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iHT² Health IT Summit Seattle 2013 - Josephine Briggs, MD, National Center for Complementary and Alternative Medicine National Institutes of Health  - Opening Keynote "Research in an IT Connected World:  Building Better Partnerships – NIH and Health Ca
 

iHT² Health IT Summit Seattle 2013 - Josephine Briggs, MD, National Center for Complementary and Alternative Medicine National Institutes of Health - Opening Keynote "Research in an IT Connected World: Building Better Partnerships – NIH and Health Ca

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Josephine Briggs, MD ...

Josephine Briggs, MD
Director
National Center for Complementary and Alternative Medicine
National Institutes of Health

Opening Keynote "Research in an IT Connected World: Building Better Partnerships – NIH and Health Care Systems"

The era of ‘Big Data’ has arrived for biomedical research, bringing with it immense challenges as well as spectacular opportunities. NIH is establishing major programs with the potential to transform the future of US biomedical research by building the capacities necessary for these challenges. These programs will strengthen research partnerships with health care systems and the IT networks that support them.

The Big Data to Knowledge (BD2K) initiative, to be launched in 2014, will implement a set of recommendations from the Data and Informatics Working Group to the Advisory Committee to the Director. Investments are planned to meet scientific needs to manage and utilize large complex datasets, including strengthening training, and investing in improved analysis methods and software development and dissemination. NIH is also evaluating strengthening data and software sharing policies, and the potential creation of catalogs of research data, and data/metadata standards.

The Common Fund’s Health Care Systems (HCS) Research Collaboratory program has the goal to strengthen the national capacity to implement cost-effective large-scale research studies by engaging major health care delivery organizations as research partners. The aim of the program is to provide a framework of implementation methods and best practices that will enable the participation of many health care systems in clinical research. Research conducted in partnership with health care systems is essential to strengthen the relevance of research results to health practice. Seven demonstration projects, currently in a feasibility phase, are developing detailed methods to implement rigorous randomized studies of questions of major public health impact. These studies, and the IT infrastructure that will make them possible, will be described in detail.

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  • Headline Figure 1
  • Within biomedical research, many data types Victims of our own success Data production outstrips data handling and analysis Major long-term changes are needed
  • Long associated with fields like particle physics, astronomy, and climatology New for biomedical research
  • The NIH DRN is a distributed data network. Each data steward (e.g., a hospital, practice, or health plan) maintains physical and operational control over its data. Queries are computer programs that can run without modification on data files that each data steward has transformed into an agreed format. A library of modular programs simplifies creation of frequently asked kinds of questions, e.g., “Among people with condition 1 who are new users of drug A, how many experience outcome X?” The software is compliant with ONC’s Query Health standards.
  • contact: jeff_brown@hphc.org
  • More detail about the functions of the coordinating center and the capabilities of the portal. Note there are a variety of projects. Project 1 represents any multi-center project that uses the DRN. “ LIRE” is a one-off sub-network built for the University of Washington pragmatic trial – the investigators have full control of it. No other user of the DRN sees it exists or can send queries to it. The investigators can choose to authorize specific other users if they wish to. “ Feasibility” is a reminder that the network can quickly do prep-to-research queries describing burden of illness, number of potential study participants, etc.

iHT² Health IT Summit Seattle 2013 - Josephine Briggs, MD, National Center for Complementary and Alternative Medicine National Institutes of Health  - Opening Keynote "Research in an IT Connected World:  Building Better Partnerships – NIH and Health Ca iHT² Health IT Summit Seattle 2013 - Josephine Briggs, MD, National Center for Complementary and Alternative Medicine National Institutes of Health - Opening Keynote "Research in an IT Connected World: Building Better Partnerships – NIH and Health Ca Presentation Transcript

