HLT 362 Application of Statistics in Health Care
HLT 362 Application of Statistics in Health Care
Statistics – numerical data gathered through measurements or observation that define the traits of population samples-help healthcare decision makers. The value, effectiveness and price of medical products and services are summarized by descriptive statistics. Organizations in the healthcare industry are increasingly using statistical analysis to evaluate their performance. To increase efficiency, hospitals and other big provider service organizations use data-driven, ongoing quality improvement programs. Using statistical data, government health and human care organizations assess the general health and well-being of the population (Ray Casto, 2017). Healthcare providers work hard to efficiently deliver high-quality products and services. The data assist the businesses in assessing performance success and failure in other to predict future outcomes, managers responsible for quality improvements develop benchmarks or criteria of service excellence. Reliable statistical data can be used to chart the viability and overall growth, reduce trade-off risks (Ray Casto, 2017).
Relevance of Statistics in Quality Improvement
Managers endeavor to raise the caliber of the services they provide, and they may use a variety of standards to predict future outcomes (“Diagnostic and screening statistics,” 2016). The massive amount of healthcare data that is daily gathered from the electronic medical record (EMR), including data on biostatistics, surveys of patient and employee satisfaction, child births, morbidity and mortality rates, and the prevalence of diseases, adverse events (catheter associated urinary tract infection and patient falls), can provide answers to specific questions through data analysis. Data analysis improves evidence-based procedures and keeps track of outcomes.
Statistics are crucial because they enable early detection of problems, allowing for their avoidance in the future. In addition to decreasing waste, they also shorten the time needed make specific goods so that a greater variety of goods can be produced consistently well (BDK UK, 2018).
Safety Significance of Statistics
Key indicators are derived from statistical analysis. For instance, monitoring catheter-associated urinary tract infection (CAUTI) in patients can show whether the right steps are being done to minimize their frequency and avoid such infections in the hospital settings. Metrics are very helpful in assessing current procedures and monitoring quality and safety (Martin, McKee, & Dixon-Woods, 2015).
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The improvement of patient safety depends heavily on fully integrated clinical, financial, and operational data as well as predictive analytics and machine learning. Utilizing this methodology, tools will identify risks and recommend interventions for use throughout the continuum of care (Stan Pestotrik, 2019).
Relevance of Statistics in Health Promotion Significance
Public health and the promotion of health heavily rely on statistics. Government agencies and healthcare providers can monitor population data using statistics to spot broad-scale health indicators and patterns. This is very helpful in determining the need for an intervention and the results that will follow. From the standpoint of public health, statistics can assist in monitoring disease outbreaks, chronic disease morbidity and mortality, immunization rates, health risks like alcohol and tobacco, and some other factors such as fatal accident rates.
The Centers for Disease Control and Prevention (CDC) track diseases and introduce practical measures to address them through practice modifications, guidelines, legislation, or public health promotion (Hayat, Powell, Johnson, and Cadwell, 2017). These details include descriptive statistics, variations, frequency distribution, and incidences.
Relevance of Statistics in Leadership
Understanding the data and being able to use it are crucial leadership skills for those in the healthcare industry. The leader should be regarded as a collaborator in the implementation of the studied data. Leaders in the healthcare sector should be able to assess the analysis’ reliability or applicability. The future of healthcare is created through data analysis. Trends are discovered throughout the data analysis, and these trends enable the assumption of predictability. The predictability assumptions strengthen care delivery models, improving patient safety and quality outcomes. The data is statistically analyzed to provide answers to issues that advance population health (Grand Canyon University, 2018)
Additionally, leadership can be statistically expressed in two ways: the capacity to exert control over components of an activity, and the ability to make prompt decisions regarding essential interventions.
Statistics in the Workplace
In every day-to-day activity in the hospital as a nurse, statics is unavoidable required as an important tool in data collection and analysis.
The process of getting the required data typically doesn’t involve much complexity, I gather data in numerical form, such as birth rates based on the frequency of pregnancies each year. Additionally, statistics is crucial in our day-to-day work when comparing the number of patients who have been admitted to the hospital or who have been discharged to the department’s overall population. Such calculations may also be helpful in the decision-making process because the correctness of the data acquired enables the development of a clear conclusion. As a result, I use statistics as a reliable method of gathering evidence.
Statistical analysis is a useful method for gathering the required proof in the health sector. Additionally, the methods employed for correlation calculations and reporting help to advance health, public safety, and leadership while also enhancing the standard of medical care. Statistics at work help healthcare professionals meet the difficulties of the day with positive results.
BDK UK, (2018). Statistical Analysis in Quality Control. Retrieved from https://www.bdk.uk.com/2018/09/importance-statistic-analysis-quality-control
Diagnostic and Screening Statistics, (2016). Using Relative Statistics and Appropriate Disease Prevalence to Compare Screening Tests. https://www.ncbi.nih.gov/pmc/articles/PMV5947324/
Grand Canyon University. (Ed.). (2018). Applied Statistics for Health Care. https://lc.gcumedia.com/htl362vn/applied-statistics-for-health-care
Hayat, M. J., Higgins, M., Schwartz, T.A., & Staggs, V.S., (2015). Statistical challenges in nursing education and research: An expert panel consensus. Nurse Educator. https://www.sciencedirect.com/science/article/abs/pii/S1555415521002798
Ray Casto, (2017). Why Are Statistics Important in the Health Care Field? https://www.fairmountbenefits.com/2017/09/19/why-are-statistics-important-in-the-health-care-field-pa-benefit-advisors/
Martin, G. P., McKee, L., & Dixon-Woods, M. (2015). Beyond metrics? Utilizing “soft intelligence” for healthcare quality and safety. Social Science & Medicine, 142, 19-26. Web
Stan, P., (2019). How to use Data to Improve Quality and Patient Safety. https://www.healthcatalyst.com/insights/use-data-improve-patient-safety