safti net kick off 12092010-mrs

SAFTINet Kick-OffFriday, December 10, 2010

Welcome!•Thank you for attending!•Goals and objectives▫Outlining project vision and aims▫Meeting SAFTINet collaborators▫Starting the process▫Clarifying concerns and questions

•Agenda•Meeting materials▫Research strategy▫SAFTINet commonly used acronyms

Agenda Agenda Item Time Presenter

Welcome and agendaSAFTINet Context and Overview

10 mins20 mins

Bethany KwanLisa Schilling

Introductions and Roll CallProject teams and investigatorsAAFPCINAUniversity of Utah CHPCDHHACherokee Health SystemsIntermountain HealthcareCCMCN/CACHIE

10 mins Bethany Kwan

Comparative Effectiveness Research

10 mins Marion Sills

Partner Engagement Community 10 mins Debbie GrahamTechnical Team Presentation 10 mins Michael KahnGetting started 5 mins Bethany KwanWrap-up and Questions 15 mins Lisa Schilling

IOM Roundtable on Value & Science-Driven Health Care•Goal: by the year 2020, 90 percent of

clinical decisions will be supported by accurate, timely, and up-to-date clinical information, and will reflect the best available evidence

•Learning Healthcare System series

IOM Roundtable on Value & Science-Driven Health Care• The Learning Healthcare System (2006)• Judging the Evidence: Standards for Determining Clinical

Effectiveness (2007)• Leadership Commitments to Improve Value in Healthcare: Toward

Common Ground (2007)• Redesigning the Clinical Effectiveness Research Paradigm:

Innovation and Practice-Based Approaches (2007)• Clinical Data as the Basic Staple of Health Learning: Creating and

Protecting a Public Good (2008)• Engineering a Learning Healthcare System: A Look to the Future

(2008)• Learning What Works: Infrastructure Required for Learning Which

Care Is Best (2008)• Value in Health Care: Accounting for Cost, Quality, Safety,

Outcomes and Innovation (2008)

Comparative Effectiveness Milestones• 2003 - MMA Section 1013 authorizes AHRQ to

conduct and support research with a focus on “outcomes, comparative clinical effectiveness, and appropriateness of health care items and services (including prescription drugs)”

• 2007- IOM Report - Learning What Works Best: The Nation’s Need for Evidence on Comparative Effectiveness In Health Care

• 2009 - ARRA provides $1.1 Billion to NIH/HHS/AHRQ

• 2010 - Patient Protection and Affordable Care Act

• Need for substantially improved understanding of the comparative clinical effectiveness of healthcare interventions.

• Strengths of the randomized controlled trial muted by constraints in time, cost, and limited applicability.

• Opportunities presented by the size and expansion of potentially interoperable administrative and clinical datasets.

• Opportunities presented by innovative study designs and statistical tools.

• Need for innovative approaches leading to a more practical and reliable clinical research paradigm.

• Need to build a system in which clinical effectiveness research is a more natural by-product of the care process.

Redesigning the Clinical Effectiveness Research Paradigm• Address current limitations in applicability of research

results• Counter inefficiencies in timeliness, costs, and volume• Define a more strategic use to the clinical experimental

model• Provide stimulus to new research designs, tools, and

analytics• Encourage innovation in clinical effectiveness research

conduct• Promote the notion of effectiveness research as a routine

part of practice• Improve access and use of clinical data as a knowledge

resource• Foster the transformational research potential of

information technology• Engage patients as full partners in the learning culture• Build toward continuous learning in all aspects of care

• resulting research paradigm, with randomized controlled double blind trials at the pinnacle, has often left important evidence needs unmet when combined with the costs, complexity, and lack of generalizability of RCTs.

•Geisinger example of the power of proper EHR use

• (pg 28 – Redesigning)

Why distributed?•Minimize security risks by allowing the

data repositories of multiple parties to remain separately owned and controlled.

•These models also provide an interface to these stores of highly useful data that allows them to function as a large combined dataset.

•Patient preferences and perspectives. What approaches might help

• to refine practical instruments to determine patient preferences—

•such as NIH’s PROMIS (Patient-Reported Outcomes Measurement

• Information System)—and apply them as central elements of outcome

•measurement?

