·
Improve the accuracy of data that needs to be shared between disparate
operational systems and external trade partners by creating a Gold Standard master
in that Info Hub.
·
Improve the operational efficiencies by automating the daunting tasks of
validating, cleansing and integrating critical reference data that needs to be
shared between operational applications and trade partners.
·
Reduce the business risks to the enterprise due to erroneous data on
critical compliance and regulatory reporting.
·
In the case of the ICD-9àICD-10
conversions. ICD-10 opens the door to
analyze medical procedures and protocols and their outcomes at a more granular
level. As companies achieve meaningful use of EMRs (Electronic Medical Records)
applications, more detail about symptoms, diagnosis, treatments, protocols,
supplies, involved professionals, outcomes, ongoing patient vitals and
re-admittance detail are available for analysis than ever before. ICD-10 encoding provides a level of detail to
enable more robust analysis.
· This opens the door for performing more sophisticated Business Discovery
and cause/effect predictive/prescriptive analytics. As Healthcare providers seek to be a member of an Accountable Care Organization (ACO) the ability to identify areas of
potential treatment improvement through predictive and prescriptive analysis puts
them in a much better position to score well across the ACO scoring
criteria as established by Centers for Medicare and Medicaid Services (CMS). Today, there are 33 measures
for quality care. Score well on these
and Medicare/Medicaid will reimburse at 100% of defined eligible benefit. Providers that do a poorer job in providing
care (as evidenced by the lower scores) will receive less of the total eligible
reimbursements. This is lost revenue
(revenue leakage).
Another area where advanced predictive/prescriptive analytics can be
helpful is in finding root causes for data quality issues that MDM hubs are commissioned
to resolve. The goal is to improve the
quality of the data (enforce MDM golden standard business rules) at point of
original inception. Move the MDM
cleansing/Golden Record processing from a bulk-batch based method to an on-demand/transactional
based processing method. Predictive
analytics helps uncover root-causes for poor quality and can analyze and
predict which data elements will have the greatest adverse ramifications due to overnight processing lag
times. This can be used to prioritize
the most critical elements that should be moved to on-demand cleansing and gold
standard processing.
Many MDM Programs do not have a means to analyze the overall enterprise
data quality improvement of an MDM Information Hub over time. Nor do they track the
changes/trends in the level of effort/operational costs applied across all of
the data elements in the MDM info Hub.
Here is an opportunity to implement data warehouse, business
discovery and advanced analytics
principles on top of their MDM business function (much like enterprises do
for their traditional line-of-business functions such as Marketing Campaign
Management, Sales Activity Management, Order Fulfillment, Inventor Management,
etc.).
Some enterprises are realizing the golden standard data asset within a specific
information hub has intrinsic value to their industry. Innovation
minded enterprises are finding ways to leverage their hubs to sell packaged, value-added
analytics and data-provider services to other enterprises and service-providers
in their industry. In the Healthcare
industry as Health Information Exchanges (HIE) gain adoption, care-provider enterprises with high quality information hubs will contribute to and take advantage of various HIEs to improve their ability to market services
via the HIE open market by exposing/promoting their performance metrics vs. that of the local competition
and/or global niche-provider/specialist competition.
Are you looking for ways to monetize your MDM Information Hubs? Are you already monetizing your MDM Information Hubs? Would love to hear from you.
