or professional references are required.
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Expert Answer and Explanation
Applied Statistics for Healthcare Profession
Statistical analysis in the health department helps in decision making and predictions since it gives a trend that healthcare providers can follow to better administer services (Frost, 2021). The information collected from the observations and measurements majorly describe the characteristics of the sample population at hand. The main aim of this paper is to discuss the significance of statistical application in healthcare.
Application of Statistics in Healthcare
Health statistics are important since they provide information that assists in the allocation of medical resources such as funds that are vital for research purposes. The quality of patient care is hence improved along with better policies and techniques for infection control (Baylina et al., 2018). When analysts use statistical methods correctly, accurate results are guaranteed since this type of analysis caters to errors and uncertainty in the results.
In quality control, statistical analysis methods are used to monitor, measure, and maintain the overall value of products. The results obtained in turn help processes such as manufacturing to ensure less wastage and time taken to manufacture medicine. Healthcare providers in this case work to ensure effective goods are produced and services are efficiently offered.
In healthcare, statistics help to understand how secure and safe working environments are since they narrow down to the group of workers most vulnerable (Boserup et al., 2020). Given this information, improvements in the areas that are considered dangerous to the healthcare provider are made to ensure good services are offered all around.
Health promotion benefits largely from statistical analysis in healthcare since the trends laid down by statistical methods, provide reliable data that greatly assist in the allocation of private and public finances and this affects how research is carried out (Baylina et al., 2018). The statistical analysis method is an important component in the needs assessment sector since budget expenses presented to various governing boards are properly used and can be accounted for.
Healthcare leadership can be greatly improved by the use of statistical methods (Fox-Tatum, 2021). Identification of trends and specific trails can ensure leaders being chosen can be relied on by other staff members. Available information on the leaders guaranteed by the help of statistical analysis helps the healthcare organizations to be confident in the success of the healthcare organization.
Acquisition and Usage of Statistical Data
Acquisition of Statistical Data
There are several processes to acquire information that can be used in statistical analysis in the healthcare profession. One of the means is data mining. This is a process of acquiring specific information or data from a large pool of data (Kumar et al., 2019). The process of data mining involves the stages of defining the information, finding the exact pieces of information being sought, and extracting the information from the large pool of data.
In this whole process, the information is recovered, merged, managed, and prepared for analysis. The resultant information following data mining is then analyzed and organized in a usable format (Kumar et al., 2019). After this process, patients and the professionals in the healthcare department benefit since the mined information can be refined to finer detail hence improving the overall status of healthcare for both the professional and the patients.
Usage of Statistical Data
Statistical knowledge can be used day to day in the healthcare profession. With this range of statistical information, individuals can monitor medical expenses on a day-to-day basis, healthcare costs, and hospital statistics. Considering the COVID-19 pandemic, statistical data is used by both healthcare professionals and even patients and other individuals to identify the trend of occurrences (Boserup et al., 2020). A lot of statistical issues are vital in the analysis of public health information in the healthcare profession.
When it comes to decision-making, statistical data plays a big influential factor. Given that statistical analysis involves the process of collecting data samples, and analyzing the data sample to discover patterns and trends to predict what could potentially happen next, the decision that comes thereof is guaranteed to be well thought through (Kumar et al., 2019).
In the healthcare profession, good decisions are a product of good statistics. Having a strong baseline of facts aids in minimizing the risks of healthcare challenges.
Conclusion
In conclusion, this paper has discussed the significance of statistical analysis for the healthcare profession. Statistical analysis for healthcare professions is vital since it majorly influences how safety, quality, health promotion, and leadership can be improved. With the information obtained through data mining, cleaned, analyzed, and stored, the healthcare profession is guaranteed that information given is purely factual and statistical and how it influences the overall performance of the profession is secure.
References
Baylina, P., Barros, C., Fonte, C., Alves, S., & Rocha, Á. (2018). Healthcare workers: Occupational health promotion and patient safety. Journal of medical systems, 42(9), 1-8
https://doi.org/10.1007/s10916-018-1013-7
Boserup, B., McKenney, M., & Elkbuli, A. (2020). The impact of the COVID-19 pandemic on emergency department visits and patient safety in the United States. The American journal of emergency medicine, 38(9), 1732-1736.
https://doi.org/10.1016/j.ajem.2020.06.007
Fox-Tatum, Oliver. (2021, March 1). Statistical leadership: Make your analytical insights count. GSS – The Government Statistical Service (GSS). https://gss.civilservice.gov.uk/blog/statistical-leadership-make-your-analytical-insights-count/
Kumar, S. R., Gayathri, N., Muthuramalingam, S., Balamurugan, B., Ramesh, C., & Nallakaruppan, M. K. (2019). Medical big data mining and processing in e-healthcare. In Internet of things in biomedical engineering (pp. 323-339). Academic Press.
https://doi.org/10.1016/B978-0-12-817356-5.00016-4
Frost, Jim. (2021, January 19). The importance of statistics. Statistics By Jim. https://statisticsbyjim.com/basics/importance-statistics/
Alternative Expert Answer and Explanation
Statistics in Healthcare
Statistics is a form of mathematical analysis that applies synopses, quantified models, and representations of a specific set of real-life studies or experimental information (Maronna et al., 2019). The authors also report that researchers can use statistics to study methodologies in a move to collect, analyze, review, and determine the conclusions from available information.
