Natalia Olchanski, MS, Paige Lin, PhD, Aaron Winn, MPP. Center for Evaluation of Value and Risk in Health, Tufts Medical Center.
|
|
- May Holland
- 8 years ago
- Views:
Transcription
1 ISPOR 2013, New Orleans, LA Using EMR data for conducting retrospective studies: Opportunities and Pitfalls Natalia Olchanski, MS, Paige Lin, PhD, Aaron Winn, MPP Center for Evaluation of Value and Risk in Health, Tufts Medical Center Kathy Lang, PhD Boston Health Economics Who we are 2 Natalia Olchanski, MS Project Director Paige Lin, PhD Assistant Professor Aaron Winn, MPP Research Associate Kathy Lang, PhD Senior Director Center for Evaluation of Value and Risk in Health, Tufts Medical Center An academic research center focusing on issues pertaining to value, cost-effectiveness, and risk tradeoffs in healthcare Boston Health Economics BHE is an independent, full-service outcomes research company providing clear, objective, rigorous data to support better healthcare decisions 1
2 Disclaimer 3 Workshop discussion leaders are not affiliated with any data vendor, and do not favor any specific data source Outline 4 Overview understanding data Framework for data decisions The power of EMR, a case study Summary the good, the bad, and the reality Q & A 2
3 Perspectives on EMRs 5 The Believer Patients Like Me Continuous Improvement The Skeptic Rapid Misinformation Patient Privacy Rapid Learning Drug Safety Payers Can Keep Score Precision Medicine Patient Centered Outcomes Disorganized Systems Biased Results Off-Label Use Learning Networks Understanding data 6 Why was the data created? How do patients enter and leave the data? How was the data aggregated? 3
4 Why was the data created? 7 Claims=Payment EMRs=Patient Care Registry=Patient Outcomes Clinical Trials=Efficacy How do patients enter and leave the data? 8 Claims Registry Clinical Trials EMRs Entry: Start Insurance Exit: Stop Insurance Entry: Broad - Having Disease Exit: Death or Cure, Loss of follow-up Entry: Narrow - Fit desired profile Exit: Trial has been completed Entry: Receive services from provider Exit: Not clear 4
5 How was the data aggregated? 9 Claims Registry Clinical Trials EMRs Payer aggregated information to pay providers Researchers aggregated information for research Researchers aggregated information for research Data vendors or large providers aggregated information for purchase Types of EMR sources 10 Single Provider Collection of Providers Geography Utilization Examples MedMining (Geisinger) Kaiser Humedica Premier 5
6 11 Framework for data decisions Important factors in data decisions 12 Research question Required variables Data coverage Project timeline Available budget 6
7 Deciding on secondary data source 13 CLAIMS CHART REVIEW EMR Access/Delivery? Size Acquisition Cost?? Clinical/Lab Data? Generalizability?? Economic Data Integrated Data?? Lag Time?? Incomplete Data? Example data decision 14 Research Question Data and Design Considerations Claims Chart Review EMR Other 7
8 Case example: blood products study 15 Research Question: Mortality and time to death in patients receiving specific blood products Required variables: Demographic, clinical characteristics, treatment, INR test results Claims Case example: blood products study 16 Research Question: Mortality and time to death in patients receiving specific blood products Required variables: Demographic, clinical characteristics, treatment, INR test results Claims 8
9 Case example: blood products study 17 Research Question: Mortality and time to death in patients receiving specific blood products Required variables: Demographic, clinical characteristics, treatment, INR test results Claims Chart Review Case example: blood products study 18 Research Question: Mortality and time to death in patients receiving specific blood products Required variables: Demographic, clinical characteristics, treatment, INR test results Claims Chart Review 9
10 Case example: blood products study 19 Research Question: Mortality and time to death in patients receiving specific blood products Required variables: Demographic, clinical characteristics, treatment, INR test results Claims Chart Review EMR Case example: Blood products study 20 Research Question: Mortality and time to death in patients receiving specific blood products Required variables: Demographic, clinical characteristics, treatment, INR test results Claims Chart Review EMR Uncorrected INR was not associated with higher risk of mortality, but was statistically significant for the intracranial hemorrhage (ICH) subgroup 10
