Interoperability and Analytics February 29, 2016

Size: px
Start display at page:

Download "Interoperability and Analytics February 29, 2016"

Transcription

1 Interoperability and Analytics February 29, 2016 Matthew Hoffman MD, CMIO Utah Health Information Network

2 Conflict of Interest Matthew Hoffman, MD Has no real or apparent conflicts of interest to report.

3 Agenda Electronic Secure Data Supplementary Clinical Data Patient Overlap Between Health Systems Diabetes Star Ratings Pilot Population Management Chronic Disease Populations Case Management Analyses Geomapping Tools Savings Encounter Notification Service and FHIR Risk Adjustment Analyses

4 Learning Objectives Describe how standards define use cases and parameters for health data analytics Identify the ways in which data analytics can help to support the business value of health information exchange Evaluate how new dimensions in standard definitions will shape data analysis applications and use cases

5 The STEPS Framework: Electronic Secure Data The Case for Interoperability -Supplementary Clinical/Hospital Data for Clinicians - Star Ratings Analysis - Shared Identities Numbers

6 Supplementary Data from Health Information Exchange MPI RECORDS LABS ADTS EMR DW EMR DW EMR DW EMR DW DATA GAIN SMFM 23, , , , , , , CUC 713,480 1,990, ,269 5,369,244 1,301,722 13,425,165 2,240,747 28,182, *Numbers as of 01/13/2016

7 Patient Overlap Between Health Systems 30% 29% 30% 25% 20% 15% 22% 19% 20% 15% 13% 10% 5% 0% HS 1 HS 2 HS 3 HS 4 HS 5 HS 6 HS 7

8 Diabetes Star Ratings Analysis Data Related to Diabetic Measures [VALUE] HIE Data EHR Data [VALUE]

9 The STEPS Framework: Population Management Analytic Tools for the Front Line - The Importance of Standards - Chronic Disease Populations - Case Management Analyses - Geomapping Tools

10 UHIN Clinical Architecture

11 Using Standards to Combine Data

12 Cost to Value of Types of Analytics Models

13 Clinician Created Analyses

14 Custom Filtering Filter Settings A1C - Gender: (female, male) - Age: (0 <= Age <= 124) - A1C_Val: (1.30 <= A1C_Val <= 21.99) MicroAlbumin - Mic_Val: (0.00 <= Mic_Val <= 11.35) BP BMI Cholesterol - BP: (82 <= BP <= 205) - BMI: (0.21 <= BMI <= 73.02) - Cholesterol: (0 <= Cholesterol <= 251)

15 Care Management Tools: Diabetic Population

16 Care Management Tools: Diabetic Population

17 Geomapping

18 The STEPS Framework: Savings For the CFO in All of Us - Encounter Notification Service and FHIR - Risk Adjustment Analyses

19 FHIR ENS Solution Diagram

20 FHIR ENS Solution Diagram

21 Results Anecdotal Post Surgery Re-admit reduction Decreased Asthma Hospital Admissions Documented 3 month pilot (Coaction): 54% reduction in hospitalization days 33% reduction in ED visits $178,547 estimated savings Medicare Patient Population (NY) 2.9% reduction in likelihood of 30 day readmission $1.24 million savings in admissions

22 Risk Adjustment Analysis Architecture

23 ICD-X from Clinical Note

24 STEP Summary Exchange 21% Avg Overlap Between Systems 17% Increase in Star Ratings Data Population Health Care Managers Physicians Public Health Savings Alerts: Decrease in Hospital Days, Readmissions and ED Visits Risk Assessment: Increased Risk Reimbursement

25 Questions Matthew Hoffman, MD CMIO, Utah Health Information Network

26 Interoperability and Analytics February 29, 2016 Daniella Meeker, PhD University of Southern California, Keck School of Medicine

27 Conflict of Interest Daniella Meeker has no real or apparent conflicts of interest to report.

28 Funding PCORI CDRN

29 Overview Multi-Institutional Learning Health Systems Data Standards and Standardization Process Computation Standards for Analysis Result Standards for Dissemination and Application

30 Learning Objectives Describe how standards define use cases and parameters for health data analytics Identify the ways in which data analytics can help to support the business value of health information exchange Evaluate how new dimensions in standard definitions will shape data analysis applications and use cases

31 Standards for Data Exchange and Persistence are Necessary but Not Sufficient to Obtain Value from Multisite Data Infrastructure.

32 Products of a Learning Health System Analysis models for causal inference and program evaluation Program X is 15% more effective at preventing readmission than Program Y Drug A has a greater risk for adverse events than Drug B Quality measurement reports Practice N is achieving 80% of quality indicators Practice L is achieving 60% of quality indicators Predictive models for patient-centered medicine For patients like John, Drug C is safer and more effective than Drug D. For patients with Debbie s goals and comorbidity profile, Program Y is better than Program X

33 pscanner Network 21M patients 5 University of California Medical Centers Cedar s Sinai Hospital Pacific NW Rural Health Practice-Based Research Network Los Angeles Department of Health Services 5 multi-site FQHCs Children s Hospital of Los Angeles Keck Medicine of USC

34 Distributed Research Network Requirements (AHRQ ) Service Oriented Architecture for privacy-preserving analytics in distributed research networks Focus on map-reduce, iterative algorithms based on paralleldistributed processing algorithms Standardized Analytic Data Warehouse at every site Role based access control -> Attribute Based Access Control De-centralized study administration no coordinating center peerto-peer analytics. GUI for menu-driven queries for multiple activities Proposing collaboration partners, data sets, and protocols Specifying regression analytics Data set extractions Cohort discovery

35 Distributed Research Network Requirements (AHRQ ) Methods repository for contributing and sharing analytic algorithms for classical statistics and machine learning Result repository for contributing and sharing analytic results (e.g. causal models, predictive models, quality reports)

36 SCANNER Network Software (AHRQ ) Need to select and implement standards for the entire analysis cycle: Data Data Processing Algorithms Data Analysis Algorithms Data Analysis Results

