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Descriptive statistics summarize the utility, efficacy and costs of medical goods and services. Increasingly, health care organizations employ statistical analysis to measure their performance outcomes.”

Descriptive statistics summarize the utility, efficacy and costs of medical goods and services. Increasingly, health care organizations employ statistical analysis to measure their performance outcomes.”

 

According to Casto (2018), “Descriptive statistics summarize the utility, efficacy and costs of medical goods and services. Increasingly, health care organizations employ statistical analysis to measure their performance outcomes.”

Reference 

Casto, R. (2018). Why Are Statistics Important in the Healthcare Field? Retrieved from https://www.livestrong.com/article/186334-why-are-statistics-important-in-the-health-care-field/ 

 Based on the reading using the following topic:

  • Needs Assessment
  • Research the topic in the Library and locate one article to review. Share the descriptive statistics from the article using your own words. Include the statistical analysis that was performed and a rationale as to why that particular test was used. Share one visual representation the data in your response (e.g., pie charts, histograms, bar charts, etc.).

 Use as References:

In two diferent paragraph give your personal opinion to  Alyssa Lucas and Marissa Sebastian

 

 Alyssa Lucas 

  • Resource Allocation

Resource Allocation is the distribution of financial resources to people groups, or programs in a healthcare organization. When it comes to allocation of resources in the healthcare field it is important to use descriptive statistics to help determine and utilize medical resources. According to Rexford Santerre and Stephen Neun, allocative and production efficiency heavily rely on statistical data in healthcare (Casto, R., 2018).

Data analyzes and priority settings have made the decision-making process more effective when determining the best method when deciding which group of people or individual receives resources. In the study and figure shown below there were 360 different terms that used decision criteria classification and descriptive statistics. Figure 3 shows the top 10 criteria for allocating resources in this study. These charts illustrate which criterion is most effective according to health outcomes, type of service, economic impact, evidence, priorities, target disease, therapeutic context, complexity, and coverall context (Guindo, 2012).

(https://resource-allocation.biomedcentral.com/articles/10.1186/1478-7547-10-9/figures/3).

  1.  equality, fairness and justice
  2. Efficacy/effectiveness
  3. Stakeholder interests and pressures
  4. Cost- effectiveness
  5. Strength of evidence
  6. Safety
  7. Mission and mandate of health system
  8. Organizational requirements and capacity
  9. Patient-reported outcomes
  10. Needs

Resources:

https://www.ahc.umn.edu/img/assets/25857/resource_allocation.pdf

Casto, R. (2018). Why are statistics important in the Health Care Field? Retrieved from https://healthfully.com/why-are-statistics-important-in-the-health-care-field-4856543.html

Guindo, L.A., Wagner, M., Baltussen, R. et al. From efficacy to equity: Literature review of decision criteria for resource allocation and healthcare decisionmaking. Cost Eff Resour Alloc 10, 9 (2012). https://doi.org/10.1186/1478-7547-10-9

 

Marissa Sebastian

            “Quality improvement initiatives and projects cannot be justified simply because “everyone is doing it”; they must be considered on the basis of financial or societal benefits” (McLaughlin, 2017, p. 223). I have used the quality improvement approach in my current role with nearly all departmental workflows, which has proven to be successful through member and provider experience survey results. The article I chose from the library focused on increasing the success rate of placing 2 large-bore intravenous (2LBIV) catheters to manage acute gastrointestinal hemorrhage (GIH). As a result of the decreased use of the 2LBIV method, a team was created to increase the use of this method, increasing results that can be measured and studied. According to (Medicine, 2019), “below is an overview of this quality improvement initiative:

  • Local Problem: Of 100 patients hospitalized with GIH in 2017, only 14 received 2LBIV access. The goal of this study was to improve this measure.
  • Methods: A multidisciplinary team used the DMAIC (define, measure, analyze, improve, and control) framework to perform a quality improvement initiative.
  • Interventions: The team used quality tools including a stakeholder survey, swimlane diagram, and fishbone diagram (example of diagram below). The first intervention involved education of the hospitalists directing admissions, and the second intervention involved education of emergency department (ED) physicians and nurses regarding the importance of 2LBIV placement.

 

  • Results: Following the second intervention, there was a substantial increase in 2LBIV placement to 37 of 86 (43%).
  • Conclusions: Carefully directed education of ED physicians and nurses with monthly feedback was effective in improving appropriate intravenous placement in patients with GIH.”

I found this article to reinforce my personal opinion that quality improvement initiatives are proven effective when the team assembled to focus on an opportunity for improvement (OFI) works to achieve the same goal/expectation. Have any of my fellow classmates implemented a quality improvement process within your current or past role?

Thank you,
Marissa

References

McLaughlin, D. (2017). Healthcare Operations Management, Third Edition. Chicago: Health Administration Press. Retrieved from https://eds-b-ebscohost-com.libauth.purdueglobal.edu/eds/ebookviewer/ebook?sid=a4ff1a84-8aec-45aa-b1c6-d374c6f769c4%40pdc-v-sessmgr05&ppid=pp_C&vid=0&format=EB

Medicine, D. o. (2019, November 14). Intravenous Access in Gastrointestinal Hemorrhage: A Multidisciplinary Quality Improvement Initiative Led by Emergency Department Nurses and Internal Medicine Physicians. Journal of Nursing Care Quality, 41-46. doi:10.1097/NCQ.0000000000000448

 


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