11 What to ask the data vendor 21 Comprehensiveness and Generalizability Patient and Services Inclusion/Exclusion Factors Appropriateness for study design Sample Size and Missing Data Accuracy and Validation Access and Cost Key questions for vendors (see handout for more) 22 Comprehensiveness and Generalizability Patient and Services Inclusion/Exclusion Factors Appropriateness for study design Sample Size and Missing Data Accuracy and Validation Access and Cost Are data provider-centric or insurer-centric? Geographic distribution of the data How are patients selected for inclusion in the data? Are relevant settings/types of care included? Are required variables available? Is the length of enrollment or follow up appropriate? Sample counts for population of interest Prevalence of missing or incomplete details How are data collected, entered, and cleaned? Can data be validated against medical charts? How much will the data cost? Time frame for receiving and how current the data? 11
12 8% 7% 7% 6% 6% 5% 4% 2% 2% 1% 1% 23 Case Study A fresh look at comorbidities in diabetes using EMRs Funding source: West Health Institute Comorbidities in type 2 diabetes patients: Prevalence rates 24 77% 65% 49% 11% 12
13 Why use EMR? 25 EMR data allow us to better understand comorbidities Humedica data 26 Provider data Ambulatory groups Hospital systems Integrated delivery networks (IDNs) Demographics Medical Rx Labs 13
14 Prescription Labs 27 Hospitalizations Encounter ID Visit ID Encounter ID Date Admitting Spec Attending Spec Procedures Prescription Procedures Demographics Hospitalizations Diagnosis Labs Diagnosis Demographics 27 Prescription ID Date Drug Description NDC Provider spec. Hospitalizations ID Visit ID Visit type Date - Start Date - End Attending Spec Encounter ID Visit ID Encounter ID Date Admitting Spec Attending Spec Labs ID Encounter ID Test code Test date Test result 28 Procedures ID Encounter ID Date Procedure code Code type Demographics ID Age group Gender Race Diagnosis ID Encounter ID Date Diagnosis code Primary diag flag 28 14
15 Identifying hypertension among type 2 diabetes patients 29 Diagnosis Source % of all hypertension patients Diagnosis 55% Lab Rx 29 Identifying hypertension among type 2 diabetes patients 30 Rx Source % of all hypertension patients Diagnosis 55% Rx 64% 30 15
16 Identifying hypertension among type 2 diabetes patients 31 Source % of all hypertension patients Diagnosis 55% Rx 64% Lab Lab 32% 31 Identifying hypertension among type 2 diabetes patients 32 Lab 24% Diagnosis 10% 2% 40% 3% 3% Rx 18% Source % of all hypertension patients Diagnosis 55% Rx 64% Lab 32% 16
17 Comorbidity clusters (Poster #PDB2) 33 21% 18% 13% 6% 5% 5% 3% 3% 2% 2% 2% 1% 1% 1% 1% 33 Summary 34 17
18 35 The good, the bad and the reality 35 The good 36 Lab results & clinical details Large sample Inexpensive (compared with RCTs or registries) Near real time analytics Natural language processing to extract information from physician notes 18
19 The bad 37 Missing data Incomplete variables HbA1c Out-of-network utilization? Sample attrition over time? % Missing 18% % % The bad 38 More expensive (compared with claims data) Natural Language Processing (NLP) not validated Prescriptions written, not filled (cannot measure adherence) Economic variables unavailable Payer-specific analyses not possible 19
20 The reality 39 EMRs are new tools Understanding heterogeneity (and messiness) of real-world practice Still a long way to link data from different EMR systems and other sources Select a data source that best meets your needs Think about trade-offs 40 Q & A 20
21 Q & A 41 Discuss your research questions Share your experiences with EMR data Natalia Olchanski, MS Paige Lin, PhD Aaron Winn, MPP Kathy Lang, PhD nolchanski@tuftsmedicalcenter.org plin@tuftsmedicalcenter.org awinn@tuftsmedicalcenter.org klang@bhei.com 21
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 informationDisclosures. Real World Data Sources
Disclosures Real World Data Sources Christopher M. Blanchette, PhD, MBA Director, HEOR, Otsuka America Pharmaceutical Inc. Research Associate Professor, Public Health Sciences, University of North Carolina,
More informationAchieving Value from Diverse Healthcare Data
Achieving Value from Diverse Healthcare Data Paul Bleicher, MD, PhD Chief Medical Officer Humedica Boston MA The Information Environment in Healthcare Pharma, Biotech, Devices Hospitals Physicians Pharmacies
More informationThe 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 informationUnderstanding Diseases and Treatments with Canadian Real-world Evidence
Understanding Diseases and Treatments with Canadian Real-world Evidence Real-World Evidence for Successful Market Access WHITEPAPER REAL-WORLD EVIDENCE Generating real-world evidence requires the right