Evidence gaps

Patient Protection and Affordable Care Act- Public Law 111-148 :Subtitle D•Patient-Centered Outcomes Research▫Comparative Clinical Effectiveness Research

•Defined Comparative Clinical Effectiveness Research▫The terms ‘comparative clinical

effectiveness research’ and ‘research’ mean research evaluating and comparing health outcomes and the clinical effectiveness, risks, and benefits of 2 or more medical treatments, services..” as described…

Patient Protection and Affordable Care Act- Public Law 111-148 :Subtitle D•Medical treatments, services, and items

described in this subparagraph are health care interventions, protocols for treatment, care management, and delivery, procedures, medical devices, diagnostic tools, pharmaceuticals (including drugs and biologicals), integrative health practices, and any other strategies or items being used in the treatment, management, and diagnosis of, or prevention of illness or injury in, individuals.

Patient Protection and Affordable Care Act- there’s more•Established Patient-Centered Outcomes

Research Institute (PCORI), a non-profit corporation with duties including:▫Identifying national research priorities▫Establish a research agenda to address

these priorities▫Carry out the research agenda (systematic

reviews, primary research, funding)▫Disseminate

SAFTINet Overview• AHRQ ARRA OS: Recovery Act 2009: Scalable

Distributed Research Networks for Comparative Effectiveness Research (R01)

• Goal: enhance the capability and capacity of electronic health networks designed for distributed research to conduct prospective, comparative effectiveness research on outcomes of clinical interventions.

• These distributed research network projects will: Build on and expand existing electronic health

infrastructure Broad, scalable and sustainable systems Enable the collection of longitudinal and comprehensive

data across diverse healthcare delivery settings Evaluate effectiveness of clinical interventions for a

diverse set of clinical conditions.

$1.1 Billion -ARRA Allocations• Research • Data Infrastructure• Dissemination and

Adoption• Administrative support,

inventory, evaluation

• $681 M (62%)• $268 M (24%)• $132 M (12%)• $ 19 M ( 2%)

Federal Coordinating Council for Comparative Effectiveness and Research (FCC)• FCC-CER IOM • Data infrastructure • Dissemination and

translation • Human and scientific capital • Real-world settings for subpopulations, priority conditions and interventions • 100 top priority CER topics – 50% focus on health care delivery systems – Only three of the topics are narrowly focused on drug vs. drug • Enhanced State Data for Analysis and Tracking of Comparative Effectiveness Impact: Improved Clinical Content and Race-Ethnicity Data • Registry of Patient Registries

• Select examples of AHRQ funding • Electronic Data Methods (EDM) Forum for Comparative Effectiveness Research• Enhanced Registries for Quality Improvement and Comparative Effectiveness Research Select examples of OS funding

AHRQ Support of Actionable Evidence•15 Evidence-based Practice Centers

(EPCs), •13 Developing Evidence to Inform

Decisions about Effectiveness (DEcIDE) Network,

•14 Centers for Education and Research on Therapeutics (CERTs),

AHRQ Support of CER•CER Methodology - 19 funded projects -

****•Laurer, Collins JAMA 2010:303;2182

Why CERPhysicians, health insurers, & patients need

information about the CE and safety of drugs, devices, therapies and processes of care.

Non-randomized studies using data collected primarily for care (or billing) can supplement the evidence of RCT.

Improving the value of CER means improving: data collection & use, data availability and access, CER methodology (design, analysis) and reporting.

Cart before horse•1904 first radical prostectomy• Jan 2010 1st US RCT active survelleince vs

RP for localized prostate Ca•100 years of action without evidence

Project Requirements• Primary focus▫Develop an electronic health network that collects

and links data from multiple and different healthcare delivery settings Capability for near-real time data extraction of de-

identified patient-level data, data analysis, and new data collection at the POC

▫Demonstrate capabilities for conducting methodologically rigorous Comparative Effectiveness Research (CER) Capability for collecting HRQoL measures, other

patient-reported outcomes at the POC

Funded Projects•Scalable Architecture for Federated

Therapeutic Inquiries Network (SAFTINet)▫Lisa M. Schilling, University of Colorado Denver

