AMAM

Newly Improved Analytics Maturity Assessment Model (AMAM) Centered on Patient Outcomes to Improve AI Strategy, Data Governance, Analytics

Female lab technician looking at scan after MRI in hospital laboratory.

HIMSS recently launched a newly upgraded Analytics Maturity Assessment Model (AMAM), a framework that helps health systems evaluate and improve their analytics strategy, data governance, and supports the effective use of artificial intelligence technology. 

The launch of our newest assessment tool for analytics maturity is another example of HIMSS's global commitment to driving health equity and improving patient outcomes through digital health transformation. HIMSS and its suite of digital tools, including the Digital Health Indicator and maturity models, are trusted resources that thousands of health systems worldwide depend on to inform and support every aspect of their digital health journey.    

Officially launched Oct. 2 at the 2024 HIMSS APAC Health Conference & Exhibition, the newly upgraded AMAM measures the real impact of analytics, including the value of analytics on patient care, system-wide operations and governance. AMAM supports health systems in building rapid access to high-quality, comprehensive patient data at every point of care, ensuring informed decisions, better outcomes, and lower costs. 

The new AMAM helps health organizations evaluate their analytics strategy, and other foundational requirements such as governance, to support the adoption of Artificial Intelligence technologies and other digital assets to support equitable, data-driven decision-making at scale. AMAM measures the true impact of analytics, including the value of analytics on quality and safety, patient and population health outcomes, and health system performance. 

AMAM also now focuses directly on outcomes, governance, privacy measures, analytics lifecycle and culture of responsible analytics. Additionally, the new AMAM looks at advanced analytics that are critical for the successful adoption of AI technologies so that health systems can strengthen proactive decision making aimed at prevention and population health.  

The refreshed AMAM now considers advanced health analytics, including prescriptive and predictive analytics in real-time, including natural language processing, and other advanced AI applications.   

In the early stages of AMAM, participating health systems create basic governance and data quality measures, creating unified data repositories and starting to use dashboards, and visualizations to support decision making. They also develop and adopt a clear analytics strategy that aligns with organizational goals. 

By stage 6-7, systems will use predictive analytics to inform analytics strategy, integrate AI and machine learning into analytics processes, and offer real-time decision support to clinicians. They will also develop systems for monitoring population health outcomes to inform health equity programs. 

AMAM is a flexible framework, not a rigid checklist. Analytics and AI are used across a variety of care settings, and any health system can use AMAM to target specific needs and focus areas on analytics, AI, and governance. 

As one of HIMSS’s six maturity models supporting digital health transformation, AMAM joins the Electronic Medical Record Adoption Model (EMRAM) and the Infrastructure Adoption Model (INFRAM) as the focus of recent enhancement efforts.  

HIMSS also launched its Community Care Outcomes Maturity Model (C-COMM) in 2023 to meet the needs of non-acute healthcare.  

Each model in the suite conducts a baseline assessment, fixes gaps in workflows, creates a clear roadmap for each stage of digital health transformation and tracks wins while planning for the future. 

Learn more about the newly enhanced AMAM. 

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