More informationUsing Real-World Data for Outcomes Research and Comparative Effectiveness Studies
Using Real-World Data for Outcomes Research and Comparative Effectiveness Studies Kathy Lang, PhD Christina Mack, MSPH, PhD Copyright 2014 Quintiles Your Presenters Kathy Lang Senior Director, EMR Data
More informationAn Optum Company. The Journey: From Healthcare To Health
The Journey: From Healthcare To Health June 2014 Cross-Continuum Clinical & Claims Analytics Platform Aggregate data across the continuum Clean, normalize and validate data Transform data into insight
More informationPredictive analytics: Poised to drive population health. White Paper
Predictive analytics: Poised to drive population health As health care moves toward value-based payments and accountable care, providers need better tools for population health and risk management. The
More informationLeveraging Social Networks to Conduct Observational Research: A Paradigm Shift in Methodology. Presented by: Elisa Cascade, MediGuard/Quintiles
Leveraging Social Networks to Conduct Observational Research: A Paradigm Shift in Methodology Presented by: Elisa Cascade, MediGuard/Quintiles About Elisa Cascade, VP MediGuard/Quintiles Assisted in site
More informationContact Information: West Texas Health Information Technology Regional Extension Center 3601 4 th Street MS 6232 Lubbock, Texas 79424 806-743-1338
Contact Information: West Texas Health Information Technology Regional Extension Center 3601 4 th Street MS 6232 Lubbock, Texas 79424 806-743-1338 http://www.wtxhitrec.org/ Grant award - $6.6m Total number
More informationMarcus Wilson, PharmD. First Plenary Session
Moderator First Plenary Session THE USE OF "BIG DATA" - WHERE ARE WE AND WHAT DOES THE FUTURE HOLD? Marcus Wilson, PharmD HealthCore Wilmington, DE, USA Speakers First Plenary Session THE USE OF "BIG DATA"
More informationSecondary Uses of Data for Comparative Effectiveness Research
Secondary Uses of Data for Comparative Effectiveness Research Paul Wallace MD Director, Center for Comparative Effectiveness Research The Lewin Group Paul.Wallace@lewin.com Disclosure/Perspectives Training:
More informationEMR Name/ Model. meridianemr 4.2 CCHIT 2011 certified
EMR Name/ Model EMR Vendor meridianemr 4.2 CCHIT 2011 certified meridianemr, Inc Core Set of Measures Objective Stage 1 Objectives Stage 1 Measures EMR Module/ Feature 1 Use CPOE for medication orders
More informationhospital s or CAH s inpatient or professional guidelines
EMR Name/ Model EMR Vendor XLEMR/XLEMR-2011-MU XLEMR Objective 1 Core Set of Measures Use CPOE for medication orders Use CPOE for medication orders More than 30% of unique patients directly entered by
More informationA Case Study of Real World Data in Health Economics and Outcomes Research. Presented by: Joe Menzin Boston Health Economics June 25, 2014
A Case Study of Real World Data in Health Economics and Outcomes Research Presented by: Joe Menzin Boston Health Economics June 25, 2014 Overview Introduction Selected EHR Studies Key Lessons 2014 Boston
More informationUsing Large Datasets for Population-based Health Services Research
Using Large Datasets for Population-based Health Services Research Leighton Chan, MD, MPH Chief, Rehabilitation Medicine Department Clinical Center NIH Disclosures No financial disclosures A new era: BIG
More informationMeaningful Use. Medicare and Medicaid EHR Incentive Programs
Meaningful Use Medicare and Medicaid Table of Contents What is Meaningful Use?... 1 Table 1: Patient Benefits... 2 What is an EP?... 4 How are Registration and Attestation Being Handled?... 5 What are
More informationEMR Name/ Model. Cerner PowerChart Ambulatory (PowerWorks ASP)
EMR Name/ Model EMR Vendor Cerner PowerChart Ambulatory (PowerWorks ASP) Cerner Corporation Core Set of Measures 1 Use CPOE for medication orders directly entered by any licensed healthcare professional
More informationDistributed 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 informationMEANINGFUL USE STAGE 2 2015 FOR ELIGIBLE PROVIDERS USING CERTIFIED EMR TECHNOLOGY
MEANINGFUL USE STAGE 2 2015 FOR ELIGIBLE PROVIDERS USING CERTIFIED EMR TECHNOLOGY STAGE 2 REQUIREMENTS EPs must meet or qualify for an exclusion to 17 core objectives EPs must meet 3 of the 6 menu measures.
More informationLeveraging EMR Data to Better Understand Local Market Potential and the Deployment of Commercial Resources
Leveraging EMR Data to Better Understand Local Market Potential and the Deployment of Commercial Resources James Charnetski, Practice Leader Commercial Analytics & Effectiveness Quintiles Integrated Healthcare
More informationDelivering Real World Evidence. Canada Let s Get Real!
