Description
Data Analyst
This engagement aims to transform a large Excel extract of potential duplicate patient encounters into a structured, interactive Power BI dashboard that supports data-quality improvement and operational cleanup. The consultant will work with HIM, data governance, and clinical operations teams to define the criteria and visualizations needed to surface duplicate patterns, encounter clusters, and high-risk records. The dashboard will help teams quickly identify duplicates, understand root causes, and prioritize remediation efforts. The resource may also be engaged in other Power BI work related to DBHDS as it arises if time in needed.
Conduct requirements sessions with HIM, data governance, and operations
Analyze the structure and quality of the duplicate-encounter extract
Build a Power BI data model capable of handling large datasets
Develop visualizations for duplicate patterns, encounter groupings, frequency, and severity indicators
Create filters for facility, date ranges, encounter type, and risk level
Implement automated refresh and validation logic
Iterate with stakeholders to refine insights and usability
Requirements document and dashboard wireframes
Power BI data model and transformation logic
Duplicate Encounter Identification dashboard
Data dictionary and process documentation
Knowledge-transfer session with internal staff
Week 1-3: Requirements gathering & data review
Week 4-8: Data modeling & initial dashboard build
Week 9-10: Stakeholder review & refinement
Week 11-12: Final dashboard delivery & documentation
Description
Data Analyst
This engagement aims to transform a large Excel extract of potential duplicate patient encounters into a structured, interactive Power BI dashboard that supports data-quality improvement and operational cleanup. The consultant will work with HIM, data governance, and clinical operations teams to define the criteria and visualizations needed to surface duplicate patterns, encounter clusters, and high-risk records. The dashboard will help teams quickly identify duplicates, understand root causes, and prioritize remediation efforts. The resource may also be engaged in other Power BI work related to DBHDS as it arises if time in needed.
Conduct requirements sessions with HIM, data governance, and operations
Analyze the structure and quality of the duplicate-encounter extract
Build a Power BI data model capable of handling large datasets
Develop visualizations for duplicate patterns, encounter groupings, frequency, and severity indicators
Create filters for facility, date ranges, encounter type, and risk level
Implement automated refresh and validation logic
Iterate with stakeholders to refine insights and usability
Requirements document and dashboard wireframes
Power BI data model and transformation logic
Duplicate Encounter Identification dashboard
Data dictionary and process documentation
Knowledge-transfer session with internal staff
Week 1-3: Requirements gathering & data review
Week 4-8: Data modeling & initial dashboard build
Week 9-10: Stakeholder review & refinement
Week 11-12: Final dashboard delivery & documentation
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