Effective health service delivery and management are based on the timely analysis of relevant data. It includes information on social, economic, demographic, environmental, and other health indicators. Such data are often presented in the form of medical statistics – rates of morbidity and recovery, allocation of resources, activities of medical institutions, and many other aspects. It is necessary for determining the causes of morbidity or death, their prevalence, and, based on the information received, for the allocation of resources.
Statistics play a significant role in improving the quality and safety of the medicine. Statistical evaluation of clinical research results determines doctors’ decisions in favor of the method of treatment being studied (Aggarwal, 2018). As a result of the inept use of statistical methods in the field of health services, many pseudo-studies and incorrect research findings may appear. The outcomes of such mistakes can be fatal since the reaction of patients to improper treatment is unpredictable.
Statistical studies are also designed to identify causal relationships between a particular lifestyle and health effects. Thus, for example, regular sports have been found to improve both physical and mental health. It was also determined that certain types of food, such as fried and fast food, have negative effects on the body, and vegetables or fruits – positive. Such statistics are widely used for health promotion – practical advice and recommendations have a scientific basis on the results of thousands of people’s observations. The seriousness of such arguments makes the necessary impression on people, and the application of the results helps prevent some diseases or accelerate recovery.
It is also crucial to note that statistics are indispensable in medicine at different leadership and management levels. The department leader in the hospital assesses their team’s effectiveness and each of its members basing on statistics. It is the rate of establishment and correctness of the diagnosis, the percentage and speed of patients’ recovery, and other similar data. The hospital’s head doctor assesses how effectively the allocated resources were used in the hospital and which doctors perform their work better.
Moreover, health statistics are used further – at higher levels of leadership. For example, local and state authorities also allocate resources based on morbidity, local demographics, and other indicators (Sousa et al., 2019). The high level of appointments to hospitals and the predominance of diseases of a specific type force them to pay attention to the causes. They can include polluted ecology, lack of necessary products, or violations of working conditions in large enterprises. Statistics and its analysis form a robust basis for making the required decisions in the field of health care.
Application of Statistics in Nursing
At first glance, nursing is limited to caring for patients, health promotion, and similar tasks. However, staff in this area should also have statistical skills to measure, understand, or interpret indicators. Patients may differently tolerate certain diseases or respond to treatment. Thus, nurses need to be prepared to display data based on specific signs correctly. Therefore, the work of a nurse requires a significant knowledge base and responsibility.
The foundation of the nurses’ job is empirical evidence that determines which work methods are useful and which are not. To be able to apply data-based practices correctly, staff in this area need knowledge of statistical analysis. Quality patient care involves nurses using data to determine priority in treatment, identify particular signs and patterns. Statistics and its methods of use can also be useful in scheduling medication.
The interpretation of statistical data by nurses significantly affects the decision-making process in a people treatment. During patient care, nurses draw many conclusions and make critical decisions that can affect recovery. For example, the degree of deviation from the norm of individual indicators, such as blood pressure, temperature, or pain, can affect a choice to call a doctor or change a medicine. Competently sharing responsibilities and assigning duties to skillful nurses can significantly save staff time and accelerate patient recovery.
Thus, the work of all health employees is related to the application of statistical analysis. Nurses are no exception – they apply statistical skills when observing patients and interpreting different data. To succeed, it is essential to respond quickly, monitor trends, and continuously improve performance. Moreover, modern technologies have opened up new possibilities in the use of statistics (Sharples, 2018). For these reasons, nurses should be ready to develop and learn continuously. Having such skills as statistical analysis helps shape medicine leaders.
Conclusion
There is currently no aspect of health services that do not use statistical methods. All of them are important – from statistical observation of various indicators (incidence of the population, number of doctors, and more) to analysis, modeling, and predicting these indicators. Today, statisticians’ participations in the planning and analysis of health services research is a traditional and ubiquitous practice. In the case of research, statistics help determine precisely the purpose and objectives of the study, choose methods, and establish the required number of patients to obtain a statistically significant opinion. Moreover, it is possible to analyze and interpret the results obtained with its help to develop a science-based conclusion. Statistics have a considerable impact not only on medical research but also on practice. Health care staff frequently apply data collection and analysis skills to improve patient health.
References
Aggarwal, R. (2018). Statistical literacy for healthcare professionals: Why is it important? Annals of Cardiac Anaesthesia, 21(4), 349-350.
Sharples, L. D. (2018). The role of statistics in the era of big data: Electronic health records for healthcare research. Statistics & Probability Letters, 136, 105-110.
Sousa, M. J., Pesqueira, A. M., Lemos, C., Sousa, M., & Rocha, Á. (2019). Decision-making based on big data analytics for people management in healthcare organizations. Journal of Medical Systems, 43(9), 290.