1 / 9

Pharmaceutical Epistemology Jim Golden, Ph.D. Global Lead, Healthcare Data Analytics Accenture

Pharmaceutical Epistemology Jim Golden, Ph.D. Global Lead, Healthcare Data Analytics Accenture (james.golden@accenture.com).

kasper-molina
Download Presentation

Pharmaceutical Epistemology Jim Golden, Ph.D. Global Lead, Healthcare Data Analytics Accenture

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Pharmaceutical Epistemology Jim Golden, Ph.D. Global Lead, Healthcare Data Analytics Accenture (james.golden@accenture.com)

  2. The healthcare system is facing severe economic, effectiveness, and quality challenges. Transformation will come through data-driven decisions and improved insights. Economic Conditions Political Environment Health Care System Customer Needs • Cost containment • Shrinking budgets • Profitability • Fragmented Value Chain • Consolidation • Health Care Reform • Funding Constraints • Regulatory Pressures • Meaningful Use • Medical Advances • Provider Shortages • HIT • Pay for Performance • Evidence-based Medicine • Comparative Effectiveness • Quality • Affordability • Choice • Safety • Effectiveness • Compliance & Adherence • Demographics

  3. Challenge: There Is No Real Healthcare Market “Value Chain” Payers Fiscal Intermediaries Providers Purchasers Producers • Government • Federal • State & local • Employers • Individuals • Coalitions • Insurers • HMOs • Pharmacy • Benefit Managers • HIE’s • Hospitals • Physicians • Pharmacies • Fed Agencies • DoD, VA • Home Care • Staffing Providers • Wholesalers • Mail-Order • Distributors • Group Purchasing Organizations • Drug Mfgrs • CRO’s • Device Mfgrs • Medical-Surgical Mfgrs • SW Providers • IT Integrators “The Wharton School Study of the Health Care Value Chain”, Lawton, Burns, DeGraaff, Danzon, Kimberly, Kissick, Pauly

  4. The Data Needed to Empower Robust Health Analytics is Distributed throughout the Ecosystem Drug Safety Data Drug Efficacy Data Medical Device Efficacy Clinical Trial Data Leading Practices Data Market Research Data Control Cost Public & Private Payers Treatment & Rx Claims & Payment Data Clinical Outcomes Data Leading Practices Data Program Effectiveness Data Population/ Disease Data Quality Outcomes Patients Prescription Data Lab Data Radiological Data Product Utilization Data Treatment Protocol Data Clinical Evidence Providers PMP Suppliers Optimize Revenue Admissions Data Physician Profile Data Benchmarking Data EBM Data Clinical Research Data Epidemiological Data Patient Profile Data Market Research Data Genomics Data Clinical Trial Data Other basic research Supply Chain Data Industry Intelligence Data Benchmarking Data Market Research Data

  5. Within the healthcare ecosystem there are very specific, near-term, high-value opportunities for data computability approaches: Discovery Clinical / Development Commercial & Revenue Operational Physician Targeting / CLV Health Outcomes Drug Launch / Marketing Strategy Simulation Evidence-Based Medicine Formulary Inclusion Strategy Sales Force Optimization Price Optimization Comparative Effectiveness Toxicity Patient Compliance Trial & Adaptive Design Supply Chain Optimization Rebate Optimization Genomics Drug Safety & Signal Detection Investigator & Site Selection Channel Optimization Meaningful Use Drug Repurposing Targeted Therapeutics Facility Utilization Fraud Detection Animal Modeling Standards of Care Inclusion / Exclusion Criteria Disease Management CDHP Analysis & Forecasting Billing Quality Institutional Safety Pharmaco-economics Portfolio Optimization Now Next Later

  6. Clinical / Development Trial & Adaptive Design Evidence-Based Medicine Inclusion / Exclusion Criteria Drug Safety & Signal Detection Current methodology for clinical data integration, warehousing and analytics: • Critical areas of data aggregation across trials: • Demography • Adverse Events • Treatment Dose • Concomitant Medication • Standardization (i.e. common variable names) • Normalization (i.e. pounds to kilograms) • Creation of derived/computed variables • Aggregation (sum, mean, min, max)

  7. Clinical / Development Trial & Adaptive Design Evidence-Based Medicine Inclusion / Exclusion Criteria Drug Safety & Signal Detection One possible desired future state:

  8. Ramon Llull (1232 – 1315) • Glymour, Ford and Hayes; Ramon Llull and the Infidels AI Magazine (1998) • http://en.wikipedia.org/wiki/Ramon_Llull http://www.wolframalpha.com/timeline.html

More Related