healthcare analytics maturity model

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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 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 AnalyticsClinical Risk Intervention& Predictive AnalyticsPopulation Health Management& Active AnalyticsData-driven Improvement of Clinical Process & OutcomeAutomated 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