Delivering Real World Evidence from Electronic Medical Records in Canada Let s Get Real! Neil Corner Director, Real World Evidence, IMS Brogan Alison Dziarmaga Director, Real World Evidence, AstraZeneca
More informationEXPANDING THE EVIDENCE BASE IN OUTCOMES RESEARCH: USING LINKED ELECTRONIC MEDICAL RECORDS (EMR) AND CLAIMS DATA
EXPANDING THE EVIDENCE BASE IN OUTCOMES RESEARCH: USING LINKED ELECTRONIC MEDICAL RECORDS (EMR) AND CLAIMS DATA A CASE STUDY EXAMINING RISK FACTORS AND COSTS OF UNCONTROLLED HYPERTENSION ISPOR 2013 WORKSHOP
More informationLEADING RESEARCH MEASURES THAT COUNT
Considerations for Implementing Surveys Evaluating Effectiveness: Sample Recruitment, Ethics, and Privacy Laurie Zografos Senior Director, Surveys and Observational Studies RTI Health Solutions zografos@rti.org
More informationNIH 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 informationSwedish RWE a goldmine?
Swedish RWE a goldmine? How is Novartis using Swedish RWE to improve decision making? Madlaina Costa, Head Health Economics and Pricing, Novartis Sweden RWE in Europe, Amsterdam 3 rd June 2015 Swedish
More informationTABLE 4: STAGE 2 MEANINGFUL USE OBJECTIVES AND ASSOCIATED MEASURES SORTED BY CORE AND MENU SET
CMS-0044-P 156 TABLE 4: STAGE 2 MEANINGFUL USE OBJECTIVES AND ASSOCIATED MEASURES SORTED BY CORE AND MENU SET Improving quality, safety, efficiency, and reducing health disparities Use computerized provider
More informationPopulation Health for Pharma: Perspectives from Aetna/Healthagen
Population Health for Pharma: Perspectives from Aetna/Healthagen Van Crocker, President, Healthagen Outcomes April 2015 The future of healthcare depends on population health management Episodic treatment
More informationHEALTH CARE DATA IN QATAR
HEALTH CARE DATA IN QATAR Daoud Al-Badriyeh, PhD President, ISPOR Qatar Chapter and Assistant Professor of Pharmacoeconomics College of Pharmacy, Qatar University Doha, Qatar Health Care Data The problem:
More informationPlan and manage clinical trials with clarity and confidence
Plan and manage clinical trials with clarity and confidence Accurately identify opportunities and avoid obstacles throughout the clinical trial process with IMS Health Clinical Trial Optimization Solutions
More informationUsing Real-World Databases for Evidence Development
Using Real-World Databases for Evidence Development Strengths, Weaknesses and Evolving Approaches Dr Terry Cox Webinar 14 th November 2012 Copyright 2012 Quintiles 1 Your Presenter Terry Cox MD, PhD Director,
More informationMeaningful Use Criteria for Eligible Hospitals and Eligible Professionals (EPs)
Meaningful Use Criteria for Eligible and Eligible Professionals (EPs) Under the Electronic Health Record (EHR) meaningful use final rules established by the Centers for Medicare and Medicaid Services (CMS),
More informationOutline. 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 informationStage 1 vs. Stage 2 Comparison Table for Eligible Hospitals and CAHs Last Updated: August, 2012
CORE OBJECTIVES (16 total) Stage 1 vs. Stage 2 Comparison Table for Eligible Hospitals and CAHs Last Updated: August, 2012 Stage 1 Objective Use CPOE for medication orders directly entered by any licensed
More informationWays to Fix the System
Building the Health Informatics Chunnel: The PHR Meets the EHR Daniel Z. Sands, MD, MPH Cisco Systems and Harvard Medical School Boston, MA Harvard Medical School Copyright D. Z. Sands IBSG - 1 U.S. Healthcare
More informationImpact Intelligence. Flexibility. Security. Ease of use. White Paper
Impact Intelligence Health care organizations continue to seek ways to improve the value they deliver to their customers and pinpoint opportunities to enhance performance. Accurately identifying trends
More informationMedical Dental Integration Study. March 2013
Medical Dental Integration Study March 2013 Executive summary The study, which was a performed by Optum, the nation s leading health services company, on behalf of UnitedHealthcare evaluates the impact
More informationComparative Effectiveness Research and Medical Devices in the Healthcare Environment
Comparative Effectiveness Research and Medical Devices in the Healthcare Environment Jessica Jalbert, PhD LA-SER Analytica/Weill Cornell Medical College Mary E Ritchey, PhD Proctor & Gamble Outline Disclaimer:
More informationFrequently Asked Questions About Quality Data Reporting
Why am I being asked to submit claims for all of my patients if SQCN does not have any payer contracts? SQCN is a Clinical Integration (CI) network. The success of our network will depend upon our CI program
More informationRobert Okwemba, BSPHS, Pharm.D. 2015 Philadelphia College of Pharmacy
Robert Okwemba, BSPHS, Pharm.D. 2015 Philadelphia College of Pharmacy Judith Long, MD,RWJCS Perelman School of Medicine Philadelphia Veteran Affairs Medical Center Background Objective Overview Methods
More informationHow To Manage Information Management In An Emr
Information Management in EMR Data Standards, Data Cleaning & Data Discipline CEM Rounds, April 15, 2008 Karim Keshavjee MD, MBA, CCFP InfoClin Inc 2006. All Rights Reserved. Learning Objectives What are
More informationElectronic Medical Record Use and the Quality of Care in Physician Offices
Electronic Medical Record Use and the Quality of Care in Physician Offices National Conference on Health Statistics August 17, 2010 Chun-Ju (Janey) Hsiao, Ph.D, M.H.S. Jill A. Marsteller, Ph.D, M.P.P.