37 Part I: Multisite Data Standardization

38 Selecting a Data Warehousing Standard Health Economic Domains are not represented in other research and quality information models, but value was So Cal Health Leadership Priorities

39 Implementation datamartist.com

40 Aside on Data Quality & Availability text Dx R x CCD Lab EHR QRDA STANDARDIZED WAREHOUSE Procedures Finance LIS

41 Standardizing 11 Health Systems CUSTOM PROGRAMMING OMOP OMOP OMOP SHARED TRANSFORMATIO N PROGRAMS Quality Model Quality Model Quality Model OMOP Quality Model OMOP Quality Model OMOP Quality Model OMOP Quality Model OMOP Quality Model OMOP DISTRIBUTED ANALYTICS QRDA Quality Model

42 Aside on Data Quality & Availability HIE? text Dx R x CCD Lab EHR QRDA STANDARDIZED WAREHOUSE Procedures Finance LIS

43 Part II: Computation Standardization

44 Why do we need standards for computation if the data is already standardized?

45 Implemented standards + process modularity Reproducibility Robustness to innovation update parts without starting from scratch Flexibility to local implementation Transparency Comparability

46 Direct and Quantifiable Comparisons dataset A dataset A 30 day readmission

47 Selecting a Standard for Computation Specification Sufficiently expressive to represent data processing concepts for transactional, time-series data (e.g. interval logic) Sufficiently expressive to represent data processing concepts that are specific to healthcare (e.g. time of administration, age of onset) Sufficiently expressive to represent basic statistics and data analysis algorithms Supported/Adopted Quality Data Model Data Processing Semantics SQL Predictive Model Markup Language

48 PORTABLE DATA PROCESSING STANDARDS OMOP OMOP OMOP OMOP DISTRIBUTED ANALYTICS OMOP OMOP OMOP OMOP OMOP PORTABLE DATA ANALYSIS STANDARDS

49 Part 3: Result Standardization

50 Part 3: Result Standardization

51 Products of a Learning Health System Analysis models for causal inference and program evaluation Program X is 15% more effective at preventing readmission than Program Y Drug A has a greater risk for adverse events than Drug B Quality measurement reports Practice N is achieving 80% of quality indicators Practice L is achieving 60% of quality indicators Predictive models for patient-centered medicine For patients like John, Drug C is safer and more effective than Drug D. For patients with Debbie s goals and comorbidity profile, Program Y is better than Program X

52 Disseminating Products of a Learning Health System aka Data Processing Computable Phenotype Cohort Inclusion Criteria Measure Denominator OMOP Reference Data Model Data Set Extraction Program Extracted Data Set ( Flat File ) Analysis Program research Publish Estimated Predictive Model Publish Patient Record CCD care Record Processing Program Standardized Extracted Record Predictive Model Computation Patient Centered Prediction

53 Selecting Standards for Disseminating LHS Products Quality Indicators can be shared & Reported with QRDA Predictive Models can be shared & Reported with PMML (but not part of Health IT standards) Causal inference & program evaluation results are (still) disseminated on paper.

54 Summary: Standards for Exchanging Analysis Process and Products Process we need to represent Standard Rationale Data processing rules Cohort definition rules HQMF>CQL CMS, ONC, HL7 endorsed Part of EHR certification process New standards in trial use HQMF>CQL 100 s of established data sets 1000s of cohort criteria Data set description QRDA PMML QRDA Quality Measurement EHR Certification & CMS PMML Data analysis Data Analysis Methods PMML UCSD Data Mining Group Extensible to support model specifications Data Analysis Results (Estimated Models, Produce Predictions) PMML Process Workflow BPML? TBD Developed to represent results Adopted by most stats packages

55 What Next? FHIR Clinical Quality Framework Data Access Framework

56 Questions? Daniella Meeker, PhD Assistant Professor, USC Keck School of Medicine Director, Clinical Research Informatics Southern California Clinical Translational Sciences Institute

Using Big Data to Advance Healthcare Gregory J. Moore MD, PhD February 4, 2014

Using Big Data to Advance Healthcare Gregory J. Moore MD, PhD February 4, 2014 Using Big Data to Advance Healthcare Gregory J. Moore MD, PhD February 4, 2014 Sequencing Technology - Hype Cycle (Gartner) Gartner - Hype Cycle for Healthcare Provider Applications, Analytics and Systems,

More information

Secondary Use of EMR Data View from SHARPn AMIA Health Policy, 12 Dec 2012

Secondary Use of EMR Data View from SHARPn AMIA Health Policy, 12 Dec 2012 Secondary Use of EMR Data View from SHARPn AMIA Health Policy, 12 Dec 2012 Christopher G. Chute, MD DrPH, Professor, Biomedical Informatics, Mayo Clinic Chair, ISO TC215 on Health Informatics Chair, International

More information

Leveraging EHR to Improve Patient Safety: A Davies Story

Leveraging EHR to Improve Patient Safety: A Davies Story Leveraging EHR to Improve Patient Safety: A Davies Story Claudia Colgan, Vice President of Quality Initiatives Bruce Darrow, MD, PhD, Interim Chief Medical Information Officer Jill Kalman, MD, Director

More information

Predictive Analytics Drives Population Health Management

Predictive Analytics Drives Population Health Management Predictive Analytics Drives Population Health Management March 1, 2016 David Seo, MD University of Miami Health System AVP IT Clinical Applications and CMIO Chitra Raghu Lockheed Martin Program Manager

More information

Data Analytics: The Next Wave in Health IT. Big Data Conference June 17, 2014. Robert Wah, MD. Global Chief Medical Officer CSC

Data Analytics: The Next Wave in Health IT. Big Data Conference June 17, 2014. Robert Wah, MD. Global Chief Medical Officer CSC Data Analytics: The Next Wave in Health IT Big Data Conference June 17, 2014 Robert Wah, MD Global Chief Medical Officer CSC 1 Building a New Health Care System Healthcare is an industry in transition.

