The document discusses challenges with healthcare data. It explains that data is created in different applications for different purposes, degrading quality as it moves through an organization with limited metadata. New data flows are often created instead of using existing data. Additionally, applications are managed separately without awareness of broader data use, and subject matter experts are difficult to identify. Creating data in silos for individual groups can be initially cheaper but leads to long-term duplicate costs across an organization. The document provides tips to address these challenges such as adopting standard metrics, collaborating across teams, educating others, and following data standards and policies.

1. Healthcare Data Challenges
Prepared by Angela Boyd
2017

2. Problem: Why is there so much data and so little value?
Some of the Challenges Explained:
-Multiple applications are used to create data (for varying purposes
with varying levels of quality). Data degrades or changes as it moves
throughout the organization.
-Limited meta data may be available/easily understood by those
trying to use the data.
-People and projects with data needs often create new data flows
because it seems easier than using existing data.
-New data is created ‘in a vacuum’ for one reporting group/project
without a view of enterprise needs/synergy with others that also
need the data.

3. Problem: Why are data challenges so hard to fix?
Some of the Challenges Explained:
-Multiple applications are managed separately by differing reporting
structures and processes. In many cases, people are not aware their
data is used for reporting by other teams that secure a copy of a
copy.
-Subject matter experts of data, sometimes referred to as Data Heros,
are hidden in the organization, or buried under requests to explain
the data. Identifying and accessing these individuals can be difficult.
-It is almost always faster/less expensive (up front) to create data ‘in a
vacuum’ for one reporting group/project without a view of enterprise
needs/synergy with others that also need the data. It’s later, you
realize the costs of multiple groups creating the same/similar data,
technical support, data storage, data quality, multiple platforms
/licenses, data security risks/compliance audits, etc.

4. Solution: Tips to Try
• Consider adopting a standardized metric template/business
information requirements for reporting/metric catalog
• Collaborate with other reporting teams to find synergy
• Educate/communicate with others/find out what you don’t know and
teach what you know
• Ensure that you’re following company data standards and policies
• The Reporting and Analytics Team(s) that are the best collaborators
and communicators will grow and be relied upon by organization
• Form close partnerships with your suppliers and consumers