More informationUsing Clinical Registries to Create Evidence-based Health Care Policy : Experiences from Ontario, Canada
Using Clinical Registries to Create Evidence-based Health Care Policy : Experiences from Ontario, Canada April 2009 Jack V. Tu, MD PhD FRCPC CANADA RESEARCH CHAIR IN HEALTH SERVICES RESEARCH Institute
More informationUse of routinely collected electronic healthcare data: Lessons Learned
Use of routinely collected electronic healthcare data: Lessons Learned Massoud Toussi, MD, PhD, MBA European lead, Pharmacoepidemiology and Safety Real World Evidence Solutions, IMS Health, France ENCePP
More informationDemonstration Study of Healthcare Utilization by Obese Patients. Joseph Vasey PhD Director, Epidemiology Quintiles Outcome May 22, 2013
Demonstration Study of Healthcare Utilization by Patients Joseph Vasey PhD Director, Epidemiology Quintiles Outcome May 22, 2013 Copyright 2013 Quintiles Revised April 2013 Introduction Obesity in the
More informationStage 1 measures. The EP/eligible hospital has enabled this functionality
EMR Name/Model Ingenix CareTracker - version 7 EMR Vendor Ingenix CareTracker Stage 1 objectives Use CPOE Use of CPOE for orders (any type) directly entered by authorizing provider (for example, MD, DO,
More informationPatient Reported Outcome Data: Why PROs Will Be The Next Wave in Big Data. Neil B. Minkoff, M.D. Chief Medical Officer EmpiraMed
Patient Reported Outcome Data: Why PROs Will Be The Next Wave in Big Data Neil B. Minkoff, M.D. Chief Medical Officer EmpiraMed PRO Overview Presentation Proprietary & Confidential PRO Use and Barriers
More informationNew Hampshire Accountable Care Project: Analytic Report User Guide
New Hampshire Accountable Care Project: Analytic Report User Guide November 2015 Contents OVERVIEW... 2 Introduction... 2 User Guide Purpose... 2 USING THE ANALYTIC REPORT... 3 Report Access... 3 Report
More informationRole of EMRs in Patient Registries & Other Post- Marketing Research
Role of EMRs in Patient Registries & Other Post- Marketing Research David Thompson, PhD Dan Levy, MS 29 March 2013 Copyright 2013 Quintiles Your Presenters David Thompson, PhD Senior Vice President and
More informationPROPOSED US MEDICARE RULING FOR USE OF DRUG CLAIMS INFORMATION FOR OUTCOMES RESEARCH, PROGRAM ANALYSIS & REPORTING AND PUBLIC FUNCTIONS
PROPOSED US MEDICARE RULING FOR USE OF DRUG CLAIMS INFORMATION FOR OUTCOMES RESEARCH, PROGRAM ANALYSIS & REPORTING AND PUBLIC FUNCTIONS The information listed below is Sections B of the proposed ruling
More informationOptum One. The Intelligent Health Platform
Optum One The Intelligent Health Platform The Optum One intelligent health platform enables healthcare providers to manage patient populations. The platform combines the industry s most advanced integrated
More informationRisk Adjustment: Implications for Community Health Centers
Risk Adjustment: Implications for Community Health Centers Todd Gilmer, PhD Division of Health Policy Department of Family and Preventive Medicine University of California, San Diego Overview Program and
More informationCardinal Health Specialty Solutions. Cardinal Health Geographic Insights Maximize Market Opportunity with Actionable Insights from Data Visualization
Cardinal Health Specialty Solutions Cardinal Health Geographic Insights Maximize Market Opportunity with Actionable Insights from Data Visualization Cardinal Health Geographic Insights lets you Dig deep
More informationActive 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 informationHow can you unlock the value in real-world data? A novel approach to predictive analytics could make the difference.
