CaMATCH Pilot Project1 Pilot Project : caMATCH Matching Patients to Clinical Trials A Contribution to Strategic Research and Standards Development for.

Slides:



Advertisements
Similar presentations
Drybridge Consulting Party Identification Directory Installing the Microsoft Research Service IDEAlliance and Drybridge Consulting – collaborating to deliver.
Advertisements

“The Honeywell Web-based Corrective Action Solution”
Welcome to Game Lets start the Game. An electronic health record (EHR) is a digital version of a patient’s paper chart. EHRs are real-time, patient-centered.
LeadManager™- Internet Marketing Lead Management Solution May, 2009.
Copyright Hub Software Engineering Ltd 2010All rights reserved Hub Document Exchange Product Overview Secure Transmission for Transaction-based Documents.
Quality Data for a Healthy Nation by Mary H. Stanfill, RHIA, CCS, CCS-P.
ELTSS Alignment to Nationwide Interoperability Roadmap DRAFT: For Stakeholder Consideration in response to public comment.
TM Aggregate Reporting of Pandemic Influenza Vaccine Doses Administered Discussion of Option 1: Data Exchange Using CDC’s CRA System and State Immunization.
EDRN’s Validation Study Information Management System Developed for EDRN by the DMCC Cancer Biomarkers Group Division of Cancer Prevention Jet Propulsion.
Optimos Solutions – Working For You Presented to JMATE 2006.
Dr Gordon Russell, Napier University Unit Data Dictionary 1 Data Dictionary Unit 5.3.
Coordinating Center Overview November 18, 2010 SPECIAL DIABETES PROGRAM FOR INDIANS Healthy Heart Project Initiative: Year 1 Meeting 1.
Changing times, Changing needs? Library Program Analysis at the Duke University Medical Center Library & UNC Health Science Library Carol Perryman, IMLS/TRLN.
Coordinating Center Overview November 16, 2010 SPECIAL DIABETES PROGRAM FOR INDIANS Diabetes Prevention Program Initiative: Year 1 Meeting 1.
Hetty Khan Health Informatics Scientist Centers for Disease Control and Prevention (CDC) National Center for Health Statistics (NCHS) August 7, 2012 Developing.
August 12, Meaningful Use *** UDOH Informatics Brown Bag Robert T Rolfs, MD, MPH.
Electronic EDI e-EDI. The EDI has been in use since 1999 using a paper-based system and computerized spreadsheets to collect and manage EDI data. Over.
OCLC Online Computer Library Center A Global OpenURL Resolver Registry Phil Norman OCLC Dlsr4lib Workshop March 23 rd, 2006 Arlington VA.
ClubRunner Connect. Collaborate. Communicate. District Training Presentation to Clubs Welcome to ClubRunner! Press or left-click on mouse to advance.
Initial slides for Layered Service Architecture
Use of OCAN in Crisis Intervention Webinar October, 2014.
Presentation To Healthcare Partners 1 December 2010.
Common Data Elements and Metadata: Their Roles in Integrating Public Health Surveillance and Information Systems Ron Fichtner, Chief, Prevention Informatics.
Classroom User Training June 29, 2005 Presented by:
Geneva, 30 October 2009 Giuseppe Sindoni, Istat, Italy An online system for multi-channel, register-based census data collection.
Small County Data Center Project: Phase 1
Presenter name. Ryan Brandon Exan Group What’s New with axiUm New Features in axiUm Patient Self-Service Options Future Plans axiUmSupport.com.
NCI Review of the Clinical Trials Process 6 th Annual National Forum on Biomedical Imaging in Oncology James H. Doroshow M.D. April 7, 2005 Bethesda, Maryland.
© 2003 East Collaborative e ast COLLABORATIVE ® eC SoftwareProducts TrackeCHealth.
