Healthcare Data Analysis and Make Healthcare Management Recommendations PART ONE: (Discussion) **200 words** For our experiential learning activity this w
Healthcare Data Analysis and Make Healthcare Management Recommendations PART ONE: (Discussion) **200 words**
For our experiential learning activity this week you will conduct a healthcare data analysis and make healthcare management recommendations.
The CDC (Centers for Disease Control and Prevention) analyzes BRFSS (Behavioral Risk Factor Surveillance System) data, to provide localized health information that can help public health practitioners identify local emerging health problems, plan and evaluate local responses, and efficiently allocate resources to specific needs. Review the data and recommend an action plan for public health practitioners.
Visit BRFSS https://www.cdc.gov/brfss/
From the BRFSS page, click Prevalence Data and Data Analysis Tools, and then click Prevalence and Trends Data.
Select one Class and Topic for the most current year available (e.g. Cholesterol Awareness -> Cholesterol High)
Provide the measure(s) definition for the map/chart. How does Florida compare to the nation on the selected class/topic?
Using an Evidence-Based-Practice (EBP) approach connecting with your knowledge from Chapter 2, provide a summary action plan recommendation to public health practitioners for ways to improve the particular factor in Florida (best practices in other states, methods, etc.).
Please be sure to include and cite your sources following best writing practices.
PART TWO: (learning journal reflection) **two pages**
complete learning journal reflection.
Learning Journal Title: Chapter 4
Learning Journal Topics:
Healthcare Quality and Data Quality
**Value Based Health & Meaningful Use
Explore Process Step
**Stat Explore Node
**Graph Explore Node
Modify Process Step
**Impute Node
**Interactive Binning Node
**Replacement Node
**Transform Variable Node
the chapter attached for PART TWO just focus at the topics under Learning Journal Topics. Chapter Summary
Figure 4.1: Chapter Focus – Explore and Modify
Chapter Learning Goals
Healthcare Quality
Value-Based Healthcare
Figure 4.2: Meaningful Use
Healthcare Data Quality
Table 4.1: Healthcare Data Quality Attributes
Experiential Learning Activity: Healthcare Data Quality
Check
Healthcare Data Quality Case Study
Six Sigma Health Data Quality
Experiential Learning Activity: Public Data Exploration
SEMMA: Exploration
Exploration Process Step Overview
Figure 4.3: Exploration Step
Data Exploration Data Discovery and Descriptive Statistics
Explore Tab Enterprise Miner Node Descriptions
Stat Explore Node
Figure 4.4: Stat Explore Node
Graph Explore Node
Figure 4.5: Graph Explore Node
Multiplot Node
Figure 4.6: MultiPlot Node
Experiential Learning Activity: Health Data Surveillance
SEMMA: Modify
Modify Process Step Overview
Figure 4.7: Modify Process Step
Modify Tab Enterprise Miner Node Descriptions
Impute Node
Figure 4.8: Impute Node
Interactive Binning Node
Figure 4.9: Interactive Binning Node
Replacement Node
Figure 4.10: Replacement Node
Transform Variables Node
Figure 4.11: Transform Variable Node
Experiential Learning Application: Heart Attack Payment
Data
Figure 4.12: Create New Diagram Step 1 of 2
Figure 4.13: Create New Diagram Step 2 of 2
Figure 4.14: Add a File Import Node
Figure 4.15: Browse for File
Figure 4.16: Edit Variables
Figure 4.17: Edit Variable Roles
Figure 4.18: Add StatExplore Node
Figure 4.19: StatExplore Results
Table 4.2: Descriptive Measures
Figure 4.20: StatExplore Excel Comparison
Heart Attack Payment Missing Data
Figure 4.21: File Import Node Missing Data
Figure 4.22: StatExplore Node Missing Data
Figure 4.23: StatExplore Results
Figure 4.24: GraphExplore Missing Data
Figure 4.25: GraphExplore Missing Data Size Property
Figure 4.26: GraphExplore Missing Data Plot
Figure 4.27: GraphExplore Missing Data Box Chart Type
Figure 4.28: GraphExplore Missing Data Box Chart Type Role
Figure 4.29: GraphExplore Missing Data Box Chart Type Role
Figure 4.30: Add MultiPlot Node
Figure 4.31: Add MultiPlot Node Results
Figure 4.32: Update File Import Variables Missing Data
Figure 4.33: Add Replacement Node
Figure 4.34: Update Replacement Node Properties
Figure 4.35 Replacement Node Results
Figure 4.36: Add Impute Node
Figure 4.37: Review Impute Node Properties
Figure 4.38: Review Impute Node Results
Experiential Learning Application: Data Quality Exploration
Figure 4.39: SEMMA Process
Learning Journal Reflection
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