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.