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Analytics 3.0: Opportunities for Healthcare
The document discusses the evolution of healthcare analytics from traditional methods (Analytics 1.0) to the integration of big data (Analytics 2.0) and finally to a strategic approach (Analytics 3.0) that focuses on fast business impact. It emphasizes the need for organizations to adopt a culture of analytics, enabling data-driven decision-making and the development of innovative data products. Practical examples are provided from various healthcare organizations utilizing analytics to improve processes and patient outcomes.
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Analytics 3.0: Opportunities for Healthcare
- 1. ANALYTICS 3.0 Opportunities forHealthcare
- 2. ANALYTICS 3.0: OPPORTUNITIES FORHEALTHCARE July 24, 2013 Jack Phillips CEO & Co-Founder Thomas H. Davenport Research Director & Co-Founder Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 3. Copyright© 2013 IIAAll Rights Reserved
- 4. INTERNAL ANALYTICS PROGRAM (TACTICAL) Copyright©2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 5. THE ANALYTICAL DELTA Adaptedfrom Analytics at Work, Davenport, Harris and Morison, 2010 Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 6. LEVELS OF ANALYTICALMATURITY Adapted from Analytics at Work, Davenport, Harris and Morison, 2010 Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 7. EXTERNAL ANALYTICS ENVIRONMENT Copyright©2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 8. ANALYTICS 1.0│TRADITIONAL ANALYTICS 1.0 Traditional Analytics •Primarily descriptive analytics and reporting • Internally sourced, relatively small, structured data • “Back room” teams of analysts • Internal decision support Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 9. ANALYTICS 1.0│ETHOS ► Stayin the back room—as far away from decision-makers as possible—and don’t cause trouble ► Take your time—nobody’s that interested in your results anyway ► Talk about “BI for the masses,” but make it all too difficult for anyone but experts to use ► Look backwards—that’s where the threats to your business are ► If possible, spend much more time getting data ready for analysis than actually analyzing it ► Keep inside the sheltering confines of the IT organization Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 10. ANALYTICS 2.0│THE BIGDATA ERA 1.0 Traditional Analytics Big Data2.0 • Primarily descriptive analytics and reporting • Internally sourced, relatively small, structured data • “Back room” teams of analysts • Internal decision support • Complex, large, unstructured data sources • New analytical and computational capabilities • “Data Scientists” emerge • Online firms create data- based products and services Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 11. ANALYTICS 2.0│ETHOS ► Be“on the bridge” if not in charge of it ► “Agile is too slow” ► “Being a consultant is the dead zone” ► Develop products, not Power Points or reports ► Information (and hardware and software) wants to be free ► All problems can be solved in a hackathon ► Share your big data tools with the community ► “Nobody’s ever done this before!” Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 12. ANALYTICS 3.0│FAST BUSINESSIMPACT FOR THE DATA ECONOMY 1.0 Traditional Analytics Fast Business Impact for the Data Economy Big Data2.0 3.0 • Primarily descriptive analytics and reporting • Internally sourced, relatively small, structured data • “Back room” teams of analysts • Internal decision support • Complex, large, unstructured data sources • New analytical and computational capabilities • “Data Scientists” emerge • Online firms create data- based products and services • A seamless blend of traditional analytics and big data • Analytics integral to running the business; strategic asset • Rapid and agile insight delivery • Analytical tools available at point of decision • Cultural evolution embeds analytics into decision and operational processes Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 13. ANALYTICS 3.0│FAST BUSINESSIMPACT FOR THE DATA ECONOMY 1.0 Traditional Analytics Fast Business Impact for the Data Economy Big Data2.0 3.0 • Primarily descriptive analytics and reporting • Internally sourced, relatively small, structured data • “Back room” teams of analysts • Internal decision support • A seamless blend of traditional analytics and big data • Analytics integral to running the business; strategic asset • Rapid an agile insight delivery • Analytical tools available at point of decision • Cultural evolution embeds analytics into decision and operational processes • Complex, large, unstructured data sources • New analytical and computational capabilities • “Data Scientists” emerge • Online firms create data- based products and services Today Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 14. ANALYTICS 3.0│COMPETING INTHE DATA ECONOMY ► Every organization—not just online firms— can create data and analytics-based products and services that change the game ► Not just supplying data, but insights and guides to decision-making ► Use “data exhaust” to help customers use your products and services more effectively ► Start with data opportunities or start with business problems? Answer is yes! ► Need “data products” team good at data science, customer knowledge, new product/service development ► Opportunities and data come at high speed, so quants must respond quickly Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 15. EXPRESS SCRIPTS Usesanalytics on data from 1.5 billion prescriptions/yr to drive behavior change and process improvement Developing proactive, customized messages to educate about more cost effective methods of filling prescriptions Using predictive analytics to identify patients at risk of skipping doses and proactively intervene Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 16. INTERMOUNTAIN HEALTHCARE Copyright© 2013IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com From Brent James’ “science experiments” to standard treatment protocols for many diseases and conditions Cost of treatment can be monitored by clinicians along with other variables Center for Informatics Research offers software and services (with Deloitte) on health outcomes analysis based on 90 million EHR records
- 17. UNITED HEALTHCARE Usingsocial network analysis to identify potential fraud Analyzing speech-to-text data from call centers to understand likely attrition candidates Predicting likelihood of success in disease management candidates “Health in numbers” marketing Optum Insights—major revenue source from data and analytics Copyright© 2013 IIA All Rights Reserved
- 18. PARTNERS HEALTHCARE SYSTEM Early adopters of EHR, CPOE, knowledge management Beginning to connect financial, operational, and clinical analytics Developed and spun out QPID for extracting intelligence from EHRs Putting in organization-wide EHR transaction foundation now—how to preserve emphasis on analytics? Copyright© 2013 IIA All Rights Reserved
- 19. CIGNA Broad useof “smart innovation” testing approaches to understand cause-and- effect from interventions, e.g. disease management calls Beginning to analyze MyCigna.com web data and call center speech-to-text Copyright© 2013 IIA All Rights Reserved
- 20. PRESCRIPTION FOR A3.0 WORLD Start with an existing capability for data management and analytics Add some unstructured, large-volume data and product/service innovation Take Hadoop and NoSQL as needed Embed this result into the organization’s processes and systems Promote the doctor or pharmacist to Chief Analytics Officer Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 21. RECOMMENDATIONS Copyright© 2013 IIAAll Rights Reserved ► Use five factors (DELTA), five levels (1-5) to establish and measure analytical maturity ► Become a student of the analytics environment ► Educate your leaders on potential of analytics based on what you’re seeing ► Use IIA as your barometer!
