(sin-thuh-sis), noun, plural - syntheses. A complex whole formed by combining.

The world of medicine is full of activities that involve synthesis of data. Every day doctors and nurses synthesize data from multiple sources as they care for patients. They aggregate verbal data from the patient, the patient’s family, emergency medical technicians, care managers and other caregivers. They combine this information with such things as data reports from laboratories, medication lists from pharmacies, notices from insurance companies, and imaging reports from free standing centers. They synthesize this data with other information such as trends reported in medical studies involving similar patients, news reports and weather information. And notice all of this data synthesis needs to occur in addition to reviewing the data available from various electronic medical record systems used by multiple providers involved in a given patient’s care.

Of course all of this data, even when available in electronic form, can be very difficult to aggregate, not to mention synthesize in an effective way to drive clinical and administrative decision making. It is rare to find a health care worker who will not admit wasting time every day searching for data, even those who work with a supposedly comprehensive electronic health record system. And I’m not proud to admit that in my own clinical practice I saw directly the impact of having to make decisions without knowing what I didn’t know, and subsequently seeing less than optimal outcomes.

I strongly believe the health care industry, like other big complex industries, is best served by a diverse range of systems that support ongoing rapid innovation, rather than dependence on a monolithic software system and a monopolistic business model. But in a world of diverse systems, interoperability of those systems is needed, and aggregation of data from diverse systems is essential to enable data synthesis for various business purposes.

The Caradigm™ Intelligence Platform (CIP) was created as a robust solution to address this issue. Now in its third generation as a commercial product, the platform includes state of the art tools that enable efficient ingestion and aggregation of data from multiple diverse source systems. These tools provide a visual environment for mapping, interpreting and validating data, correctly matching data to patients, deriving calculated fields, applying predictive analytic algorithms, tagging to standardized terminology services, and grouping data into intelligent conceptual entities.

In turn, CIP surfaces that data through an open application framework for multiple uses, whether end user applications are built by Caradigm, customers or third-party partners. All of these mechanisms allow CIP to “pre-position” data for further data synthesis by healthcare knowledge workers, so they can do their jobs with high efficiency and high quality. Diverse data systems supporting innovation, and at the same time aggregating data to support data synthesis tasks by smart people, result in improved outcomes – pretty cool stuff!