Unit 9 Assignment: Statistical Analyses for Organizational Decision-Making in Healthcare

• HS312-6: Explain the relationship between health data analytics and business decisions to improve a specific healthcare initiative. 

Please complete using Microsoft Word and PowerPoint–as indicated in the instructions.

Assignment Requirements

• The body of your Microsoft Word document should be at least 1500 words in length.
• Your PowerPoint presentation should be at least 10 slides–excluding the title slide and references.
• Quoting should be less than 10% of the entire paper and presentation. Paraphrasing is necessary.
• Students must cite and reference at least 4 credible sources from the online Library.
• Please be sure to utilize the resources available in Academic Tools  to help with meeting  APA expectations for written assignments.

Instructions

Imagine that you are an executive for a health organization. As part  of your role within the healthcare leadership team, you are tasked with  analyzing organizational data for decision-making purposes. For this  assignment, you will obtain raw data, analyze it, and make  recommendations for organizational decisions. Please follow the  instructions below in completion of this multi-part assignment.

Apply analytical results to facilitate decision-making

   

Instructions

 

1

Apply analytical results to facilitate decision-making

Create a presentation on your exploratory data analysis of mined data  sets for an executive healthcare team. Include a summary of your  analysis, statistical tables, and data visualizations. Conclude your  presentation on the importance of executive dashboards.

 

2

Recommended organizational action based on knowledge obtained from data exploration and mining

Based on your analysis, make three (3) recommendations for  evidence-based decision-making relevant for organizational action or  change.

 

3

Analyze clinical data to identify trends that demonstrate quality, safety, and effectiveness of healthcare

Examine the clinical data to identify trends related to healthcare (1) quality, (2) safety, and (3) effectiveness.

 

4

Evaluate administrative reports using appropriate software

Obtain a raw data set from www.healthdata.gov and  explore the data set using PSPP. Generate analytical outputs from PSPP  that include the appropriate selection of both descriptive and  inferential statistics. If you are not able to process one data set  using descriptive and inferential statistics, then select one data set  for descriptive statistics and another data set for inferential  statistics. Generate tables in PSPP that reflect your statistical  analyses and include at least three (3) appropriate data visualizations.

 

5

Interpret inferential statistics

Compose a discussion in which you evaluate the findings from your  analyses—interpreting the descriptive and inferential statistics.

 

6

Analyze statistical data for decision making

Within your presentation, analyze the statistical data for  decision-making by organizing various presentations of data  visualizations—highlighting multiple perspectives on the same topic.

 

7

Plan adherence to Institutional Review Board (IRB) Processes and policies

Demonstrate your understanding of IRBs by earning a certification on  national guidelines regarding human-subjects research. Begin by first  creating an account at http://phrp.nihtraining.com/users/login.php.  Once you have completed the Readings for each module, complete the  quizzes and obtain the training certificate. You will take a screenshot  of your certificate of completion and insert this image into this paper.  Following a screenshot of your earned certificate in protecting human  subjects, plan adherence to Institutional Review Board (IRB) processes  and policies by reflecting upon the concepts of (1) Respect, (2)  Justice, (3) Nonmaleficence, and (4) Beneficence by providing (A) your  interpretation of the concept, (B) an example of complying with the  principle within healhcare, and (C) connecting each concept with the  characteristics of quality data.