Lighthouse Achieves Review Efficiency and Cost Control for a Global Healthcare Company
Lighthouse partners with a healthcare company, saving $145K in document review costs after reducing review time by 90% through a custom review process.Download case study PDF
Reduction in Document Review
How We Did It
Lighthouse used our proprietary processing automation to ingest, load, and deduplicate a total of 690K documents. Our deduplication process was able to immediately achieve a 25% data reduction by removing 175K documents.
ECA Culling and Search Term Iteration Results
Next, Lighthouse applied our customized culling and search term iteration processes to the 143K eligible documents and families. This process removed 81K documents, reducing the review population by over 55%.
Thread Suppression and Proprietary Review Technology Results
Lighthouse then implemented a customized workflow that combined email thread suppression with our proprietary review technology to identify the most unique documents. This process removed a total of 31K documents from the review population, thereby reducing the review population by another 50%.
Lighthouse TAR and Advanced Analytic Results
After the culling process, Lighthouse’s Review & Advanced Analytics team guided counsel through a Continuous Active Learning TAR workflow to find relevant documents. Once we reached a point of diminishing returns, we leveraged advanced analytics such as clustering, categorization, and concept search to ensure that no relevant documents were left behind. Our TAR and advanced analytics removed 17K documents, representing another 50% in data reduction.