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Healthcare Analytic Adoption Model
In the Healthcare Analytic Adoption Model, a robust data governance
function is required in order to achieve the conditions of Level 5 maturity.
Level 8
Level 7
Level 6
Level 5
Level 4
Level 3
Level 2
Level 1
Level 0
Precision Medicine, Big Data
& Prescriptive Analytics
Clinical Risk Intervention
& Predictive Analytics
Population Health Management
& Active Analytics
Data-driven Improvement of
Clinical Process & Outcome
Automated External Reporting
Automated Internal Reporting
Standardized Controlled Vocabulary
& Patient Registries
Enterprise Data Warehouse
Fragmented Point Solutions
• Tailoring patient care based on population outcomes and
genomics data. Treatment and engagement include IoT.
• Organizational processes for intervention are supported
with predictive risk models. Fee-for-quality includes fixed
per capita payment.
• Tailoring patient care based on population metrics. Fee-for-
quality includes bundled per case payment.
• Reducing variability in care processes. Focusing on
internal optimization and waste reduction.
• Efficient, consistent production of reports & adaptability
to changing requirements.
• Efficient, consistent production of reports & dashboards
widely available in the organization.
• Relating and organizing the core data content.
• Collecting and integrating the core data content.
• Inefficient, inconsistent versions of the truth.
Cumbersome internal and external reporting.
HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang 1

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Healthcare Analytics Maturity Model

  • 1. Healthcare Analytic Adoption Model In the Healthcare Analytic Adoption Model, a robust data governance function is required in order to achieve the conditions of Level 5 maturity. Level 8 Level 7 Level 6 Level 5 Level 4 Level 3 Level 2 Level 1 Level 0 Precision Medicine, Big Data & Prescriptive Analytics Clinical Risk Intervention & Predictive Analytics Population Health Management & Active Analytics Data-driven Improvement of Clinical Process & Outcome Automated External Reporting Automated Internal Reporting Standardized Controlled Vocabulary & Patient Registries Enterprise Data Warehouse Fragmented Point Solutions • Tailoring patient care based on population outcomes and genomics data. Treatment and engagement include IoT. • Organizational processes for intervention are supported with predictive risk models. Fee-for-quality includes fixed per capita payment. • Tailoring patient care based on population metrics. Fee-for- quality includes bundled per case payment. • Reducing variability in care processes. Focusing on internal optimization and waste reduction. • Efficient, consistent production of reports & adaptability to changing requirements. • Efficient, consistent production of reports & dashboards widely available in the organization. • Relating and organizing the core data content. • Collecting and integrating the core data content. • Inefficient, inconsistent versions of the truth. Cumbersome internal and external reporting. HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang 1