ADOPTION MODEL FOR ANALYTICS MATURITY (AMAM)

Build advanced analytics and transform care delivery.

Maturity Models
Turn data into actionable insights

AMAM gives you an evidence-based framework for improving your data governance, predictive analytics, and AI usage.

  • Improve your data quality

    AMAM supports systems in building rapid access to high- quality, comprehensive patient data at every point of care.

  • Develop full data governance

    AMAM helps measure the strength of your governance practices, which are needed for advanced analytics and AI adoption.

  • Break down data silos

    You’ll improve data-sharing across different platforms, so providers and patients have the data they need to inform decisions.

  • Give providers real-time insights

    We’ll help you manage and analyze patient data at scale, so providers can deliver equitable and personalized care.

  • Focus on value, not a checklist

    AMAM shifts the focus of analytics strategy to achieving value, so you’re looking at its real impact on care delivery and organizational performance.

  • The fact that we had such broad buy- in across the organization was a testament to the clarity AMAM gave us.

    Kent. A Anderson

    Executive Director, Data Center of Excellence | UC Davis Health

  • Your AMAM journey

    Explore the stages of the AMAM implementation process and see how this solution will allow you to optimize your healthcare analytics capabilities.

  • Fragmented point solutions

    Your organization desires to learn about developing analytics capabilities in response to business demands and market pressures.

  • Data aggregation and initial data governance

    Document and begin execution of an analytics strategy that brings basic data together from appropriate systems of record. Learn to manage and define data to be used and referenced by a broad cross section of analysts.

  • Centralized database with an analytics competency center

    Data is presented in a formal data warehouse as an enterprise resource with master data management that supports ad hoc queries and descriptive reporting.

  • Internal and external repost production and agility

    Demonstrate mastery of descriptive reporting broadly across the enterprise. Data quality is stable and predictable, tools are standardized and broadly available, and data warehouse access is managed and reliable.

  • Measuring and managing evidence-based care, care visibility, and waste reduction

    Make a concerted effort to understand and optimize clinical care by honing analytics resources that support evidence-based care, track and report care and operational variability, and identify and minimize clinical and operational waste.

  • Enhancing quality of care and population health

    Demonstrate expanded point-of-care oriented analytics and support of population health. Align data governance to support quality-based performance reporting and bring further understanding around the economics of care.

  • Clinical risk intervention and predictive analytics

    Demonstrate maturity in use of predictive analytics and show expanded focus on advanced data content and clinical support.

  • Personalized medicine and prescriptive analytics

    Leverage advanced data sets, such as genomics and biometrics data, to support the uniquely tailored and specific prescriptive healthcare treatments of personalized medicine. Deliver mass customization of care combined with prescriptive analytics.

Talk to an expert about our maturity models

There's a HIMSS maturity model for everyone, and each model classifies a dimension of your digital health from Stages 0 to 7. Your system’s future starts right here.

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