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Intelligent Document Processing in Healthcare. Choosing the Right Solutions.

Healthcare organizations generate piles of documents and forms in different formats, making it difficult to achieve operational excellence and streamline business processes. Manual entry and OCR are no longer viable, and healthcare entities are looking for new solutions to handle documents.

In this presentation you can learn about:
- Healthcare document types and use cases
- IDP framework: building blocks for document processing solutions
- The document processing market landscape
- Methodology for solution evaluation: comparing apples to apples

Whether you are looking for a ready-made solution or plan to build a custom solution of your own, this webinar will help you find the best fit for your healthcare use cases.

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Intelligent Document Processing in Healthcare. Choosing the Right Solutions.

  1. 1. Choosing the Right Document Processing Solution for Healthcare Organizations Presented by: Iskandar Sitdikov, ML Solutions Architect @ Provectus Stepan Pushkarev, CTO @ Provectus
  2. 2. Webinar Objectives 1. Provide an overview of the market for document processing solutions 2. Outline critical factors for choosing the right document processing solution for your healthcare use case 1. Strategize on whether you should look for a ready-made solution to purchase, or to build a custom solution of your own 1. Get qualified for the Provectus IDP Solution Discovery Program
  3. 3. Agenda 1. Introduction 2. Healthcare use cases 3. Document processing in 60 seconds 4. Solutions map, advantages, and problems 5. Evaluation
  4. 4. Introductions Iskandar Sitdikov ML Solutions Architect Provectus Stepan Pushkarev Chief Technology Officer Provectus
  5. 5. AI-first Consultancy & Solutions Provider 500 employees and growing Established in 2010 HQ in Palo Alto Offices in North America, LATAM, and Europe Machine Learning DevOps Big Data Analytics We are obsessed about leveraging cloud, data, and AI to reimagine the way businesses operate, compete, and deliver customer value
  6. 6. Our Clients Innovative Tech Vendors Seeking for niche expertise to differentiate and win the market Midsize to Large Enterprises Seeking to accelerate innovation, achieve operational excellence
  7. 7. Healthcare Use Cases Document processing 101
  8. 8. Use cases: Clinical notes, medical records, insurance medical claims, clinical studies, medical imaging reports, lab reports, and transfers. Administrative overhead to process data from these types of documents is huge. Main benefits: Operational speed and cost reduction. In our practice, we see 2-8x сost reduction compared to a fully manual process and 30%+ savings in comparison to legacy OCR solutions. Healthcare Use Cases
  9. 9. Use cases: Clinical notes, medical records, insurance medical claims, clinical studies, medical imaging reports, lab reports, and transfers. Administrative overhead to process data from these types of documents is huge. Main benefits: Operational speed and cost reduction. In our practice, we see 2-8x сost reduction compared to a fully manual process and 30%+ savings in comparison to legacy OCR solutions. Healthcare Use Cases Clinician notes Claims Transfer summaries Medical imaging reports Lab reports Medical record Clinical studies
  10. 10. General goal is to spot main entities in the document (paragraphs, forms, tables, etc.) and then successfully identify written text in them (segmentation and OCR). Both problems can be resolved separately or using end-to-end networks. IDP / CV
  11. 11. Context search on data from OCR + segmentation Forms and tables greatly impact overall performance. Data extraction from forms is resolved (due to a straightforward key-value structure). Tables are still a pain point for all data extractors. For unstructured texts, deep networks are a solution at this point. Ex: BERT — good for finding key-value (question / answer) pairs in context. IDP / Data Extraction
  12. 12. Evaluation of the document processing model is a task in progress. Results with a low-confidence score and missing information are forwarded to human experts. Samples of successfully extracted information are also forwarded to human experts for evaluation. IDP / Evaluation and Monitoring
  13. 13. Data lake + Ontology specifications Fast Healthcare Interoperability Resources (FHIR) is a standard describing data formats and elements and an application programming interface for exchanging electronic health records. The standard was created by the Health Level Seven International healthcare standards organization. IDP / Storage
  14. 14. Data lake + Ontology specifications Fast Healthcare Interoperability Resources (FHIR) is a standard describing data formats and elements and an application programming interface for exchanging electronic health records. The standard was created by the Health Level Seven International healthcare standards organization. IDP / Storage Storage Hospitals Providers Pharmaceutical companies Patients Labs Health plans
  15. 15. Automation encapsulates all processes mentioned above and unites them into one single product, featuring: ● Document capture ● Model lifecycle ○ Labeling ○ (Re)Training ○ Evaluation ○ Monitoring ● Human-in-the-loop ● Integrations ● System monitoring IDP / Automation
  16. 16. IDP is more than just OCR. To resolve the problem in-house, you need to take care of data capture, data ingestion, preprocessing, OCR, data extraction, evaluation, and further integrations to destination systems. Bottleneck: Tables and unstructured text IDP / Takeaways
  17. 17. Solutions Landscape Market Overview
  18. 18. Documents are everywhere... and solutions for document processing are everywhere, too! Competitive Landscape