AL-MAAREFA COLLEGE FOR SCIENCE AND TECHNOLOGY INFO 232: DATABASE SYSTEMS CHAPTER 1 DATABASE SYSTEMS (Cont’d) Instructor Ms. Arwa Binsaleh.
LexEVS Overview Mayo Clinic Rochester, Minnesota June 2009.
THINK LEARN LEAD LINK Flinders University Web Redevelopment An overview May 2006 Antonia Malavazos, Web Project Officer.
Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine Cancer Center Administration Database.
What is a Business Analyst? A Business Analyst is someone who works as a liaison among stakeholders in order to elicit, analyze, communicate and validate.
Chapter 6 – Data Handling and EPR. Electronic Health Record Systems: Government Initiatives and Public/Private Partnerships EHR is systematic collection.
OEI’s Services Portfolio December 13, 2007 Draft / Working Concepts.
CRIX: toward a secure, standards-based, clinical research information exchange.
Treatment Summary University of California San Francisco Center of Excellence for Breast Cancer Care PI: Laura J Esserman MD MBA; Edward Mahoney; Elly.
Building Clinical Infrastructure and Expert Support Michael Steinberg, MD, FACR ULAAC Disparity Project Centinela/Freeman Health System.
FEA DRM Management Strategy Presented by : Mary McCaffery, US EPA.
Using the Right Method to Collect Information IW233 Amanda Murphy.
This material was developed by Oregon Health & Science University, funded by the Department of Health and Human Services, Office of the National Coordinator.
National Information Exchange Model (NIEM) Executive Introduction November 29, 2006 Thomas O’Reilly NIEM Program Management Office.
Integrating a Federated Healthcare Data Query Platform With Electronic IRB Information Systems Shan He IPHIE 2010.
Data Registry to support HIPAA standards The Health Insurance Portability and Accountability Act of 1996 Title II - Subtitle F Administrative Simplification.
This material was developed by Duke University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information.
ULTIMA*DCF for children and adolescents clinics and hospitals.
Reduce Waiting & No-Shows  Increase Admissions & Continuation Reduce Waiting & No-Shows  Increase Admissions & Continuation Lessons Learned.
XIP™/AVT Project Plans 2012 A report to the caBIG® In-Vivo Imaging Workspace Lawrence Tarbox, Ph.D.. December 2011.
State of Georgia Release Management Training
SAGE Nick Beard Vice President, IDX Systems Corp..
Structured Protocol Representation for the Cancer Biomedical Informatics Grid: caSPR and caPRI.
May 2007 CTMS / Imaging Interoperability Scenarios March 2009.
Accurate  Consistent  Compliant Contact: i4i the structured content company the structured content company.
Uses of the NIH Collaboratory Distributed Research Network Jeffrey Brown, PhD for the DRN Team Harvard Pilgrim Health Care Institute and Harvard Medical.
International Planetary Data Alliance Registry Project Update September 16, 2011.
C3PR: An Introduction for Users A Tool Demonstration from caBIG™ Vijaya Chadaram Duke Cancer Center April 29, 2008.
OnCore Current Status and Implementation Project Plan
People Inc. from P&A Software
What is the Best Way to Select an EHR
Health Advocate Overview
DATABASE SEARCH & REVIEW GETTING STARTED GUIDE FOR EMIS WEB USERS
EDRN’s Validation Study Information Management System
Electronic Health Information Systems
People Inc. from P&A Software
Health Ingenuity Exchange - HingX
Omnibus Care Plan (OCP) Care Coordination System
HLN Consulting, LLC® November 8, 2006
Module 1.1 Overview of Master Facility Lists in Nigeria
Presentation transcript:

caMATCH Pilot Project1 Pilot Project : caMATCH Matching Patients to Clinical Trials A Contribution to Strategic Research and Standards Development for Clinical Trials Matching Tools

caMATCH Pilot Project2 CaMATCH Background BreastCancerTrials.org (BCT.org), is a patient centric clinical trial matching tool Conceived of by patient advocates, a prototype was developed collaboratively with UCSF NCI Center for Bioinformatics (NCICB), in a collaborative effort with the patient advocates and UCSF further developed the prototype to build a robust back end and to provide matching algorithms against a structured eligibility format NCI’s Office of Communications (OC), worked as members of the core team and actively input eligibility criteria from PDQ trials in the bay area

caMATCH Pilot Project3 caMATCH Concept Match patient provided medical history to clinical trial screening criteria –More effective screening of potential patients for investigators through detailed, patient provided health information and patient initiated contacts –Patient health history is documented through a series of forms that are detailed about their diagnosis and treatment history –Structured, computable eligibility screening criteria are completed by core team members and reviewed/approved by investigators –System matches the data from both sources, providing a more detailed match of patient to trial

caMATCH Pilot Project4 caMATCH Concept Facilitate patient access to eligible clinical trials –Pilot is limited to the San Francisco Bay Area –Accessible and open to the general public –Designed for patient use with patient tested interface –Through series of Learn More content, patient is guided through documenting detailed information –Personal one-on-one assistance available if needed –Patient encouraged to involve their community oncologist in gathering the information Preserve privacy of all parties –Through a series of consents, patients control the exchange of information with potential investigators

caMATCH Pilot Project5 What is bct.org? Breast Cancer Patient/Caregiver Breast Cancer Investigator IRB-Approved Study Information Eligibility Criteria Educational Information Update Info Request Matched Trial Info PI Contact Info Database Patient Info Trial Info Match Rules Clinical Trial Search and Recruitment Processing Currency of Records? Timer Consent Demographics Medical Record Contact Information Patient Info by Consent Update Info Request Paper Forms?

caMATCH Pilot Project6 BCT Pilot San Francisco Bay area for trials: 50 – 100 Trials Goal is to recruit ALL Breast Cancer trials for San Francisco Bay Area –Incent patients with comprehensive, accurate information –Incent investigators with more patient participation Start Date for Pilot: March 2005 No restrictions on patient participation No regulator roles involved –System development and maintenance support from NCICB –Trial information gathering support from NCI Office of Communications Local patient and system user support from –UCSF Carol Franc Buck Breast Care Center –The Center of Excellence for Breast Cancer Care

caMATCH Pilot Project7 CaMATCH Scenario Investigators approve screening criteria for their trial entered by PDQ staff Patient creates a Personal Health Record (PHR): –Cancer diagnosis and current clinical status –Detailed information about treatment Patients request a match of their record against eligibility screening criteria System matches both sources of data and shows results Patient initiates the contact for the matched trials Investigator follows up with screening

caMATCH Pilot Project8

9

10

caMATCH Pilot Project11

caMATCH Pilot Project12

caMATCH Pilot Project13

caMATCH Pilot Project14

caMATCH Pilot Project15

caMATCH Pilot Project16

caMATCH Pilot Project17

caMATCH Pilot Project18

caMATCH Pilot Project19

caMATCH Pilot Project20

caMATCH Pilot Project21

caMATCH Pilot Project22

caMATCH Pilot Project23

caMATCH Pilot Project24

caMATCH Pilot Project25

caMATCH Pilot Project26

caMATCH Pilot Project27

caMATCH Pilot Project28

caMATCH Pilot Project29

caMATCH Pilot Project30

caMATCH Pilot Project31

caMATCH Pilot Project32 Current caMatch Architecture Proprietary structured protocol and patient representation Manual Eligibility Criteria Management Predetermined patterns of eligibility criteria matching based on breast cancer trials Access to data via Browser interface Investigators Logical Data Model - Reusable Services - Component Library caMatch Infrastructure J2EE, Struts, Hibernate, JDBC, XML Database Patients Site Administration caMatch Application Components Patient Management Trial Management Eligibility Criteria Management Matching Service Browser

caMATCH Pilot Project33 Matching Service Patient Health Record Protocol Matching Service Structured Eligibility Criteria (Matching Rules) Match/No Match

