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How do i expand my markets by identifying undiagnosed patients

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This presentation throws light on how to:
• Identify where highest at-risk patients are geographically.
• Understand untreated population, and how to gain access to them.
• Align regional marketing program(s) around care plan messaging.
• Refine brand Strategy/forecasting.
• Optimize FTE alignment & requirements.
• Add insight to messages to HCPs on persona of patients with greatest risk.
• Add measure on value of HCP with most at-risk patients and HCPs with most persona’s that fit brand.
• Gain general awareness and understanding of regional (ZIP level) variations and heat mapping.

For more information on our Commercial effectiveness solutions, please visit: http://www.sciohealthanalytics.com/offerings/solutions/commercial-effectiveness

Published in: Healthcare
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How do i expand my markets by identifying undiagnosed patients

  1. 1. |1©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved.©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. SCIO HEALTH ANALYTICS® How Do I Expand My Markets By Identifying Undiagnosed Patients May 23, 2017
  2. 2. |2©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. SCIO® AT A GLANCE FOUNDED GROWTH December 2007 through organic and inorganic strategies PLATFORM delivering insights and outcomes across the healthcare spectrum INVESTORS include Sequoia Capital & Health Enterprise Partners AWARDS GLOBAL RESOURCES INDIA 503 US 412 UK 37 BY GEOGRAPHY GLOBAL PARTNERS
  3. 3. |3©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. CLIENT CREDENTIALS PAYERS PBMS PROVIDERS & HEALTH SERVICES LIFE SCIENCES 400 Million+ Medical claims 1.3 Billion+ Pharmacy claims analyzed annually $600+ Million Client Savings in 2016 Client Retention 95% 30+ health plans representing 90 + million members 3 of the top 5 PBMs 20+ provider groups 8 of the top 15 global pharmaceutical companies 80+ healthcare organizations served in these key markets
  4. 4. |4©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. OVERVIEW: SCIO® ANALYTICAL & PREDICTIVE EXPERTISE 25 million patient database updated monthly used to measure improvements in patient health based on out of pocket expenses with a specific ROI Strong benchmark databases across Commercial, Medicare, Medicaid lines of business Personas that have clinical and financial risk scores – Propensity for chronic conditions Surgical prediction models at the patient level Proprietary Technology and Apps that is scalable Flexible engagement model- Analytics as a Service Global delivery model –follow the Sun Strong Medical, Clinical and Data Scientist expertise in the US
  5. 5. |5©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. SCIO’S PATIENT PERSONAS
  6. 6. |6©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. PROFILES AS AN ANALYTIC FOUNDATION CLAIM, PATIENT & PROVIDER PROFILES Behaviors & Attitudes Demographic & Attribution Clinical Factors Cost & Quality Utilization Risk
  7. 7. |7©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. OBJECTIVE OF PATIENT PERSONAS PROVIDER Integrate Multiple Data Sources : Symphony Health de-identified medical claims data, Aetna data, Optum data, ZIP level demographics, Symphony Health prescriber level data. Call center and outreach data (if available) can add to the prediction of treatment pathways. PREDICTIVE ANALYTICS PRESCRIPTIVE ANALYTICS Dynamic Risk Management of Patient Populations 1 Treatment Pathways individualized for each Persona 3 Patient Migration Towards greater Compliance 4 Provider Performance Management 2 PATIENT
  8. 8. |8©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. BALANCED ADULTS 12% 68% 19% 1% 65+ 55-64 35-54 16-34 Age Group 27% 43% 22% 8% $200k+ $100k - $200k $50k - $100k Less than $50k Estimated Income Description Well managed and balanced middle age adults. Mostly female, predominately with college level education and white collar employees with medium income. They are healthy population with low utilization and PMPM cost which is aligned to average number of chronic conditions Intervention: Low risk and well managed individuals, so no need to spend high value resources. Demographic Attributes % Above Poverty Level 94% % Blue Collar Employed 14% % Single Family Dwelling 73% % Household with children 30% Clinical Attributes IP Utilization 0.05 ER Utilization 0.22 # Average Chronic Conditions 0.69 Paid Amount PMPM ER $9 Paid Amount PMPM IP $72 Gender Education School College Individuals with Income Level > $50K Median Age 48 $285K 73% Frequent Spending Median Home Value Socio-Economic Score 90 70 100 Spending Pattern Low Risk Median Risk Prospective Score 56
  9. 9. |9©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. EXAMPLE OF PERSONAS – CLINICAL Healthy & Affluent Balanced Adults High Utilizers Quality Driven Cost Conscious Chronic older Adults High Cost Baby Boomers No.of chronic conditions ER Paid PMPM IP Paid PMPM ER Utilization IP Utilization 0.54 0.70 0.71 0.86 0.82 1.02 1.13 Median Risk Prospective Score 0.6 0.7 0.8 1.2 1.2 1.3 1.6 0.09 0.05 0.10 0.04 0.07 0.08 0.09 0.25 0.22 0.34 0.23 0.18 0.21 0.23 $75 $73 $147 $54 $75 $118 $248 $10 $9 $14 $9 $7 $10 $11