Some of the measures in statistics include skewness, mean, variance, regression analysis, kurtosis, and analysis variance (Siegel et al., 2016). In statistics, mean is used to measure the average of a given data set. Regression analysis is used to determine how one factor affects the other. For instance, the extend at which nurse shortage affects patient care.
Skewness can be used to describe the extend at which the given factor varies from the standard distribution in a set of information (Maronna et al., 2019). Kurtosis is used to measure whether a data set is heavy-tallied or light-tallied that the normal distribution. Variance is used to measure a span of numbers in a set of information. Statistics is a branch of mathematics but can be used in healthcare for various reasons. That said, this assignment describes the significance of statistics in the healthcare sector.
Application of Statistics in Healthcare
Healthcare decision making in healthcare practice largely depends on statistical data gathered from observations or measurements that describe the features of specific populations under quantitative healthcare studies. Sharples (2018) mentions that healthcare providers use descriptive statistics to summarize the costs, efficacy, and utility of medical services and products.
The healthcare institutions also use statistical analysis to measure the performance of the facilities. For instance, organizations can use continuous quality improvement projects that are data-driven to maximize their performance and efficiency. Healthcare agencies use statistical information to gauge the quality of medications and treatment protocols.
For instance, the agencies can assess the quality of medication by analyzing the number of patients in the randomized controlled trails who responded well to the drugs. Also, through statistics, the agencies can determine whether the population used in the study can be generalized to a larger group (Kaur et al., 2018). Lastly, the healthcare industry can improve the quality of care by determining the demographics and the type of care available for them.
Statistics can be helpful in health promotion. For instance, healthcare providers can statistically conduct research to find out the healthcare issues affecting the people in the community. Quantitative research can show how race, sex, disabilities, age, and income can affect the health of people in a community (Kaur et al., 2018).
Also, through statistics, nurses can recruit populations to be included in any health promotion programs. Another significance of statistics in promotion is measuring whether the program has achieved its aims or not. Statistics can also be used by healthcare leaders to improve their workplace leadership.
For instance, through statistics, a leader can measure the satisfaction rate of their workers and, from there, determine how to improve their morale. Also, through statistics, leaders can conduct a quantitative study about their workplace safety and improve it in case changes are required. Sharples (2018) reports that statistics has led to achievements in disease modification and personalized medicine.
Utilizing Statistical Knowledge in Care Specialty
In my care setting, statistical data can be collected in the following ways, first, through surveys. A survey is a process where a researcher distributes questionnaires to a population to collect data about a healthcare issue under study (Peace & Hsu, 2018). Apart from surveys, data can be collected through interviews.
Healthcare professionals can gather information by structuring an interview with the specific population. The interview can either be face-to-face or through an online platform. Apart from interviews, document review can be used to collect information in my care setting. The institution can review information from other healthcare agencies and find out the medical issues affecting the population under study. Case analysis is another way of collecting data in healthcare institutions, especially where I work.
Case analysis is the process of analyzing the cases in the hospital in a move to collect information. All the methods above can provide the hospital with accurate information for making informed decisions. After gathering data, the information can be used for various activities in day to day operations of the hospital.
For instance, the data can be used in making decisions about which promotion program should be given priority. Also, the data can be used, confirming whether the researched medications are safe for use by the target population. In terms of leadership, the collected data can be used to make decisions about the best interventions to apply in improving nurse satisfaction, motivation, and reduce burnout and shortage.
Conclusion
Statistics is important in healthcare in that it can be used to improve the quality of medical interventions, conduct health promotions, and to make other vital decisions in the medical sector. For instance, the statistic has been so vital in personalized medicine and disease modification processes. Some of the ways in gathering statistical data include interviews, surveys, case analysis, and document reviews.
References
Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60. Retrieved from http://www.ijam-web.org/article.asp?issn=2455-5568;year=2018;volume=4;issue=1;spage=60;epage=63;aulast=Kaur
Maronna, R. A., Martin, R. D., Yohai, V. J., & Salibián-Barrera, M. (2019). Robust statistics: theory and methods (with R). John Wiley & Sons.
Peace K., & Hsu, Jp. (2018). The Importance of Statistics in Medical Science Available from: https://www.researchgate.net/publication/237518872_The_Importance_of_Statistics_in_Medica_Science. [Last accessed 2019 May 05].
Sharples, L. D. (2018). The role of statistics in the era of big data: Electronic health records for healthcare research. Statistics & Probability Letters, 136, 105-110. https://doi.org/10.1016/j.spl.2018.02.044
Siegel, R. L., Miller, K. D., & Jemal, A. (2016). Cancer statistics, 2016. CA: a cancer journal for clinicians, 66(1), 7-30.