More information

Preparing Electronic Health Records for Multi-Site CER Studies

Preparing Electronic Health Records for Multi-Site CER Studies Preparing Electronic Health Records for Multi-Site CER Studies Michael G. Kahn 1,3,4, Lisa Schilling 2 1 Department of Pediatrics, University of Colorado, Denver 2 Department of Medicine, University of

More information

A Glimpse at the Future of Predictive Analytics in Healthcare

A Glimpse at the Future of Predictive Analytics in Healthcare A Glimpse at the Future of Predictive Analytics in Healthcare 1 Dr. Thomas Hill Dell Executive Director, Analytics Dell Software Group Tom.Hill@software.dell.com www.linkedin.com/in/drthomashill @DrTomHill

More information

NIH BD2K Think Tank. Session 2: Multiple Providers/EHRs for Single Participant; Multiple Other Data Sources

NIH BD2K Think Tank. Session 2: Multiple Providers/EHRs for Single Participant; Multiple Other Data Sources NIH BD2K Think Tank Session 2: Multiple Providers/EHRs for Single Participant; Multiple Other Data Sources Jeffery Talbert, PhD University of Kentucky Agenda KDOC Project Example Background Strategy Lessons

More information

Health IT: Better Information for Better Decisions. HSE Healthcare Leaders Masterclass 2015. 21 April 2015. Robert Wah, MD

Health IT: Better Information for Better Decisions. HSE Healthcare Leaders Masterclass 2015. 21 April 2015. Robert Wah, MD Health IT: Better Information for Better Decisions HSE Healthcare Leaders Masterclass 2015 21 April 2015 Robert Wah, MD Global Chief Medical Officer CSC 1 This image cannot currently be displayed. https://www.youtube.com/watch?v=wyzxoxvat2s

More information

I n t e r S y S t e m S W h I t e P a P e r F O R H E A L T H C A R E IT E X E C U T I V E S. In accountable care

I n t e r S y S t e m S W h I t e P a P e r F O R H E A L T H C A R E IT E X E C U T I V E S. In accountable care I n t e r S y S t e m S W h I t e P a P e r F O R H E A L T H C A R E IT E X E C U T I V E S The Role of healthcare InfoRmaTIcs In accountable care I n t e r S y S t e m S W h I t e P a P e r F OR H E

More information

West Virginia Information Technology Summit. November 4, 2009

West Virginia Information Technology Summit. November 4, 2009 West Virginia Information Technology Summit November 4, 2009 WVHIN Background Enabled by W. Va. Code seq. (2006) 16-29G-1, et Managed by 17-member public/private Board of Directors Charged to design, implement

More information

Utility of Common Data Models for EHR and Registry Data Integration: Use in Automated Surveillance

Utility of Common Data Models for EHR and Registry Data Integration: Use in Automated Surveillance Utility of Common Data Models for EHR and Registry Data Integration: Use in Automated Surveillance Frederic S. Resnic, MS, MSc Chairman, Department of Cardiovascular Medicine Co-Director, Comparative Effectiveness

More information

LANES. A key component of the LANES Initiative is to develop a Health Information Exchange.

LANES. A key component of the LANES Initiative is to develop a Health Information Exchange. powered by Vision and Mission Vision: An integrated, secure and forward-looking information management system that will facilitate the provision of timely, patient-centered and high quality healthcare

More information

Population Health Management Systems

Population Health Management Systems Population Health Management Systems What are they and how can they help public health? August 18, 1:00 p.m. 2:30 p.m. EDT Presented by the Public Health Informatics Working Group Webinar sponsored by

More information

TRUVEN HEALTH UNIFY. Population Health Management Enterprise Solution

TRUVEN HEALTH UNIFY. Population Health Management Enterprise Solution TRUVEN HEALTH UNIFY Population Health Enterprise Solution A Comprehensive Suite of Solutions for Improving Care and Managing Population Health With Truven Health Unify, you can achieve: Clinical data integration

More information

When Interoperability Challenges Are Unrelated to Technology Michael Bakerman, MD CMIO, UMMHC

When Interoperability Challenges Are Unrelated to Technology Michael Bakerman, MD CMIO, UMMHC When Interoperability Challenges Are Unrelated to Technology Michael Bakerman, MD CMIO, UMMHC Conflict of Interest Disclosure Michael Bakerman, MD Has no real or apparent conflicts of interest to report.

More information

Using EHRs, HIE, & Data Analytics to Support Accountable Care. Jonathan Shoemaker June 2014

Using EHRs, HIE, & Data Analytics to Support Accountable Care. Jonathan Shoemaker June 2014 Using EHRs, HIE, & Data Analytics to Support Accountable Care Jonathan Shoemaker June 2014 Agenda Allina Health overview ACO framework- setting the stage Health Information Technology and ACOs Role of

More information

An Overview Data Analytics & IT Infrastructure Challenges Using Community Data

An Overview Data Analytics & IT Infrastructure Challenges Using Community Data An Overview Data Analytics & IT Infrastructure Challenges Using Community Data HealthBridge is one of the nation s largest and most successful health information exchange organizations. Keith Hepp, CEO

More information

population health surveillance

population health surveillance Query Health: standardsbased, cross-platform population health surveillance Jeffrey Klann, PhD; Michael D Buck, PHD; Jeffrey Brown, PhD; Marc Hadley, PhD; Richard Elmore, MA; Griffin M Weber, MD, PhD;

More information

Quantifying the ROI of Population Health Solutions March 1, 2016

Quantifying the ROI of Population Health Solutions March 1, 2016 Quantifying the ROI of Population Health Solutions March 1, 2016 Curt Magnuson, Principal, The FiscalHealth Group Michael S. Wilson, Principal, The FiscalHealth Group Conflict of Interest Curt Magnuson,

More information

Michigan Medicaid EHR Incentive Program Update November 28, 2012. Jason Werner, MDCH

Michigan Medicaid EHR Incentive Program Update November 28, 2012. Jason Werner, MDCH Michigan Medicaid EHR Incentive Program Update November 28, 2012 Jason Werner, MDCH Program Summary This ARRA funded program provides financial incentives (100% Federal) to eligible Medicaid professionals

More information

HEAL NY Phase 5 Health IT RGA Section 7.1: HEAL NY Phase 5 Health IT Candidate Use Cases Interoperable EHR Use Case for Medicaid