  • Research in an IT Connected World: Building Better Partnerships – NIH and Health Care Systems August 21, 2013
  • Building Partnerships 1. Why? The urgent need 2. Concrete examples of partnerships – the Health Care System Collaboratory Demonstration Projects 3. Preliminary thoughts about IT capacities, methods, rules
  •  Cost: personal, institutional, and national  Outcomes
  • IOM: The Imperative for Action Drivers of the Problem  Scientific uncertainty  Perverse economic and practice incentives  System fragmentation  Opacity as to cost, quality and outcomes  Lack of patient involvement  Underinvestment in population health Clinical evidence development is not keeping pace with the emergence of new diagnostics, treatments and insights into individual variation. IOM- Learning Health Care System
  • Mayo Clinic Proceedings: A Breakdown of NEJM Articles Concerning a Medical Practice
  • Reversals  Examples:  Mortality was higher with recommended glycemic targets as opposed to more permissive standards (ACCORD, NEJM 2008)  Routine use of pulmonary artery catheters worsened ICU outcomes (NEJM, 2009)  Breast cancer survival was not improved by autologous stem cell transplant and intensified chemo compared with standard chemo (Tallman et al NEJM 2005)  Impermeable bedcovers have no benefit for adults with asthma, in spite reduced dust mite exposure (Woodcock, 2003 NEJM
  • Take home lesson: We don’t always know what we think we know. (hence the need to continue to examine standards of care)
  • What is a Practical Trial?  Defined Practical (pragmatic) Trials as those in which “the hypothesis and study design are developed specifically to answer the questions faced by decision makers”  Decision makers include patients, clinicians, payers,  & health care system policy makers
  • Pragmatic vs. Explanatory  Broad eligibility  Flexible interventions  Typical practitioners  No follow-up visits  Objective clinical outcome  Usual compliance  Intent-to-treat  Narrow eligibility  Strict instructions  Expert practitioners  Frequent follow-up visits  Surrogate outcomes  Close monitoring  ITT plus per protocol Thorpe KE et al. J Clin Epidemiol 2009;62:464-75
  • What is a Pragmatic/Practical Trial? The PRECIS Tool is Developed Thorpe KE et al. CMAJ 2009;180:E47
  • Pragmatic Study Elements Broad eligibility criteria Flexible interventions Typical practitioners No follow-up visits Clinical outcomes Usual compliance Intent-to-treat Thorpe KE et al. CMAJ 2009;180:E47
  • The Urgent Need  We need continual improvement in standards of care  To achieve that we need pragmatic trials  We cannot maintain an artificial distinction between research and quality improvement
  • Building a Partnership 1. Why? The urgent need 2. Concrete examples of partnerships – the Health Care System Collaboratory Demonstration Projects 3. Preliminary thoughts about IT capacities, methods, rules
  • The overall goal of the Commons Fund’s Health Care System (HCS) Collaboratory is to strengthen the national capacity to implement cost-effective large-scale research studies that engage health care delivery organizations as research partners.
  • Pragmatic Trial Demonstration Projects 1. Preventing hospital acquired infections: (PI Huang) Do intensified antibacterial bathing measures reduce hospital- acquired infections? Cluster randomized trial - HCA randomizing 50 hospitals – 375,000 patients
  • “The implications of this study are highly important. The lack of effectiveness of active detection and isolation should prompt hospitals to discontinue the practice for control of endemic MRSA in ICUs….”
  • Pragmatic Trial Demonstration Projects 1. Preventing hospital acquired infections: (PI Huang) Do intensified antibacterial bathing measures reduce hospital-acquired infections? Cluster randomized trial - HCA randomizing 50 hospitals – 375,000 patients. 2. Colorectal cancer screening: (PI Coronado) Does a simple intervention implemented through Federally Qualified Health Centers improve colorectal cancer screening? Cluster randomized trial 18 OCHIN Clinics – 10,000 patients. 3. Suicide prevention: (PI Simon) A pragmatic trial comparing suicide prevention programs. Can patients who admit to suicidal thoughts in a health care encounter be successfully randomized to one of two management strategies and do interventions reduce subsequent suicide attempts? Group Health, Kaiser Colorado – 16,000 patients.
