Building Data Capacity for Patient-Centered Outcomes Research Priorities for the Next Decade (2022) / Chapter Skim
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Appendix D: Building Data Capacity for Patient-Centered Outcomes Research: Interim Report 3A Comprehensive Ecosystem for PCOR
Appendix D: Building Data Capacity for Patient-Centered Outcomes Research: Interim Report 3A Comprehensive Ecosystem for PCOR
Pages 237-334
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Appendix D Building Data Capacity for Patient-Centered Outcomes Research: Interim Report 3– A Comprehensive Ecosystem for PCOR (Full text of the committee's third interim report released on January 11, 2022.) 1 1 https://www.nap.edu/catalog/26396/building-data-capacity-for-patient-centered-outcomes research-interim-report.
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APPENDIX D 239 Committee on Building Data Capacity for Patient-Centered Outcomes Research: An Agenda for 2021 to 2030 Committee on National Statistics Division of Behavioral and Social Sciences and Education Board on Health Care Services Health and Medicine Division Computer Science and Telecommunications Board Division on Engineering and Physical Sciences A Consensus Study Report of
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. Building Data Capacity for Patient-Centered Outcomes Research: Interim Report 3– A Comprehensive Ecosystem for PCOR.
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APPENDIX D 241 The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research.
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242 BUILDING DATA CAPACITY FOR PCOR Consensus Study Reports published by the National Academies of Sciences, Engineering, and Medicine document the evidence-based consensus on the study's statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information gathered by the committee and the committee's deliberations.
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BRIDGES, The Ohio State University JULIE BYNUM, University of Michigan ANGELA DOBES, IBD Plexus, Crohn's & Colitis Foundation DEBORAH ESTRIN, Cornell Tech OLUWADAMILOLA FAYANJU, The University of Pennsylvania CONSTANTINE GATSONIS, Brown University ROBERT GOERGE, Chapin Hall, University of Chicago GEORGE HRIPCSAK, Columbia University LISA IEZZONI, Massachusetts General Hospital S CLAIBORNE JOHNSTON, The University of Texas at Austin MIGUEL MARINO, Oregon Health & Science University ELIZABETH McGLYNN, Kaiser Permanente DAVID MELTZER, University of Chicago PAUL TANG, Stanford University and Palo Alto Medical Foundation KRISZTINA MARTON, Study Director CRYSTAL BELL, Associate Program Officer RUTH COOPER, Associate Program Officer MARY GHITELMAN, Senior Program Assistant BRIAN HARRIS-KOJETIN, Director, Committee on National Statistics SHARYL NASS, Director, Board on Health Care Services JON EISENBERG, Director, Computer Science and Telecommunications Board SAUL RIVAS (National Academy of Medicine Fellow)
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CURRIE, Princeton University DIANA FARRELL, JPMorgan Chase Institute, Washington, DC ROBERT GOERGE, Chapin Hall, University of Chicago ERICA L GROSHEN, Cornell University HILARY HOYNES, University of California-Berkeley DANIEL KIFER, The Pennsylvania State University SHARON LOHR, Arizona State University, Emeritus JEROME P
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CALMAN, The Institute for Family Health PAUL CHUNG, Kaiser Permanente School of Medicine PATRICIA M DAVIDSON, Johns Hopkins University School of Nursing MARTHA DAVIGLUS, University of Illinois at Chicago JENNIFER E
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246 BUILDING DATA CAPACITY FOR PCOR COMPUTER SCIENCE AND TELECOMMUNICATIONS BOARD LAURA HAAS (Chair) , University of Massachusetts, Amherst DAVID CULLER, University of California, Berkeley ERIC HORVITZ, Microsoft Corporation CHARLES ISBELL, Georgia Institute of Technology BETH MYNATT, Georgia Institute of Technology CRAIG PARTRIDGE, Colorado State University DANIELA RUS, Massachusetts Institute of Technology FRED B
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The review of this report was overseen by Andrew B Bindman, chief medical officer, Kaiser Foundation Health Plan and Hospitals, and Alicia L
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APPENDIX D 249 Contents Summary 1 1 Introduction 5 2 Federal Partnerships 17 3 State-Level Data and Collaborations 33 4 Clinical Trial Networks and Collaborations 43 5 Public-Private Partnerships 51 6 Collaborations with Patient Groups 57 Appendixes A Biographical Sketches of Committee Members 63 B Workshop Agenda 69 C Biographical Sketches of Workshop Speakers 73 xi