How can you unlock the value in real-world data? A novel approach to predictive analytics could make the difference. What if you could diagnose patients sooner, start treatment earlier, and prevent symptoms
More informationAdvances in Underwriting, #1 The power of predictive modeling for small group new business underwriting
Advances in Underwriting, #1 The power of predictive modeling for small group new business underwriting The information in this document is subject to change without notice. This documentation contains
More informationPrior Authorization, Pharmacy and Health Case Management Information. Prior Authorization. Pharmacy Information. Health Case Management
Prior Authorization, Pharmacy and Health Case Management Information The purpose of this information sheet is to provide you with details on how Great-West Life will be assessing and managing your claim
More informationData Quality in Healthcare Comparative Databases. University HealthSystem Consortium
Data Quality in Healthcare Comparative Databases Steve Meurer PhD, MBA/MHS Vice President, Clinical Data & Informatics 1 2007 University HealthSystem Consortium University HealthSystem Consortium A member
More informationThe EP/eligible hospital has enabled this functionality
EMR Name/Model Amazing Charts Version 5 EMR Vendor Amazing Charts Please note: All of our answers refer to use for an Eligible Professional. Amazing Charts is not Stage 1 objectives Use CPOE Use of CPOE
More informationGuide to Electronic Medical Records. Assistant Professor, Department of Family Medicine, University of Manitoba. Faculty of Medicine Family Medicine
Guide to Electronic Medical Records Dr. Alexander Singer BSc. MB BAO BCh. CCFP Assistant Professor, Department of Family Medicine, University of Manitoba Faculty of Medicine Family Medicine Handouts Section
More informationData Use and the Liquid Grids Model
Data Use Policy Revision 1.1 03/09/2014 Ramos M. Mays, Chief Technology Officer Table of Contents 1. Information Sources... 3 2. Information we receive... 3 3. How we use information... 4 4. How long we
More informationTotal Cost of Care and Resource Use Frequently Asked Questions (FAQ)
Total Cost of Care and Resource Use Frequently Asked Questions (FAQ) Contact Email: TCOCMeasurement@HealthPartners.com for questions. Contents Attribution Benchmarks Billed vs. Paid Licensing Missing Data
More informationReal World Data: How It s Used at a Medical Device Company
MD MEDICAL SAFETY Real World Data: How It s Used at a Medical Device Company Myoung Kim, Ph.D., MBA. Andrew Yoo, M.D., M.S. Epidemiology and Health Informatics Medical Devices Johnson & Johnson May 29,
More informationThe Importance of Clinical and Claims Data
ON The Importance of Clinical and Claims Data In the rapidly evolving health care economy, getting comprehensive data has become essential for providers as they move to manage more patient risk. Clinical
More informationEQR PROTOCOL 4 VALIDATION OF ENCOUNTER DATA REPORTED BY THE MCO
OMB Approval No. 0938-0786 EQR PROTOCOL 4 VALIDATION OF ENCOUNTER DATA REPORTED BY THE MCO A Voluntary Protocol for External Quality Review (EQR) Protocol 1: Assessment of Compliance with Medicaid Managed
More informationMeaningful Use Rules Proposed for Electronic Health Record Incentives Under HITECH Act By: Cherilyn G. Murer, JD, CRA
Meaningful Use Rules Proposed for Electronic Health Record Incentives Under HITECH Act By: Cherilyn G. Murer, JD, CRA Introduction On December 30, 2009, The Centers for Medicare & Medicaid Services (CMS)
More informationThe Value of Healthcare Information Exchange and Interoperability
The Value of Healthcare Information Exchange and Interoperability Blackford Middleton, MD, MPH, MSc Chairman, Center for IT Leadership Director, Clinical Informatics R&D, Partners Healthcare Assistant
More informationResearch Opportunities using the PaTH Network
Research Opportunities using the PaTH Network DBMI Colloquium Chuck Borromeo Oct. 30, 2015 PaTH is funded through the Patient Centered Outcomes Research Institute (PCORI) PaTH Network Goals Build network
More informationBig Data in Healthcare: Current Possibilities and Emerging Opportunities
Big Data in Healthcare: Current Possibilities and Emerging Opportunities Andrew Bate Senior Director, Epidemiology Group Lead, Analytics 23 th March 2015 The Long Road In Developing a New Medicine Clinical
More informationThe EP/eligible hospital has enabled this functionality
EMR Name/Model EMR Vendor Electronic Patient Charts American Medical Software Stage 1 objectives Use CPOE Use of CPOE for orders (any type) directly entered by authorizing provider (for example, MD, DO,
