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[NEW LAUNCH!] Introducing Amazon Comprehend Medical (AIM398) - AWS re:Invent 2018

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Amazon Comprehend Medical is a service that makes it easier for developers to leverage state-of-the-art machine learning to extract medical entities (such as medical condition, medication, dosage, strength, and frequency) from unstructured text (such as doctor’s notes, clinical trial reports, and patient health records) with high accuracy. Come learn more about how you can use Amazon Comprehend Medical to help healthcare providers and clinical researchers reduce the cost, time, and effort in processing large amounts of unstructured medical text.

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[NEW LAUNCH!] Introducing Amazon Comprehend Medical (AIM398) - AWS re:Invent 2018

  1. 1. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Comprehend Medical Arun Ravi Sr. Product Manager AWS AI/ML Taha Kass-Hout, MD, MS Amazon Introducing
  2. 2. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  3. 3. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Comprehend Medical A new HIPAA eligible service that uses machine learning to extract medical information with high accuracy, reducing the cost, time and effort of processing large amounts of unstructured medical text
  4. 4. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Agenda The customer problem of analyzing unstructured text in healthcare What is Amazon Comprehend Medical? How does Amazon Comprehend Medical Work? Where can I use Amazon Comprehend Medical? Customer –1 (Fred Hutchinson Cancer Research Center) Customer – 2 (Roche Diagnostics Information Solutions) Call to action
  5. 5. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Customer Problems 1.2 B unstructured clinical documents created per year Critical information “trapped” in these documents Difficult to extract insights
  6. 6. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Comprehend Medical Entities • Medication • Medical condition • Test, Treatments and Procedures • Anatomy • Protected Health Information (PHI) Relationship Extraction • Medication and dosage • Test and result • Many more Entity Traits • Negation • Diagnosis, Sign or Symptom Protected Health Information Identification (PHId API) Distill a complex process into a simple API call Medical Named Entity and Relationship Extraction (NERe API)
  7. 7. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Protected Health Information (PHI) Mr. Smith: Name 63: Age Comprehend Medical - NERe API Mr. Smith is a 63-year-old gentleman with coronary artery disease and hypertension. CURRENT MEDICATIONS: taking a dose of LIPITOR 20 mg once daily aws comprehend-medical detect-entities --region us- east-1 --text “<Insert Text Here>” Named Entities
  8. 8. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Comprehend Medical – NERe API CURRENT MEDICATIONS: taking a dose of LIPITOR 20 mg once daily aws comprehend-medical detect-entities --region us- east-1 --text “<Insert Text Here>” Relationship Extraction
  9. 9. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Comprehend – NERe API What are Entity Traits? (1) Negation (2) Diagnosis, sign or symptom Rash Discontinue Abraxane, patient denies taking Tylenol 325 mg and is not taking calcium carbonate, patient also stopped taking cholecalciferol 1,000 units PO Entity Traits
  10. 10. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Comprehend – PHId API Mr. Smith is a 63-year-old gentleman with coronary artery disease and hypertension. He currently lives in Seattle and works as a teacher. His PCP, Dr. John, works at the University of Washington aws comprehend-medical detect-phi --region us-east-1 - -text “<Insert Text Here>” In addition to extracting PHI, the PHId API identifies relevant patient identifiers described in HIPAA Safe Harbor method of de-identification Protected Health Information
  11. 11. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  12. 12. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Where is NLP leveraged in Healthcare? Patient & population health analytics Clinical Trial managementRevenue cycle management (Medical Coding) Pharmacovigilance PHI Compliance What else?
  13. 13. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Patient & Population Health Analytics Challenges Amazon Comprehend Medical Outcomes Unstructured data is difficult to mine Example: Clinical team in the ICU makes over 120 decisions about care per day, how do you keep up? Create ”single-lens” on a single patient
  14. 14. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Revenue Cycle Management – Medical Coding Challenges Amazon Comprehend Medical Outcomes Process of coding or classifying patient records according to the International Classification of Diseases (ICD) is one of the most complex transactions Impact coding efficiency and reduce burden on clinical staff
  15. 15. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Clinical Trial Management Challenges Amazon Comprehend Medical Outcomes Identify the right patients for clinical trials quickly Allow for quick and accurate indexing across large patient populations
  16. 16. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Pharmacovigilance Challenges Amazon Comprehend Medical Outcomes Multiple avenues of reporting adverse drug reactions or adverse events Decreased burden on staff and improved throughput
  17. 17. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. PHI Compliance Challenges Amazon Comprehend Medical Outcomes Difficult to maintain HIPAA compliance and technical requirements for PHI Accurate way to create inventory of sensitive PHI
  18. 18. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Fred Hutchinson Cancer Research Center Hutch Data Commonwealth Matthew Trunnell Chief Information Officer and Vice President of Information Technology Executive Director, Hutch Data Commonwealth Customer Story
  19. 19. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  20. 20. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  21. 21. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
