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Unleashing Healthcare data from Silos
of the biggest issues in healthcare research is the inability of
researchers to obtain meaningful healthcare related data easily.
Information silos of healthcare data exist across both private and
public sectors with almost no cross-team access. Its almost like
multiple players trying to solve a puzzle with each player having one
piece. Anyone who loves puzzles can see how difficult it can be if you
can only see your own puzzle piece and none of the others. Believe me,
it is frustrating!
What is a data silo and why is it bad?
silos is data that is aggregated from a few isolated data sources and
accessible by one or a few related organizations. This can result in
lack of transparency, efficiency and the kinds of applications that the
data can be used for. This is true for any kind of data but is
especially true for data in health care sector. Management of healthcare
data in addition to having usual challenges of hard-to-obtain IT
skills, limited budgets and managerial overload also must carry the
burden of additional privacy regulations and legal frameworks such as
HIPAA and others.
What are some steps you can do to bust out of data silos?
first and most powerful tool in your arsenal is to educate and increase
awareness of your administrators and management about the benefits of
collaborations that come into play once data silos are busted.
The second most important step
is to choose the right technology stack or family of products that
enables this. It is important to note that if you choose the wrong tool,
even if your team is motivated to live in a data silo-less world it
will not be easy. So, choose your tool carefully, very carefully.
While making the necessary
changes will not be simple or speedy, enhancing seamless data access is
an objective that will help the healthcare industry meet the majority of
its quality, safety, and efficiency goals cutting across multiple
dimensions of care and research. So, keep chugging!
Pro Tip: Look for tools that can work along side your existing tools and avoid the whole dreaded "rip-and-replace" path.
In the just concluded Wimbledon Tennis Tournament IBM showcased some cool technology. IBM SlamTracker™ - a real time statistics and data visualization platform that leverages IBM's predictive analytics technology. It provides an ‘at a glance’ visual representation of a match using scores and statistics and encourages fans to get more involved by interacting with the data to gain deeper insight into the game. IBM SlamTracker™ analyses over eight years of Grand Slam data (over 41 million data points), to identify patterns in players and their styles. Before each match, IBM analyses historical matches between the players (or between players of similar styles if the players in question have not met before). In the last couple of years IBM did trial runs of SecondSight , which for the first time enabled the viewer to track the direction, speed and distance of players as they moved about the court. Data from SecondSight enables displays such as one below. Hopefully
Following is a great resource for any one considering different choices for their "NoSQL" style frame work. As always, "one-size-fits-all" approach does * not * work for NoSQL frameworks. Just as a side note that MongoDB, Cassandra and CouchDB are the top three skills sought out on indeed.com (popular aggregator of job boards) of all the databases in the table below. Having a large pool of talent is always a good thing for your technology choice. Source : International Journal of Database Theory and Application, NoSQL Database: New Era of Databases for Big data Analytics Classification, Characteristics and Comparison, A B M Moniruzzaman and Syed Akhter