HEAL NY Phase 5 Health IT RGA Section 7.1: HEAL NY Phase 5 Health IT Candidate Use Cases Interoperable EHR Use Case for Medicaid HEAL NY Phase 5 Health IT RGA Section 7.1: HEAL NY Phase 5 Health IT Candidate Use Cases Interoperable EHR Use Case for Medicaid Interoperable Electronic Health Records (EHRs) Use Case for Medicaid (Medication

More information

Adam Wilcox, PhD PhD Columbia University

Adam Wilcox, PhD PhD Columbia University Adam Wilcox, PhD Adam Wilcox, PhD Columbia University Intermountain Healthcare Columbia University Medical Center/ NewYork Presbyterian Hospital Evolving EHR Data Needs for Research, Business Intelligence

More information

Presenters. How to Maximize Technology to Improve Care and Reduce Cost 9/17/2015

Presenters. How to Maximize Technology to Improve Care and Reduce Cost 9/17/2015 How to Maximize Technology to Improve Care and Reduce Cost Presenters Justin Miller Director of Synergy Jordan Health services Dallas, TX jmiller@jhsi.com Justine Garcia Director of Software Solutions

More information

UAE Progress on the Acute Care EMRAM. Prepared by HIMSS Analytics Presented by Jeremy Bonfini

UAE Progress on the Acute Care EMRAM. Prepared by HIMSS Analytics Presented by Jeremy Bonfini UAE Progress on the Acute Care EMRAM Prepared by HIMSS Analytics Presented by Jeremy Bonfini 2013 Q3 2013 Q4 Complete EMR, CCD transactions to share data; Data warehousing; Data continuity with ED, ambulatory,

More information

Bench to Bedside Clinical Decision Support:

Bench to Bedside Clinical Decision Support: Bench to Bedside Clinical Decision Support: The Role of Semantic Web Technologies in Clinical and Translational Medicine Tonya Hongsermeier, MD, MBA Corporate Manager, Clinical Knowledge Management and

More information

Uncovering Value in Healthcare Data with Cognitive Analytics. Christine Livingston, Perficient Ken Dugan, IBM

Uncovering Value in Healthcare Data with Cognitive Analytics. Christine Livingston, Perficient Ken Dugan, IBM Uncovering Value in Healthcare Data with Cognitive Analytics Christine Livingston, Perficient Ken Dugan, IBM Conflict of Interest Christine Livingston Ken Dugan Has no real or apparent conflicts of interest

More information

New York ehealth Collaborative. Health Information Exchange and Interoperability April 2012

New York ehealth Collaborative. Health Information Exchange and Interoperability April 2012 New York ehealth Collaborative Health Information Exchange and Interoperability April 2012 1 Introductions Information exchange patient, information, care team How is Health information exchanged Value

More information

MemorialCare Health System: Steven Beal, VP Information Services

MemorialCare Health System: Steven Beal, VP Information Services MemorialCare Health System: Steven Beal, VP Information Services Serving Our Community Overview - Inpatient Six Hospitals Epic Clinical and Rev Cycle at 5 hospitals MedSeries4 at 6 th hospital Multiple

More information

THE CHALLENGE OF COORDINATING EMR

THE CHALLENGE OF COORDINATING EMR THE CHALLENGE OF COORDINATING EMR CLINICAL CONNECT: TWO YEARS OF REGIONAL ELECTRONIC HEALTH INFORMATION EXCHANGE NANCY A. LANDMAN, CIO INTERNATIONAL & COMMERCIAL SERVICES, UPMC 10/8/2014 2 UPMC Today:

More information

Embedding Guidance in the Kaiser Permanente EHR. Wiley Chan, MD Kaiser Permanente Care Management Institute Oakland, CA, USA

Embedding Guidance in the Kaiser Permanente EHR. Wiley Chan, MD Kaiser Permanente Care Management Institute Oakland, CA, USA Embedding Guidance in the Kaiser Permanente EHR Wiley Chan, MD Kaiser Permanente Care Management Institute Oakland, CA, USA Statement of Disclosure Wiley Chan, MD I have no commercial or academic conflicts

More information

ADVANCING MEASUREMENT OF PATIENT- CENTERED OUTCOMES AND QUALITY METRICS WITH ELECTRONIC HEALTH RECORDS

ADVANCING MEASUREMENT OF PATIENT- CENTERED OUTCOMES AND QUALITY METRICS WITH ELECTRONIC HEALTH RECORDS ADVANCING MEASUREMENT OF PATIENT- CENTERED OUTCOMES AND QUALITY METRICS WITH ELECTRONIC HEALTH RECORDS Tina Hernandez-Boussard, PhD, MPH, MS Director, Surgical Health Services Research Unit Assistant Professor

More information

patient-centered SCAlable National Network for Effectiveness Research

patient-centered SCAlable National Network for Effectiveness Research patient-centered SCAlable National Network for Effectiveness Research Data Sharing Meeting 2014 La Jolla, CA September 16, 2014 1 Disclosures No conflicts to declare Report of work in progress involving

More information

USE OF ELECTRONIC HEALTH RECORD DATA IN THE FIELD: CONDUCTING RANDOMIZED STUDIES ACROSS DIVERSE PRACTICE SETTINGS

USE OF ELECTRONIC HEALTH RECORD DATA IN THE FIELD: CONDUCTING RANDOMIZED STUDIES ACROSS DIVERSE PRACTICE SETTINGS USE OF ELECTRONIC HEALTH RECORD DATA IN THE FIELD: CONDUCTING RANDOMIZED STUDIES ACROSS DIVERSE PRACTICE SETTINGS Jason N. Doctor University of Southern California National Institute on Aging 1RC4AG039115

More information

Active AnAlytics: Driving informed Decisions leading to Better clinical AnD financial outcomes

Active AnAlytics: Driving informed Decisions leading to Better clinical AnD financial outcomes Active AnAlytics: Driving informed Decisions leading to Better clinical AnD financial outcomes An InterSystems White Paper for Healthcare IT Executives Active AnAlytics: Driving informed Decisions leading

