Secondary Uses of Data for Comparative Effectiveness Research
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1 Secondary Uses of Data for Comparative Effectiveness Research Paul Wallace MD Director, Center for Comparative Effectiveness Research The Lewin Group
2 Disclosure/Perspectives Training: Internist/Hematologist/Cancer Research Practice: Hematology and Medical Oncology; Population Medicine; EBM/CER/PCOR Kaiser Permanente (past) Heme/Onc Practice EBM (Guidelines & Population Management) HIT (EMR, Pop n Mgmt, Oncology Systems) Lewin/Optum (current) Center for CER Inventory of CER and PCOR (ASPE/HHS; AHRQ & NIH) Multi-Payer Claims Database (HHS/ASPE) Autism Registry (NIMH) Geographic Variation (IOM)
3 Observations on the data and information infrastructure for cancer This is a very complex area There is increasing certainty that there are workable and even elegant technical solutions There is minimal agreement about how to scale solutions to a national level and/or sustain them over time Hypothesis: The current evolving national effort around comparative effectiveness research is a rich laboratory for exploring and refining effective and durable scaling and sustainability of the informatics support for cancer care and learning
4 Overview Comparative Effectiveness Research (CER) and Patient Centered Outcomes Research (PCOR) Secondary use of data Examples Sustainability Key issues Conceptual framework
5 CER Comparative effectiveness research is the conduct and synthesis of research comparing the benefits and harms of different interventions and strategies to prevent, diagnose, treat and monitor health conditions in real world settings Federal Coordinating Council for Comparative Effectiveness Research 2009
6 Medicare Modernization Act 2003; Section 1013 ($15-30M) Comparative effectiveness research is the conduct and synthesis of research comparing the benefits and harms of different interventions and strategies to prevent, diagnose, treat and monitor health conditions in real world settings AHRQ Effective Health Care Program 2003-Present ARRA 2009 ($1.1B) ACA 2010
7 The Patient-Centered Outcomes Research Institute (PCORI) is an independent, non-profit health research organization. Its mission is to fund research that offers patients and caregivers the information they need to make important healthcare decisions. 7
8 Patient Centered Outcomes Research (PCOR) helps people make informed health care decisions and allows their voice to be heard in assessing the value of health care options. This research answers patient-focused questions: Given my personal characteristics, conditions and preferences, what should I expect will happen to me? What are my options and what are the benefits and harms of those options? What can I do to improve the outcomes that are most important to me? How can the health care system improve my chances of achieving the outcomes I prefer? 8
9 PCORI Draft Research Agenda 9
10 The Evolving Evidence Perspective Study Type Methods Data Source/Organization Perspective Expert Opinion Case Reports Case Series Charts Experience Effect on Patients (N of 1)
11 The Evolving Evidence Perspective Study Type Methods Data Source/Organization Perspective Expert Opinion Case Reports Case Series Evidence Based Medicine RCTs Systematic Reviews (Observation) Charts Experience Trial Data & Databases Meta-analysis Reports & Series Effect on Patients (N of 1) Population Efficacy (N of Many)
12 The Evolving Evidence Perspective Study Type Methods Data Source/Organization Perspective Expert Opinion Case Reports Case Series Evidence Based Medicine Comparative Effectiveness Research RCTs Systematic Reviews (Observation) RCTs Systematic Reviews Observation Charts Experience Trial Data & Databases Meta-analysis Reports & Series Trial Data & Databases Meta-analysis Large Pop n Databases Reports & Series Effect on Patients (N of 1) Population Efficacy (N of Many) Population Effectiveness (N of Many)
13 The Evolving Evidence Perspective Study Type Methods Data Source/Organization Perspective Expert Opinion Case Reports Case Series Evidence Based Medicine Comparative Effectiveness Research Patient Centered Outcomes Research RCTs Systematic Reviews (Observation) RCTs Systematic Reviews Observation RCTs Systematic Reviews Systematic Observation Charts Experience Trial Data & Databases Meta-analysis Reports & Series Trial Data & Databases Meta-analysis Large Pop n Databases Reports & Series Trial Data & Databases Meta-analysis Large Pop n Databases Reports & Series Patient Generated Data Effect on Patients (N of 1) Population Efficacy (N of Many) Population Effectiveness (N of Many) Patient Effectiveness Many (N of 1)s
14 Secondary Use of Data Reactive Secondary Use Insurance Claims Single payer Multiple payer Clinical Lab, radiology, pathology, EMR, Population Management Planned Secondary Use Structured data creation and capture Expanded common data sets outside clinical trials Common intervention protocols Patient related and generated data Expanded demographics (race, ethnicity, language, SES, ) Functional status Personal and family preferences and values Genomics, etc
