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W. Haque

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  • OS30 - Enabling High Value Analytics (ID 44)

    • Event: e-Health 2018 Virtual Meeting
    • Type: Oral Session
    • Track: Clinical Delivery
    • Presentations: 1
    • OS30.01 - Using Business Intelligence for Insights into Healthcare Data (ID 128)

      W. Haque, University of Northern British Columbia; Prince George/CA

      • Abstract
      • Slides

      Purpose/Objectives: Healthcare organizations gather large volumes of data which continues to exist in legacy formats making it difficult to analyze or use effectively. Over the last few years, we have engaged in collaborative research projects to apply business intelligence (BI) techniques for integrating, analyzing and reporting on such data. The projects have spanned areas of Critical Care, Services Availability, Ambulatory Care, Patient Transfer, and Trauma. Services availability is guided by population, patient and case mix group profiles. While population profiles focus on demographics, the patient profile provides an overview of health-related metrics within selected regions by showing information such as births, commonality of chronic conditions, and prevalent or vaccine preventable diseases. Comparative reports are generated at various levels of hierarchy ranging from health service delivery areas to individual facilities. Adequate analysis of ambulatory care sensitive conditions results in preventable hospitalizations and enhanced patient care. In addition, predictive analytics models were built to guide resource allocation based on the forecasted trends. The inter-facility patient transfer dashboard uses BI techniques to analyze data related to healthcare infrastructure and services, and provides a web-based system to quickly identify optimal destinations for inter-facility transfers. The solution is now being extended for province-wide adoption. Finally, the trauma project is intended to provide data-driven perspective of incidences, mortality and transportation along several dimensions.

      Methodology/Approach: Our agile methodology consists of building multi-dimensional online analytical processing (OLAP) cubes and render reports using business intelligence tools. Intuitive navigation eliminates the need for training or user manuals; this is further enhanced by mapping tools, customized shape files and embedded objects. Data visualization, adhoc reporting, and ease of use has been the key factors in rapid adoption and deployment of these solutions. Aesthetically pleasant and interactive dashboards display KPIs with ability to navigate at finer granularity using multi-level drill-down and drill-through reports. Parameterized reports allow selection of multiple dimensions simultaneously and are rendered in a matter of seconds while sifting through years of data. The performance is further enhanced by connecting selected reports directly to optimized backend data warehouse. User-friendly web forms safely constrain future data entry and ensure consistency. For existing repositories, integration modules are developed to cleanse and upload data from disparate sources. Data anonymization and aggregation is used where warranted. For privileged information, access controls have been implemented. Our designs are modular and allow for incremental development.

      Finding/Results: The benefits are multi-faceted with the audience ranging from managers and physicians to strategic decision makers. In some cases, this work has also yielded unintended benefits. For instance, the critical care and services availability dashboards have been used for orientation of newly recruited physicians.

      Conclusion/Implications/Recommendations: Our objective is to share our findings from several years of demonstrated success with peer groups and demonstrate the effectiveness of our approach. Most development occurs in an academic setting working closely with partners in the healthcare organizations. The presentation will consist of numerous dashboards, web forms and reports. The challenges encountered will also be discussed.

      140 Character Summary: Analytical processing techniques can immensely accentuate healthcare data making it more valuable. This will be demonstrated via dashboards, forms and reports.

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