(R01 HS19908-01)•SCANNER: Scalable National Network for

Effectiveness Research▫Lucila Ohno-Machado, University of California

San Diego (R01 HS19913-01)•Scalable PArtnering Network for CER: Across

Lifespan, Conditions, and Settings▫ John F. Steiner, Kaiser Foundation Research

Institute (R01 HS19912-01)

SAFTINet GovernanceAHRQ Project O

fficer

Lisa Schilling, MD, MSPH

Principal Investigator

David West, PhDCo-investigator

Project Oversight

Michael Kahn, MD, PhDCo-investigator

DARTNet/SAFTINet Informatics

Cathy Bryan, RN, MHAQED Clinical, Inc. d/b/a CINA

Julio Facelli, PhDUniv of Utah Center for High

Performance Computing

SAFTINet Technical TeamWison Pace, MDCo-investigator

DARTNet/SAFTINet Informatics

Art Davidson, MD, MSPHCo-investigatorDH Informatics,

Medicaid Relationships

Marion Sills, MD, MPHCo-investigator

CER, Cohort Development

SAFTINet Comparative Effectiveness Research

Team

Debbie Graham, MSPHAAFP/NRN

Partner Engagement Community

SAFTINet Partner Engagement Community

Group

Bethany Kwan, PhD, MSPH Project Manager

Research Partnership and Learning Community•Specific Aim 1: Establish a broad, safety-net

focused, research partnership and learning community to govern relationships, establish priorities, provide data quality oversight, and evaluate the purpose and value of the community’s effort that leverages the established governance structure of DARTNet.

•Overall Goal: Create a trusted, valued multi-state community of safety net stakeholders and researchers to lead and participate in a learning community to address evidence-gaps relevant to the safety net populations – with special emphasis upon those populations served by Medicaid and State Child Health Insurance Program (SCHIP).

Technology Development•Specific Aim 2: Extend the DARTNet

framework to build, deploy and assess a safety-net focused distributed research network which combines ambulatory and inpatient clinical data and Medicaid claims and eligibility data for clinical and research purposes

•Overall Goal: Build the technology necessary to support a valued, virtual organization that securely federates clinical EHR and Medicaid/CHIP+ data, (consistent with Medicaid agency efforts to develop Medicaid Information Technology Architecture plans and systems) to promote quality care and provide enhanced data for comparative effectiveness research.

Comparative Effectiveness Research• 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. ▫ Including delivery system strategies

• Specific Aim 3: Develop and enhance four sentinel cohort pairs of patients with asthma (pediatric and adult), hypertension, and hypercholesterolemia distinguished by their care delivery characteristics which can support comparative effectiveness research. ▫ System-level factors

Patient-Centered Medical Home Integrated Mental Health care

▫ Enhanced data collection at point-of-care

Introductions•BRIEF organizational descriptions, roles

and personnel•Roll Call• Investigator bios and full research strategy

posted on SharePoint site

Project team investigatorsPartner Engagement Community

Technical Team Investigators

• Debbie Graham (AAFP)• Jeanne Rozwadowski

(DHHA)• Lucy Savitz (IMH)• Parinda Khatri (CHS)• Heather Stocker (CCMCN)• Bethany Kwan (UCD)• Lisa Schilling (UCD)

• Michael Kahn (UCD)• Wilson Pace (UCD)• Julio Facelli (Utah)• Cathy Bryan (CINA)• Ron Price (Utah)• Jim May (CINA)• Art Davidson (DHHA)• Nathan Hulse (IMH)• Lisa Schilling (UCD)

Project team investigatorsCER Team Investigators

• Marion Sills (UCD)• Elaine Morrato (UCD)• Lisa Schilling (UCD)• Karl Hammermeister (UCD)• Monica Federico (UCD)• Ben Miller (UCD)• Rob Valuck (UCD)• Diane Fairclough (UCD)• Bethany Kwan (UCD)• Barbara Yawn (consultant)• Lucy Savitz (IMH)• Brian Sauer (Utah)

SAFTINet CER Team

CER Methodology Experts

Health Outcomes Content Experts

Health Care Delivery

System and Process Experts

American Academy of Family Physicians (AAFP) National Research Network (NRN)•Personnel:▫Debbie Graham, MSPH, AAFP Site PI▫Elias Brandt, Research Systems Analyst▫Project Manager, to be hired

•Established in 1999 to conduct, support, promote, and advocate for primary care research in practice-based settings.