  • Pragmatic Trial Demonstration Projects 4. Lumbar Spine imaging: (PI Jarvik) Does insertion of epidemiological information into imaging reports reduce subsequent diagnostic and therapeutic interventions? Kaiser, N Ca; Group Health, Mayo, Henry Ford. Cluster randomized 128 clinics,135,000 imaging reports. 5. Nocturnal blood pressure control: (PI Rosenthal) Does taking anti- hypertensive medications at night reduce CV events? U of Iowa and Duke primary care clinics, 6,000 patients. 6. Collaborative care pain management model: (PI Debar) Study impact of integration of psycho-social supports for patients with chronic pain on pain measures and opioid use. 3 Kaiser regions, Georgia, Hawaii, Northwest. Cluster randomized by practice. Several hundred practices, 6,000 patients. 7. Longer dialysis duration: (PI Dember) Does increasing dialysis duration reduce mortality? Partners Fresenius, da Vita, Cluster randomized trial of 402 dialysis units. 7000 patients.
  • Test and Strengthen Models for Clinical Research in Partnership with Health Care Delivery Systems  Develop capacity to leverage resources of major integrated health care systems for large scale clinical research studies  Test and improve methods to extract research quality data from electronic health information systems  Strengthen relevance and translatability of research results to ‘real world’ health practice  Develop and test more cost-effective models for large scale randomized clinical trials
  • Building a Partnership 1. Why? The urgent need 2. Concrete examples of partnerships – the Health Care System Collaboratory Demonstration Projects 3. Preliminary thoughts about Health IT capacities, methods, rules to facilitate a learning health care system
  • Myriad Data Types Other ‘Omic Imaging Phenotypic EHR Genomic Administrative
  • Data Steward #1 Authorized user NIH DRN Secure Network Portal 1 52 Data tables Review & Run Query 3 Review & Return Results 4 6 Data tables Review & Run Query 3 Review & Return Results 4 1- User creates and submits query (a computer program) 2- Data partners retrieve query 3- Data partners review and run query against their local data 4- Data partners review results 5- Data partners return results via secure network 6 Results are aggregated Data Steward #2 ONC Query Health Compliant
  • Send the question to the data!
  • The Goal of the IT Approach  Creating secure networking capabilities and analysis tools  Build networking capacity, not a network  Insure that access to data occurs only with data stewards’ permission and active engagement
  •  Leverages existing networks’ data and analysis tools  Can use many data types, e.g., EHR, claims, registries  Can use many data models, e.g., Mini-Sentinel, i2b2, OMOP  Can use existing querying tools, e.g., Mini-Sentinel modular programs  Every use requires the agreement of the data steward Health Plan 1 Health Plan 2 CTSA 1 Research Dataset 1 NIH Distributed Research Network Secure Portal Research Dataset 2 CTSA 2 Registry
  • NIH DRN Secure Portal Mini-Sentinel Site A Registry 1 Mini-Sentinel Site B Medical Practice 1 PBRN 1 CTSA 1 Hospital 1 Research dataset 1 NIH Distributed Research Network Coordinating Center CTSA 2 Health Plan 2 Health Plan 1 Network Managemen t Research Support Query Support Query Tool Developmen t Knowledge Database Software Developmen t Project Managemen t Data Models & Standards Consultation Health System Expertise Knowledge Management System Cross project lessons learned, query tracking, meta-data capture, search functions, etc AdministrationQuery Tools SAS, SQL, menu-drivenModular Programs Summary Tables Project 1 PROJECTS LIRE study Analytic ToolsFeasibility study Query Interface Reporting Tools Security Access Control File Query Repository User Administration Workflow Management
  • Thorny issues  Defining the right questions  Ethical issues surrounding research on standards of care: eg. when is waiver of consent appropriate  Optimum trial design for group or cluster randomized trials  Preserving effective public-private partnerships https://www.nihcollaboratory.org/
  • National Center for Complementary and Alternative Medicine Clearinghouse: 1-888-644-6226 Web site: nccam.nih.gov Twitter: @NCCAM 31
  • Pragmatic Trials  Pragmatic trials should test an intervention, or compare several interventions.  The question should be important – to patients, payers and with health care delivery systems.  The intervention should be reasonable simple and not require a complex structure for implementation. System level interventions may be particularly suitable.  The trial design should incorporate rigorous controls, prospectively identified, preferable by randomization.  The monitoring and outcome assessment should be as simple as possible – and potentially utilize electronic health records.