More informationThe EP/eligible hospital has enabled this functionality. At least 80% of all unique patients. seen by the EP or admitted to the
EMR Name/Model EMR Vendor Allscripts Stage 1 objectives Eligible professionals Hospitals Use CPOE Use of CPOE for orders (any type) directly entered by authorizing provider (for example, MD, DO, RN, PA,
More informationThe Potential for Research Using Electronic Medical Records in Ontario
The Potential for Research Using Electronic Medical Records in Ontario University of Toronto Summer Workshop on Big Data for Health Rick Glazier, MD, MPH, FCFP Senior Scientist, Institute for Clinical
More informationMeasure #130 (NQF 0419): Documentation of Current Medications in the Medical Record National Quality Strategy Domain: Patient Safety
Measure #130 (NQF 0419): Documentation of Current Medications in the Medical Record National Quality Strategy Domain: Patient Safety 2016 PQRS OPTIONS FOR INDIVIDUAL MEASURES: CLAIMS, REGISTRY DESCRIPTION:
More informationHow To Integrate Diabetes Manager With Allscripts Ehr
Intégration de la Télémédecine dans le Dossier Médical Hospitalier Joshua L. Cohen, M.D. Professor of Medicine Division of Endocrinology & Metabolism Director, Medical Faculty Associates Diabetes Center
More informationPractice Readiness Assessment
Practice Demographics Practice Name: Tax ID Number: Practice Address: REC Implementation Agent: Practice Telephone Number: Practice Fax Number: Lead Physician: Project Primary Contact: Lead Physician Email
More informationQuantifying Medication Adherence: Practical Challenges and an Approach to Linking Alternative Measures
Quantifying Medication Adherence: Practical Challenges and an Approach to Linking Alternative Measures Christine Poulos, PhD, RTI Health Solutions Jay P. Bae, PhD, Eli Lilly and Company Sean D. Candrilli,
More informationCharles E. Drum, MPA, JD, PhD, Principal Investigator. December 3, 2014
Disability and Rehabilitation Research Project: Health and Health Care Disparities Among Individuals with Disabilities (Health Disparities) Project Highlights Charles E. Drum, MPA, JD, PhD, Principal Investigator
More informationBig Data and Oncology Care Quality Improvement in the United States
Big Data and Oncology Care Quality Improvement in the United States Peter P. Yu, MD, FACP, FASCO President, American Society of Clinical Oncology Director of Cancer Research, Palo Alto Medical Foundation
More informationPresented by. Terri Gonzalez Director of Practice Improvement North Carolina Medical Society
Presented by Terri Gonzalez Director of Practice Improvement North Carolina Medical Society Meaningful Use is using certified EHR technology to: Improve quality, safety, efficiency, and reduce errors Engage
More informationSUPPORT PATH PROGRAM INTAKE FORM PHONE: 1-855-769-7284 FAX: 1-855-298-8700
SUPPORT PATH PROGRAM INTAKE FORM PHONE: 1-855-769-7284 FAX: 1-855-298-8700 1 REQUESTED SERVICE(S) (REQUIRED) CHECK ALL BOXES THAT APPLY Benefits Investigation Prior Authorization and Appeals Support Patient
More informationBig Data and Healthcare Information. Ed Reiner Quintiles Transnational
Big Data and Healthcare Information Ed Reiner Quintiles Transnational About Me 30 years in the information sector McGraw-Hill Information Division Elsevier Science (Cardiosource, ScienceDirect) Medical
More informationFederal Employees Health Benefits Program Report on Health Information Technology (HIT) and Transparency. September 2007
Federal Employees Health Benefits Program Report on Health Information Technology (HIT) and Transparency Executive Summary September 2007 This report is based on information collected from health participating
More informationFind the signal in the noise
Find the signal in the noise Electronic Health Records: The challenge The adoption of Electronic Health Records (EHRs) in the USA is rapidly increasing, due to the Health Information Technology and Clinical
More informationMeaningful Use Stage 1:
Whitepaper Meaningful Use Stage 1: EHR Incentive Program Information -------------------------------------------------------------- Daw Systems, Inc. UPDATED: November 2012 This document is designed to
More informationUsing electronic feedback reporting to support clinicians ability to understand and improve population patient care in primary health care
Using electronic feedback reporting to support clinicians ability to understand and improve population patient care in primary health care Shaheena Mukhi Primary Health Care Information CPHA 2011 Monday,