15 Reactive Secondary Use: Optum Natural History of Disease (NHD) Model Challenge: Using claims Define a disease protocol Find people who match the protocol Gather all their medical history Find control cohorts for each individual Find their history Compare clinical and financial attributes between the two groups in every conceivable way Do this in a minute or two Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 15
16 Big Data and NHD Massively parallel database (Netezza) Optimized Data Storage structures User Interface for mix and match attributes Medical Codes Temporal requirements Member demographics SQL based Real Time cohort matching Signal Visualizations Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 16
17 Matched sets Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 17
18 Pre exposure Dx comparison Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 18
19 Planned Secondary Use: Optum Claims Linked Registries (CLRs) A Registry for Healthcare Operations Initial Focus on Breast and Lung Cancer The registry is being created for healthcare operations purposes. All services provided by Optum in creation of the registry are conducted on behalf of the holder of the data. The holder of the data has sole discretion over the design of the registry, use of any PHI and whether to de-identify the data for healthcare operations and/or research purposes. Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 19
20 Linked Longitudinal Data Claims Data Other Linkages Member Plan characteristics Age Gender Dates of benefit eligibility Pharmacy Claims Prescribing Physician Drug Dispensed NDC Quantity and Date Drug Strength Physician & Facility Claims Physician or Facility Identifier Procedures (CPT-4, revenue codes, ICD9, J-codes for medications) Diagnosis (ICD-9-CM, DRG) Admission and Discharge Dates Dates and Places of Service Patient/Plan Paid Amounts Linked Medical Records selected relevant clinical data Fill gap in claims: Identify patients from claims and add clinical data from medical record Baseline data and annual follow-up Periodically add new patients, and follow-up on existing patient Socio-economic Status * Income Net Worth Education Race/ethnicity * Available for a subset of members. Date of Death Days Supply Patient/Plan Paid Amounts Standardized Costs Standardized Costs Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 20
21 A few of the many applicable lines of research In both breast and lung cancer: How many patients have more than one line of therapy? What lines are used? Is there a relationship with survival rates? How do survival and costs compare for advanced cancer patients who opt not to have therapy compared to those who are treated? Can differences in costs and response rates for various lines of therapy be demonstrated? What is the incidence of severe infusion reactions among treated patients? How are they managed and treated? How much do they cost? How are chemotherapy regimens altered in response to adverse events (e.g., neutropenia, neuropathy)? Do dose delays or reductions follow? Breast cancer: What are the treatment patterns among triple negative (HER2 under expressed, ER/PR negative) breast cancer patients? What are survival rates? Costs? Rates of disease progression? Lung cancer: What are the treatment patterns among non-small cell lung cancer (NSCLC) patients? What are survival rates? Costs? Rates of disease progression? Confidential property of Optum. Do not distribute or reproduce without express permission from Optum. 21
22 Practical Clinical Trials Bayesian Approaches Structured Learning Modeling e.g. Archimedes Expanded Registries Multi-payer Databases Analytic Approaches (e.g. Heterogeneity of Treatment Effects) Experimental RESEARCH Observational
23 National Secondary Use of Data Efforts to Support CER, PCOR and Related Research The HMO Research Network AHRQ (AcademyHealth): The Electronic Data Methods Forum Sentinel (FDA) Health Care Cost Institute (HCCI) PACES (FDA) Multi-Payer Claims Database (ASPE/HHS) Registry for Autism Spectrum Disorders (NIMH) Others
24 Resources for Increasingly Structured Learning Examples with a Lewin/Optum Role Multi-Payer Claims Database (ASPE/HHS) Build a database to include multiple data partners (public and private) for CER CMS (MediCare and MediCaid) Commercial Plan Others possibly state All Payer Databases Design to allow both distributed and aggregated analyses Beta-test for application to CER Develop a strategy for longer term sustainability Registry of Individuals with Autism Spectrum Disorders (NIMH) Develop an advisory group including patients and families Build a registry from commercial claims that includes the individuals of interest plus their families Validate the registry through chart review Test hypotheses about etiology and health services use by patients and families Examine options for sustainability
25 Sustainability Funding Data Users Data Sources Governance
26 A Framework for Sustainability Funding Data Users Sustainability Data Sources Governance
27 A Framework for Sustainability Cost Structure Funding Distributed vs. Aggregated Data Users Sustainability Data Sources Privacy and Confidentiality Governance Proprietary and Ownership Issues
28 Medical Knowledge Personalized Care Expertise 50 s 60 s 70 s 80 s 90 s 00 s 10 s 20 s
29 Thanks Paul Wallace MD Director, Center for Comparative Effectiveness Research The Lewin Group
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