Source proof for Myriad Genetics speeds document processing with AWS GenAI Intelligent Document Processing Accelerator

How Myriad Genetics achieved fast, accurate, and cost-efficient document processing using the AWS open-source Generative AI Intelligent Document Processing Accelerator | Artificial Intelligence Skip to Main Content Filter: All English Contact us A…

…imized prompts for document classification, achieving significant improvements: classification accuracy increased from 94% to 98%, processing costs decreased by 77%, and processing speed improved by 80%—reducing classification time from 8.5 minutes to 1.5 minutes per document. Automating Key Information Extraction with generative AI Myriad’s information e…

…n four minutes instead of six minutes due to faster access to tagged documents. This improvement saves 300 hours monthly across 9,000 prior authorizations in Women’s Health alone, equivalent to 50 hours per prior authorization specialist. These measurable improvements have transformed Myriad’s operations, as their en…

…ations need solutions to process documents effectively to meet growing demands. Myriad Genetics , a provider of genetic testing and precision medicine solutions serving healthcare providers and patients worldwide, addresses this challenge. Myriad’s Revenue Engineering Department processes th…

…st was written with Martyna Shallenberg and Brode Mccrady from Myriad Genetics. Healthcare organizations face challenges in processing and managing high volumes of complex medical documentation while maintaining quality in patient care. These organizations need solutions to process documents effectively to meet gro…

…Character Recognition (OCR) with Amazon Comprehend for document classification. Despite 94% classification accuracy, this solution had operational challenges: Operational costs : 3 cents per page resulting in $15,000 monthly expenses per business unit Classification latency : 8.5 minutes per document, delaying downstream prior authorization workflows Information extraction was entirely manual, requiring contextual understanding to differentiate critical clinical distinctions (like “is metastatic” versus “is not metastatic”) and to locate information like insurance numbers and patient information across varying document formats. This processing burden was substantial, with Women’s Health customer service requiring up to 10 full-time employees contribu…

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…rehensive benchmarking using the GenAI IDP Accelerator’s evaluation framework . We tested four foundation models—Amazon Nova Lite, Amazon Nova Pro, Amazon Nova Premier, and Anthropic Claude Sonnet 3.7—using 1,200 healthcare documents across three document classes: Test Request Forms, Lab Results, and Insurance. We assessed each model using three critical metrics: classification accuracy, p…

…employees working 78 hours daily per business unit. Business impact and rollout Myriad has planned a phased rollout beginning with document classification. They plan to launch our new classification solution in the Women’s Health business unit, followed by Oncology and Mental Health divisions. As a result of our work, Myriad will realize up to $132K in annual savings in t…

…raightforward per-page pricing. This pattern is recommended for most use cases. Pattern 2 – Uses Amazon Textract and Amazon Bedrock with Amazon Nova, Anthropic’s Claude, or custom fine-tuned Amazon Nova models. This pattern is ideal for complex documents requiring custom logic. Pattern 3 – Uses Amazon Textract, Amazon SageMaker with a fine-tuned model for…

…ering, document-format based classification strategies, and negative prompting. We reduced classification costs by 77% (from 3.1 to 0.7 cents per page) by migrating from Amazon Comprehend to Amazon Nova Pro with optimized prompts. We reduced classification time by 80% (from 8.5 to 1.5 minutes per document) by…

…Women’s Health business unit, followed by Oncology and Mental Health divisions. As a result of our work, Myriad will realize up to $132K in annual savings in their document classification costs. The solution reduces each prior authorization submission time by 2 minutes—spec…

…oss multiple business units and document types Amazon Bedrock and generative AI Modern large language models (LLMs) process complex healthcare documents with high accuracy due to pre-training on massive text corpora. This pre-training enables LLMs to…

…ain by focusing on prompt design, including negative prompting and visual cues. We optimized both cost and performance by selecting Amazon Nova Pro for classification and Nova Premier for complex extraction—matching the right model to each specific task. Explore the solution for yourself Organizations looking to improve their docume…

…and document structures without feature engineering or large labeled datasets. Amazon Bedrock is a fully managed service that offers a broad range of high-performing LLMs from leading AI companies. It provides the security, privacy, and responsible AI capabilities that healthc…

…and document structures without feature engineering or large labeled datasets. Amazon Bedrock is a fully managed service that offers a broad range of high-performing LLMs from leading AI companies. It provides the security, privacy, and responsible AI capabilities that healthc…