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APPENDIX D 251 Boxes and Figures BOXES 1-1 Key Data Infrastructure Functionalities in the Existing Strategic Framework for Patient-Centered Outcomes Research, 10 1-2 Building Blocks of the Patient-Centered Outcomes Research Data Infrastructure, 11 1-3 Statement of Task for the Overall Study, 13 2-1 Collaborations Between the Centers for Medicare & Medicaid Services Office of Minority Health and Federal Partners, 23 FIGURES 1-1 Patient-Centered Outcomes Research Trust Fund: Three streams of work and funding, 7 1-2 The Office of the Assistant Secretary for Planning and Evaluation's strategic framework for the patient-centered outcomes research data infrastructure, 9 2-1 Prevalence of diabetes in 2018, 22 4-1 National Cancer Institute National Clinical Trials Network structure, 44 xiii
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As part of its information-gathering activities, the committee organized three workshops to collect input from stakeholders on the PCOR data infrastructure, which includes a variety of types of data, such as clinical data, research data, administrative data from payer records, and patientprovided data. This report, the third in a series of three interim reports, summarizes the discussion and committee conclusions from the third workshop, which focused on ways of enhancing collaborations, data linkages, 1
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CONCLUSION 2-1: Collaboration among federal agencies and be tween federal agencies and other partners (such as states, patient groups, and others) is essential for continuing to build the patient centered outcomes research data infrastructure.
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CONCLUSION 2-2: There is a need to increase awareness among all stakeholders about new data infrastructure developments funded by the Patient-Centered Outcomes Research Trust Fund. Increased aware ness will enhance the efficiency and effectiveness of research, which will increase the impact of the investments made in infrastructure development.
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CONCLUSION 4-1: Infrastructure investments could enhance the util ity of data routinely generated in the course of care for clinical trials. PUBLIC-PRIVATE PARTNERSHIPS While the benefits of data sharing are clear, the workshop also underscored the risks involved for the organizations providing the data.
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. The PCOR data infrastructure provides decision makers with objective, scientific evidence on the effectiveness of treatments, services, and other interventions used in health care.
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The remaining funding, which constitutes 4 percent of the PCOR Trust Fund, is allocated for building data capacity for PCOR and is overseen by ASPE. Specifically, Section 937(f)
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As the coordinating agency for the data infrastructure investment portfolio across HHS agencies, ASPE guides the PCOR data infrastructure's strategic framework and vision, sets funding priorities, and coordinates interagency workgroups. ASPE's work is assisted by a Leadership Council for the PCOR Trust Fund, which includes representatives from other HHS agencies, including the Administration for Children and Families; the Administration for Community Living; AHRQ; the Assistant Secretary for Preparedness and Response; the Centers for Disease Control and Prevention (CDC)
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During the period from 2010 to 2019, the PCOR Trust Fund funded 53 projects, which translated to 76 agency awards, totaling approximately $131 million. Figure 1-2 is a visual representation of ASPE's current framework for the PCOR data infrastructure.
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APPENDIX D FIGURE 1-2 The Office of the Assistant Secretary for Planning and Evaluation's strategic framework for the patient-centered outcomes research data infrastructure. 9 SOURCE: Workshop presentation by ASPE, May 3, 2021.
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. Linking of Clinical and Other Data for Research Researchers will be able to follow patients across the care continuum over time, including those enrolled in clinical trials.