More information

Big Data Analytics in Healthcare In pursuit of the Triple Aim with Analytics. David Wiggin, Director, Industry Marketing, Teradata 20 November, 2014

Big Data Analytics in Healthcare In pursuit of the Triple Aim with Analytics. David Wiggin, Director, Industry Marketing, Teradata 20 November, 2014 Big Data Analytics in Healthcare In pursuit of the Triple Aim with Analytics David Wiggin, Director, Industry Marketing, Teradata 20 November, 2014 Agenda The Triple Aim Population Health in Russia The

More information

Health Information Management Systems Technology and Analysis. Domain 3: Assessment, System Selection and Implementation

Health Information Management Systems Technology and Analysis. Domain 3: Assessment, System Selection and Implementation 1 Health Information Management Systems Technology and Analysis Domain 3: Assessment, System Selection and Implementation Module 3A: Purpose, Adoption and Use of Health Information Systems Lecture #1:

More information

Distributed Networking

Distributed Networking Distributed Networking Millions of people. Strong collaborations. Privacy first. Jeffrey Brown, Lesley Curtis, Richard Platt Harvard Pilgrim Health Care Institute and Harvard Medical School Duke Medical

More information

Meaningful Use. Goals and Principles

Meaningful Use. Goals and Principles Meaningful Use Goals and Principles 1 HISTORY OF MEANINGFUL USE American Recovery and Reinvestment Act, 2009 Two Programs Medicare Medicaid 3 Stages 2 ULTIMATE GOAL Enhance the quality of patient care

More information

The registry of the future: Leveraging EHR and patient data to drive better outcomes

The registry of the future: Leveraging EHR and patient data to drive better outcomes The registry of the future: Leveraging EHR and patient data to drive better outcomes Brian J. Kelly, M.D. President, Payer and Provider Solutions, Quintiles Jason Colquitt, VP, IT, Head of RWLPR IT, Global

More information

Electronic Health Records: Why are they important?

Electronic Health Records: Why are they important? Electronic Health Records: Why are they important? Linette T Scott, MD, MPH Deputy Director Health Information and Strategic Planning California Department of Public Health November 9, 2009 Presenter Disclosures

More information

BENCHMARKING EMR ADOPTION FOR HELSIT 2013

BENCHMARKING EMR ADOPTION FOR HELSIT 2013 Subtitle BENCHMARKING EMR ADOPTION FOR HELSIT 2013 Introduction to EMRAM & status as of Q2/2013 PRESENTED BY: DANIEL CZERMAK-WÄNN, NORDIC CLIENT RELATIONS MANAGER, HIMSS ANALYTICS EUROPE HIMSS Analytics

More information

Setting the World on FHIR

Setting the World on FHIR Setting the World on FHIR W. Ed Hammond. Ph.D., FACMI, FAIMBE, FIMIA, FHL7 Director, Duke Center for Health Informatics Director, Applied Informatics Research, DHTS Director of Academic Affairs, MMCi Program

More information

4. Understanding Clinical Data and Workflow Understanding Surveillance Data Exchange Processes Guide and Worksheet

4. Understanding Clinical Data and Workflow Understanding Surveillance Data Exchange Processes Guide and Worksheet To properly prepare for implementing the pilot of your surveillance program and its subsequent rollout, you must understand the surveillance data exchange processes. These processes can vary depending

More information

Advanced Solutions for Accountable Care Organizations (ACOs)

Advanced Solutions for Accountable Care Organizations (ACOs) Advanced Solutions for Accountable Care Organizations (ACOs) Since our founding more than 21 years ago, Iatric Systems has been dedicated to supporting the quality and delivery of healthcare, while helping

More information

Research Into Care: Identifying Barriers and Gaps in Care. AAFP National Research Network Robert Graham Center Wilson D. Pace, MD

Research Into Care: Identifying Barriers and Gaps in Care. AAFP National Research Network Robert Graham Center Wilson D. Pace, MD Research Into Care: Identifying Barriers and Gaps in Care AAFP National Research Network Robert Graham Center Wilson D. Pace, MD AAFP National Research Network The AAFP National Research Network is a nationwide

More information

Analytics and Business Intelligence

Analytics and Business Intelligence Analytics and Business Intelligence CE-IT Virtual Town Hall series December 12, 2012 JD Whitlock, MPH, MBA, CPHIMS James E. Gaston, FHIMSS HIMSS Clinical & Business Intelligence Overview HIMSS Resources

More information

One Research Court, Suite 200 Rockville, MD 20850 www.ctisinc.com Tel: 301.948.3033 Fax: 301.948.2242

One Research Court, Suite 200 Rockville, MD 20850 www.ctisinc.com Tel: 301.948.3033 Fax: 301.948.2242 TRANSFORMATION OF HEALTH INDUSTRY THROUGH PERFORMANCE PYRAMID: Providing Excellent End-to-End Healthcare to the Population with a 30% Reduction in Cost and Time. Introduction The American health industry

More information

Environmental Health Science. Brian S. Schwartz, MD, MS

Environmental Health Science. Brian S. Schwartz, MD, MS Environmental Health Science Data Streams Health Data Brian S. Schwartz, MD, MS January 10, 2013 When is a data stream not a data stream? When it is health data. EHR data = PHI of health system Data stream

More information

Daniel Mingle, MD MS 219 Streaked Mt Rd, South Paris, ME 04281 (207) 441-3064 Daniel.Mingle@mingleanalytics.com

Daniel Mingle, MD MS 219 Streaked Mt Rd, South Paris, ME 04281 (207) 441-3064 Daniel.Mingle@mingleanalytics.com Daniel Mingle, MD MS 219 Streaked Mt Rd, South Paris, ME 04281 (207) 441-3064 Daniel.Mingle@mingleanalytics.com Healthcare Consultant Optimizing Healthcare Systems on an EMR Platform With over 30 years

More information

Leveraging EHR Data Reporting Anita Christie, RN MHA CPHQ MA Department of Public Health

