Pharmaceutical Epistemology Jim Golden, Ph.D. Global Lead, Healthcare Data Analytics Accenture
Post on 01-Jan-2016
29 Views
Preview:
DESCRIPTION
Transcript
Pharmaceutical EpistemologyJim Golden, Ph.D.
Global Lead, Healthcare Data Analytics
Accenture
(james.golden@accenture.com)
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
“The Wharton School Study of the Health Care Value Chain”, Lawton, Burns, DeGraaff, Danzon, Kimberly, Kissick, Pauly
ProvidersFiscal
IntermediariesPayers Purchasers Producers
Government Federal
State & local
Employers IndividualsCoalitions
InsurersHMOsPharmacyBenefit Managers
HIE’s
HospitalsPhysiciansPharmaciesFed Agencies
DoD, VA
Home CareStaffing Providers
WholesalersMail-OrderDistributorsGroup Purchasing Organizations
Drug MfgrsCRO’sDevice Mfgrs
Medical-Surgical Mfgrs
SW Providers
IT Integrators
Challenge: There Is No Real Healthcare Market “Value Chain”
The Data Needed to Empower Robust Health Analytics is Distributed throughout the Ecosystem
Patients
PMPSuppliers
Public &Private Payers
Providers
Supply Chain DataIndustry Intelligence DataBenchmarking DataMarket Research Data
Treatment & Rx Claims & Payment DataClinical Outcomes DataLeading Practices DataProgram Effectiveness DataPopulation/ Disease Data
Drug Safety DataDrug Efficacy DataMedical Device EfficacyClinical Trial DataLeading Practices DataMarket Research Data
Prescription DataLab DataRadiological DataProduct Utilization Data Treatment Protocol Data
Admissions DataPhysician Profile DataBenchmarking DataEBM DataClinical Research Data
Epidemiological DataPatient Profile DataMarket Research DataGenomics DataClinical Trial DataOther basic research
Optimize Revenue
Control Cost
Quality Outcomes
Clinical Evidence
Within the healthcare ecosystem there are very specific, near-term, high-value opportunities for data computability approaches:
Inclusion / Exclusion
Criteria
Discovery
Trial & Adaptive Design
Simulation
Pharmaco-economics
Formulary Inclusion Strategy
Physician Targeting / CLV
Sales Force Optimization
Evidence-Based Medicine
Targeted Therapeutics
Drug Safety & Signal Detection
Institutional Safety
Facility Utilization
Commercial & Revenue OperationalClinical / Development
Disease Management
Drug Launch / Marketing Strategy
Portfolio Optimization
Fraud Detection
Channel Optimization
Patient Compliance
Supply Chain Optimization
Toxicity
Genomics Investigator & Site Selection
Drug Repurposing
Meaningful Use
CDHP Analysis & Forecasting
Standards of CareBilling Quality
Health Outcomes
Price Optimization
Rebate Optimization
Comparative Effectiveness
Now Next Later
Animal Modeling
Inclusion / Exclusion
Criteria
Trial & Adaptive Design
Evidence-Based Medicine
Drug Safety & Signal Detection
Clinical / Development 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)
Current methodology for clinical data integration, warehousing and analytics:
Inclusion / Exclusion
Criteria
Trial & Adaptive Design
Evidence-Based Medicine
Drug Safety & Signal Detection
Clinical / Development
One possible desired future state:
http://www.wolframalpha.com/timeline.html
Ramon Llull (1232 – 1315)• Glymour, Ford and Hayes; Ramon Llull and the Infidels
AI Magazine (1998)• http://en.wikipedia.org/wiki/Ramon_Llull
top related