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Policies are standards of behavior that participants can rely on consistently to build patient-centered data for research. Policies may include federal policies, as well as models for standardized state and local policies, that will lead to a trusted framework within the patient-centered outcomes research (PCOR)
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That first interim report summarized the discussion and committee conclusions from the first workshop, which focused on looking ahead at data user needs over the next decade.3 The second interim report in the series centered on data standards, methods, and policies that could make the PCOR data infrastructure more useful.4 This report summarizes the discussion and committee conclusions from the third workshop, which focused on ways of enhancing collaborations, data linkages, and the interoperability of electronic databases to make the PCOR data infrastructure more useful in the years ahead. As an interim report focused on one in a series of information-gathering activities, the scope of this report is limited to a subset of the topics relevant to the committee's charge, and the conclusions reached by the committee are, at this stage, fairly high-level.
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• Assess anticipated changes to health care priorities and priorities for health data and their impact on building data capacity into the foresee able future, as identified by ASPE. • Evaluate the feasibility and utility of developing a phased-in approach to building the interoperable data capacity for patient-centered outcomes research with existing databases in Department of Health and Human Services, other federal departments, and the private sector in a phased approach, such as projects identified in the Cures Act Title III Section 4003 (Interoperability)
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; clinical trial networks and collaborations (Chapter 4) ; publicprivate partnerships (Chapter 5)
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APPENDIX D 267 INTRODUCTION 15 The conclusions are based primarily on the input collected as part of the workshop, background documentation received from ASPE and other public sources, and the committee members' synthesis and expert judgment. Because this is an interim report, the committee's conclusions at this stage are big-picture conclusions, which will be integrated with additional input over the course of the study.
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Micky Tripathi, National Coordinator for Health Information Technology, discussed the work that the Office of the National Coordinator for Health Information Technology (ONC) is doing to support activities related to patient-centered outcomes research (PCOR)
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Such tools can safeguard patient privacy and support appropriate stewardship practices in which real patient data are only accessed and used when necessary. These and other mentioned projects have been funded through the Patient-Centered Outcomes Research Trust Fund (PCORTF)
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Blue Button leverages FHIR standards, also discussed by Tripathi. CMS data linkage projects that have been funded by the PCOR Trust Fund include3 • Augmenting the National Hospital Care Survey Data through Linkages with Administrative Records; • National COVID-19 Longitudinal Research Database, which is linked to CMS data; and • National Death Index -- Medicare Enrollment Data Linkage.
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Khau noted that federal datasets often are not disaggregated by key demographic variables, such as race, ethnicity, gender, disability, income, and veteran status. CMS is working on gaining a better understanding of what datasets contain data elements of interest, and what standards are being used.
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, said that the FDA has 13 projects that are funded by the PCOR Trust Fund.7 The projects are as follows: 4 https://aspe.hhs.gov/basic-report/hhs-implementation-guidance-data-collection-standards race-ethnicity-sex-primary-language-and-disability-status. 5 https://data.cms.gov/mapping-medicare-disparities.
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• Collection of Patient-Provided Information through a Mobile Device Application for Use in Comparative Effectiveness and Drug Safety Research; • Common Data Model Harmonization (CDMH) and Open Stan dards for Evidence Generation; • Cross-Network Directory Service; • CURE ID: Aggregating and Analyzing COVID-19 Treatments from EHRs & Registries Globally; • Developing a Strategically Coordinated Registry Network (CRN)
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and Commercial Claims; • Making Medicaid Data More Accessible Through Common Data Models and FHIR APIs; • SHIELD - Standardization of Lab Data to Enhance Patient-Centered Outcomes and Value-Based Care; • Source Data Capture from Electronic Health Records (EHRs) : Using Standardized Clinical Research Data; • Standardization and Querying of Data Quality Metrics and Char acteristics for Electronic Health Data; • Utilizing Data from Various Data Partners in a Distributed Manner; and • WHT-CRN Project: Bridging the PCOR Infrastructure and Innova tion through Coordinated Registry Network (CRN)
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She argued that the integration of health care and clinical research will require a change in culture that begins at the point of care, where data are generated. Regarding suggestions for building an interoperable data capacity for PCOR, Rocca highlighted the following: • Linking existing databases within HHS and other federal govern ment agencies and the private sector; • Developing a universal data use agreement; • Applying tools, standards, and services developed as part of PCOR Trust Fund projects to other types of HHS data; • Encouraging the development of common architectures and inte gration frameworks to enable interoperability, rather than develop ing single solutions; and • Focusing the PCOR Trust Fund investments on cutting-edge solu tions that may result in technical leaps.
