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Status Quo is No Longer an Option

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Presentation by Marty Smith, CTO, Craneware at the Smart Health Conference 2018, held at Bally's Las Vegas on the 26-27th of April, 2018.

Published in: Healthcare
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Status Quo is No Longer an Option

  1. 1. This document contains confidential or proprietary information which may be legally privileged. It is intended only for the named recipients and may not be shared with vendors outside of Craneware. Status Quo is No Longer an Option Marty S. Smith, Chief Technology Officer 5/3/2018
  2. 2. © 2017 Craneware craneware.com craneware.com 5/3/2018 • My Background • Craneware Background • Status Quo is Not an Option • AI, Machine Learning and Big Data • Questions Agenda
  3. 3. © 2017 Craneware craneware.com craneware.com * https://www.healthaffairs.org/doi/full/10.1377/hlthaff.2017.1655 US Healthcare spending versus quality outcomes US Spend 2017 $3.5 trillion - will increase 5.6% for 2018* Status Quo
  4. 4. © 2017 Craneware craneware.com craneware.com The problem is complex #1 #2 #3 #4 #5 Today healthcare providers: Don’t understand true margins Cannot couple financial and clinical outcomes Unable to control and manage costs Have no control over revenue models and sources Don’t influence community health behaviors Market interest is growing to find a system that will: #1 #2 #3 #4 #5 Bring together financial and clinical outcomes Integrate cost & outcome analytics with overall financial management Instill confidence in financial clarity Provide visibility into improved margins Foster quality patient outcomes through behavioral and genetic applications At its core is maximizing value for patients: that is, achieving the best outcomes at the lowest cost. We must move away from a supply-driven health care system organized around what physicians do and toward a patient-centered system organized around what patients need. We must shift the focus from the volume and profitability of services provided—physician visits, hospitalizations, procedures, and tests—to the patient outcomes achieved. - Michael Porter, The Strategy That Will Fix Healthcare Health care leaders and policy makers have tried countless incremental fixes—attacking fraud, reducing errors, enforcing practice guidelines, making patients better “consumers,” implementing electronic medical records—but none have had much impact Manage all aspects of revenue (FFS and VSB), costs, and operations for whole picture Genomics and Financial Data – combining the two to create a holistic patient picture Providing a ‘system’ that enables healthcare providers to plan, execute, and monitor value-based economics
  5. 5. © 2017 Craneware craneware.com craneware.com How we tend to look for solutions
  6. 6. © 2017 Craneware craneware.com craneware.comLet the Data Tell the Story
  7. 7. © 2017 Craneware craneware.com craneware.com 5/3/2018 • Wealth of Data • Complexity of data • Changing Healthcare Landscape • Improve Value-Based Economics to Enable Clinicians to Focus on Better Patient Outcomes Why AI in Healthcare Value-Based Economics: A healthcare economic theory (developed by Craneware) that advocates an informational approach to understanding the underlying pressures on margin in healthcare and its bidirectional correlation to patient outcomes. www.valuecycle.com
  8. 8. © 2017 Craneware craneware.com craneware.com 5/3/2018 Artificial Intelligence: An intelligent task carried out by a machine Machine Learning: An application of or subset of AI in which machines learn from data Predictive Modelling: Leveraging statistics to predict outcomes AI Defined – High Level Definitions
  9. 9. © 2017 Craneware craneware.com craneware.com Analytics PredictiveDescriptive Prescriptive Providing insight to what happened in the past. For example, presenting descriptive statistics such as averages and medians Providing insight into what will happen in the future utilizing various machine learning and statistical modelling techniques Providing insight into what action should be taken in the future based on the result of modelling activities Analytics Defined
  10. 10. © 2017 Craneware craneware.com craneware.com Types of Machine Learning Classification Example: Predict whether a patient will be admitted to the hospital Regression Example: Predict patient length of stay Clustering Example: Group admitted patients based on their diagnosis history
  11. 11. © 2017 Craneware craneware.com craneware.com Deep Learning ContinuousCategorical Neural Networks: An application or subset of machine learning originally inspired by the function of the brain Deep Learning: An application or subset of machine learning that leverages neural networks with many layers http://www.eoi.es/blogs/redinnovacionEOI/2016/10/04/deep-learning-que-es-y-porque-esta-de-moda/
  12. 12. © 2017 Craneware craneware.com craneware.com Big Data – The 3 Vs Big Data – Data that is significantly difficult to analyze using traditional methods due to its volume or complexity. Big data is often characterize by the traditional “3 Vs” (volume, variety, velocity) that have now been expanded to include other terms such as veracity and value
  13. 13. © 2017 Craneware craneware.com craneware.com • Population Health Management • Precision Medicine • Scheduling and Operational Efficiency • Genomics • Natural Language Processing & Extracting Value from Unstructured Data • Imaging and Radiology • Revenue Cycle Analytics • Many, many more 5/3/2018 Health Care Machine Learning Applications
  14. 14. © 2017 Craneware craneware.com craneware.comLet the Data Tell the Story
  15. 15. © 2017 Craneware craneware.com craneware.com Don’t look for common solutions to common problems, instead look for uncommon solutions to the complex problems facing us in healthcare.
  16. 16. © 2017 Craneware craneware.com craneware.com QUESTIONS? 5/3/2018 Email: m.smith@craneware.com LinkedIn: https://www.linkedin.com/in/therealmartysmith Twitter: @martystweets

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