Historical Application of Statistics in Healthcare and Florence Nightingale’s Contribution | Assignment Collections | assignmentcollections.com

Since ancient times, the integration of statistical analysis methods in public health research is an essential asset in healthcare agencies. Health statistics provide empirical data to assist in allocation of public and private funds, enable understanding of population characteristics like disease mortality rates, incidence, morbidity or prevalence, and quantification of health disparities. Moreover, previous scholars such as Florence Nightingale have impacted the health industry through applications of statistical models to demonstrate required healthcare initiatives.

During the eighteenth century, registrars and physicians applied numerical methods to understand the bills of mortality. Clinicians such as William Farr (1807-1883) developed vital statistics and wrote about medical reforms that were presumed to enhance medical research (Newsholme, 2016). Farr insisted that physicians should adopt critical approaches like the use of logarithms, ratios and calculus of probability to investigate accuracy of data and discover population relationships. For instance, Farr used the vital statistics data in the 1841 census in England to put together tables and analyze mortality statistics. He also introduced the death certificate in 1845 through his analysis (Newsholme, 2016). Farr’s methods are applied in current health systems to define standard expressions of mortality using the life table and life expectancy.

Additionally, Florence Nightingale (1820 – 1910) contributed to the use of statistical information, particularly in graphical representation of data for purposes of establishing health policies. Florence is credited with developing polar area diagrams, which she used to demonstrate causes of patient mortality in a military field hospital she once managed (McDonald, 2016). For example, Nightingale compiled graphical reports on the British Army in India to explain how contaminated water, overcrowding, and poor ventilation caused high death rates (Cohen, 1984). Her graphical displays gave a comprehensive study in Indian rural life and established interventions that improved medical care and public health services.

These sporadic statistical inventions from ancient medical and nursing researchers enhanced the effectiveness of health systems in analyzing data. Likewise, physicians gained an ability to determine causes of disease epidemics besides finding appropriate interventions to prevent further infections.