There is a popular word game in newspapers called ScrambleTM where the player is asked to take a list of seemingly random letters and rearrange them to form a meaningful word or phrase. My task in this blog is not dis-similar in that for healthcare reform efforts to be successful at the provider level, an unscrambling of the key information into meaningful analysis at the point of care is required. Healthcare Intelligence aims to solve the problem of unrelated, disparate data sources into actionable insight. Organizing the data through modern technologies to solve today’s toughest challenges is what “HI” is all about.
OILSS FO NITAMROFNOI
Healthcare providers have a wide variety of systems that are used to solve particular needs within their practice today. There are practice management (PM) systems that help keep track of the business side of medicine. Then there are electronic medical record (EMR) systems used for the ongoing clinical record of patients. As if this were not enough of a challenge to data management, there are new systems emerging that help assist with chronic care management programs and still others that help with community of care needs like health information exchange (HIE) to keep track of a patient’s care across the care continuum. The resulting mass of disconnected data which typically reigns in the current environment amounts to “SILOS OF INFORMATION”. Few practices have a strategy today let alone a system that makes sense between clinical, financial, and external sources of data to provide a holistic view of the cost and quality performance for a given physician, within a specialty, within a larger practice, or across an IDN.
With the explosion of data created privately as well as the increasingly available public sources of data, the requirement for a reporting and analytic system to handle “BIG DATA” applications is increasingly important. Big data is a loosely defined term that involves technologies and processes to handle very large quantities of data. A bevy of new technologies have emerged in this space including Cassandra, Hadoop, R, and Dynamo. As a practical matter, providers should know that whatever new capabilities they want to build for handling tomorrow’s information challenge, a solid infrastructure built on modern technologies is recommended in place of yesterday’s relational database, non-distributed platforms that are not structured to handle the performance requirements of modern intelligence needs.
The formidable challenge of healthcare reform is to solve a number of individually difficult tasks outlined by the Triple Aim, which is “better care for individuals, better health for populations, and lower per capita costs”. The intersection of these three tasks require coordination of resources and a heck of a lot of data analysis which can adequately inform the various parties, including the patient, as to the best plan of action. The spirit of “accountable care” is that responsible parties manage to improve on all three dimensions without compromise. Putting aside the veritable task of coordination of providers, the challenge of arranging the data so that it is comparable and relevant across sources is perhaps the biggest challenge of all with respect to healthcare intelligence.
Healthcare Intelligence, then, is a new umbrella that can used to describe the processes and science including reporting, analytics, forecasting, prediction, or prescriptive techniques used to affect decisions in the healthcare industry. Where business intelligence commonly refers to financial and operational trending and analysis, “Healthcare Intelligence” is a mix of business intelligence and clinical informatics, where clinical informatics is used to measure and optimize processes around clinical care by providers and researchers.
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