10 Trends in Healthcare Data Warehousing That Every Health System Needs to Know
As I travel around the country and chat with folks in our industry about analytics, I see topics of interest come and go in the healthcare data warehousing and analytics space. Below are the trends and topics that are hot right now, listed in no particular order, along with the questions that organizations are struggling to answer. By the way, I purposely left off the forgone topics of predictive analytics and population health management.
- Mergers, Acquisitions, and Partnerships: The reality is settling in – the grand aspirations of MA&P are now facing the harsh reality of data integration. The newco executive team is having a difficult, if not impossible, time producing simple GL and other management reports about the new organization. The dreams of measuring clinical quality and costs across the new enterprise are now seen as somewhat unrealistic. It’s back to basics for analytics. Word to the wise: your MA&P strategy must be accompanied by a data acquisition and integration strategy, too.
- Evolving Legacy Platforms: How do we evolve our existing data warehouse for the future that requires agile data consumption and utilization? Most organizations that are asking this question are typically using a very “early binding” data model, characterized with a centralized, monolithic data model. They are struggling to keep pace with loading new data sources – for example, coming from their ACO partners – and meeting new analytics use cases under Healthcare 2.0.
- EHR vs. Analytics Specialty Vendors: Will our EHR vendor meet our analytics needs or do we need an analytics specialty vendor? Do we need both? If so, how do we minimize the overlap and maximize the strengths of each?
- Data Governance: How do we get it started and what is its charter and purpose? Who should be on the committee and what should the committee be worried about? If we had a data governance function and it faded, how do we get it back on-track?
- Research vs. Operational Analytics: The data gap in academic medical centers between research analytics and operational analytics has been a problem for years, but now it’s less tolerable because of security risks and inherent inefficiencies. How do we close that gap with a common technology and governance structure?
- ACO Analytics: Who’s going to “own” the data warehouse and analytics function in an ACO (commercial or federal) and what does that data warehouse offer for data content and services? Where does that data warehouse physically reside, who is responsible for its operation, and how is it governed?
- Analytics Skills: There is a critical shortage of analytics skills and a general lack of data literacy in the existing workforce – what are we going to do about that in our organization?
- Cost Accounting Analytics: There is greater attention to and momentum behind cost accounting (vs. charges or reimbursement) analytics. I expect this trend to continue for the next several years, and rightly so. We are way behind on this topic in our industry.
- Physician-led ACOs: There is increasing attention on, and momentum behind, analytics investments from physician-led ACOs. The tide has turned.
- Small Hospital ACOs: There is increasing attention on, and momentum behind, analytics in safety net and critical access hospitals. How do small organizations with limited budgets and skills pool those resources for shared analytics?
Are there other healthcare data warehousing and analytics trends that you’re aware of? Something I’ve overlooked? Contact me directly by commenting below, or share your thoughts and concerns with me and our followers via LinkedIn, Facebook or Twitter.
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