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PPRL solutions are now available through commercial vendors, and PPRL algorithms have been applied to large, commercially available health datasets, such as laboratory data, pharmacy data, claims information, and EHRs. There are also many published examples of real-world applications of PPRL and their associated benefits, and Gundlapalli argued that these benefits have to be balanced with the risk to privacy and the efforts required to implement PPRL solutions.
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An example is the NICHD Data and Specimen Hub, which allows clinical research data, including PROs, to be posted and shared. NICHD also funds the Data Sharing for Demographic Research infrastructure, which provides curation and archiving services for data relevant to health policy and health systems research as well as broader demographic research.
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These linkages would make it possible to monitor the impact of emerging public health concerns, such as infectious diseases, to examine the adverse effects of commonly used medications during pregnancy and postpartum on the pregnant person and the infant, and to determine predictive models that can help address various inequities such as inequalities in maternal morbidity and mortality. Cernich noted that NICHD is leading a consortium of projects focused on maternal health to enable coordination and collaboration within this portfolio through the PCOR Trust Fund.
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While a complete alignment is probably impossible, HHS efforts to harmonize standards are helping remove the barriers posed by the lack of standardization. Kean also underscored the value of HHS support for the development of opensource tools around agreed-upon standards and data models so that the consistency of the work around clinical data improves and also reduces the barrier to entry.
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In the future, technology solutions such as blockchain technologies could greatly advance the PCOR data infrastructure. Inherent in every blockchain technology is a distributed ledger, which documents all manipulation and use of data and helps to prevent any unauthorized use.
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However, the discussion also made it clear that awareness about the data infrastructure projects is limited among external stakeholders and end users. 9 https://www.nap.edu/catalog/26297/building-data-capacity-for-patient-centered-outcomes research-interim-report.
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While there is frequent collaboration among HHS partners on PCOR data infrastructure work, and the Office of the Assistant Secretary for Planning and Evaluation's public website contains a comprehensive list of past and current projects funded from the PCOR Trust Fund, additional dissemination efforts focused on external stakeholders could further increase the usefulness of these investments. CONCLUSION 2-2: There is a need to increase awareness among all stakeholders about new data infrastructure developments funded by the Patient-Centered Outcomes Research Trust Fund.
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Blewett said that large federal data projects using electronic health records (EHRs) and linked data are critical to patient outcomes research, but the time lags in the availability of these data make the results less actionable for state health policy.
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The following are what has worked in the data sharing consortium: • Skilled and innovative researchers are embedded in the health systems. • A distributed data network model is followed (avoids concerns about data privacy and simplifies data use agreements)
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• Data sharing agreements and data use agreements are still required for university-based research access to data files unless all of the analysis is run by the state. • Financing is needed to support sustainability of network/models.
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, a survey that she worked on while she was at the Centers for Medicare & Medicaid Services.2 A nationally representative survey of adult Medicaid recipients with state-specific samples, NAM CAHPS is a collaboration among several federal partners as well as 46 states and DC. The data produced include state-specific NAM CAHPS files, which states can get access to on the basis of a data-use agreement.
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In terms of building data capacity, two areas emphasized by LillieBlanton are (1) supporting the development of state Medicaid infrastructure for data collection, analysis, and reporting; and (2)
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There are also efforts underway to improve data quality, targeting 21 indicators, such as reasonableness of eligible counts, beneficiary demographics, and completeness of key claims service data elements.
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Claudia Steiner, Kaiser Permanente Colorado, discussed datasets produced by AHRQ based on inpatient, emergency department, and ambulatory surgery discharge data. Discharge data are available in all states except Alabama.