caMATCH Pilot Project34 Architecture Roadmap Pilot caBig Bronze CaBig Silver Architecture Roadmap Proprietary Custom structured protocol and patient Non standard vocabulary Enhanced Matching 2 Step matching process Extensions to patterns of eligibility criteria for other cancer domains Eligibility Criteria Authoring Tool to compose eligibility criteria Eligibility Criteria Versioning Enhanced Data Collection Vocabulary driven data entry (CDE’s from caDSR) Reuse Built on common platform (J2EE) Open Source Software (Struts, Hibernate, XML) Services Expose a web service to receive protocols from external systems Expose a web service to match an Patient’s EHR HL7 Standards Receive and match Patient Records received as HL7 EHR’s Collaborate with the HL7 structured protocol efforts

caMATCH Pilot Project35 Target caMatch Architecture Investigators caMatch Infrastructure J2EE, Struts, Hibernate, JDBC, XML Application Database Patients Site Administration caMatch Application Components Patient Management Trial Management Eligibility Criteria Management Matching Service Browser PDQ Pharma Companies Other Protocol Data sources HL7 Structured Protocol Record Presentation Layer JSP / HTML/ Javascript Exposed API Web Services \ WSDL caDSR Standardized representation for common data elements Patient Providers HL7 EHR Match Requests Matching and Eligibility Criteria Enhancements

caMATCH Pilot Project36 Unique caMATCH Traits Accuracy and Quality –Focus on one disease allows for data collection and data matching rules that are customized to breast cancer. –Algorithms generate matches that are highly specific and tailored to individual patients. –Currency of records is monitored: patients are required to update their records twice annually and investigators once annually. –Match results are updated when data from either source changes. –Matching is based on specific criteria and patient observations, not a text search or a general classification of the trials Investigator Anonymity –Investigators do not openly post their trials. –Only patients who match a trial receive investigator contact information.

caMATCH Pilot Project37 Unique caMATCH Traits Usability –Patients input their history once, after which it is saved and automatically compared to newly registered trials on an ongoing basis. –User-friendly forms capture structured data in pull-down menus, check boxes, and radio buttons. Usability lab tested interface! –The system is a patient resource for organizing and storing personal health information that can be downloaded and printed. –The site features educational information about clinical trials and resources for helping patients make decisions about participation. Accessibility –caMATCH has provisions for patients who do not have access to computers by allowing for alternative contacts or registration on print forms by mail.

caMATCH Pilot Project38 caMATCH Pilot Operational Goals Enable patients to store personal health data. Provide a user-friendly interface for data entry, matching, and access to additional supportive information and resources. Ensure security and confidentiality for the storage and exchange of personal health data, with HIPAA compliance as a floor. Execute valid matches of individual patients to appropriate trials. Enable clinical trials researchers to receive standards- based patient profiles for assessment of eligibility.

caMATCH Pilot Project39 caMATCH Strategic Goals Improve patient and provider access to information about clinical trials: –Single source of information about clinical trials. –Easily understandable information specific to patient. Enhance collaboration between researchers and patients. Reduced clinical research costs due to: –More effective patient recruiting efforts –Improve investigator access to patients for clinical trials. –Faster and less costly research due to reduced duplication of effort. –Reduced inconsistencies in meaning of information. –Reduces redundant systems (hardware/software) at multiple sites. –Leverage information for research applications. Maximize the utility of the caBIG infrastructure.

caMATCH Pilot Project40 caMATCH Strategic Research Can interactive online tools improve clinical trials recruitment? What are the human factor issues related to interactive online tools? What are the technical issues related to successfully matching patients to appropriate trials? What are patients’ attitudes toward online personal health management tools? What are researchers’ attitudes toward patient-controlled online recruitment tools? What special issues are involved in working with underserved populations to develop, implement and promote online recruitment tools? What is needed to develop standards-based approaches to patient data entry and eligibility criteria?

caMATCH Pilot Project41 caMATCH: Evaluating Standards- based Approaches to Online Clinical Trial Matching Work with standards development organizations (e.g. hl7, CDISC, OMG) Work with providers of online matching services (commercial and not-for-profit) Work with other stakeholders, including research, policy, and patient advocacy groups