Statistical application in healthcare

Statistical application in healthcare

Statistics is the collection and analysis of data in large quantities drawing references for uptake in decision-making. Healthcare cuts across all the facets of human life, thus involve the collection of volumes of data to detect the trends in particular healthcare issues. Statistics in healthcare are vast, ranging from biomedical laboratory research, health promotions, national and global health systems, epidemiology, and clinical research. Collectively, statistics in healthcare are referred to as biostatistics, which helps medics design and undertakes studies to identify real causes of health issues (Daniel, 2018). It also does researches to make sense of data collected before actualization in the entire program. In this document, therefore, our objective will be critical of statistical applications in healthcare programs.

Statistics are essential for quality assurance in healthcare as they provide a benchmark against which success or failure measurement is useful.  Statistics provide prediction models that quality managers can utilize in measuring future results. Basing on the effectiveness of the product in a said market, the product developers can improve their systems to achieve the quality required. Additionally, quality is improved, as there is robust product design as it bases on the conditions of the real world (Daniel, 2018). Data increases cognizance with environmental factors through utilizing a lot of models in identifying metrics related to a disease.

Statistics are also crucial for improving safety in healthcare; statisticians often help in the development of new consistent and efficient statistical measures for self-recorded conditions. Through questionnaires, healthcare providers sort effective means in the satisfaction of healthcare (Bauer, 2017). Moreover, statistics ensures the availability of better information about patients, thus informing more effective treatment techniques. Statistics have also contributed to robust ways of assessing disease risks; for example, heart attack probability is dependent on behavior, history, and environment. Statisticians, therefore, have intricate assessment tools that hat can predict the chance of patients to such occurrences. These systems are essential in the guidance on the possibility of recommendations for a possible screening fostering early detection and treatment. Ultimately, these systems help in lowering health costs and minimizing risks of disease dominance.

In health promotion, statistics are useful in epidemiology showing the extent of the spread of contagious diseases such as Flu or Ebola. For example, in West Africa, with the outbreak of the Ebola virus in 2016, statistical parameters were used to inform the extent of the spread of the virus, which informed the extent of quarantine in the said region. Similarly, the Gates Foundation, in their quest to make the globe polio-free used statistical parameters to show the extent of spread. In our department, however, statistics will help in identifying specific patterns in symptoms and signs, thus ensuring an effective response to pathological changes occurring in the patient (Bauer, 2017).  It also provides an avenue for different nursing options when decision-making is at stake in cases where our experience and instincts have been compromised in one way or the other; statistics can help in providing the best option possible such as choice of administrations sets or intravenous fluids.

In leadership, statistics will help in providing the best approaches for employee training. Statistics provide a baseline for attrition rates and other environmental factors that will be useful in training new nurses.  Moreover, statistical data ensure the determination of financial data for various activities in the institution. This will, therefore, work to inform our monetary policies, which would ultimately translate to adequate healthcare provision. This is so as medical supplies will always be available on time without financial challenges that often rock and deter effective service delivery in health centers.

Healthcare data emanates from various sources such as medical records, surveys, disease entries, peer-reviewed literature, among many more. In conducting studies, we use in depth interviews via phone or in-person and questionnaires, whose scope and design are geared towards particular details of concern (Soni et al., 2017). We also check on vital records such as information on rare disorders, deaths, and marriages. Additionally, we consult peer-reviewed academic databases such as MEDLINE, American Psychological Association, and Embase.  The data is useful in informing the type and extent of medication based on a unique condition.

Moreover, the data helps us in needs assessment; that is, based on the conditions of a patient, the data will help in providing pertinent information on how to deal with a situation (Soni et al., 2017). We also use the data in informing our resource allocation, the samples of the human population, such as age, sex, and disabilities help in predicting the type of healthcare that is commensurate with their income. Finally, the statistics are useful in an adequate and safe supply of blood. Statistics helps us in understanding the social demographics, health, and social factors, which ensure a reduction of risks related to transfusion. Besides, the data helps in dealing with cases of insufficient blood supply, thus informing outreach programs for blood donations to offset these challenges.

The right decisions require healthcare practitioners to have relevant information about the condition. Statistical analysis provides information on the trend of diseases and effective control mechanisms with the appropriate risk assessment tools that informs the best possible solution. Healthcare workers will, therefore, make decisions based on the sound statistical judgment from the varying parameters.

References

Bauer, J. C. (2017). Statistical Analysis for Decision Makers in Healthcare: Understanding and Evaluating Critical Information in Changing Times. CRC Press.

Daniel, W. W., & Cross, C. L. (2018). Biostatistics: a foundation for analysis in the health sciences. Wiley.

Soni, A. S., Weinert, S., Rasch-Menges, J., Walling, P. D., Bousamra, S. A., & Greenburg, A. M. (2017). U.S. Patent No. 9,659,037. Washington, DC: U.S. Patent and Trademark Office