Leveraging EHR Data Reporting Anita Christie, RN MHA CPHQ MA Department of Public Health Improve Population Health Outcomes Leveraging EHR Data Reporting Anita Christie, RN MHA CPHQ MA Department of Public Health Massachusetts ehealth Institute MBI MASSACHUSETTS BROADBAND INSTITUTE MeHI MASSACHUSETTS

More information

Summary of Patient-Centered Outcomes Research Provisions Prepared by AAMC Government Relations, March 2010

Summary of Patient-Centered Outcomes Research Provisions Prepared by AAMC Government Relations, March 2010 Summary of Patient-Centered Outcomes Research Provisions Prepared by AAMC Government Relations, March 2010 Section 6301 of the Patient Protection and Affordable Care Act (as modified by Section 10602)

More information

Public Health and the Learning Health Care System Lessons from Two Distributed Networks for Public Health

Public Health and the Learning Health Care System Lessons from Two Distributed Networks for Public Health Public Health and the Learning Health Care System Lessons from Two Distributed Networks for Public Health Jeffrey Brown, PhD Assistant Professor Department of Population Medicine Harvard Medical School

More information

Standardized Representation for Electronic Health Record-Driven Phenotypes

Standardized Representation for Electronic Health Record-Driven Phenotypes Standardized Representation for Electronic Health Record-Driven Phenotypes April 8, 2014 AMIA Joint Summits for Translational Research Rachel L. Richesson, PhD Shelley A. Rusincovitch Michelle M. Smerek

More information

Advanced Models of Primary Care: Care Management Plus pilot and dissemination

Advanced Models of Primary Care: Care Management Plus pilot and dissemination Advanced Models of Primary Care: Care Management Plus pilot and dissemination Presented by David A. Dorr, MD, MS; Oregon Health & Science University, dorrd@ohsu.edu Funded by The John A. Hartford Foundation,

More information

An Essential Ingredient for a Successful ACO: The Clinical Knowledge Exchange

An Essential Ingredient for a Successful ACO: The Clinical Knowledge Exchange An Essential Ingredient for a Successful ACO: The Clinical Knowledge Exchange Jonathan Everett Director, Health Information Technology Chinese Community Health Care Association Darren Schulte, MD, MPP

More information

Data Warehousing Part 1: What is a Data Warehouse and How Your Organization Can Benefit

Data Warehousing Part 1: What is a Data Warehouse and How Your Organization Can Benefit Data Warehousing Part 1: What is a Data Warehouse and How Your Organization Can Benefit Presented by: David Hartzband, D.Sc. Matthew Grob, CPHIMS, FHIMSS Director, Technology Research Director & Practice

More information

6/12/2015. Dignity Health Population Health Management and Compliance Programs. Moving Towards Accountable Care. Dignity Health Poised for Innovation

6/12/2015. Dignity Health Population Health Management and Compliance Programs. Moving Towards Accountable Care. Dignity Health Poised for Innovation Dignity Health Population Health Management and Compliance Programs Julie Bietsch, VP Population Health Management Dawnese Kindelt, Senior Compliance Director, Clinical Integration June 8, 2015 Moving

More information

Analytic-Driven Quality Keys Success in Risk-Based Contracts. Ross Gustafson, Vice President Allina Performance Resources, Health Catalyst

Analytic-Driven Quality Keys Success in Risk-Based Contracts. Ross Gustafson, Vice President Allina Performance Resources, Health Catalyst Analytic-Driven Quality Keys Success in Risk-Based Contracts March 2 nd, 2016 Ross Gustafson, Vice President Allina Performance Resources, Health Catalyst Brian Rice, Vice President Network/ACO Integration,

More information

Nandan Banerjee Cogent Infotech Corporation COGENT INFOTECH CORPORATION

Nandan Banerjee Cogent Infotech Corporation COGENT INFOTECH CORPORATION Nandan Banerjee Cogent Infotech Corporation Health Care Cost Better, Efficient, Valuable Health care services Stakeholders demand for metrics across clinical, operational and financial disciplines. Overcoming

More information

Realizing ACO Success with ICW Solutions

Realizing ACO Success with ICW Solutions Realizing ACO Success with ICW Solutions A Pathway to Collaborative Care Coordination and Care Management Decrease Healthcare Costs Improve Population Health Enhance Care for the Individual connect. manage.

More information

Adventures in EHR Computable Phenotypes: Lessons Learned from the Southeastern Diabetes Initiative (SEDI)

Adventures in EHR Computable Phenotypes: Lessons Learned from the Southeastern Diabetes Initiative (SEDI) Adventures in EHR Computable Phenotypes: Lessons Learned from the Southeastern Diabetes Initiative (SEDI) PCORnet Best Practices Sharing Session Wednesday, August 5, 2015 Introductions to the Round Table

More information

What is HealthShare?

What is HealthShare? What is HealthShare? The Problem Interoperability Informatics Healthcare Transformation Journey Current EHR & HIE Focus Next Generation Healthcare Informatics HealthShare Target Opportunities HealthShare

More information

Children s Medical Center of Dallas

Children s Medical Center of Dallas Dallas, TX Overview (Children s) is an academic medical center with 591 licensed beds. It has campuses in Dallas, Plano and Southlake, Texas, including an outpatient center in Southlake and 16 MyChildren

More information

Challenges Reporting Quality Measures in Small Rural Practices: Lessons Learned from the InteGREAT Project

Challenges Reporting Quality Measures in Small Rural Practices: Lessons Learned from the InteGREAT Project Challenges Reporting Quality Measures in Small Rural Practices: Lessons Learned from the InteGREAT Project James McCormack, PhD, Instructor, OHSU Department of Medical Informatics and Clinical Epidemiology

More information

Electronic Medical Records Getting It Right and Going to Scale

Electronic Medical Records Getting It Right and Going to Scale Electronic Medical Records Getting It Right and Going to Scale W. Ed Hammond, Ph.D. Duke University Medical Center 02/03/2000 e-hammond, Duke 0 Driving Factors Patient Safety Quality Reduction in cost

More information

The NYC Macroscope: Harnessing Data from Electronic Health Records for Population Health Surveillance in NYC