•Role in project:▫Coordination with CINA activities▫Partner Engagement Community leadership

QED Clinical, Inc. d/b/a CINA• Personnel▫ Cathy Bryan, MHA, BSN, RN, Chief Clinical Officer ▫ Jim May, MBA, Chief Executive Officer ▫ Project Manager, to be named

• CINA provides innovative technology solutions that support quality focused, evidence-based health care.

• CINA technology can be used for discrete, validated data extraction virtually real-time from ambulatory clinical records for research purposes.

• CINA also provides tools for Point of Care decision support, Population reporting, and Disease Registries http://cina-us.com/

• Project Role▫ Data extraction, standardization, reporting processes (Cherokee)▫ Data aggregation across sources (Cherokee, Medicaid) and sharing with SAFTINet

, as applicable▫ Contributing to technological development for scalable, distributed networking

http://cina-us.com/

http://cina-us.com/

University of Utah Center for High Performance Computing (CHPC) and Biomedical Informatics (BMI)•Personnel and Technical Team:▫ Julio Facelli, PhD, CHPC Director, BMI Vice Chair, PI of

Utah Team▫Ron Price, Sr. Software Engineer/Architect and Project

Manager▫Derick Huth, Jr. Software Engineer ▫ Jody Smith, Database Administrator▫Walter Scott, Database Administrator▫Steve Harper, System Administrator

•Project role▫Build the Grid

Cherokee Health Systems, Inc.• Personnel▫ Parinda Khatri, PhD, CHS Director of Integrated Care, CHS Site PI▫ Jeff Howard, CPA, CHS Chief Financial Officer▫ Bob Franko, MBA, CHS training and marketing▫ Monty Bryant, BS, Programmer/Analyst▫ Jennifer Poling, MBA, Data Analyst

• Cherokee Health Systems is a network of 20 clinical sites in 14 counties in Tennessee, with strategic emphases on integration of behavioral health and primary care, outreach to underserved populations, and safety net preservation (http://www.cherokeehealth.com )

• Project role▫ Collaboration on technical and Partner Engagement Community

teams▫ Supporting participating Cherokee practices for data sharing, point

of care data collection, and data use

http://www.cherokeehealth.com/

Intermountain Healthcare• Personnel▫ Lucy Savitz, PhD, MBA, Director of Research and Education,

Institute for Health Care Delivery Research, Intermountain site PI▫ Nathan Hulse, PhD, Intermountain informaticist▫ Brian Sauer, PhD, CER methodology expert▫ Amy Wuthrich, MS, Project Manager

• Non-for-profit integrated health care delivery network of 24 hospitals, more than 130 outpatient clinics, a 1,000 member employed physician group with 2,000+ affiliated physicians, and associated care delivery support functions located in Utah and southeastern Idaho.

• Project roles▫ Collaboration on technical, CER, and Partner Engagement

Community teams▫ Supporting participating Intermountain practices for data

sharing, point of care data collection, and data use

CCMCN/CACHIE• Personnel▫ Jason Greer, CACHIE Director▫ Dan Tuteur, CCMCN Executive Director▫ Heather Stocker, CCMCN Director of Clinical Programs &

Development• Colorado Community Managed Care Network (CCMCN)▫ A non-profit Network of 15 Federally Qualified Health

Centers (FQHCs) providing primary health care services to the medically underserved throughout Colorado.