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Examples include linking to birth or death certificates, state-level surveys, patient-reported outcomes, and social determinants of health data collections. Steiner noted that AHRQ is currently actively exploring links to social determinants of health data as well as physician practice variables for Medical Expenditure Panel survey and HCUP data.
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CONCLUSION 3-1: There are opportunities to learn from what states have accomplished in building data capacity. The data collected, their quality, and ease of access all vary by state.
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Two additional research bases conduct only cancer control and outcomes research, such as research on symptom science, patient-reported outcomes, and cancer care delivery, through the NCORP with more than 1,000 practices throughout the United States. Carlos described the NCORP as a valuable setting for cancer clinical trials, because 80 percent of cancer patients receive their treatment in community oncology practices.
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. The potential and the challenge of building data capacity for PCOR, according to Carlos, are highlighted by the "four Vs" of big data: volume, variety, velocity, and veracity.
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Esserman argued that to realize the vision of shared data, it is necessary to reimagine the process of generating clinical data. As an example, she discussed her work on the OneSource project in collaboration with the UCSF-Stanford Center of Excellence in Regulatory Science and Innovation.
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Lesley Curtis, Duke University, began by describing two organizations that she has worked with, the National Institutes of Health (NIH) Healthcare Systems Collaboratory and the Patient-Centered Outcomes Research Institute's Patient-Centered Outcomes Research Network (PCORnet)
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She noted that a significant challenge to using those data in clinical trials is that most clinical trials do not collect a Medicare beneficiary ID or social security number, which makes it difficult to link CMS claims data. She said that an additional challenge to using CMS claims data is that beneficiary IDs or social security numbers are usually stored in areas of EHRs that are separate from clinical data records and are difficult to access even with patient consent.
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CONCLUSION 4-1: Infrastructure investments could enhance the utility of data routinely generated in the course of care for clinical trials.
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UC Health has a centralized electronic health record (EHR) database that uses the Observational Medical Outcomes Partnership Common Data Model with data elements that are continuously being harmonized.
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Imbedded Pragmatic Alzheimer's Disease and AD-Related Dementias Clinical Trials Collaboratory (IMPACT Collaboratory) , which builds capacity to conduct pragmatic clinical trials of interventions embedded within health care systems for people living with dementia and their care partners.
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While researchers at Brown University and others who are part of the IMPACT Collaboratory will be the first users of the data, the data will later become available for other NIA investigators. The data from the electronic medical records can be particularly useful for recruiting facilities for trials and clinical research, while the electronic medical records data linked to claims data can further expand the possibilities to areas such as pharmacoepidemiological research, public health surveillance research, and studies of the impact of treatments or policies.
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DISCUSSION A central theme of the discussions that followed the presentations was the risks associated with data sharing. Speakers noted that resistance to transparency is common among all types of entities.
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Successful data sharing agreements can be established when these factors are taken into consideration. CONCLUSION 5-1: Successful partnerships across health care systems require participant trust, clear evidence of mutual benefit, and the abil ity to control risk.
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Each of those clinical trials, she said, set up a significant data infrastructure, but when the trial failed, the infrastructure was dismantled, and frequently the data collected during the trial were lost. Furlong also noted that the data from failed clinical trials were not integrated into any other datasets.
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Furlong concluded by emphasizing the importance of data sharing and improving stakeholder access to data for the benefit of patients. James Lewis, University of Pennsylvania, spoke about his experiences with patient-centered outcomes research (PCOR)
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The platform includes a master data-use agreement and protocol that applies to all participating institutions, and to all identified and de-identified data, which flow bi-directionally between research sites, CARRA's Data Coordinating Center, and clinical centers. Natter explained that CARRA continues to build on its data infrastructure, which has facilitated a variety of pediatric rheumatology PCOR studies.
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1 https://www.nap.edu/catalog/26297/building-data-capacity-for-patient-centered-outcomes research-interim-report.