  19. 19. Major technology platforms offer general- purpose technology components for document processing, such as: ● Amazon Textract + Comprehend ● Google Document AI ● Microsoft Azure Form Recognizer Solutions: Cloud Vendors Pros: ● Cloud infrastructure and integration ● Long lifespan and support ● Constant development Cons: ● General purpose a.k.a require additional work to extract necessary information and integrate with current workflows
  20. 20. These are emerging use case-focused vendors that offer solutions using AI-native platforms to tackle the most demanding automation challenges. They can handle more complex documents with a greater variability. As a result, they often deliver a better business impact than obsolete technologies. Since they are free from legacy technical debt, it is easier for them to build next-gen, future-oriented solutions. Solutions: Startups Pros: ● Modern tech ● Constant development ● More focused applications ● Support — For a new independent player, support is one of the highest priorities to gain customer loyalty Cons: ● Only few startups in this market can survive competition with big vendors ● Challenging to customize ● May not align with your cloud strategy ● Support — On the other hand, new startups might struggle with support
  21. 21. Legacy vendors typically build IDP solutions on top of legacy platforms. Niche vendors that are focused on limited types of documents and use cases. You might find hidden gems here! Vendors that restructure your documents workflow by introducing standard types of documents, which are really easy to process. Solutions: Other Vendors Pros: ● Wide variety of integrations ● Niche use cases ● Large portfolio of clients Cons: ● In some cases, they rely on outdated, less performant technologies ● Document flow restructure
  22. 22. System Integrators may offer IDP as part of their portfolio of solutions. Their IDP offering may be a solution from another IDP vendor or developed in-house. Solutions: System Integrators
  23. 23. Vendors Evaluation Methodology
  24. 24. What to Choose? Now, you have all the information about possible go-to solutions in your market segment. What’s next? You need to fairly compare each and every solution to choose one that fits and aligns with your use case the most. Deep evaluation is key to making the right decision.
  25. 25. Data ● EDA (exploratory data analysis) — Knowing your data is the key to success ● Sample data based on EDA ● Use this data as the evaluation dataset for measuring performance of solutions on the market / in the segment Composite Index ● F1, Accuracy, Recall, etc. ● Robustness ● Key, value extraction ● Table data ● Language, character recognition, spelling, handwritten text Provectus Evaluation Methodology
  26. 26. Evaluation / Composite Index Name Score Provider 1 0.64 Provider 2 0.81 Provider 3 0.78 Composite Index Dimensions
  27. 27. Evaluation / Text Index Text index
  28. 28. Evaluation / Robustness Index Spacing index Noise index
  29. 29. TCO and Case Study: Under NDA Client General TCO structure: ● Infrastructure (data pipelines, storage, control panel) ● CV, NLP, Human-in-the-loop ● R&D costs (if building in house) ● Support TCO targets for end-to-end solution: ~20-30 cents per document for simple use cases and 50+ cents for more complex documents Result: The cost of processing one document was reduced from 24 to 11 cents, since the right OCR/CV vendor was selected (it saved almost 10 cents per document). Also, serverless architecture was leveraged to reduce infrastructure costs. OCR/CV solutions performance vs. cost: For a given use case, the most expensive solution delivered the worst result. A second to best result was demonstrated by the vendor with the second to cheapest solution. Performance vs. price
  30. 30. Buy vs. Customize vs. Build Cloud OCR + extraction APIs vs. Custom model In cases with high volume of documents, it’s worth investing in an in-house built custom model to reduce costs of extra services (ex. form and table API) in the long run. ~8th month is a break-even point on average for the IDP custom extraction model vs. APIs
  31. 31. Takeaways 1. Ecosystem matters: Data integration with built-in industry specific connectors, data pipelines, OCR, NLP, security, storage, and a human-in-the-loop workflow — All these elements should be integrated with each other for optimal performance. 1. Use unbiased benchmarking framework for evaluating real performance of different providers, based on your use case and datasets. 1. Work with Provectus to reduce your Document Processing costs a. By 2-8x comparing to manual workflows b. By 30%+ comparing to legacy OCR solutions c. By 10%+ comparing to modern cloud solutions.
  32. 32. Getting Started: Unbiased Evaluation for IDP by Provectus
  33. 33. Commitments & Deliverables Helping businesses choose the right document processing solution for their healthcare use cases. A fully funded engagement for qualified customers. IDP Solution Discovery Program. Unbiased! Schedule a 30 min. pre-assessment session here: IDP Solution Discovery Program You provide: 1. Business use cases overview 2. Access to datasets 3. Commitment to support the engagement We deliver: 1. Solutions evaluation report based on your unique data 2. Solution architecture 3. TCO estimate
  34. 34. 125 University Avenue Suite 295, Palo Alto California, 94301 provectus.com Questions, details? We would be happy to answer!

    Als Erste(r) kommentieren

Healthcare organizations generate piles of documents and forms in different formats, making it difficult to achieve operational excellence and streamline business processes. Manual entry and OCR are no longer viable, and healthcare entities are looking for new solutions to handle documents. In this presentation you can learn about: - Healthcare document types and use cases - IDP framework: building blocks for document processing solutions - The document processing market landscape - Methodology for solution evaluation: comparing apples to apples Whether you are looking for a ready-made solution or plan to build a custom solution of your own, this webinar will help you find the best fit for your healthcare use cases.

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