IBM Insight 2014 session (4152 )- Accelerating Insights in Healthcare with “Big Data” with HaDoop
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The document discusses the application of big data and predictive analytics in healthcare, emphasizing the importance of structured and unstructured data in deriving insights related to patient health and well-being. It highlights various business cases such as product recalls and customer complaints where innovative analytics techniques can enhance decision-making processes. Key personnel from Independence Blue Cross and Baystate Healthcare are mentioned, illustrating their roles in developing and implementing these analytic strategies.
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IBM Insight 2014 session (4152 )- Accelerating Insights in Healthcare with “Big Data” with HaDoop
- 1. Accelerating Insights in Healthcare with “Big Data” with HaDoop - 4152 Ed Macko – CTO Healthcare Darwin Leung – Director of Informatics Applications, IBC Alex Zeltov – Research Scientist, IBC Joel Vengco – CIO, Baystate © 2014 IBM Corporation
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- 3. Acknowledgements and Disclaimers Availability. References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. The workshops, sessions and materials have been prepared by IBM or the session speakers and reflect their own views. They are provided for informational purposes only, and are neither intended to, nor shall have the effect of being, legal or other guidance or advice to any participant. While efforts were made to verify the completeness and accuracy of the information contained in this presentation, it is provided AS-IS without warranty of any kind, express or implied. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this presentation or any other materials. Nothing contained in this presentation is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software. All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics may vary by customer. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or other results. © Copyright IBM Corporation 2014. All rights reserved. — U.S. Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. — Please update paragraph below for the particular product or family brand trademarks you mention such as WebSphere, DB2,Maximo, Clearcase, Lotus, etc IBM, the IBM logo, ibm.com, [IBM Brand, if trademarked], and [IBM Product, if trademarked] are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked on their first occurrence in this information with a trademark symbol (® or TM), these symbols indicate U.S. registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at •“Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml •If you have mentioned trademarks that are not from IBM, please update and add the following lines:[Insert any special 3rd party trademark names/attributions here] •Other company, product, or service names may be trademarks or service marks of others. 3
- 4. IBM Smarter Care uncovers valuable insights into lifestyle choices, social determinants, clinical and financial factors that effect the overall health of an individual … Social Demographic determinants such as where one is born, grows, lives, works and ages have direct impact on an individual’s overall health, mental health and well-being. Lifestyle Choices have direct impact on an individual’s mental and physical wellness. Clinical Factors such as specific medical symptoms, history, medications, diagnoses, etc are indicators of an individual’s health. Financial Costs, insurance, reimbursement, incentive to modify behavior, new payment models, co-pays, etc. will pay a significant role.
- 5. Every organization is on its own analytics journey Foundational • What happened? • When and where? • How much? Advanced, Predictive • What will happen? • What will be the impact? •Dashboards •Clinical data repositories •Departmental data marts •Enterprise data warehouse BI Reporting •Enterprise analytics •Unstructured content analytics •Outcomes analytics •Evidence-based medicine Population Analytics •Streaming analytics •Similarity analytics •Personalized healthcare •Consumer engagement •Cognitive Computing Care Optimization Prescriptive • What are potential scenarios? • What is the best course? • How can we pre-empt and mitigate the crisis?
- 6. • How are you measuring and reducing preventative readmissions? • How are you providing clinicians with targeted diagnostic assistance? • Which patients are following discharge instructions? • How are you using data to predict intervention program candidates? • Would revealing insights trapped in unstructured information facilitate more informed decision making? Physician notes and discharge summaries Patient history, symptoms and non-symptoms Pathology reports Tweets, text messages and online forums Satisfaction surveys Claims and case management data Forms based data and comments Emails and correspondence Trusted reference journals including portals Paper based records and documents Over 80% of stored health information is unstructured* Does unlocking the unstructured data help accelerate your transformation? ... Biggest blind spot still remains unstructured data
- 7. 7 BIOGRAPHY Independence Blue Cross Darwin Leung Director, Informatics Application Development and Operations Responsible for the development of analytical applications across the Informatics Division for Independence Blue Cross. Alex Zeltov Research Scientist, Advanced Analytics Lead the development and research of Big Data initiative and predictive analytics. Contact Info: Email: darwin.leung@ibx.com / Phone:215.241.2255 Email: alex.zeltov@ibx.com / Phone: 215.241.9885
