Measure Authoring Tool: An Introduction Please dial-in to the number provided below. We will begin shortly. Webinar Call-In Information Tel: (888) | Passcode:

The Measure Authoring Tool: An Introduction Thursday October 27, Floyd Eisenberg, MD, MPH, FACP Chris Millet Senior Vice President, Health IT Senior Project Manager, Health IT National Quality Forum

NQF’s Mission To improve the quality of American healthcare by:  Building consensus on national priorities and goals for performance improvement and working in partnership to achieve them;  Endorsing national consensus standards for measuring and publicly reporting on performance; and  Promoting the attainment of national goals through education and outreach programs. 3

Session Objectives At the end of this session, participants should better understand and be able to describe: Explain what the MAT is, its purpose, importance, and its anticipated impact on performance measurement and quality improvement How the Quality Data Model (QDM) supports the MAT in eMeasure development What information in the MAT can be shared across users Future functionality and the general timeline for new releases. 4

Real-Time Information to Clinician Quality Measure Quality Data Model Measure Authoring Tool eMeasureEHR Develop Performance Measures QDM in the Clinical Realm Electronic Reporting and Sharing Capture Data Provide Care eMeasure: Health Quality Measure Format Inform all Stakeholders 5

What is the Measure Authoring Tool? Web-based application that allows you to create eMeasures without writing XML An eMeasure is a quality measure in a standardized XML file that can be read by both humans and computer systems Target Audience –Measure developers will be primary users. –Quality and health IT stakeholders (e.g., providers, health IT vendors, QIO) will also benefit with better access to, capture of, and reporting on comparable data. 6

How will the Measure Authoring Tool add value? Simplify the process of creating an eMeasure Standardize how eMeasures are expressed, for greater comparability Usable by all measure developers, to support internal quality improvement as well as public reporting programs 7

How QDM Supports the MAT A standard structure and grammar to precisely and accurately represent eMeasures that can be used across clinical IT systems. Purpose –Provides a standard way to clearly and consistently describe clinical concepts in quality measures and for sharing information across EHRs and other clinical systems. Importance –Defines a method to express quality measure requirements compatible with data captured in EHRs and other clinical IT systems. –Only “standard” for eMeasures that exists today. For more information on QDM, visit 8

Basic Release launched September 29, AT)/Measure_Authoring_Tool_(MAT) MAT Releases 9

Create and share eMeasures and their corresponding code lists with other users Create and reuse standard value sets (known as Code Lists in the MAT) and other measure components limiting rework as new measures are developed Use the Quality Data Model (QDM) as the grammar and structure to fully define and express eMeasures in a standard way Export eMeasures in an EHR readable format to enable collection of comparable healthcare quality data Key Features and Functions 10

Checklist for Creating an eMeasure in the MAT List of questions to consider before creating an eMeasure o Do I have existing Code lists that I want to use? o Do I already have Object Identifiers (OIDs) for code lists? o Have I Identified QDM Categories and Datatypes that I will need for this measure? 11

Sample Measure Percentage of patients aged 18 years and older with a diagnosis of CAD who were prescribed a lipid-lowering therapy Initial Patient Population Patients aged 18 years and older before the start of the measurement period. Patients that have a documented diagnosis of coronary artery disease before or simultaneously to encounter date Patients who have at least 2 outpatient or nurse facility encounters during the measurement period DenominatorPatients aged 18 years and older with a diagnosis of coronary artery disease NumeratorPatients who were prescribed lipid-lowering therapy ExclusionsPatients who have documentation of a medical, system or patient reason for not prescribed lipid lowering therapy 12

What data elements do we need? Patients who…What kind of data are we dealing with? What about the data? How do we define this data? …Are diagnosed with Coronary Artery Disease DiagnosisActiveICD-9, ICD-10, SNOMED-CT …Were prescribed Lipid-lowering Therapy MedicationAdministered Order Dispensed Active RxNorm …Have had at least two encounters during the measurement period EncountersCPT …Are at least 18 years old or older Patient CharacteristicLOINC Quality Data Model 13

What’s next? Create Code lists –select QDM Category Apply Code list to Measure –select QDM Data Type Build phrases using QDM Elements –Add QDM attributes Add phrases to Clauses 14

Create Code Lists 15

Select QDM Category 16

Apply Code List to Measure 17

Select QDM Data Type 18

Build Phrase Using QDM Elements 19

Add QDM Attribute to a Phrase 20

Add QDM Attribute to a Phrase 21

Select QDM Attribute 22

Select QDM Attribute 23

Select QDM Attribute 24

Add QDM Attribute to a Phrase 25

Package the eMeasure 26

Export the eMeasure 27

The eMeasure 28

The eMeasure 29

How will the Measure Authoring Tool add value? Impact on performance measurement and quality improvement Standardize how eMeasures are expressed, for greater comparability Usable by all measure developers, to support internal quality improvement as well as public reporting programs 30

Measure Authoring Tool User Guide –Available to access from the Measure Authoring Tool or –Download from Guide for Reading Eligible Providers (EP) and Hospital Measures emID= emID=52706 For MAT technical support, including user access and troubleshooting, contact To submit comments and suggestions for enhancements on the MAT, contact Resources 31

Questions? Thank You 32

Thank You! 33