The NYC Macroscope: Harnessing Data from Electronic Health Records for Population Health Surveillance in NYC The NYC Macroscope: Harnessing Data from Electronic Health Records for Population Health Surveillance in NYC Remle Newton-Dame, MPH Senior Epidemiologist, Primary Care Information Project Tiffany G. Harris,

More information

How to Enable Value-Based Care and Clinical Integration with Epic Cogito

How to Enable Value-Based Care and Clinical Integration with Epic Cogito How to Enable Value-Based Care and Clinical Integration with Epic Cogito Background Many newly formed, subsidiary organizations of integrated delivery networks are now the nucleus for clinical integration

More information

Health Information Exchange in NYS

Health Information Exchange in NYS Health Information Exchange in NYS Roy Gomes, RHIT, CHPS Implementation Project Manager 1 Who is NYeC? 2 Agenda NYeC Background Overview and programs Assist providers transitioning from paper to electronic

More information

Clinical Document Exchange Integration Guide - Outbound

Clinical Document Exchange Integration Guide - Outbound Clinical Document Exchange Integration Guide - Outbound Integrate your healthcare IT system with Practice Fusion s Electronic Health Record (EHR) System Table of Contents 1 Introduction... 2 2 Integration

More information

Outline. Vision for Delivering Quality Care Do the Right Thing. Lessons from Quality

Outline. Vision for Delivering Quality Care Do the Right Thing. Lessons from Quality Outline Effectiveness Research Using EHRs: Gold Mine or Tower of Babel? Paul Tang, MD VP, Chief Medical Information Officer Palo Alto Medical Foundation Consulting Associate Professor Stanford University

More information

By Debra Davidson, PhD, MSA, MS Luciane Tarter, RN, BSN. SBIRT grant for Behavioral Health APCP. Mo Health Net Health Home Program SBIRT

By Debra Davidson, PhD, MSA, MS Luciane Tarter, RN, BSN. SBIRT grant for Behavioral Health APCP. Mo Health Net Health Home Program SBIRT By Debra Davidson, PhD, MSA, MS Luciane Tarter, RN, BSN 1 2 Team Based Care for Chronic Illness Our journey: 24 months APCP: Advanced Primary Care Practice Grant for Medicare : NCQA Level 3 by 2014 MoHealth

More information

Beacon User Stories Version 1.0

Beacon User Stories Version 1.0 Table of Contents 1. Introduction... 2 2. User Stories... 2 2.1 Update Clinical Data Repository and Disease Registry... 2 2.1.1 Beacon Context... 2 2.1.2 Actors... 2 2.1.3 Preconditions... 3 2.1.4 Story

More information

Innovations in AAFP Clinical Care Demonstrating Better Results for Patients

Innovations in AAFP Clinical Care Demonstrating Better Results for Patients Innovations in AAFP Clinical Care Demonstrating Better Results for Patients Perry A. Pugno, MD, MPH, FAAFP, Vice President for Education Bruce Bagley, MD, FAAFP, Medical Director, Quality Improvement Ann

More information

A New Paradigm for Large, Simple Trials Based on Electronic Health Records

A New Paradigm for Large, Simple Trials Based on Electronic Health Records A New Paradigm for Large, Simple Trials Based on Electronic Health Records KyungMann Kim kmkim@biostat.wisc.edu University of Wisconsin-Madison, Madison, WI, USA May 20, 2013 Outline Introduction New Initiatives

More information

SALUS: Enabling the Secondary Use of EHRs for Post Market Safety Studies

SALUS: Enabling the Secondary Use of EHRs for Post Market Safety Studies SALUS: Enabling the Secondary Use of EHRs for Post Market Safety Studies May 2015 A. Anil SINACI, Deputy Project Coordinator SALUS: Scalable, Standard based Interoperability Framework for Sustainable Proactive

More information

Genomic Medicine Centers Meeting VII. Summary of Themes Discussed in Keynote and Panel Discussions October 3, 2014

Genomic Medicine Centers Meeting VII. Summary of Themes Discussed in Keynote and Panel Discussions October 3, 2014 Genomic Medicine Centers Meeting VII Summary of Themes Discussed in Keynote and Panel Discussions October 3, 2014 Meeting Objectives GM 7 will convene key thought leaders in genomic implementation and

More information

Health Information Technology and the National Quality Agenda. Daphne Ayn Bascom, MD PhD Chief Clinical Systems Officer Medical Operations

Health Information Technology and the National Quality Agenda. Daphne Ayn Bascom, MD PhD Chief Clinical Systems Officer Medical Operations Health Information Technology and the National Quality Agenda Daphne Ayn Bascom, MD PhD Chief Clinical Systems Officer Medical Operations Institute of Medicine Definition of Quality "The degree to which

More information

Population Health Management Innovation Payer and Provider Collaboration. Population Health Management Innovation Payer and Provider Collaboration

Population Health Management Innovation Payer and Provider Collaboration. Population Health Management Innovation Payer and Provider Collaboration Population Health Management Innovation Payer and Provider Collaboration Population Health Management Innovation Payer and Provider Collaboration Agenda Strategic Context Population Health Journey Key

More information

Big Data Integration and Governance Considerations for Healthcare

Big Data Integration and Governance Considerations for Healthcare White Paper Big Data Integration and Governance Considerations for Healthcare by Sunil Soares, Founder & Managing Partner, Information Asset, LLC Big Data Integration and Governance Considerations for

More information

Hospital IT Expenses and Budgets Related to Clinical Sophistication. Market Findings from HIMSS Analytics

Hospital IT Expenses and Budgets Related to Clinical Sophistication. Market Findings from HIMSS Analytics Hospital IT Expenses and Budgets Related to Clinical Sophistication Market Findings from HIMSS Analytics Table of Contents 2 3 4 8 13 14 Executive Summary Expense Metrics Used for this Research Operating

More information

EHR Recruitment Process and Methods Workgroup. John Buse, UNC-CH On behalf of Marie Rape, Chunhua Weng and Peter Embi

