New Analytics Maturity Adoption Model Pushes for Digital Transformation and Data-Driven Decisions

Thousands of health systems worldwide rely on HIMSS and its range of digital tools as trusted resources to guide and assist in all aspects of their digital health journey. The newly updated Analytics Maturity Assessment Model (AMAM) has continued to showcase HIMSS’s commitment to driving health equity and digital health transformation globally through its expert-guided frameworks.  

The upgraded AMAM guides organizations through advanced health analytics, including prescriptive and predictive analytics in real-time, including natural language processing, and other advanced AI applications, along with a renowned framework that helps health systems evaluate and improve their analytics strategy and data governance. 

Anne Snowdon, RN, PhD, FAAN, chief scientific research officer for HIMSS, shared her expertise on the refreshed AMAM model and how digital transformation contributes to health system performance and improved clinical outcomes.  

How does AMAM help health systems connect analytics to outcomes? 

Analytics is the only possibility an organization has in understanding their outcomes. Analytics, at both the patient care level and at the organizational level, is the range of tools that help transform organizations’ data from simple data points into insights and knowledge to inform decisions. Analytics is centrally important in enabling and driving data-driven decision making at scale for health organizations. That is a hallmark feature of AMAM.  

How does AMAM support data governance? 

The recently launched AMAM has an entire dimension focused solely on governance. It helps and guides organizations to ensure a secure and private data infrastructure, which is required by any country in the world. Data governance has become incredibly important in analytics given the rapid emergence of artificial intelligence technologies. This model really cultivates and guides organizations to achieve a culture of responsible analytics, meaning they protect the privacy and security of patients. Data governance is all about identifying risks, mitigating and managing those risks and determining if the data governance and infrastructure is ethical and equitable.  

How does AMAM help support AI adoption? 

In order to effectively adopt AI and to achieve the many areas of value AI offers, an organization must have the key foundation needed in place before they advance AI adoption. They must have a very strong governance framework in place and a clear analytics strategy endorsed, supported and resourced by your senior executives. They also should have an analytics life cycle, a system by which you plan your analytics, design, implement and monitor data to make sure the tools are achieving strategic objectives. The first five levels of maturity for AMAM create and guide organizations to ensure they have the foundations, so that by level six and seven they are exceptionally well positioned to adopt AI technologies.  

What is the role of analytics in advancing digital transformation? 

Analytics is one of the four central dimensions of digital transformation. It transforms data into knowledge and insights which turns into informed decisions. When that’s achieved, an organization can become a data-driven health system. When that is in place, those data and analytics tools can be offered to patients, where they can track and manage their own health and can make their own data-driven informed decisions to help them achieve their health goals. Analytics is the heart of digital transformation. Without it, there would simply be data with very few insights and knowledge that organizations have to use to make the right decisions for their patients.