• Colorado Associated Community Health Information Enterprise (CACHIE)▫ Built and maintains a shared data warehouse on behalf of

CCMCN health centers• Project Role▫ Collaboration on technical and Partner Engagement

Community teams▫ Supporting two participating Colorado Community Health

Centers for data sharing, point of care data collection, and data use

Denver Health & Hospital Authority (DHHA)• Personnel▫Art Davidson, MD, MSPH, SAFTINet Co-Investigator▫ Jeanne Rozwadowski, MD, DHHA Site Co-investigator▫Dean McEwen, MS, Informatics

•Vertically integrated, public urban safety net health care system▫Eight federally qualified community health centers, twelve

school-based clinics in the Denver public school system• Project roles ▫Collaboration on technical and Partner Engagement

Community teams▫Supporting participating DHHA FQHCs for data sharing,

point of care data collection, and data use

Project teams•Partner Engagement Community•Technical team•Comparative effectiveness research team

Partner Engagement Community• Mission

• Culture of collaboration • Community-based participatory research

• Objectives• Vehicle for communications between partners• Decision making (e.g., POC data collection)• Encouraging members to identify topics, bring value to

stakeholders, prioritize future CER questions• Learning Community

• Membership• Meet monthly – 1st Wednesday at 12:00 MT/1:00 CT/2:00 ET• Listserv

Technical Team Presentations•Aims and objectives•Process▫Technical requirements

•Milestones and timeline▫Build the grid▫Set up the nodes▫End of year 1 goal: Two entities with nodes

on the grid

Informatics Objectives: Starting with the End Objectives•What we need to accomplish:

A way for local participants to control what data are and are not available for collaborative projects - what is “on the grid”

A way to control who/what/where/when/why for all data access

A way to ensure patient confidentiality A way to include patient-reported data A way to include State Medicaid data

•Not all of the technical details are completely determined

Some “givens”; others open for negotiation Need to engage the various technical teams

EHR

Color code:• Blue = A given• Yellow = Optional• Red = Still in analysis

• EHR: Electronic Health Record

CER/CDSDM

Other

EHR


In SAFTINet participants, we have:• CINA CDR• Local data warehouse

• EHR: Electronic Health Record• Other data sources include: claims, hospital, and third party databases• CER/CDS DM: Comparative effectiveness research/Clinical decision support data mart

PE

CER/CDSDM

Other

EHR

Guidelineprotocols

Patient specific report

Practice provider reports


• EHR: Electronic Health Record• Other data sources include: claims, hospital, and third party databases• CER/CDS DM: Comparative effectiveness research/Clinical decision support data mart • PE: Protocol Engine

PE

CER/CDSDM

Other

EHR

Guidelineprotocols




Shared Dataw/ PHI

Shared DataEncrypted

Developed and Supported by SAFTINet

• EHR: Electronic Health Record• Other data sources include: claims, hospital, and third party databases• CER/CDS DM: Comparative effectiveness research/Clinical decision support data mart • PE: Protocol Engine

PE

CER/CDSDM

Other

EHR

Guidelineprotocols



• EHR: Electronic Health Record• Other data sources include: claims, hospital, and third party databases• CER/CDS DM: Comparative effectiveness research/Clinical decision support data mart • PE: Protocol Engine• TRIAD: Translational Informatics and Data management


Shared Dataw/ PHI



SaftinetPortal

TRIADNode

Web ServicesQueries and Data Transfers

CER/CDSDM

Other

EHR


Shared Dataw/ PHI



SaftinetPortal

TRIADNode


The Trickier Bits…..

MedicaidData

? ?

?

Uni-directional Or Bi-directional?

CER/CDSDM

Other

EHR


Shared Dataw/ PHI



SaftinetPortal

TRIADNode


The Trickier Bits…..

MedicaidData

? ?

?

Patient Reported

Data

??

What’s been happening•Creating the use cases▫What types of actions do we need to

support? Types of questions to be answered Types of security and access controls

•Use cases drives data elements and database▫What do we need to extract from each

CER/CDS?•Pilot implementations of TRIAD technology▫Kicking the technology tires with large data

sets to discover the warts and “gotchas”

What’s next?•Engage all of the technical contacts▫Share use cases to understand data

availability and gaps▫Discuss how best to develop data extracts▫Develop data quality procedures▫Develop technology deployment and

support plans Including validation, acceptance, and training

Comparative Effectiveness Research•Aims•Process

Comparative Effectiveness Research•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. ▫ Including delivery system strategies

CER Aim•Specific Aim Related to CER (Aim 3):

Develop and enhance four sentinel cohort pairs of patients with asthma (pediatric and adult), hypertension, and hypercholesterolemia distinguished by their care delivery characteristics which can support comparative effectiveness research.

