Statistics are used to recapitulate processes that a specialist, e.g., a nurse, uses to illustrate a data set in ways that make them easier to understand. Statistical analysis encompasses the process of congregation and assessing data and then summarizing it into a mathematical form (Bottle & Aylin, 2016). Health care providers use statistics to summarize information related to health since, more often, human responses to clinical treatments and interventions are infinitely variable and uncertain, and statistics caters for both uncertainty and variation.
In healthcare systems, statistics is applied in many areas. Firstly, to evaluate Clinical Intervention-Healthcare vocation is grounded on practical evidence that establishes operative protocols for patient care; thus, statistical knowledge is used to determine whether the treatment intercessions of healthcare providers' choice are useful. Statistics also aid in generalizing evidences such as healthcare behaviors, cancer, mortality, and morbidity attained in a study sample to the target population of attention. For example, Symptoms that necessitate patient reportage, such as ache and lethargy, are hard to quantify. Thus, statistical methods that help adapt inquiries to each patient while permitting comparisons to broader populations come in handy.
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Secondly, statistics are used to enhance patient care. Awareness of statistical principles aids in understanding and estimate the outcomes of health care studies. Statistics enable prioritization of handlings and determination of whether a patient requires instantaneous medical devotion or follow-up care. Another way of using statistics to enhance patient care maybe by detailing the average span of hospital stay or average rate of treating patients with specific diagnosis, the timing of medication specified to patients through data sheets and frequency charts. For example, finding out whether ‘type A illness causes B’ may take several years of learning (Bottle & Aylin, 2016). Still, statistics are used to detect specific patterns in vital signs and symptoms and better respond to any medical variations to the patients.
Statistics also help make decisions during critical care- For example, a patient presented to an emergency room with stomach pains, several diagnoses are possible. Statistical analysis combines several rudiments of a patient's history and clinical findings to attain one or a few ailments that are very likely in him, a few that are probable but less likely, and several that are highly questionable (Ranganathan & Aggarwal, 2018).
Statistical analysis is a valuable strategy in healthcare because it enables a reduction in the data collected from patients into a summary figure, thus allowing the healthcare providers to deduce meaning from the outcomes. They clench the imagination and quantify observation like in the research design, investigation of drug trials, and issues of commercialization of medicines.
References
Bottle, A., & Aylin, P. (2016). Statistical methods for healthcare performance monitoring. CRC Press.
Ranganathan, P., & Aggarwal, R. (2018). Common pitfalls in statistical analysis: Understanding the properties of diagnostic tests – Part 1. Perspectives in Clinical Research, 9(1), 40.
https://doi.org/10.4103/picr.picr_170_17
