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  1. Application of Statistics in Health Care   





    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.



Subject Nursing Pages 6 Style APA


Application of Statistics in Health Care

Major advancements in technology over the years as well as continued research in the area of computational statistics have paved way for advanced statistical applications and models (Leonelli & Tempini, 2018). Among others, these advancements have made it possible for situations to be described and predictions made based on the evidences generated from analysis of data. Many settings have benefitted from this possibility. Health care is one setting where data as well as statistical applications play a significant role in many ways. Many health care organizations make use of statistical applications to inform nearly, if not all, areas of their operations (Tilahun et al., 2018. These operations include but not limited to quality improvement, resource allocation, needs assessment and performance. This paper provides a synopsis of the importance of statistical application in the healthcare setting. Specifically, how statistical tools are applied in the area of quality, safety, health promotion and leadership is discussed. Further, statistical application in an identified specialty will be discussed, detailing how the data is obtained, how statistical knowledge is used in day-to-day operations and how it is applied in decision making.

Use of Statistical Application in the area of Quality

Various parameters are used in the measurement of quality in the healthcare setting. Organizational performances, service utility, allocation of health resources, employee productivity are areas that can be used to measure the quality of a health care organization employ (Vayena & Blasimme, 2018). To measure organizational performance, health care organizations use statistical application to measure their performance outcomes to implement continuous data driven program to improve quality of work and maximize efficiency variables can be measured at different period then using statistical analysis, it is possible to measure change. Based on this, decisions can be made about ways for improvement.

Statistical applications are also used to measure employee productivity. In a large pharmaceutical organization, it is possible to measure the extent to which each employee is delivering on their roles and goals. The data to be analyzed may be their job attendance and the number of hours spent working on a given task. A high score means that the quality is high and vice versa. All quality improvement measures in a healthcare organization should ultimately be based on evidences derived from data using statistical applications (Tilahun et al., 2018).

Use of Statistics in the Area of Safety

Many workers are exposed to preventable work place tragedies that affect their health and undermine the economy. Statistics has been widely used in workplace safety promotion initiatives the various organizations (Tilahun et al., 2018). By examining workplace safety, statistics can help health care organization managers to identify specific risks and come up with mitigation measures and policies against these risks. Data on the number of accidents occurring in an organization and their specific causes can be made available. Through use of statistical applications, these data can be analyzed in order to identity the leading causes of such accidents (employ (Vayena & Blasimme, 2018)). Statistics on lost work time is also used by organizations to come up with strategies that will compensate for such gaps.

Use of Statistics in the area of Health Promotion

Aside from curative services, many health care organizations have the mandate of disease prevention and health promotion (Leonelli & Tempini, 2018). Many countries have developed ‘out of hospital’ programs targeting community members with health promotion initiatives. In such countries, there exists a community based data system which captures demographic and other health related variables employ (Vayena & Blasimme, 2018). Such variables may include health seeking behaviour, household size, income levels, chronic disease and environmental hazards. These data are analyzed periodically, the results of which are used in coming up with health promotive strategies (Leonelli & Tempini, 2018; Tilahun et al., 2018). For instance, if statistical applications reveal poor sanitation in a given area, the health organization under whose jurisdiction the area is can decide to come up with health promotion strategies to improve sanitation.

Use of Statistics in the area of Leadership

To be leaders in innovations and service provision, health care organizations must use data in making decisions that are based on evidence. For example in clinical trials of new treatments, data are collected which can be used to compare new and old treatments, or weigh benefits against risks employ (Vayena & Blasimme, 2018). To gain price leadership, these organizations have to use data to determine optimal prices for their products. Pharmaceutical companies for instance, have a goal of producing the best products and services, most efficiently. They need statistical applications that will enable them make decisions on the most efficient strategies to employ (Vayena & Blasimme, 2018).

Application of Statistical Knowledge to Organization or Specialty Area

I work at a mother and child welfare clinic in a large city hospital. As a nurse taking care of pediatric and pregnant women patients who visit the clinic, I am charged with the responsibility of collecting various kinds of data from my patients. I also keep records of medical supplies where I track stock in and stock out as well as damages. Every time a patient comes for care, we record their age, gender, name, place of residence, whether it is a revisit or a new visit, medical history, medication given, parity, level of education, occupation, client satisfaction, diagnosis and gestation.

These data are collected every day. At the end of each data summaries are made. Through these summaries it is possible to know how many patients visited on a given day, their gender, the medications given and the diagnosis. These summaries allow the clinic to know the number of patients visiting each day, and as such use this data to allocate daily resources. The clinic is also able to identify common ailments and in case of a sudden increase on a given diseases, the management is able to come up with measures based on these evidences. Data on client satisfaction is specifically important because it provides views of the patient regarding the services provided the clinic. Any gaps are identified and measures put in place to improve the quality of service.

Because these data are collected over time, it is also possible to monitor trends of given variables. For example, the clinic uses data on number of children immunized to work out immunization coverage rates. In case this rate stalls or decreases below what is recommended, the clinic management comes up with strategies, such as outreach programs for health promotion.




 Tilahun, B., Teklu, A., Mancuso, A., Abebaw, Z., Dessie, K., & Zegeye, D.  (2018). How can the use of data within the immunisation programme be increased in order to improve data quality and ensure greater accountability in the health system? A protocol for implementation science study. Health Research Policy and Systems, (1), 1. https://doi.org/10.1186/s12961-018-0312-2

Leonelli, S., & Tempini, N. (2018). Where Health and Environment Meet: The Use of Invariant Parameters for Big Data Analysis. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=edsupp&AN=edsupp.14741&site=eds-live

Vayena, E., & Blasimme, A. (2018). Health Research with Big Data: Time for Systemic Oversight. Journal of Law, Medicine and Ethics, (Issue 1), 119. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=edshol&AN=edshol.hein.journals.medeth46.14&site=eds-live




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