CER Goals•Demonstrate the capability of SAFTINet to

collect and accurately link patient-level data necessary for CER of delivery systems

•Lay the groundwork to conduct prospective observational studies and clinical trials

CER Hypothesis•Health care delivery system factors, such as the

patient-centered medical home…

PROCESSES OF CARE

(clinician factors)+

STRUCTURES OFCARE

(system factors)+ PATIENT FACTORS →

OUTCOMES(chronic disease

control)


patient-centered medical home,

PROCESSES OF CARE


STRUCTURES OFCARE



control)

outweigh clinician factors, patient factors, and medication effectiveness…


patient-centered medical home,

PROCESSES OF CARE


STRUCTURES OFCARE



control)

outweigh clinician factors, patient factors, and medication effectiveness in the control of asthma, high blood pressure and hypercholesterolemia.

CER Conceptual Model

Relatively Mutable

Clinical inertiaCounselingDrug selectionDosage selectionConcomitant medsFollow-upDecision support

Patient-Centered Medical Home

Integrated Mental Health Care

Disease-specific case management

Access to careOutcomes feedback

Therapy adherenceTherapy persistenceMental health statusHealth knowledgePerceived need for

careSymptomsDrug side effects

Patient-centered outcomes

Health-related quality of life

Clinical outcomesProcess

PROCESSES OF CARE

(clinician factors)

+STRUCTURES OF

CARE(system factors)

+ PATIENT FACTORS → OUTCOMES

Relatively immutable

Appointment timePatient loadPhysical facilitiesPractice typeSupport personnelGeneralist vs.

specialist

AgeGenderRace/ethnicitySESMarital statusReligious/cultural

beliefsComorbidity

Comparative Effectiveness Research•Aims•Process

CER Process: The Team

Marion SillsCo-investigator

SAFTINet Comparative Effectiveness Research Team

Measures experts

Cohort experts

Brian Sauer

Diane Fairclough

Rob Valuck

Elaine Morrato

PCMH: Lisa Schilling

IMHC: Ben Miller

Pediatric asthma: Monica Federico

Adult asthma: Barbara Yawn

HTN, Hypercholesterolemia: Karl Hammermeister

CER methods experts

CER Process: Sources of Data•Electronic health records•Medicaid claims•Enhanced point-of-care data collection•Organizational or practice-level survey

CER/CDSDMOther

EHR MedicaidData

Org. Survey

Patient Reported

Data

CER/CDS DM: Comparative effectiveness research/Clinical decision support data mart

CER Process•Establish data dictionary•Develop CER-specific technology use

cases•Review data profiling and quality reports

to improve data quality (ongoing) •Analytical plan

CER Process•Hypothesis generation

CER Process•Hypothesis generation•Cohort identification▫Clinical/demographic parameters▫Eligibility

CER/CDSDM

EHR MedicaidData

CER Process•Hypothesis generation•Cohort identification•Measures▫Outcome measures▫Explanatory measures▫Covariates

PROCESSES OF CARE


STRUCTURES OFCARE



control)

CER/CDSDM

EHR MedicaidData

CER Process•Hypothesis generation•Cohort identification•Measures•Enhanced data collection▫Patient-reported outcomes▫Quality of life▫PCMH▫IMHC

CER/CDSDM

Org. Survey

Patient Reported

Data

CER Process•Hypothesis generation•Cohort identification•Measures•Enhanced data collection

CER/CDSDMOther

EHR MedicaidData

Org. Survey

Patient Reported

Data

CER Process•Establish data dictionary•Develop CER-specific technology use

cases•Review data profiling and quality reports

to improve data quality (ongoing) •Analytical plan

Next steps…•Getting started•Wrap-up

Getting Started•Subcontracts•SharePoint▫Shared Documents▫Calendar▫Announcements▫Discussions

•Upcoming events and meetings▫Partner Engagement Community (Scheduling in

progress)▫Technical team (Thursdays @ 2pm MT starting 12/16)▫CER team (Mondays @ 1:30pm MT)

•Quarterly SAFTINet Update meetings

Wrap-Up“Knowing is not enough; we must apply.

Willing is not enough; we must do.” —Goethe

Questions/Comments --

safti net kick off 12092010-mrs

Health & Medicine