Significance of Statistics in Health Care

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Table of Contents

Introduction
Application of Statistics to Health Care
Acute Hospital and Statistics
References

Introduction

The study of health care and medical practice as an umbrella term for various endeavors is explicitly interrelated with tangible and quantitative science, as any medical intervention should be scientifically justified prior to its wide application. One of the most widespread means of justifying information is gathering and systematizing statistical data based on empirical research. In a broad sense, statistical analysis concerns applying statistical testing to the categorization and assessment of empirical data in order to either justify or criticize an outlined hypothesis (Vandever, 2020). Thus, the aim of the present paper is to analyze the extent to which statistics and statistical analysis, in particular, are significant to health care, nursing competence, and the functioning of acute hospital facilities.

Application of Statistics to Health Care

Significance to Quality

Ensuring quality and efficient care is, by all means, the most important objective of statistics in health care. The vast majority of today’s healthcare research relies upon hypothesis-based statistical analysis. Essentially, researchers present a hypothesis concerning medical intervention. The hypothesis is then followed by gathering empirical data from medical cases and applying statistical analysis in order to evaluate the relevance of the hypothesis (Vandever. 2020). Regarding the fact that the hypotheses may concern all the aspects of patient experience, it becomes evident that statistics is a significant contributor to the quality of health care. For example, there is a study that applied statistical analysis in order to assess the quality of patients’ experiences both in public and private facilities (Fatima et al., 2018). The statistical data presented in the form of ranking provided practitioners with a perspective where private care is considered more patient-oriented and trustworthy. Hence, such studies help scholars and practitioners have a realistic perception of patient experience and, in the long-term perspective, contribute to their satisfaction within the setting.

Significance to Safety

One of the most challenging aspects of statistics and analysis is the ethical dilemma of securing one’s personal data used for the analysis. Currently, the vast majority of data for the statistics processing is collected through the systematization of the Electronic Health Records (EHR) filled in by the practitioners. However, according to researchers, since the introduction of wide EHR use, much progress has been made in the field of cybersecurity and encoding one’s sensitive data in the system through eliminating one’s name (McDermott et al., 2019). Hence, when used wisely and ethically, statistics present the quantitative interpretation of data solely while indicating no personal information.

Significance to Health Promotion

The demonstration of statistical data has already become an integral part of health promotion and public health administration. Since the establishment of the Centers for Disease Control and Prevention (CDC), people have obtained the chance to become more involved in public health while raising their awareness of the current health challenges tackling their community. The importance of statistics presented in the form of quantitative indicators such as percentage help draw the public’s attention to the information, as they tend to perceive information easier with the help of data. Hence, health promotion benefits significantly from the use of statistics.

Significance to Leadership

The employment of statistics within hospital settings and staff is crucial for the team’s productivity and long-term planning. When it comes to statistical analysis, some of the most important cases of statistical data include patient ratio and retention, patient-to-bed ratio, and readmission rates. A meticulous analysis of such data allows healthcare leaders to assess current gaps in terms of treatment and efficiency and create a roadmap of actions to improve the present scenario.

Acute Hospital and Statistics

Acute hospital facilities are to respond rapidly to various health scenarios in order to secure safe and efficient patient outcomes. As a result, it means that both administration and practitioners should have explicit access to current statistical data for the hospital, including the tabulation of data on the present hospital population, occupation rates, and the testing resources available for the patients. The data is primary obtained through the EHR system dilled in by the admission nurse and practitioner (Pasek, 2019). The system is connected to the overall facility’s electronic database, allowing the practitioners to access it anytime.

The first and the most common way of accessing statistical tools is the nurse’s interaction with the EHR. When working with patients, nurses have the ability to access all the previous information about the patient’s treatment in order not to waste time and focus more on the direct medical intervention. Another important daily interaction with statistics concerns filling the frequency charts and data sheets concerning medication intake plans and treatment schedules.

Finally, the decision-making process depends greatly on the ability to analyze statistics. Case manager nurses in acute hospitals bear the responsibility of creating a long-term intervention for the patient. Thus, it is imperative to address various options in order to find the most appropriate treatment given the patient’s individual peculiarities. Consulting the quantitative outcomes of the primary research and previous hospital interventions is a way to eliminate the risks of inefficiency and treatment incompatibility with the patient’s health history. Hence, it may be concluded that the application of statistics is beneficial for practically any aspect of medical practice.

References

Fatima, T., Malik, S. A., & Shabbir, A. (2018). Hospital healthcare service quality, patient satisfaction and loyalty.International Journal of Quality & Reliability Management, 35(6), 1195-1214. Web.

McDermott, D. S., Kamerer, J. L., & Birk, A. T. (2019). Electronic health records: A literature review of cyber threats and security measures. International Journal of Cyber Research and Education (IJCRE), 1(2), 42-49.

Pasek, L. (2019). Learning to do data science healthcare research. 45th Biennial Convention 2019, Washington, DC, US. Web.

Vandever, C. (2020). Introduction to research statistical analysis: An overview of the basics. HCA Healthcare Journal of Medicine, 1(2), 71-75. Web.

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