Data Management Model
Breaking ground on the future
Each enterprise clinical data management model is unique to the context of every system. However, the foundation of the model is built on best practices and insights obtained after more than 1,000 hospital partners throughout the country.
An Intelligent Model
Without adequate change management solutions, health care providers who embark on visionary change are prone to less-than-optimal results. In fact, Harvard Business Review reports that 70% of traditional change management end in failure. The white waters of change are arduous to navigate alone. They require a seasoned guide.
Our project management experts implement solutions across the breadth of our portfolio, aligned with your distinct context and tailored to industry best practices.
A Dedicated Advisor
In addition to the project management team, every partner is assigned a Dedicated Advisor at the beginning of their partnership. The Dedicated Advisor is a subject matter expert in Q-Centrix and a clinical expert in at least one of the service lines we serve. He or she will guide each hospital in best practices throughout their partnership – beginning with change management. The Dedicated Advisor removes the learning curve from the Q-Centrix experience through guidance, best practices, data insighs and connecting members of the Q-Centrix Partner Community.
The Data Management Model Build is a lean process that defines the optimal data management model through a series of seven key milestones focused on data mapping, workflow and education.
Align on vision and plan
Data Mapping & Workflow
Discussion of current process and best practices
Education on the quality assurance program and associated analytics package.
Provisioning and validation of credentials
Detailed walk through of the proposed data management model
First transaction is complete. After Go-Live, it is common to iterate on the process to arrive at the ideal vision
How we work
Throughout the Data Management Model Build, participants focus on:
Value management and realization
Designing a model that drives process improvements
Developing systems architecture and deployment plans
Architecting organizational learning strategy and drive adoption for faster time to value