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APPENDIX D 313 COLLABORATIONS WITH PATIENT GROUPS 61 CONCLUSION 6-1: Patient groups can be helpful partners in all aspects of patient-centered outcomes research, including engaging pa tients in order to improve research participation and the impact of results. CONCLUSION 6-2: Patient-directed disease registries can be a source of in-depth, longitudinal, prospective clinical and patient-reported data that are not available from other data sources.
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is a senior fellow at the HealthPartners Institute and a senior advisor for the Alliance of Community Health Plans. Previously, he served as a senior advisor to the board of directors and the senior management team of HealthPartners, and prior to that, he was HealthPartners' medical director and chief health officer, responsible for quality of care and health and health care improvement.
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She is currently serving as principal investigator on a study to enhance engagement, research participation, and collaboration through the IBD Partners Patient Powered Research Network.
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He was founding director of the Center for Statistical Sciences and founding chair of the Department of Biostatistics at Brown University. He is a leading authority on the evaluation of diagnostic and screening tests and has made major contributions to the development of methods for medical technology assessment and health services and outcomes research.
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His research is focused on clinical trials and health services research in stroke. He is also an expert in medical
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She is the lead of Kaiser Permanente & Strategic Partners Patient Outcomes Research To Advance Learning (PORTAL) Network.
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He was formerly chief innovation and technology officer at the Palo Alto Medical Foundation and vice president, chief health transformation officer at IBM Watson Health. He has more than 25 years of executive leadership experience in health information technology within medical groups, health systems, and corporate settings.
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APPENDIX D 321 Appendix B Workshop Agenda Building Data Capacity for Patient-Centered Outcomes Research: An Agenda for 2021 to 2030 Virtual Workshop 3: A Comprehensive Data Ecosystem for Patient-Centered Outcomes Research June 14, 2021, 11 am – 5 pm EDT OBJECTIVES FOR THE WORKSHOP • Discuss how research and data collaborations can evolve to meet PCOR and data capacity challenges, and how HHS can support effective research and data collaborations • Identify barriers and potential solutions to the access and use of linked public data, and to the access and use of linked public and private/proprietary data • Discuss the feasibility and utility of developing a phased-in ap proach to building the interoperable data capacity for patient centered outcomes research with existing databases in HHS, other federal departments, and the private sector 11:00-11:05 am Goals for the Workshop EDT George Isham (Committee Chair) , HealthPartners Institute 69
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322 BUILDING DATA CAPACITY FOR PCOR 70 INTERIM REPORT 3 -- A COMPREHENSIVE ECOSYSTEM FOR PCOR 11:05 am-12:50 pm Federal Partners for PCOR EDT Moderators: Julie Bynum, University of Michigan, and George Hripcsak, Columbia University Speakers: Micky Tripathi, Office of the National Coordinator for Health Information Technology Allison Oelschlaeger, Office of Enterprise Data & Analytics, Centers for Medicare & Medicaid Services Meagan Khau, Office of Minority Health, Centers for Medicare & Medicaid Services Mitra Rocca, Center for Drug Evaluation and Research, Food and Drug Administration Adi Gundlapalli, Public Health Informatics Office, Centers for Disease Control and Prevention Alison Cernich, Eunice Kennedy Shriver National Institute of Child Health and Human Development Jacob Kean, Salt Lake City VA Health Care System, Department of Veterans Affairs and University of Utah 12:50-1:00 pm Break EDT 1:00-2:00 pm State-Level Data and Data Collaborations EDT Moderators: Robert Goerge, University of Chicago, and Lisa Iezzoni, Massachusetts General Hospital Speakers: Lynn Blewett, State Health Access Data Assistance Center Marsha Lillie-Blanton, George Washington University Todd Gilmer, University of California, San Diego Claudia Steiner, Kaiser Permanente Research
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APPENDIX D 323 APPENDIX B 71 2:00-2:50 pm Clinical Trial Networks and Collaborations EDT Moderators: David Meltzer, University of Chicago, and Constantine Gatsonis, Brown University Speakers: Ruth Carlos, University of Michigan Laura Esserman, University of California, San Francisco Lesley Curtis, Duke University 2:50-3:05 pm Break EDT 3:05-4:00 pm Public-Private Partnerships EDT Moderators: Elizabeth Mcglynn, Kaiser Permanente Research, and Miguel Marino, Oregon Health & Science University Speakers: Atul Butte, University of California, San Francisco Vincent Mor, Brown University Marc Overhage, Anthem 4:00-4:50 pm Collaborations with Patient Groups EDT Moderators: John F.P. Bridges, The Ohio State University, and Angela Dobes, Crohn's & Colitis Foundation Speakers: Pat Furlong, Parent Project Muscular Dystrophy James Lewis, University of Pennsylvania Marc Natter, Harvard University 4:50-5:00 pm Wrap-up EDT George Isham (Committee Chair)
