Data Maturity – How Imaging Enterprises Can Advance Their Use of Analytics
Maturity is always something to strive for – and data is no different.
Maturity models can be a valuable guide in moving an imaging business forward in terms of their use of data analytics. It can provide a helpful roadmap toward deriving more value, and greater insight than in the past, says Geoff Clemmons, Enterprise Analytics Marketing Manager at Canon Medical.
“With the move to value-based care, imaging leaders are recognizing they need to leverage data not only to become more clinically efficient, but also to run their businesses smarter and uncover opportunities for greater cost-efficiency,” says Clemmons. “Like their clinical counterparts, who have embraced an evidence-based care model, we now are seeing imaging leaders embrace the concept of evidence-based management — using financial, clinical and operational data to inform business decision-making.
Where do you sit on the analytics maturity curve?
Every imaging business sits somewhere on the maturity spectrum, explains Clemmons. “To become data driven, the trick is to understand where you are today, and where you want to be in three or five years time.”
For many organizations, the first crucial step is unlocking access to data stores scattered across the organization. The next big leap is in adopting a solution that allows non-IT people to efficiently access the data they need, in a timely manner, and in a format that is easily understood by someone other than a trained data scientist.
“Currently, many organizations are hamstrung in their ability to access, and interpret data in real-time,” says Clemmons. “I envision a day — and I don’t think this is far off — where a management team can sit at a boardroom table and call up the data they need to make a sound business decision during the meeting. The fact imaging leaders have to enlist specialized data expertise today and wait weeks to get the answers they need is ludicrous.”
HIMSS Adoption Model for Analytics Maturity
To better understand the power analytics can offer to their organization, Clemmons points imaging business leaders to the HIMSS Adoption Model for Analytics Maturity (AMAM). It is an international eight stage model that measures the capabilities a healthcare business gains from from installing technology and surrounding processes.
Says Clemmons, “Most data today is locked in proprietary databases. And when you finally gain access to it you don’t need more spreadsheets. That’s not helpful. You need to be able to get a clear picture of business-related data, presented in the moment. And it needs to be delivered in a visual way that is most meaningful to you.”
Sidebar: HIMSS Adoption Model for Analytics Maturity
Stage 7
Personalized medicine and prescriptive analytics
Stage 6
Clinical risk intervention and prescriptive analytics
Stage 5
Enhancing quality of care, population health, and understanding the economics of care
Stage 4
Measuring and managing evidence-based care, care visibility and waste reduction
Stage 3
Efficient, Consistent Internal And External Report Production And Agility
Stage 2
Core Data Warehouse Workout: Centralized Database With An Analytics Competency Center
Stage 1
Foundation Building: Data Aggregation And Initial Data Governance
Stage 0
Fragmented point solutions