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FAQs
Significance of statistics to quality safety health promotion and leadership
Statistics plays a crucial role in quality, safety, health promotion, and leadership in several ways. Here are some of the key ways:
- Quality: Statistics helps in measuring and monitoring the quality of products or services provided by an organization. By analyzing data, organizations can identify quality issues, determine their root causes, and implement corrective actions to improve quality.
- Safety: Statistics helps in identifying potential safety hazards and risks. By analyzing data, organizations can identify patterns and trends that may lead to safety incidents and take corrective actions to prevent them. Statistics also helps in measuring the effectiveness of safety programs and initiatives.
- Health Promotion: Statistics helps in identifying health trends and patterns. By analyzing data, organizations can identify health issues, determine their root causes, and implement initiatives to promote health and prevent illness. Statistics also helps in measuring the effectiveness of health promotion programs and initiatives.
- Leadership: Statistics helps leaders make informed decisions. By analyzing data, leaders can identify trends, patterns, and opportunities for improvement. Statistics also helps leaders measure the effectiveness of initiatives and programs and make data-driven decisions.
Application of statistics in health care leadership
Statistics has several applications in health care leadership. Here are some of the key ways in which statistics is used in health care leadership:
- Performance Measurement: Health care leaders use statistical methods to measure the performance of health care facilities, programs, and providers. For example, statistical methods can be used to measure patient satisfaction, readmission rates, and mortality rates.
- Quality Improvement: Health care leaders use statistical methods to identify areas for improvement in patient care. Statistical methods can be used to identify trends and patterns in patient outcomes, which can then be used to develop quality improvement initiatives.
- Resource Allocation: Health care leaders use statistical methods to allocate resources effectively. For example, statistical methods can be used to predict patient volumes and identify staffing needs.
- Risk Assessment: Health care leaders use statistical methods to assess and manage risk. Statistical methods can be used to identify patient populations that are at high risk for certain health conditions, which can then be used to develop targeted interventions.
- Research: Health care leaders use statistical methods to conduct research studies. Statistical methods are used to analyze data and draw conclusions about the effectiveness of treatments, interventions, and programs.
Significance of statistics in health promotion
Statistics plays a vital role in health promotion in several ways. Here are some of the key ways:
- Identifying Health Trends: Statistics helps to identify patterns and trends in health outcomes, such as the prevalence of certain diseases, health behaviors, and risk factors. This information is essential in developing health promotion interventions that are evidence-based and relevant to the needs of the community.
- Measuring the Effectiveness of Interventions: Statistics helps to evaluate the impact of health promotion interventions. Statistical methods can be used to determine whether an intervention is effective in changing health behaviors, reducing the incidence of diseases, and improving health outcomes.
- Resource Allocation: Statistics helps in the allocation of resources for health promotion initiatives. By analyzing data on health behaviors and risk factors, health promotion professionals can identify priority areas for intervention and allocate resources accordingly.
- Planning and Evaluation: Statistics plays a critical role in the planning and evaluation of health promotion initiatives. Statistical methods can be used to set objectives, develop strategies, and monitor progress towards achieving the desired outcomes.
- Identifying Health Inequalities: Statistics helps to identify health inequalities and disparities, such as differences in health outcomes based on socioeconomic status, race, and gender. This information is essential in developing targeted health promotion interventions that address the specific needs of marginalized communities.
Discuss the historical application of statistics in the field of health care
Statistics has been used in the field of healthcare for centuries, and its application has evolved over time. Here is a brief overview of the historical application of statistics in healthcare:
- 17th-18th Century: The use of statistics in healthcare began in the 17th century with the publication of John Graunt’s book “Natural and Political Observations Made upon the Bills of Mortality.” Graunt analyzed data from London’s death records and calculated mortality rates for different causes of death. This book is considered to be one of the first attempts at using statistics in healthcare.
- 19th Century: In the 19th century, the field of biostatistics began to emerge. Biostatistics is the application of statistical methods to biological and medical data. One of the key figures in this field was Adolphe Quetelet, who developed the concept of the “average man” and used statistical methods to study the relationship between height, weight, and other physical characteristics.
- Early 20th Century: In the early 20th century, statistical methods were used to study the spread of infectious diseases. Ronald Ross, a British physician, used statistical methods to study the spread of malaria in India and helped develop effective control strategies.
- Mid-20th Century: In the mid-20th century, statistical methods were used to study the effectiveness of medical treatments. For example, the randomized controlled trial, which is now widely used to evaluate the effectiveness of medical interventions, was first introduced in the 1940s.
- Late 20th Century – Present: In the late 20th century and the present day, statistical methods continue to be used to study a wide range of healthcare issues, including the epidemiology of diseases, the effectiveness of medical treatments, and the allocation of healthcare resources.
In summary, the application of statistics in healthcare has a long and rich history. From the analysis of death records in the 17th century to the randomized controlled trial in the 20th century, statistical methods have been used to advance our understanding of health and disease and improve healthcare outcomes.
