MVP Health: Centralize data for a competitive advantage
One of the greatest assets to a health insurer is all the data it amasses. But the information won't do any good if it's disorganized and unsystematic.
MVP Health Care decided it was fed up with poor data management systems that featured siloed data and disconnected legacy systems, and took action to centralize its data. The New York-based insurer hired veteran business intelligence expert Linda McCann to initiate a "data turnaround" by centralizing all of its information and implementing rigorous data governance standards.
FierceHealthPayer: What's the problem with information in silos for a health insurer? What kind of breakdowns in communication does it cause?
Linda McCann: For too long, health payers have been doing whatever they can to support increasing reporting needs, regulatory compliance and special requests. Payer analytics are just enough to alleviate and prevent an impending 'analytic heart attack.'
But in the competitive healthcare industry market place, it's no longer enough to barely stay alive in this manner. Payers are facing growing information demands, consumer expectations and heightened competition for members. We must get healthy at our core or risk the business equivalent of a coronary bypass--or worse.
MVP's challenge--as with many payers--is to unravel decades of siloed data, disconnected legacy software and systems, and disjointed short-term data management efforts. We need to start fresh and do things differently. Otherwise, we'll make less informed decisions from inadequate data. The risk of human error from misinterpretation of undefined data is higher. Costs will increase rather than decrease, and resources will be constrained. We're more likely to underserve--or risk losing--our healthiest (and most preferred) members. Ultimately, we will not be in a position to innovate, and we will be at a competitive disadvantage.
FHP: What steps are you taking to centralize all of MVP's information?
McCann: Last fall, MVP recruited me to lead a bottom-up data environment transformation because previous information initiatives were only semi-effective and weren't moving the needle far enough. This kind of effort requires C-level support or it won't go anywhere. Now, with a team in place, we're actively building a next-generation business intelligence competency center (BICC) to be an analytically-driven organization. My team consists of informatics analysts, data architects, data governance experts and a BICC steering committee.
This is a multiphase, multiyear program. In this phase, we created a blueprint and roadmap that takes into account our technical landscape, business drivers, analytical processes and more, all rolled into one detailed plan designed to take us from our current state to the envisioned end-state environment.
Aside from all the hard work that must be done, our team is on the same page when it comes to the most critical factors for BICC success. They are:
- Our technical solution must align with MVP's business strategy and have specific metrics to define success.
- The BICC must understand our business unit needs and the users. What's their technical sophistication? What do they need information for?
- We must carefully manage change and set expectations. What business processes can be improved easily? We can start there for a quick win. We need to map out the process for training, education, knowledge transfer and communications involved during the entire effort.
- We will focus on data quality from the start. Poor data quality is the number one reason business intelligence projects fail. Not only is user satisfaction directly tied to data quality, but the better the data, the more it will be used. In fact, the BICC motto is 'Provide the right information to the right people at the right time.'
- We will build in increments. Big bang doesn't work, and defining all requirements upfront is a recipe for disaster.
- It's not just about the build; it's about maintenance too. We are accounting for all the people, resources and funding needed to teach, support and maintain the BICC into the future.
FHP: What type of data governance standards are you putting in place?
McCann: A data governance program is key not only for BICC's success, but for control and management of our data across all of MVP. We have an information management strategy consisting of business intelligence and analytics, master data management, data quality management, metadata management, data integration, data security, management, content management and third party data management. For each of these, data governance will serve as owner of standards and controls. We've put in place the 'people' structure to support this through a steering committee, data governance council and set of data trustees.
FHP: What are the goals for MVP's data turnaround? What does MVP hope to achieve once its data is centralized?
McCann: The goal of our data turnaround is simply articulated, but requires steerage and commitment to achieve--to provide the right information to the right people at the right time. We will improve our customer satisfaction, drive smarter decision-making and unlock new frontiers of competitive advantage. The BICC is one example of how MVP Health Care is evolving into a better, more dynamic payer by utilizing a thoughtful, systemic approach.
Editor's Note: This interview has been edited for clarity.