Application of Statistics in Health Care Paper

Application of Statistics in Health Care Paper

Statistics is undoubtedly significant in the health care sector. The day-to-day collaboration between statisticians and health care professionals is vital, and leads to extraction of relevant information that impacts patient care. According to the American Statistical Association [ASA] (2017), statistics refers to collection and analysis of large quantities of numerical data. In health care, the information inferred from the analyzed numerical data helps in monitoring ailments and treatments (ASA, 2017). The purpose of this paper is to relay the significance of statistics in health care, stating its applications in nursing, medicine and the health sector as a whole.

Application of Statistics in Health Care Paper

Assessment of Disease Risk

Assessment, in this context, refers to determining a person’s risk of having a particular disease or a condition. The risk of a person getting a disease depends on different factors, including but not limited to family history, lifestyle, cholesterol, age, weight and environment (ASA, 2017). To determine these factors, advanced statistical tools are required. The field of statistics has produced various risk assessment tools capable of predicting a patient’s probability of developing a disease. Ability to identify possible risk factors of a disease in an individual spurs the urgency for effective screening and early detection of a disease.

For example, risk assessment tools have been used to determine the risk for breast cancer, melanoma, and heart attack (ASA, 2017 Application of Statistics in Health Care Paper). The breast cancer risk assessment tools enables nurses to determine a woman’s risk of getting invasive cancer of the breast for the next five years and up to 90-years of age (ASA, 2017; Rodrigues, Lima, & Barbosa, 2017). The tool requires family history of first degree relative breast cancer, personal medical history and reproductive details. Similarly, the heart disease risk calculator also requires entry of personal health data such as age, gender, height, weight and race (ASA, 2017). The assessment enables nurses to identify early disease risk factors in an individual and determine appropriate interventions of treatment.

Informing Clinical Decisions

Statistics play a major role in medical decision making. Using an obstetric/gynecologic example, here is a case where statistics is used to make informed decisions. As women advance in their age, their fertility decreases. Additionally, the chance of having obstetric complications or bearing children with birth defects rises. Using statistical decision making tools, clinicians can advise women hopeful to be mothers in future, on the duration they can attempt natural pregnancy before opting for the use of in vitro fertilization or other fertility management technologies (ASA, 2017; CDC, 2020).

The tools also enable nurses to provide advice to women on healthy pregnancy ways such as appropriate nutrition (ASA, 2017). Examples of such statistical tools include the Pregnancy Mortality Surveillance System (PMSS). The PMSS is a United States-based statistical tool used to determine pregnancy-related deaths, its levels and causes (CDC, 2020). The information provided by the PMSS helps clinicians and nurses to understand the factors that cause pregnancy-related deaths and to determine appropriate interventions to mitigate them.

Understanding Disease Epidemiology

Often, disease epidemiology refers to its distribution and determinants. In the health sector, incidence, prevalence, morbidity and mortality rates of a disease play significant roles in determining the burden of the disease. These are aspects of basic statistics. According to the WHO (2016), incidence of a disease refers to the newly diagnosed cases. It allows health care professionals to estimate a person’s chance of being found with the disease (WHO, 2016). For example, the current WHO statistics on coronavirus pandemic reveals sex-based incidence as from 1st of November are as follows:

Female have an incidence of 406 cases/100,000 people while males have an incidence of 401.1 cases/100,000 people. Prevalence refers to the existing cases in a population (WHO, 2016). How frequent a disease appears in a population is termed as the morbidity rate (WHO, 2016). In health insurance, it is used to set the premium that customers pay. Mortality rate is the death rate in a specific population. It is possible to use statistical methods to determine the specific mortality rate of a given disease. Based on this review, statistics makes significant contribution to the practice of healthcare, as it help determine, among others, the burden of a disease, related contributing factors and specific interventions strategies to be used.

Measuring Patient Ailment

Patients present with various symptoms, measurable and non-measurable. Some of the symptoms that are difficult to measure include fatigue and pain. Even though these symptoms are hard to measure, statisticians have developed new statistical clinical measures that are consistent and efficient in measuring such symptoms (ASA, 2017). These include the use of questionnaire tools that adequately collects patients’ history (ASA, 2017). Use of such tools has been associated with improved patient satisfaction (ASA, 2017). Additionally, for many years, patient satisfaction survey tools have been used as a means of improving quality of care (Califf, 2016). It is a statistical tool that identifies gaps in the quality of care and helps care providers determine appropriate action plans to be initiated.

Importance in Blood Transfusion

It is essential that patients get adequate and safe blood supply. There are various factors surrounding the understanding of blood transfusion that deters the goals of achieving safe transfusion. These factors can be social, health, or demographic-related (ASA, 2017; Roubinian, Brambilla, & Murphy, 2017). To reduce the deterrent role of the factors, and to lower infections related to blood transfusion, sophisticated statistical modeling and analyses are a requirement (Roubinian et al., 2017). Nurses and other healthcare providers can in turn use the information obtained to minimize infections associated with blood transfusion. Additionally, due to the recent statistics on the outcomes of blood transfusion such as infections, various countries have initiated advanced inspection of the procedures used during and after blood transfusion (Roubinian et al., 2017). For example, the United States Food and Drug Administration set standards for safe collection, storage and manipulation of blood (Roubinian et al., 2017). This is one of the strides countries take to minimize the negative outcomes following allogeneic blood transfusion. Ultimately, such initiatives result in improved quality and safety of blood transfusion.

Resource Allocation

Since medical resources, just like any other resource, are scarce, it is possible to leverage statistical knowledge and methods in determining the most optimal way of allocating the scarce resources. For example, if the morbidity rate of diabetes is high within a specific population, health care economists can advise increased supply of anti-diabetic drugs and glucometers to that specific population (WHO, 2016). As a result, health care economists need to work together with statisticians to identify products to be produced, resources to allocate, and to what specific population thy would produce optimal outcomes.


Statistics has myriad applications in the health care sector. For this reason, statisticians and health care professionals should collaborate in their day-to-day practice to ensure provision of an integrated care to patients. Among the possible applications include resource allocation, product development, quality improvement, decision making, disease epidemiology and in blood transfusion. Additionally, statistics help in identifying specific risks and trends of disease within the population. The trends help health care providers to develop appropriate interventions and action plans for their patients. Despite its significance in health care, it has not been adequately utilized in diagnostic procedures spurring the need for further research.

Application of Statistics in Health Care Paper References