Business Intelligence and Big Data

Why Invest in Health and Human Service Business Intelligence?

Business Intelligence (BI) provides information that will assist DSS to:

  • Design program and services that deliver individualized care matched to the person (just like precision medicine).
  • Evaluate and identify services that are meaningful, cost-effective, efficient, add value, and improve people’s lives.

The challenge is in predicting and prescribing services that are person-centered but can be delivered at the program-level.


DSS will use data that are directly related to the services received enriched with contextual data.  This would happen when we “meaningfully” integrate clinical, non-clinical, cost, location, and social determinant data to understand the complexity of social issues and challenges. Once we have a better understanding of the context of these lives, only then can we address challenges, learn from our processes, resulting in delivery of effective, and efficient services.

DSS’s HealthIT and BI Framework

DSS Health Information Technology (Health IT) and BI framework is built upon the 2012 recommendations of the Health Technology Workgroup of the Connecticut Health Care Cabinet[1] and the 2013 Health IT Strategic and Operational Plan.[2]   The Health IT and BI framework is driven by a person-centric focus and follows the premise that technology needs to support the health care systems, information, and business needs.  The ultimate goal is better health outcomes for people.  The health care delivery system is built with the aim of improving access to services, educating and informing people, better services and supports, and a transparent system of care.

DSS’s HealthIT & BI Framework

Health IT & BI Framework chart.

DSS’s Big Data Technology Solutions

In 2016, DSS started integrating a variety of clinical and administrative data to describe the population served, using standards-based software.  The Business Intelligence team at DSS continues to build and index databases that integrate many disparate data sources.  DSS uses the Zato Health Interoperability Platform (ZHIP) a cooperative distributed processing  platform to aggregate and index large datasets from a variety of programs and service areas.  This solution also uses natural language processing tools and a medical ontology to mine text data [3] in real-time to extract meaningful concepts for coding, analysis, and interpretations.  . In 2016 ZHIP was certified through OSEHRA to compute eCQMs to CMS standards using the popHealth software tool.  In 2018, DSS is just beginning to receive admission-discharge-transfer feeds in real-time, and is currently working to implement the personal health record on the HealthShare platform which will support Medicaid’s HIE note.

Additionally, in the past two years the ZHIP was used to match and assess population overlap with services captured in previously unconnected systems, like the Homeless Management System, Dept. of Labor, Supplemental Nutrition Assistance Program, Medicaid, and other DSS data sets. Currently Zato Health is enhancing its cooperative edge server architecture by adding federated databases, which enable data analytics across systems without moving the data to a centralized location.

If you would like additional information on this project or would like to leverage our technology, please

Updated 2/4//2020

[1] Integrating Connecticut’s Health Information Technology: A White Paper prepared by the Health Technology Workgroup of the Connecticut Health Care Cabinet, August 29, 2012.

[2] Department of Public Health, Update to Strategic and Operational Plan for Statewide HIE in Connecticut, February 28, 2013.

[3] A key feature of this software is the ability to automatically hyperlink to highlight evidence within the source data in order to more easily and quickly verify the accuracy of results in performance reports and audits