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She also heads up a project funded by the Robert Wood Johnson Foundation to provide expertise in the use of data analytics to inform and monitor implementation of the Patient Protection and Affordable Care Act and was instrumental in establishing the University of Minnesota-based Census Research Data Center, which focuses on health services research and policy. She is also principal investigator of the Integrated Health Interview Series, a project funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development to harmonize and integrate more than 50 years of the NHIS and make it accessible through a web portal for academic and policy research.
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She also holds a master's degree from the School of Public Health at the University of Michigan. ALISON CERNICH is the deputy director of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
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A health services researcher by training, she is an expert in the use of Medicare claims data for health services and clinical outcomes research and a leader in national data quality efforts. She serves as co-principal investigator of the Food and Drug Administration's (FDA's)
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She is a professor of surgery and radiology at UCSF as well as a faculty member at the UCSF Helen Diller Family Comprehensive Cancer Center. Her research has focused on tailoring treatment to biology, which requires the integration of translational science, bioinformatics, medical and clinical informatics, systems integration, and clinical care delivery.
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Prior to coming to the CDC, he was the chief health informatics officer for the Salt Lake City Veterans Affairs Health Care System and an infectious diseases staff physician in Utah. He was a tenured professor of internal medicine at the University of Utah School of Medicine and a physician at the University of Utah Hospitals and Clinics.
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for Cognition Following Complex Traumatic Brain Injury network; and co-PI of the VA-funded Brain Injury Data Sharing Project -- all of which are electronic health records–based learning health systems focused primarily on the care of persons with acquired neurological disorders.
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His work has been funded by the National Institutes of Health, the Department of Health and Human Services Agency for Healthcare Research and Quality, the Patient-Centered Outcomes Research Institute, the Centers for Disease Control and Prevention, and numerous foundations and corporate sponsors. He previously served as the chair of the National Scientific Advisory Committee and as a member of the National Board of the Crohn's & Colitis Foundation.
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MARC NATTER is a pediatric rheumatologist and researcher in bioinformatics at the Boston Children's Hospital Computational Health Informatics Program whose research is centered on the development and implementation of scalable software platforms that enable new ways of collecting and sharing data for research into chronic diseases. He is the chief informatics architect of the multi-site Childhood Arthritis & Rheumatology Research Alliance Registry for pediatric rheumatic diseases, leads the development of patient-facing technology for the Harvard Medical School-led Scalable Collaborative Infrastructure for Learning Healthcare System Clinical Data Research Network, and coordinates data integration and patient-facing technology for the PARTNERS Patient Powered Research Network and other projects.
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He is an internationally recognized expert in health information modeling, standards, and interoperability as well as clinical decision support, health services research, and implementation science. Previously, Overhage was the director of medical informatics and a research scientist at the Regenstrief Institute, Inc., and professor of medicine and Regenstrief professor of medical informatics at the Indiana University School of Medicine.
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He served as the president and chief executive officer of the Massachusetts eHealth Collaborative, a nonprofit health IT advisory and clinical data analytics company. He was also the founding president and chief executive officer of the Indiana Health Information Exchange (HIE)
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