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Maturity Models Promote Data Governance

Defining Maturity Models

Maturity models in health IT promote customer experience and positive outcomes for patients and employees. Oftentimes, maturity models allow businesses to assess their goals and achievements in a productive way that promotes improvement [1]. Maturity models also allow companies to create a plan for organizing and communicating new data governance strategies to the rest of the company. There are different maturity models that can be implemented in health IT, all of which have various benefits in the healthcare industry.

Data governance

Types of Maturity Models

Progressive Data Governance Maturity Model

The Progressive Data Governance Model model goes through the levels of data governance within a company [2]. The first level is when the company is only able to be reactive and is generally not aware of the importance of data governance [2]. This is usually at the very beginning of a company’s development. The second level is when the company becomes more aware and starts implementing documented data practices [2]. This level begins with keeping track of the various data sets available to the company. The third level is when the company becomes more defined in its data governance requirements. This level involves creating policies and a governance committee to overlook responsibilities related to data governance [2]. The fourth level is when the policies are enforced and training is provided to ensure practical data analysis [2]. Finally, the last level is improving and optimizing the data governance process.

IMB Data Governance Maturity Model

The IMB data governance model promotes awareness and data management. The first level is when the company has no data governance process and lacks a formal process for managing and tracking data [2]. Once a company creates a plan to meet the needs of the company and the stakeholders, they move to the second level. This is when the employees become aware of the importance of data governance and create teams to improve the data infrastructure in a measurable way [2]. Next, the company must create documentation to support the infrastructure and necessary requirements [2]. This third level allows companies to create data policies and a data integration plan [2]. The fourth level is when the data policies are defined and performance management is used to track the progress of data governance [2]. Finally, the last level is when the data management process is optimized, often with automation.

Maturity Models Promote Digital Health Transformation

Maturity models promote standards and policies that improve data governance infrastructures in health IT companies. There are different health IT-specific models that can be incorporated to measure capabilities and ensure that the use of data is optimized. The first model is the Adoption Model for Analytics Maturity (AMAM) which tracks the analytical technologies used by a company [1]. This model promotes the use of data to support actionable items that promote customer experience and optimizes the capabilities of the company [1]. Furthermore, this model promotes the growth of data content which can improve operational and clinical outputs. This model also creates a data infrastructure that can be used across a health system to track various sources of medical records. AMAM also promotes analytical tools to measure data assets and organize them in an effective way that promotes analytical competency and decision-making processes for positive customer experiences.

Data governance

Another crucial maturity model is the Infrastructure Adoption Model (INFRAM) which helps leaders map out their technology capabilities with their infrastructure plans to meet and assess goals [1]. Healthcare companies often need a strong infrastructure so they can meet their functional requirements and promote customer experience throughout the digital transformation. INFRAM allows companies to define the capabilities of different domains of the healthcare infrastructure so they can work together. INFRAM also allows companies to assess the current stage of the company and establish goals to meet the desired future state [1]. Furthermore, this model promotes care delivery by optimizing data governance through an improved infrastructure that allows data to be accessed when needed. Moreover, this maturity model mitigates the risk associated with data growth by creating an infrastructure that decreases cyber risks [1]. Overall, maturity models are implemented to promote efficient care services and positive customer experiences.


HITS promotes data governance by incorporating the customer experience into the process and by co-facilitating working groups to complete project deliverables that meet stakeholders’ requirements. We also work with leadership to create the next steps needed for project development. Furthermore, HITS incorporates customer experience principles into the data strategy plan with measurable performances to improve the overall process. Clients frequently commend HITS for our hands-on approach to improving customer experience that ensures their day-to-day operations run smoothly and that no project or task is missed. Data governance is crucial to the smooth operation of a business and ensures that human-centered design is delivered to consumers. Therefore, HITS works with companies to create, manage, and optimize personalized plans to achieve data governance goals.


  1. https://www.himss.org/what-we-do-solutions/digital-health-transformation/maturity-models 
  2. https://www.ovaledge.com/blog/data-governance-maturity-model#:~:text=Governance%20Maturity%20Model%3F-,A%20data%20governance%20maturity%20model%20is%20a%20tool%20and%20methodology,data%20assets%20are%20in%20place
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