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Michael Kolodziej, M.D., FACP National Medical Director, Oncology Solutions Aetna

Quality health plans & benefits Healthier living Financial well-being Intelligent solutions. How data will change oncology: the Aetna perspective. Michael Kolodziej, M.D., FACP National Medical Director, Oncology Solutions Aetna.

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Michael Kolodziej, M.D., FACP National Medical Director, Oncology Solutions Aetna

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  1. Quality health plans & benefits Healthier living Financial well-being Intelligent solutions How data will change oncology: the Aetna perspective Michael Kolodziej, M.D., FACP National Medical Director, Oncology Solutions Aetna

  2. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  3. Assessing the Cost and Efficacy in Cancer Care means solving for the Value Equation • Guideline Based Therapies • Targeted Impact • Low Toxicities • Improved Survival • Improved QOL Q V = C • Best Supportive Care • Avoidance Hospital Days • Avoidance ED Visits • Site of Service Costs ↓ • Medically Unnecessary Care ↓ at EOL How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  4. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  5. Results on Evidence Based Medicine Adherence Pre-Pilot Baseline Adherence For every 100 patients treated in 6 oncology practices in the 6 months prior to using the clinical decision support system, 62 received an evidenced based treatment plan Pilot Group Adherence For every 100 patients treated in 6 oncology practices when using the clinical decision support system during the pilot, 87 received an evidenced based treatment plan                                                                                                                                                                                                          Patient receiving an evidence based treatment plan Patient receiving a non-evidence based treatment plan • Our study showed a 43% relative improvement in adherence to evidence based treatment selection • Peer-reviewed, published evidence-based treatment options, sourced from leading oncology guideline bodies such as the American Society of Clinical Oncology and the National Comprehensive Cancer Network, were selected for 25 more patients for every 100 cancer patients in our study How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  6. Adherence to Evidence Based Medicine by Cancer TypeResults Exceeding our ExpectationsAcross the board, our hypothesis was confirmed relative to increased adherence to EBM • Baseline adherence data on more than 200 patients was pulled from chart review of 5 practices for the 6 month period prior to the start of our pilot • We compared our study group of 103 patients against this baseline data, examining changes in evidence based adherence – in total, the absolute increase was 25%, a 43% relative increase Pre-/Post- Study Comparison in Adherence to Evidence Based Medicine Baseline Study 25% 0% 10% 39% 38% 22% Study Sample Size 103 28 22 18 8 27 How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  7. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  8. Enabling physicians with clinical decision support helps them better care for patients and reduce costs How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  9. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  10. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  11. Cancer is the most costly medical item and increasing at 2-3x the rate of other costs $55 B 1000% $123 B Cumulative percentage increase 0% 2010 1996 www.cancer.gov/newscenter/pressreleases/2011/CostCancer2020 • Aetna’s top cost drivers in cancer care Medical Rx 30.8% 1.5 B Inpatient 23.3% 1.1 B Radiology 22.4% 1.1 B Specialist physician 9.4% 483 M *2010CY Claims; Commercial & Medicare; All Funding; Excludes AGB/SH/SRC Cancer care is the leading edge of medical cost trend How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  12. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  13. • 144 patients included in the period 06/01/2013 - 11/30/2013 25 28 • 106 patients enrolled in PSS • 76 patients introduced to ACP 6 • 19 patients participated in ACP 23 13 • 177 total regimens ordered, of which 78% were on-Pathway • 58% of off-Pathway regimens had documented exceptions • Returned member satisfaction surveys resulted in a 92% satisfaction 16 33 • 2 ordered regimens exceeded the recommended maximum line of therapy • Pain was assessed in 89% of eligible calls Breast Colorectal Lung Ovarian Myeloma Pancreatic Other* * Leukemia, lymphoma, GI, myeloma, prostate Innovent OncologyAetna Medicare Advantage Pilot How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  14. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  15. Flatiron operates OncologyCloud™, an oncology “big data” software platform that organizes and structures clinical and financial data and delivers impactful applications back to the provider. About Flatiron - How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  16. OncologyCloud™ EHR/EMR Charges/Remit Reference Labs Affiliated Centers Sequencing Drug Admin. PDF’s PRO Surgery Rad. Path. Labs (LIS) Nightly Data Feeds Data is captured from the cancer centers EMR and PM system agnostically and integrated with Flatiron EMR-Agnostic Integration Layer 2 3 1 4 Continuous Data Updates Data is continuously captured, structured and cleaned upfront in real-time from multiple sources Occurs within 24-72 hours of activity Patient data, including notes and PDF’s, are processed using machine learning + NLP and trained by humans Rapid-Learning Data Processing Disease-Specific Data Models Standardized vocabulary and data model for each cancer type, allowing for normalized data across sites • Quality Tracking • Custom Metrics • Operational Metrics • Regimen Review • Research Queries Applications for Cancer Centers How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  17. OncologyCloud™ (Demo) How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  18. Currently Five Biomarkers Are Required For Compliant Value Pathways Reporting Markers associated with targeted therapies increase over time Drugs on the market with associated markers EGFR 2000 2010 2010 2015 BRAF EGFR BRAF KIT AKT1 KIT AKT1 EGFR KRAS EML4-ALK EML4-ALK KRAS PIK3CA HER2 PIK3CA HER2 APC NRAS APC NRAS AP2K1 AP2K1 PTEN CTNNB1 PTEN CTNNB1 ER / PR IDH1 ERCC1 IDH1 NOTCH1 NOTCH1 TP53 TP53 ERCC1 Biomarkers in orange are elements critical to successful reporting for Value Pathways Powered by NCCN How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  19. Can prepare oncology practices for life in an ACO model Enablement of oncology-specific component for ACOs B Text ACO Hospital Oncology MH Solution: Text Text + Oncology Practice Payor Community Oncology Practice Text Primary Care Practice Aetna contracts with community oncology practices to become medical homes Aetna leverages ACS to facilitate relationships between enabled oncology practices and ACOs 1 2 How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  20. Total Costs and Payments for Cancer Care Total Cost of Cancer Care All other Cancer care Spending elements All other cancer care spending elements Waste and inefficiency Waste and inefficiency Payment for all other cancer care Payment for all other cancer care Total physician payment Care coordination fee Case management payment Total physician payment FFS payments to physicians FFS payments to physicians Current Model Proposed Model Total Payments for Cancer Care Total physician payment All other payments Proposed Model Current Model The Brookings Institution, Washington, D.C. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  21. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  22. How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

  23. Our values guide our approach to creating a better health care system Our cause To make quality health care more affordable and more accessible Our strategy To be the global leader in empowering people to live healthier lives How data will change oncology: the Aetna perspective PROPRIETARY AND CONFIDENTIAL

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