- 8. I ndependence and i t s subsi di ar i es and af f i l i at es Dat a War ehous e We ser ve mor e t han 7 mi l l i on peopl e i n 24 st at es as wel l as t he Di st r i ct of Col umbi a – 4 mi l l i on t hr ough our medi cal cover age and admi ni st r at i ve ser vi ces, and 3 mi l l i on t hr ough phar macy, dent al , and vi si on cover age and ot her anci l l ar y pr oduct s. AmeriHealth Caritas AmeriHealth Administrators AmeriHealth Administrators AmeriHealth Caritas AmeriHealth Caritas AmeriHealth Caritas and AmeriHealth Administrators AmeriHealth Caritas AmeriHealth AmeriHealth Caritas AmeriHealth Administrators AmeriHealth Caritas AmeriHealth Caritas PA & NJ Market Independence Blue Cross AmeriHealth AmeriHealth Administrators CompServices AmeriHealth Caritas AmeriHealth Caritas AmeriHealth Caritas AmeriHealth and AmeriHealth Administrators AmeriHealth Administrators Medical, service, and ancillary Medical and ancillary Service and ancillary Medical Service Ancillary AmeriHealth Caritas and AmeriHealth Administrators AmeriHealth Caritas and AmeriHealth Administrators AmeriHealth Caritas
- 9. What are key business drivers that require “Big Data” solution @ IBC ? Apply text analytics to all information available for different business cases. Need to bring all information (structured and instructed) to a level where our technologies can be applied. Use advanced predictive analytics for various business use cases. Apply search technologies to all of our structured and unstructured data
- 10. Business Cases Product Recall Nurse Chart Review Process Predictive models: – Customer complaints / grievances – Diabetes – Likelihood of hospitalization Sentiment analysis Text Search on Electronic Medical Records/Data
- 11. Business Case: Product Recall
- 12. The text mining process helps identify the manufacturers that are on recall list. Scheduled report alerts with potential identified members that match the recall manufacturers. Create a database of extracted patient and manufacturer information. The OCR + Text mining process analyzes charts 300+ pages long on average Generated reports on the OCR results in IBM BigSheets Business Case: Product Recall
- 13. Nurse Chart Review Process The text mining process helps identify conditions and diagnoses based on the medical ontology matches for the nurse review. The text analytics priorities the charts for nurse review, the highest scored EMR charts are presented first for the nurse review process. The nurse has the ability to open the text version of the chart that was created part of the OCR process to the exact location of the matched terms in the scanned version of chart.
- 14. Predictive models: Customer complaints / grievances Diabetes Likelihood of hospitalization 14
- 15. CTM and Grievances Rates 15 Issue: Identify Members with a High Likelihood to file a CTM/Grievance Results: – Customer Satisfaction – STAR Ratings
- 16. Likelihood to File a CTM : Pre-Intervention 16 Likelihood to File a CTM 0 .50 1.0 Unlikely Very Likely .25 .75 David Pierce John Doe Barbara Wilson Jessica Smith Mary Miller “Benefits ” “Upset ” “Bill”
- 17. Outreach Intervention 17 17 “Hello John Doe. I see that you called yesterday about a billing issue. How can I assist you?
- 18. Likelihood to File a CTM : Post-Intervention 18 18 Likelihood to File a CTM 0 .50 1.0 Unlikely Very Likely .25 .75 David Pierce John Doe Barbara Wilson Jessica Smith Mary Miller “Positive Interventio n” “Great Customer Experience ” “Better Stars Rating”
- 19. 19 BIOGRAPHY Joel Vengco Chief Information Officer Baystate Responsible for xxxxthe development of analytical applications across Baystate Contact Info: Phone:xxx.xxx.xxxx Email: joel.vengco@baystate.com
- 20. Who is Baystate ? Give 1 page overview of Baystate (who do you serve, # provider, # patients, demographics, etc. )
- 21. Q & A
- 22. Thank You
Editor's Notes
- #5: Key message: The path forward is IBM Smarter Care… which expresses the power available today to uncover the KEY insights about an individual– their lifestyle choices, social determinants, and clinical factors. And then bring to bear all of that valuable information -- which is distilled, synthesized, and can be acted upon – as never before! Information about lifestyle, such as… do you choose to smoke? Do you choose to exercise? Do you make healthy nutrition a focus? Social determinants…such as where an individual is born, where they live and work, and their age, which can all have a direct impact on overall health and wellness And of course, clinical factors – the more traditional component, such as medical history and symptoms, predisposition to disease, medications, etc This is the recognition that everything matters when it comes to the individual. It’s not just clinical – it is also about their lifestyle choices, and social determinants – that impact overall health and wellbeing, and ability to contribute to community vitality.
- #7: Key Points to Make Let’s look at that all that raw data or raw information itself. Most existing analytics platforms only address structured data. Many analytics processes today only rely on current and historical data. In other words, what information sources can we leverage to unlock trapped insights … those that are causing the blind spots. We “think” we know the answers – but we are even asking the right questions? It is estimated that over 80% of information is maintained as unstructured data (or text) … basically anything not in a structured database Structured data includes things like checklists (yes/no, vitals) Unstructured data exists in many sources: physician notes, registration forms, discharge summaries, text messages, documents, paper records and many many more. Because this content lacks structure, it is arduous for healthcare enterprises to include it in business analysis and therefore it is routinely left out. This is a major missed opportunity … are you only leveraging 1/5th (or 20%) of your information? What are you doing about the other 4/5ths of you information?