1. Using Business Intelligence to Monitor Clinical Quality Metrics Ervina Resetar a,MIM, PMP, Laura Noirot a, BS, Richard M. Reichley b, RPh, Patricia Storey b, MHA, RHIA, Ann M. Skiles b, MIM, Patrick Traynor b, MA, Wm. Claiborne Dunagan a,b,MD, and Thomas C. Bailey a,b, MD a Washington University School of Medicine & b BJC HealthCare Saint Louis, MO BJC HealthCare (BJC) uses a number of clinical measures to monitor the quality of services provided by each of its hospitals and alternate care sites. By establishing an enterprise data warehouse as a central repository of clinical quality information, BJC is able to monitor clinical quality performance in a timely manner and improve clinical quality. Abstract Introduction Establishing an enterprise data warehouse as a central repository of clinical quality information and utilizing ETL and BI tools for automation of data collection and report generation processes enabled BJC to support hospitals as they assess clinical performance metrics and continue to improve overall quality and resulting measurements. Conclusions  Enterprise data warehouse (EDW) was established as a central repository of clinical quality information.  Multiple data sources were integrated into clinical subject areas (data marts) within EDW.  New BIC scorecard reports with drill-through capabilities feature continuous data updates for more timely reporting.  The new infrastructure supports development and addition of new clinical quality measures.  Table 1 and Chart 1 are examples of the information available from the Best-in-Class portal. Results  Internal initiative known as “Best-in-Class” (BIC) was established as an enterprise wide clinical quality management incentive program to help hospitals to:  Achieve superior clinical quality  Minimize medical errors  Adopt evidence-based medicine standards  Ensure excellence in clinical support services  BIC organization scorecards include:  CMS Hospital Quality Initiative Measures  Joint Commission ORYX® Core Measures and  Measures supported by BJC Senior Leadership  The Scorecards are produced monthly and are used by individual organizations to measure quality and make timely adjustments.  Producing BIC scorecards in the past was mostly a manual process involving collecting clinical data from multiple data sources, reconciling results in Excel spreadsheets and emailing users with final reports resulting in a two month lag in the data.  This poster demonstrates the efforts involved in automating the data feed and scorecard generation processes.  To support the automation of the Best-in-Class scorecard:  Majority of data collection processes were automated using Informatica’s ETL (Extract, Transform and Load) tools  The new BIC scorecard reports were developed using Cognos’s Business Intelligence (BI) tool  The new scorecards were made available to users on a dashboard like intranet site offering html and PDF formats for viewing or printing  Drill-thru reports were developed for detailed data analysis  Figure 1 shows high level data and process flow. Methods Chart 1: BIC Performance Graph Table 1: BIC Organization Scorecard Figure 1: BIC Automation High Level Data & Process Flow