  10. 10. |10©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. PREDICTIVE ANALYTICS CREATES AN ENHANCED VIEW OF THE PATIENT FOR ENGAGEMENT DATA MART INGESTS Claims Data RXEligibility Social Economic Data Lab EMRFitness Devices Personas with no claims data but social economic and eligibility data and fitness Claims data and RX and Clinical data from the Health Plan • Chronic conditions Patients DATA MART PRODUCES Prospective risk models • Low risk • Moderate risk • High risk Impactablity risk for clinical care gaps • Low – Low – Moderate – High Palliative care End of life • Moderate – Low – Moderate – High • High – Low – Moderate – High Identify pain point- Medicare Advantage or Managed Medicaid patients – Maternity – Diabetes – CHF Use of SCIO® financial risk models to predict • Avoidable hospital events • readmissions • End of Life Add clinical risk metrics i.e. lab or high tech imaging • Adjust risk for clinical plus financials Pool risk in finer pools or quintiles of risk- IDN’s • Low risk- monitor and track risk migration and steer towards high quality providers • Moderate risk- shift to more Accountable Care Mgt Functions • High Risk – shift towards capitated structures Medical Reduction – Quality/ Cost
  11. 11. |11©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. CASE STUDY STRATIFYING THE OPIOID PATIENT AND IDENTIFYING THE UNTREATED PATIENT
  12. 12. |12©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. MEDICAID SAMPLE POPULATION PROFILE 2014 – 2015 • Average risk for general patient population is 1.00 • Average risk for Opioid patient population is double to 2.00 − This forecasts that patients to spend 100% more in the next 12 months • Average risk for this comorbid patient population is significantly higher @ 3.5! − This forecasts that patients will spend 350% more in the next 12 months
  13. 13. |13©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. EXAMPLE OF PERSONA TYPES BY CBSA
  14. 14. |14©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. EXAMPLE OF PROSPECTIVE RISK BY CBSA Top 5 CBSAs % of US Opioid Dependence Rx New York 4.7% Philadelphia 3.7% Pittsburgh 3.6% Boston 2.6% Detroit 2.3% High=top 20% Middle=middle 30% Bottom=bottom 50%
  15. 15. |15©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. CBSA PERSONA PROFILES – SAN DIEGO CA & PALM BAY FL Palm Bay FL San Diego CA Persona Type: Chronic Older Adults Risk: High Persona Type: Healthy Affluent Risk: High
  16. 16. |16©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. SAMPLE PATIENT COUNTS BY COMPLIANCE AND CBSA • Patient counts by opioid dependence compliance and geography… • This provides insight on how where marketing dollars can be utilized to address patients who present the highest risk
  17. 17. |17©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. EXISTING AND UNTREATED PATIENTS BY OPIOID DEPENDENCE AND COMPLIANCE RISK • Market Potential is up to 6x the current number of patients on Opioid Dependence therapy. 80% of which are non compliant. Patients are stratified by compliance and prospective risk (10) Highest prospective risk patients (e.g. decile 10) consume 75% of healthcare spend Each year prospective risks shifts patients between each decile group (e.g. patients health improves resulting in lower risk while other patients become more sick)
  18. 18. |18©2017 SCIOInspire, Corp. d/b/a SCIO Health Analytics®. Confidential and Proprietary. All rights reserved. LIFE SCIENCE POTENTIAL UTILIZATION • Risk stratify current and future patient population • Collaborate with customer on 360* of patient • Roadmap to align on risk based contract − Measure based on reducing agreed upon gaps in care • Align with payor on risk assessment • Identify optimal pricing and contracting • Roadmap patient universe (treated + untreated) and craft access strategy and implementation plan • Develop Treatment Algorithms • Identify where highest at risk patients are geographically • Align regional marketing program(s) around care plan messaging • Strategically identify where to focus co-pay assist programs • Understand untreated population – how to gain access? • Co-Promotion Partner alignment • Brand Strategy/forecasting • Align NPP for HCP non-targets in White Space geographies • Added insight to message to HCP on persona of patients with greatest risk • Added measure on value of HCP with most at risk patients and HCPs with most persona’s that fit brand • General awareness and understanding of regional (ZIP level) variations and heat mapping • FTE alignment &.requirements • Value add in deployment and right sizing of field force • Added variable to value HCP and institutions • Understand KPIs of high risk geography and map out operational plan and budget with SVP • Referral Patterns • Leakages • Tiers by service • Capitation • MARCA and Bundled Pay • Align with KOLs and Academic institutions on what risk means • Educate KOLs /COE’s with data to improve health outcomes • Identify to MSL team HCPs with most at risk patients Undiagnosed Patients Managed Markets Market Access Marketing Sales Commercial Operations Medical Affairs Other?

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