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  23. 23. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  24. 24. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  25. 25. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
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  35. 35. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  36. 36. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  37. 37. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  38. 38. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  39. 39. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  40. 40. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  41. 41. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  42. 42. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  43. 43. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  44. 44. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  45. 45. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  46. 46. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  47. 47. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  48. 48. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  49. 49. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  50. 50. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. NAVIFY®: Using NLP to enhance data quality and enable Clinical Decision Support Anish Kejariwal Director of Engineering, Analytics Roche Diagnostics Information Solutions (DIS) Customer Story
  51. 51. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. Roche is positioned to deliver cutting-edge capabilities Decision support software with 120 years of medical innovation rooted in science • Leading provider of cancer treatments worldwide • 137 million patients treated with Roche medicines • Focused on major medical indications and disease areas • #1 in biotechnology and in vitro diagnostics • 19 billion+ diagnostic tests performed • Advanced scientific knowledge and technology that increases the medical value of diagnostic solutions NAVIFY® Decision Support Portfolio Workflow + Data + Analytics Diagnostics Pharmaceuticals
  52. 52. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. NAVIFY® Decision Support portfolio A fully integrated portfolio of scalable, secure workflow solutions and apps designed to support care teams with analytics and actionable insights.
  53. 53. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. Unstructured healthcare data challenges for NAVIFY® Portfolio • Diverse customers distributed across the world • Multiple languages • Different diseases* • Different report formats (ex: pathology, radiology) • Different terminologies Must unlock unstructured data to build a comprehensive, longitudinal view of the patient, and enable both clinical decision support and population analytics *In development
  54. 54. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. Sample TCGA Pathology Report • The Cancer Genome Atlas (TCGA) is a joint effort of the NCI and the NHGRI to accelerate our understanding of the molecular basis of cancer • Hosted on Amazon S3 and NCI’s Cancer Genomics Cloud • Pathology reports are very diverse • Pathology reports often have tables, key-value pairs, and hand-written notes
  55. 55. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. Manually curated TCGA report Manual curation is extremely time consuming, expensive, and prone to error
  56. 56. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. Sample results from curation Token (word) Entity Category Mastectomy Procedure Left Specimen Laterality Upper outer quadrant Tumor Site 4.5 x 2.0 x 2.0 cm Size of Invasive Carcinoma Medullary carcinoma Histologic Type 0 Number of Lymph nodes Involved in Tumor 5 Number of Lymph nodes examined pT2 Primary Tumor (pT) pN0(i-) Category (pN)
  57. 57. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. The NAVIFY® team identified two significant needs NLP: specialized for medical data • Minimizes time to train NLP models Standard Criteria: • Scalable (support 10 million pathology reports per year) • Low cost • Compliant with applicable privacy laws • Integrates easily with AWS services • Serverless, when possible Text and Structured Data Extraction: extract text from scanned documents into a machine-readable format • Retains document structure (e.g., tabular data) to provide context for NLP
  58. 58. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. [] [] [] [] [] [] [] [] [] [] [] [] [] [] [] [] [] [] [] [] NAVIFY® Portfolio Architecture in Consideration Support NAVIFY® products and analytics Raw PDFs Text Extraction Machine Readable Text Structured Data Data Flow Overview* Unstructured Text Structured Text from EMR NLP H O S P I T A L S *In Development
  59. 59. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. © 2018 F. Hoffmann-La Roche, Ltd. NAVIFY is a trademark of Roche. This presentation is for educational purposes. The use of NLP will be a journey • Initial goal of speeding up review of pathology reports • Will then automate extraction of high confidence entities and relationships (low hanging fruit) • Will keep increasing automation of NLP over time The release of Amazon Comprehend Medical and Amazon Textract is well timed to begin the journey of structuring data to improve data quality and better enable clinical decision support Automated Manual T I M E
  60. 60. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Thank you! Anish Kejariwal Director of Engineering, Analytics Roche Diagnostics Information Solutions (DIS) anish.kejariwal@roche.com We are hiring! https://www.navify.com/careers/
  61. 61. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Call to Action Webpage: aws.amazon.com/comprehend/medical Blog: https://aws.amazon.com/blogs/aws/amazon-comprehend-medical- continuously-trained-natural-language-processing-for-healthcare-customers Email: ravarun@amazon.com
  62. 62. Thank you! © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  63. 63. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

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