Tag Archives: data as an asset
A lesson learned from other industries, like retail and financial services, is that while analytics and data warehouses are critical components to delivering big results from data — neither is easy. Gartner reported that 80% of data warehousing initiatives fail to meet expectations, often running over budget and failing to deliver a ROI.
- Executives are often frustrated because responses to their requests for new reports and edited reports take too long
- Misunderstood requirements and costly rework are the result of a lack of collaboration between stakeholders and IT
- BI consumers lose confidence in data; they don’t trust it because they lack transparency into its lineage and don’t understand why it appears differently after being aggregated with data from other applications
Expecting value from data without making a commiserate investment in data results in unmet expectations. Accessing data is hard, each request requires new effort, establishing enterprise standards for data quality are an enormous effort and transforming data to fit into a heterogeneous intelligence environment is complicated and time consuming.
Introducing multiple sources of data across organizational boundaries creates a need for an environment that supports effective collaboration between stakeholders and the information technology team implementing solutions to manage data. To be genuinely useful, data must be verifiable and trustworthy since only then will stakeholders have the confidence to make data-driven decisions. To realize the value of data, from Epic and beyond, IT leaders must implement business intelligence and data warehousing best practices that:
- bring data together across applications including clinical and financial data
- foster collaboration between clinicians, IT and business stakeholders
- establish trust and confidence in business intelligence and decision making.
EMR vendors have long encouraged that their EMR and business intelligence capabilities negate the need to have a plan to integrate data or implement a separate data warehousing and business intelligence. This philosophy begs the question – how can one transactional clinical application support the intelligence needs of an enterprise? Consider customer relationship management data for feeding customer driven marketing initiatives, time tracking data full of valuable employee utilization stats, payer claims data and newly acquired practices running an EMR independent of Epic… just to name a few.
With the recognition that an EMR accounts for only a fraction of the data needed for reliable and comprehensive business intelligence comes requirements to reconcile terminology and data quality standards across an increasingly large set of trading partners and stakeholders, to access data from other sources (like payroll, CRM and claims) and to migrate clinical data from legacy applications.
In fact, business intelligence and analytics are dependent on data from across the enterprise. Most clinical and financial decisions are dependent on data; great potential lies within data – making it a valuable asset. This is not a new idea. What is a newer concept is what it means to really elevate data to the status of an asset. Unlocking the potential of data as an asset requires that healthcare organizations begin to think about and invest in data in new ways; making investments beyond traditional infrastructure like databases and data storage. Healthcare organizations must make investments in the ongoing management and improvement of the data itself as they do with any other asset, like talent, buildings or their EMR – for example understanding its quality and allocating people and systems to managing it. Moving faster in this competitive climate and delivering differentiated results requires it.
Check back next week for Part II which explores treating data as an asset further.
If data is an asset, why should you give it away? Open data is based on the notion that some data should be freely available to everyone to use, similar to other “Open” movements such as open source software. But open data doesn’t have to only be about exposing information publicly; the same concepts can be applied inside your firewall. Here are a few examples: (more…)