patient-centered SCAlable National Network for Effectiveness Research
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1 patient-centered SCAlable National Network for Effectiveness Research Data Sharing Meeting 2014 La Jolla, CA September 16,
2 Disclosures No conflicts to declare Report of work in progress involving multiple collaborators Slides were collected from pscanner members 2
3 Outline Member health systems and pre-existing networks (VA VINCI, UC-ReX, SCANNER) pscanner s role in PCORnet Distributed analytics enabled by pscanner Collaboration with Patient-Powered Research Networks A vision for the future 3
4 Team Central Coordination Lucila Ohno-Machado, UCSD OMOP transf: Daniella Meeker, RAND Analytics: Michael Matheny, VA & Vanderbilt Stakeholder Engagement: Kathy Kim, UC Davis Management: Michele Day, UCSD Site PIs Central VA (VINCI) Jonathan Nebeker Salt Lake City VA Scott Duvall San Diego VA Dena Rifkin Tennessee Valley VA Michael Matheny USC LA clinics Jason Doctor UC Research exchange manager Lattice Armstead Davis Mike Hogarth Irvine Pietro Galassetti Los Angeles Doug Bell San Francisco Mary Wooley San Diego Lucila Ohno-Machado 4
5 First UC-ReX Meeting San Francisco April 2010
6 UC- ReX Data Sources 6
7 Submit request Comment & Approve Es4mate & Deliver Data 7
8 8
9 Supported by the Pa/ent- Centered Outcomes Research Ins/tute (PCORI) Contract CDRN
10 10
11 11 pscanner request distribu/on hub
12 12 Pa/ents in all states and territories subcontracts
13 Project Overview pscanner = patient-centered SCAlable National Network for Effectiveness Research on 21 million patients Goal Implement a distributed architecture to integrate data from three existing networks partnering in PCORnet, and prepare for large-scale, patient centered research with focus on: Weight (10,000) Congestive Heart Failure (10,000) Kawasaki Disease (1,000) Timeline 18 months (April 2014 October 2015) 13
14 Goals 1. Engage stakeholders at multi-levels of governance Stakeholder Advisory Board (SAB) Governance» Advise on network governance and operations» 10 patients and advocates, clinicians Stakeholder Advisory Board (SAB) Education» Advise on prioritization process, educational materials, and Delphi consensus software» 20 patients and advocates, clinicians Stakeholder Research Prioritization Panel» Online Delphi consensus process» 360 members: 120 patients, 120 clinicians, 120 researchers for 3 cohorts 14
15 Goals 2. Recruit and survey cohorts Weight (10,000), Congestive Heart Failure (10,000) Kawasaki Disease (1,000) 3. Transform data into a Common Data Model Clinical Data Warehouse formats into OMOP Automated transformation from OMOP into PCORnet CDM 4. Allow pscanner users to query data and build models without patientlevel data leaving the institutions Query Distribution via PopMedNet Statistical analysis tools 15
16 16 pscanner VA 8.7m ALTAMED 0.3m QUEENSCARE TCC 24k 19k UCI SFGH 0.5m UCSF 3m pscanner CENTRAL UCSD 1.4m 2.1m UCD 2.2m UCLA 4.1m?- PREP TO STUDY OMOP DATASET QUERY VM SUMMARY Legend: Site Patient count TCC: The Children s Clinic VM: Virtual Machine SFGH: San Francisco General Hospital OMOP: Observational Medical Outcomes Partnership
17 Tasks for each site OMOP data normalization and harmonization Implementation of a pscanner node Connection of the pscanner node with clinical variables for the 3 CDRN target conditions (weight, CHF, KD) Assist in the recruitment of participants for PCORI-specified patient surveys Provide members to Advisory Board and Stakeholder Panel 17
18 pscanner Working Groups 18 OMOP Transforma4on Technical & Analy4cs IRB Coordina4on & Streamlining Pa4ent Engagement SCANNER Daniella Meeker Daniella Meeker Jason Doctor Kathy Kim UC- ReX Davera Gabriel Mike Hogarth Doug Berman UC Site PI VA Michael Matheny Michael Matheny Jeffrey Scehnet Carl Stepnowsky
19 Weight Cohort Original Case Definition was BMI>30 using the median weights in EHR for 12 months, and at least 1 PCP visit in 24 months Participants: 10,000 Data Elements Clinical lab data Radiology reports Vital signs Pharmacy data (orders, prescriptions) Encounters Procedures Mortality 19
20 CHF Cohort Case Definition: combination of ICD-9-CM codes in claims and LVEF on Echo. Will use a tool developed within VA that performs cnlp and correctly identifies LVEF measure in text report (98% sensitivity, 100% specificity) Participants: 10,000 Data Elements Clinical lab data Echo Medications Pacemaker device information Co-morbidities (diabetes, atherosclerosis, etc) 20
21 Kawasaki Disease Case Definition ICD-9 code is insufficient as many cases may be undiagnosed KD is an autoimmune disease that affects many organ systems, most serious issue is coronary artery aneurysm Unknown cause, probably combination of genetic + environmental (? infection) factors limited treatment options, variable efficacy Estimated 2,000-4,000 US cases annually Participants: 1,000 total Data Elements Clinical lab data Echo Medications Vital status (mortality) 21
22 Federated Query System Centralized query system All the data are aggregated in a single site Federated query system Rather than moving data out of a system to make queries against it, we bring the questions to the data Queries typically result in aggregate numbers SCANNER innovated by allowing distributed analytics: in addition to returning counts, it could return coefficients for global models 22
23 Beyond Counts User requests data for Quality Improvement or Research Trusted Broker(s) Identity & Trust Management Policy enforcement Clinical Data Network Diverse Healthcare Entities in 3 different states (federal, state, private) How many pa/ents over 65 are on Warfarin or Dabigatran? What are the major and minor bleeding rates for pa/ents on these drugs, adjusted for co- morbidi/es? Can we predict the chance of complica/ons? Kim K et al. Development of a Privacy and Security Policy Framework for a Mul/- State Compara/ve Effec/veness Research Network. Medical Care 2013 Jiang X et al. Privacy Technology to Support Data Sharing for Compara/ve Effec/veness Research: A Systema/c Review. Medical Care 2013 Kim K et al. Data Governance Requirements for Distributed Clinical Research Networks: Triangula/ng Perspec/ves of Diverse Stakeholders. JAMIA
24 Distributed Logistic Regression User requests data for Quality Improvement or Research Clinical Data Network Trusted Broker(s) Identity & Trust Management Policy enforcement Diverse Healthcare Entities in 3 different states (federal, state, private) Wu Y et al. Grid Binary LOgis/c REgression (GLORE): Building Shared Models Without Sharing Data. JAMIA 2012 Wang Set al. EXpecta/on Propaga/on LOgis/c REgRession (EXPLORER): Distributed Privacy- Preserving Online Model Learning. J Biomed Inf 2013 Jiang W et al.. WebGLORE: A Webservice for Grid Logis/c Regression. Bioinforma:cs
25 PPRN/CDRN joint activities Duchenne Connect Partners at UCLA CENA Community Engaged Network for All Genetic Alliance, partners at UC Davis and UCSF Health eheart Partners at UCSF SAPCON Sleep Apnea Partners at VA CDRNs working with OMOP, interoperability 25
26 26 26 hep://jamia.bmj.com/content/early/2014/04/29/amiajnl abstract
27 Thank you Ques/ons? 27
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