- 22. DELTA POWERED ANALYTICASSESSMENT TM DEVELOPED IN PARTNERSHIP WITH HIMSS ANALYTICS Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 23. Copyright© 2013 IIAAll Rights Reserved
- 24. LEARN ABOUT THEDELTA-POWERED ANALYTICS ASSESSMENT TM Copyright© 2013 IIA All Rights Reserved http://info.iianalytics.com/healthcarebenchmarking
- 25. ANALYTICS 3.0 RESOURCES http://iianalytics.com/a3/ ResearchNote & Diagram Research Brief Frequently Asked Questions E-book Blogs IIA Members can download “Big Data in Big Companies” from client website. Copyright© 2013 IIA All Rights Reserved
- 26. JOIN US FORTHE NEXT IIA WEBCAST August 22 Improving analytic results with decision modeling James Taylor, IIA Faculty and CEO of Decision Management Solutions Register at iianalytics.com Copyright© 2013 IIA All Rights ReservedInquiries about IIA services should be directed to sales@iianalytics.com
- 27.
Editor's Notes
- #3 Sarah
- #4 Jack – 18 named to Honor Roll overall, 3 IIA clients in the top 10.We know in our guts that the investment in analytics
- #5 Jack
- #6 Jack
- #7 Jack
- #8 Jack – transition to Tom
- #9 Tom
- #11 Tom
- #13 Tom
- #14 Tom – main point – we agree that Big Data is still the topic of the day. But, we’re pointing to a future state that we think will become the norm.
- #16 Express Scripts, Inc., one of the largest pharmacy benefit management companies in North America, See article for more detailsPharmacy benefit management firm Express Scripts is rolling out a software service to identify patients at high risk for not following their medication regime.The firm calls the service ScreenRx and has tested it in a large-scale pilot program with 600,000 members. The pilot is scaling down and Express Scripts during the summer expects to start making the service available, initially focusing on members with high blood pressure, high cholesterol, diabetes, asthma and osteoporosis.The pilot testing found that 69 percent of non-adherence cases are caused by forgetfulness and procrastination, 16 percent because of the cost of medication and 15 percent because of clinical questions or concerns a patient has about the medication or disease.Express Scripts uses more than 400 known factors about patients, their physician, the disease and prescribed therapy, and contends ScreenRx is 98 percent accurate in predicting non-adherence one year in advance. Patients identified as being at-risk because of forgetfulness or procrastination may receive daily alerts to take the medication, 90-day prescriptions or auto-renewals.Eliminating non-adherence would save an estimated $317.4 billion annually, enough to cover insurance costs for 44.8 million Americans, according to the firm.
- #18 Big Data at United HealthcareUnited Healthcare, like many large organizations pursuing big data, has been focused on structured data analysis for many years, and even advertises its analytical capabilities to consumers (“Health in Numbers”). Now, however, it is focusing its analytical attention on unstructured data—in particular, the data on customer attitudes that is sitting in recorded voice files from customer calls to call centers. The level of customer satisfaction is increasingly important to health insurers, because consumers increasingly have choice about what health plans they belong to. Service levels are also being monitored by state and federal government groups, and published by organizations such as Consumer Reports. In the past, that valuable data from calls couldn’t be analyzed. Now, however, United is turning the voice data into text, and then analyzing it with “natural language processing” software. The analysis process can identify—though it’s not easy, given the vagaries of the English language—customers who use terms suggesting strong dissatisfaction. A United representative can then make some sort of intervention—perhaps a call exploring the nature of the problem. The decision being made is the same as in the past—how to identify a dissatisfied customer—but the tools are different. To analyze the text data, United Healthcare uses a variety of tools. The data initially goes into a “data lake” using Hadoop and NoSQL storage, so the data doesn’t have to be normalized. The natural language processing—primarily a “singular value decomposition”, or modified word count—takes place on a database appliance. A variety of other technologies are being surveyed and tested to assess their fit within the “future state architecture. United also makes use of interfaces between its statistical analysis tools and Hadoop. The work to put the customer satisfaction data, along with many other sources of customer data, into a customer data warehouse and analyze it is being led by Mark Pitts, who is based in the Finance organization. However, several other functions and units of United, including its Optum business specializing in selling data and related services to healthcare organizations, are participating. Pitt’s team includes both conventional quantitative analysts and data scientists with strong IT and data management skills.