WGU D601 VKN2: Tasks 1 and 2 | New 2026 Update with complete
solutions.
D601 – Task 1: Data Analysis Plan
A. Business Problem Summary
Hospital readmissions within 30 days are a major concern in the healthcare industry. The Centers
for Medicare and Medicaid Services (CMS) penalize hospitals with excessive readmissions
Medical_Readmission_Scenario_an…
.
The hospital chain wants to:
Identify key drivers of 30-day readmissions
Detect demographic and regional trends
Analyze correlations between patient conditions and readmissions
Provide executive leadership with actionable insights
The goal is to reduce penalties and improve patient outcomes through data-driven strategies.
B. Stakeholder Needs
1. Senior Vice President (SVP) of Hospital Operations
Interested in:
Regional readmission trends (State, County, Area)
Demographic trends (Age, Gender, Income)
Population density impact
2. Executive Vice President (EVP) of Research
Interested in:
Patterns between health conditions and readmissions
Risk factors (Diabetes, HighBlood, Stroke, Complication_risk)
Admission type impact
, 3. Chief Medical Officer (CMO)
Interested in:
Correlations between treatments and readmission
Length of stay (Initial_days)
Services provided
Clinical care effectiveness
C. Dataset Description
The dataset contains:
10,000 patients
50 variables
Includes:
o Demographics
o Hospitalization data
o Medical conditions
o Survey responses
o Readmission indicator (ReAdmis)
The target variable:
ReAdmis (Yes/No)
D. Key Variables for Analysis
Dependent Variable:
ReAdmis
Independent Variables:
Demographics
Age
Gender
Income
Marital
State
solutions.
D601 – Task 1: Data Analysis Plan
A. Business Problem Summary
Hospital readmissions within 30 days are a major concern in the healthcare industry. The Centers
for Medicare and Medicaid Services (CMS) penalize hospitals with excessive readmissions
Medical_Readmission_Scenario_an…
.
The hospital chain wants to:
Identify key drivers of 30-day readmissions
Detect demographic and regional trends
Analyze correlations between patient conditions and readmissions
Provide executive leadership with actionable insights
The goal is to reduce penalties and improve patient outcomes through data-driven strategies.
B. Stakeholder Needs
1. Senior Vice President (SVP) of Hospital Operations
Interested in:
Regional readmission trends (State, County, Area)
Demographic trends (Age, Gender, Income)
Population density impact
2. Executive Vice President (EVP) of Research
Interested in:
Patterns between health conditions and readmissions
Risk factors (Diabetes, HighBlood, Stroke, Complication_risk)
Admission type impact
, 3. Chief Medical Officer (CMO)
Interested in:
Correlations between treatments and readmission
Length of stay (Initial_days)
Services provided
Clinical care effectiveness
C. Dataset Description
The dataset contains:
10,000 patients
50 variables
Includes:
o Demographics
o Hospitalization data
o Medical conditions
o Survey responses
o Readmission indicator (ReAdmis)
The target variable:
ReAdmis (Yes/No)
D. Key Variables for Analysis
Dependent Variable:
ReAdmis
Independent Variables:
Demographics
Age
Gender
Income
Marital
State