More informationMy Big Data experience getting my feet wet in the puddle and still treading water 2 years later 28 th June 2013. Rob Walls Healthcare Data Analytics
My Big Data experience getting my feet wet in the puddle and still treading water 2 years later 28 th June 2013 Rob Walls Healthcare Data Analytics Abstract "Big Data" - Electronic Health Records (EHR)
More informationHITECH Act Update: An Overview of the Medicare and Medicaid EHR Incentive Programs Regulations
HITECH Act Update: An Overview of the Medicare and Medicaid EHR Incentive Programs Regulations The Health Information Technology for Economic and Clinical Health Act (HITECH Act) was enacted as part of
More informationIncentives to Accelerate EHR Adoption
Incentives to Accelerate EHR Adoption The passage of the American Recovery and Reinvestment Act (ARRA) of 2009 provides incentives for eligible professionals (EPs) to adopt and use electronic health records
More informationThe affordable way to pay for healthcare expenses not covered by your regular health insurance
The affordable way to pay for healthcare expenses not covered by your regular health insurance America s #1 option for individuals and families that have a $2,000 health insurance deductible or more Enroll
More informationData Standards, Data Cleaning and Data Discipline. Insight November 24, 2008
Data Standards, Data Cleaning and Data Discipline Designing the Next Generation of EMRs Insight November 24, 2008 InfoClin Inc 2006. All Rights Reserved. Agenda Why is data quality important? Why data
More informationElectronic Health Record (EHR) Data Analysis Capabilities
Electronic Health Record (EHR) Data Analysis Capabilities January 2014 Boston Strategic Partners, Inc. 4 Wellington St. Suite 3 Boston, MA 02118 www.bostonsp.com Boston Strategic Partners is uniquely positioned
More informationData Management considerations in Observational studies
Data Management considerations in Observational studies Valerie Alward, Manager RWLPR Data Management Zia Haque, Senior Director RWLPR Data Management Copyright 2015 Quintiles Your Presenters Valerie Alward
More informationWhat is Population Health Management? Spend less time. changing, more time improving. Belinda Ireland, MD, MS TheEvidenceDoc
What is Population Health Management? Spend less time Belinda Ireland, MD, MS TheEvidenceDoc changing, more time improving TheEvidenceDoc 2016 GoToWebinar The Questions Chat Box Set your audio option Hot
More informationWhat to Expect in Next Year & Developing Your ACO Action Plan
What to Expect in Next Year & Developing Your ACO Action Plan Welcome The webinar will start at 3:00 pm ET. It is interactive, so please make sure that you have connected via phone with your audio pin.
More informationPERSPECTIVES ON HEALTH INFORMATION TECHNOLOGY. Connected Digital Health For Patients, Clinicians, And Health Systems
PERSPECTIVES ON HEALTH INFORMATION TECHNOLOGY Connected Digital Health For Patients, Clinicians, And Health Systems Kaiser Permanente Overview USA s largest non-profit health plan and hospitals Integrated
More informationPromoting Access and Quality Through h Health Information Exchange
Health Exchange Promoting Access and Quality Through h Health Exchange NCSL Legislative Update August 2011 Healthcare San Antonio 2011 Gijs van Oort PhD Healthcare Access San Antonio 210-233-7079 2 How
More informationJoint Position on the Disclosure of Clinical Trial Information via Clinical Trial Registries and Databases 1 Updated November 10, 2009
Joint Position on the Disclosure of Clinical Trial Information via Clinical Trial Registries and Databases 1 Updated November 10, 2009 The innovative pharmaceutical industry 2 is committed to the transparency
More informationHITPC Meaningful Use Stage 3 Final Recommendations
Contents Meaningful Use Stage 3 Final Recommendations... 2 HIT Policy Committee Member Concerns... 14 Objectives Considered for Inclusion - Not Included in Final Recommendations... 14 1 Meaningful Use
More informationHIPAA and Big Data Twenty Third National HIPAA Summit. March 17, 2015 Mitchell W. Granberg, Optum Chief Privacy Officer
HIPAA and Big Data Twenty Third National HIPAA Summit March 17, 2015 Mitchell W. Granberg, Optum Chief Privacy Officer Overview HIPAA and Big Data Big Data Definitions Big Data and Health Care Benefits
More informationAchieving Meaningful Use with Centricity EMR
GE Healthcare Achieving Meaningful Use with Centricity EMR Are you Ready to Report? GE Healthcare EMR Consulting CHUG Fall Conference October 2010 Achieving Meaningful Use with Centricity EMR The EMR Consulting
More information