Browsing by Subject "data warehouse"

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    A Multidimensional Data Warehouse for Community Health Centers
    (2015-11-05) Kunjan, Kislaya; Toscos, Tammy; Turkcan, Ayten; Doebbeling, Brad N.; BioHealth Informatics, School of Informatics and Computing
    Community health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics. The resulting multidimensional data warehouse is highly practical and is designed to provide a foundation for wide-ranging healthcare data analytics over time and across the community health research enterprise.
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    Overview, not Overwhelm: Framing Operational BI Tools using Organizational Capabilities
    (2013) Purkayastha, Saptarshi; Braa, Jørn
    In contexts where fragmentation of information systems is a problem, data warehouse (DW) has brought disparate sources of information together. While bringing data together from multiple health programs and patient record systems, how does one make sense of huge amounts of integrated information? Recent research and industry uses the term, “Operational BI” for decision making tools used in operational activities. In this paper, we highlight the use of DHIS 2, a large-scale, open-source, Health Management Information System (HMIS) that acts as a DW. Firstly, we present the results of a survey done in 13 countries to assess how Operational BI Tools are used. We then show 3 generations of BI Tools in DHIS 2 that have evolved from action-research done over 18 years in more than 30 countries. Secondly, we develop the Overview-Overwhelm (O-O) analytical framework for large-scale systems that need to work with Big Data. The O-O framework combines lessons from DHIS 2 BI Tools design and implementation survey results.