HLT 362 Discuss the historical application of statistics in the field of health care
HLT 362 Discuss the historical application of statistics in the field of health care
HLT 362 Discuss the historical application of statistics in the field of health care
History of Statistics
Statistics is not a newly developed concept when it comes to looking for answers. In fact, it has been around for hundreds of years. “The roots of nursing practice are based on the use and statistical analysis of patient data” (Ambrose et al., 2022). Health statistics provide data to assist in the allocation of public as well as private funds. Statistics also enable the understanding of population characteristics, for example, disease mortality rates, morbidity or prevalence, and even quantification of health disparities. Previous scholars such as Florence Nightingale have impacted the health industry through the use of statistics to demonstrate needed healthcare initiatives.
Example of Statistical Application in Healthcare
Because of how complex the human body, and mind are, and the ways in which all of these aspects interact with their surroundings, statisticians and nursing researchers need to work together on a continuous basis. Sir Edwin Chadwick (1800-1890) had written a report in 2842 on the sanitary conditions among the laboring population in Great Britain. “Edwin demonstrated the existence of a mass of preventable illnesses and premature death in the community caused, he argued, by unsanitary physical circumstances” (Green et al., 2018). The painstaking documentation of statistical evidence written in his report about the social and spatial inequalities in health and unsanitary conditions is one of the earliest (1824) examples of providing evidence-based health advice to the public. His findings provided the foundation for advances made later on by figures such as William Farr (Green et al., 2018).
References
Ambrose, J., Helbig, J., Ryan, C., & Torres, E. (2022). Applied Statistics for Healthcare (Second Edition ed.). Grand Canyon University. https://bibliu.com/app/#/view/books/1000000000581/epub/Chapter1.html#page_8
Green, M. A., Dorling, D., & Mitchell, R. (2018, January). Updating Edwin Chadwick’s seminal work on geographical inequalities by occupation. National Library of Medicine, 59-62. 10.1016/j.socscimed.2017.11.055
That is an interesting example of how early statisticians like Edwin Chadwick had a significant impact on how we approach healthcare today. You are right that the use of statistics to provide evidence-based health advice has been around for centuries. As you mentioned, Florence Nightingale was another pioneer in this field, and she is credited for the modern use of pie charts, line graphs, and histograms to track data. She was also known for her work in developing the first hospital-based nursing school which used a data-driven approach to show that better hygiene practices could lower mortality rates (Lane, 2020). The work of these early figures in developing healthcare has been extremely influential to the field of healthcare today and it is amazing to see how far we have come.
Reference
Lane, C. (2020). Nursing: The Finest Art. Florence Nightingale. Retrieved August 12, 2020, from https://www.florence-nightingale.co.uk/nursing-the-finest-art/florence-nightingale/
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in planning and improving healthcare activities as well as allocating resources to be used. Statistics were also used in healthcare to analyze research data, laboratory results, outcomes of treatment and the epidemiology of some condition (Health statistics: Past, present, and future – Toward a health statistics system for the 21st century – NCBI bookshelf, n.d.). With the statistical data, there has been significant improvement in the quality of care delivered and safety of patients since previous data inform the current practice on what to do and what to avoid. Use of statistics has been applied in preventing and managing infections in care facilities. Statistical methods such as rates, ratios and proportions have been used to present data concerning infections in care
facilities hence informing the stakeholders on the appropriate methods of
minimizing the cases (Basic statistics for infection Preventionists, 2019).
References:
Health statistics: Past, present, and future – Toward a health
statistics system for the 21st century – NCBI bookshelf. (n.d.). National
Center for Biotechnology
Information. https://www.ncbi.nlm.nih.gov/books/NBK223602/
Basic statistics for infection Preventionists. (2019, February
15). APIC. https://apic.org/course/basic-statistics-for-infection-preventionists/
The historical application of statistics has been used in healthcare for many years to analyze data and create and utilize evidence-based practice. Evidence-based practice is important because it helps improve patient outcomes and quality of life (Helbig, & Ambrose, 2018). As we know nurses and other healthcare professionals use data from the statistics. As we know, Nightingale contributed to statistics on injuries, infection, and insanitary conditions, gathered that data and used it to help improve infection rates, mortality rates, and decrease injuries. Edwin Chadwick has greatly influenced health care practice when he appointed the poor sanitations. He used statistics to help improve sanitary conditions in turn improving individuals’ quality of life. Clara Barton was also a nurse who focused on the quality of life and health of the public. She used the application of statistics to change health cate by establishing the red cross, building data on the thousands of people homeless and helped raise money, food and supplies to aid survivors (Bolick, 2021).

Reference
Bolick , K. (2021, December 1). Clara Barton epitomized the heroism of Nurses. Smithsonian.com. Retrieved January 31, 2023, from https://www.smithsonianmag.com/history/clara-barton-hero-nurse-180979006/
Helbig, J. & Ambrose, J. (2018). Applied Statistics for Health Care. https://www.gcumedia.com/digital-resources/grand-canyon- university/2018/applied-statistics-for-health-care_1e.php
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 has been used in the health care field for centuries, beginning with the contributions of Florence Nightingale in the mid 1800s. Since then, statistics have been used to better understand and improve patient care. One example of this is the use of statistical process control (SPC) in health care. SPC is a data-driven method of monitoring and controlling processes, and has been used in the health care field since the 1970s. SPC has been used to measure and improve the quality of care and patient outcomes, as well as to monitor and reduce medical errors and costs.
More recently, statistics has been used to understand and analyze health care data from sources such as electronic health records (EHRs). This data can be used to understand trends in patient care and outcomes, and to identify gaps in care, such as inadequate access to care for certain patients or populations. This data can also be used to inform decisions about care and to improve patient outcomes. For example, a recent study published in the Journal of the American Medical Informatics Association found that the use of EHR data to identify and intervene in high-risk patients with diabetes was associated with improved patient outcomes (Ahmed et al., 2020).
In conclusion, statistics has been used in the health care field for centuries, and has significantly improved patient care and outcomes. From SPC to the use of EHR data, statistics has been used to measure and improve the quality of care, reduce medical errors and costs, and inform decisions about care.
References
Ahmed, A. M., Zhao, Y., Hong, Q., Yoon, S. L., & Zheng, J. (2020). Impact of using electronic health record data to identify and intervene in high-risk patients with diabetes. Journal of the American Medical Informatics Association, 27(3), 355-363. https://doi.org/10.1093/jamia/ocaa029