HLT 362 Application of Statistics in Health Care SOLUTION

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).

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.

 

References

 

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

Sample Answer 3 for HLT 362 Application of Statistics in Health Care SOLUTION

The Healthcare system and practices are constantly changing to improve the quality of care delivered to the patients. Evidence-based practices help in identifying the areas that need to improve based. However, the first step in the change process requires identification of the needs, and this is achieved by gathering relevant data, analyzing and interpreting them. Therefore, statistical application is critical in healthcare delivery. Meaningful data analysis allows clinicians and other healthcare providers to make informed decisions. It becomes easy to justify the change process when having enough data to support the need. The current paper discusses the significance of statistical applications in healthcare.

Significance of Statistical Application to Quality and Safety

According to Petrie and Sabin (2019), the statistical application helps in improving safety and the quality of healthcare delivery. For example, the introduction of the Medicaid readmission program aimed at reducing the cases of patients readmitted 30 days after discharge. In such cases, the hospitals must record the number of people admitted in the hospitals, those discharged, and the ones who are readmitted within 30 days to determine the readmission rate. Each hospital needs to keep the rate below the recommended national value. In such a case, the statistical applications help in promoting quality healthcare delivery. Similarly, analysis can be done to determine the major contributing factors to the increased cases of readmissions. While there could be many factors, their impact on the health issue varies, and so the statistical analysis helps the hospital to determine the most significant burden to be prioritized.

Furthermore, Vellido (2019) indicates that statistical applications involve creating charts, and this helps in identifying the signals on the areas of concern. Similarly, the laboratory units in the hospitals are required to chart temperatures and other variables over time. The trends in the variables can be used to determine whether any of the outcomes lie outside the expected range. In the same way, the hospital can monitor incidences of mortalities and readmissions within thirty days to identify days with outrageous outcomes. The abnormal record can raise the alarm that eventually leads to an inquiry process with the goal of improving the quality of healthcare services to the patients.

Evidence-based practice development depends mainly on data analysis and statistical applications. As the nurses and other healthcare providers interact with the patients, they determine the key health determinants. The data collected are then used in determining the key areas in the population that needs to be addressed. For example, various studies have indicated the incidences of childhood obesity are on the rise, and this necessitates urgent interventions. In such a case, data on the life patterns among the population are collected and used to determine the best approaches to addressing the issue. The case illustrates how statistical applications are useful in promoting population health. Health promotional activities begin by analyzing the life patterns among the people in a community and using the information to develop a customized response. Also, as part of the public health promotion, statistical applications have been used to track the Covid-19 infection rates, and this has been used to guide the healthcare policy and response measures.

Statistics Knowledge and Application

Obtaining data for statistical analysis is also essential; using dubious methods could result in unrealistic data. The data to be analyzed in this case were obtained from the hospital health records systems. The healthcare institution uses an electronic health system and so captures various data (Suman & Prajapati, 2018). Also, the data may be collected through the interviews from the interactions between the healthcare providers and the patients. The approach provides comprehensive data that health the healthcare providers understand the magnitude of the burden presented by the healthcare issue.

Statistical knowledge is important and is used on a daily basis. Healthcare providers interact with data on a daily basis, beginning from scheduling the patients and offering the best clinical care (Suman & Prajapati, 2018). Understanding the patients’ flow allows the healthcare facilities to determine the number of healthcare providers required to facilitate the smooth flow of the patients. In terms of decision-making, the data on the number of patients scheduled for a given day can be used to decide on the number of observation rooms and consultation units needed to effectively attend to the patients. Besides, by analyzing the amount of time taken in the consultation room by the patients, the healthcare providers are able to manage their queues accordingly.

Conclusion

Finally, statistical applications are part of the daily experiences in the healthcare delivery process. The healthcare providers interact with their patients and gather relevant data, which are analyzed and used to make decisions on how to improve the experiences of the patients. Statistical analysis helps organizations make appropriate decisions, improve the quality of healthcare delivery and identify warning indicators in their daily operations.

References

Petrie, A., & Sabin, C. (2019). Medical statistics at a glance. John Wiley & Sons.

Suman, G., & Prajapati, D. (2018). Control chart applications in healthcare: A literature review. International Journal of Metrology and Quality Engineering, 9, 5. https://doi.org/10.1051/ijmqe/2018003

Vellido, A. (2019). The importance of interpretability and visualization in machine learning for applications in medicine and health care. Neural Computing and Applications, 32(24), 18069-18083. https://doi.org/10.1007/s00521-019-04051-w