EHR Recruitment Process and Methods Workgroup. John Buse, UNC-CH On behalf of Marie Rape, Chunhua Weng and Peter Embi EHR Recruitment Process and Methods Workgroup John Buse, UNC-CH On behalf of Marie Rape, Chunhua Weng and Peter Embi REDCap Survey INTRODUCTION The Methods and Process Domain Task Force has established

More information

Building Regional and National Health Information Systems. Mike LaRocca

Building Regional and National Health Information Systems. Mike LaRocca Building Regional and National Health Information Systems Mike LaRocca Agenda What are the key use cases driving New York? What is the SHIN-NY NY and its architecture? What standards and protocols were

More information

Data Analytics in Health Care

Data Analytics in Health Care Data Analytics in Health Care ONUP 2016 April 4, 2016 Presented by: Dennis Giokas, CTO, Innovation Ecosystem Group A lot of data, but limited information 2 Data collection might be the single greatest

More information

Singapore s National Electronic Health Record

Singapore s National Electronic Health Record Singapore s National Electronic Health Record The Roadmap to 2010 Dr Sarah Christine Muttitt Chief Information Officer Information Systems Division 17 th July, 2009 Taking the Next Step (MSM April 2008)

More information

2016 Leadership Summit

2016 Leadership Summit CRISP: A Regional Health Information Exchange Serving Maryland and D.C. 2016 Leadership Summit Ross Martin, MD, MHA Program Director, Integrated Delivery Network @RossMartin 24 May 2016 Maryland State-Designated

More information

Indiana Council of Community Mental Health Centers. October 14, 2013

Indiana Council of Community Mental Health Centers. October 14, 2013 Indiana Council of Community Mental Health Centers October 14, 2013 Role of the State HIT Coordinator Develop and advocate for HIT Policy Coordinate efforts with Medicaid, public health, and other federally

More information

TRUVEN HEALTH UNIFY. Population Health Management Enterprise Solution

TRUVEN HEALTH UNIFY. Population Health Management Enterprise Solution TRUVEN HEALTH UNIFY Population Health Enterprise Solution A Comprehensive Suite of Solutions for Improving Care and Managing Population Health With Truven Health Unify, you can achieve: Clinical data integration

More information

Dual RFI Response Summary

Dual RFI Response Summary Dual RFI Response Summary Improving Care through Integrated Medicare and Medi- Cal Delivery Models Stuart Levine, MD., MHA. Keith Wilson, MD Robert Margolis, MD. Stakeholder Meeting August 30, 2011 1 Organization

More information

Understanding EHRs: Common Features and Strategic Approaches for Medicaid/SCHIP

Understanding EHRs: Common Features and Strategic Approaches for Medicaid/SCHIP Understanding EHRs: Common Features and Strategic Approaches for Medicaid/SCHIP Presented by: Karen M. Bell MD, MMS, Director, HIT Adoption W. David Patterson PhD, Deputy Chief, Health and Demographics

More information

NHCHC Meaningful Use of Electronic Health Records Resource Catalogue. Meaningful Use Overview

NHCHC Meaningful Use of Electronic Health Records Resource Catalogue. Meaningful Use Overview Meaningful Use Overview Meaningful use is the use of a certified electronic health record (EHR) to demonstrate improved quality and safety of health care delivery for a patient population within a clinical

More information

Using Health Information Technology to Improve Quality of Care: Clinical Decision Support

Using Health Information Technology to Improve Quality of Care: Clinical Decision Support Using Health Information Technology to Improve Quality of Care: Clinical Decision Support Vince Fonseca, MD, MPH Director of Medical Informatics Intellica Corporation Objectives Describe the 5 health priorities

More information

HL7 and SOA Based Distributed Electronic Patient Record Architecture Using Open EMR

HL7 and SOA Based Distributed Electronic Patient Record Architecture Using Open EMR HL7 and SOA Based Distributed Electronic Patient Record Architecture Using Open EMR Priti Kalode 1, Dr Onkar S Kemkar 2, Dr P R Gundalwar 3 Research Student, Dept of Comp Sci &Elec, RTM Nagpur University

More information

Disclosure of Conflict of Interest

Disclosure of Conflict of Interest Challenging the Status Quo of Telehealth in Policy, Technology, & Clinical Care H. Stephen Lieber President and Chief Executive Officer HIMSS Disclosure of Conflict of Interest No Conflict of Interest

More information

Enterprise Analytics Strategic Planning

Enterprise Analytics Strategic Planning Enterprise Analytics Strategic Planning June 5, 2013 1 "The first question a data driven organization needs to ask itself is not "what do we think?" but rather "what do we know? Big Data: The Management

More information

THE ACTIVELY CONNECTED PHYSICIAN

THE ACTIVELY CONNECTED PHYSICIAN THE ACTIVELY CONNECTED PHYSICIAN How Direct Messaging Leads to Improved Patient Care OVERVIEW Health care connectivity made great strides in 2014. As more health delivery networks, hospitals and physicians

More information

Context. Accessibility. Relevance.

Context. Accessibility. Relevance. CLINICAL COLLABORATION PLATFORM Context. Accessibility. Relevance. CLINICAL DATA WORKFLOW FOR MEANINGFUL COLLABORATION. Connect. Collaborate. Care. Give physicians and administrators the clinical support

More information

Implementation of FHIR at University of Michigan

Implementation of FHIR at University of Michigan Implementation of FHIR at University of Michigan Early forays into one future of interoperability Connecting Michigan for Health 6 5 2015 Andrew Rosenberg MD CMIO University of Michigan Health System The

More information

From Fishing to Attracting Chicks

From Fishing to Attracting Chicks The Greater Plains Collaborative: a PCORNet Clinical Data Research Network s Strategies for Creating an Interoperable Architecture From Fishing to Attracting Chicks Russ Waitman, PhD Associate Professor,

More information

Job list - Research China

Job list - Research China Job list - Research China Job # Job Title Page 010499 Scientist for Mechanical Engineering P2-3 002590 Senior Scientist for Biomedical Engineering P4-5 022831 Research Scientist for MRI P6-7 010501 Scientist

More information