Building a Digital Quality EcosystemSes s ion 190 , Augus t 12, 2021

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Executive Vice President, Quality Measurement and Research Group, NCQAMichael S. Barr, MD, MBA, MACP

DISCLAIMER: The views and opinions expressed in this presentation are solely those of the author/presenter and do not necessarily represent any policy or position of HIMSS.

Brad Ryan, MDChief Product Officer, NCQA

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Welcome

Chief Product Officer, NCQABrad Ryan, MD

Executive Vice President, Quality Measurement and Research Group, NCQA

Michael S. Barr, MD, MBA, MACP

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Conflict of Interest

Michael S. Barr, MD, MBA, MACP and Brad Ryan, MD have no real or apparent

conflicts of interest to report.

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#HIMSS21

Agenda• The environment

• Measure roadmap

• Use cases for digital measures for value-based payment models

• Problems with current environments and barriers

• Public-private digital quality ecosystem model

• The alignment model as the solution

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Learning Objectives

• Explain public/private digital quality utility and ecosystem need and benefits

• Compare/contrast the ecosystem to the current, more limited quality

enterprise

• Describe challenges and steps needed to move to this ecosystem

• Prepare attendees to meet challenges and thrive in the ecosystem

• Generate excitement and broader participation in collaborating on and

moving to the new ecosystem

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The Environment

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Move to Digital

Focus on Health Equity

Growth in Virtual and Home Care

Challenges in Value-Based Payments

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Quality Content Today – Implementation Burden and Cost

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Inefficiencies

Practice GuidelinesGuideline TextProgram Goals

Measurement

Measure Specifications

Data Collection, Transfer,

AggregationReports, CDS, Care

Gaps, Analytics

Fragmented, narrative,

disconnected

Variation; inconsistent validation

Retrospective; limited by data;

“specs” only

High cost; manual; duplicative effort and

infrastructure

~$20B per year

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Public-Private Digital Quality Ecosystem Model

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Shared Tools, Infrastructure, Approaches

Data Collection, Transfer,

Aggregation

FHIR/QI Core, eCR, CCD

Measurement

dQM, eCQM

Practice Guidelines

CPG, CDS

• Integrated, end-to-end• Multi-plan/program• Efficient

Evidence-Based Medicine

Research

Data Science

Moving From Linear and Fragmented to Connected and Consistent

Standards and Utilities

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Reduced burden and cost

Integrated and consistent across ecosystem

Trusted by all stakeholders

Timely insights for care

Relevant insights at the level of action

Benefits of Digital Quality

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CMS Vision for Future of Digital Quality Measurement

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• dQMs as software for end-to-end measure calculation and reporting

• Data collected from providers, payers, CMS, and other organizations via FHIR-based

Application Programming Interfaces (APIs)

• Pro-competitive and open-source system

• Data quality strengthened and tested

• dQMs audited and manual processes to compare data against original data source

(e.g., the medical record) automated where possible

• Data collection from third-party aggregators (e.g., HIEs and clinical registries)

expanded and policies established for data aggregation, measure calculation and

data integrity

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The Journey from Paper to Digital Quality Measures

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Paper Quality Measures (pQMs)Data from claims, manual chart extractions and patient experience surveys

Electronic Clinical Quality Measures (eCQMs)Data primarily from electronic health records (EHRs)

Digital Quality Measures (dQMs)Data from EHRs, registries, HIEs, claims, devices, surveys, etc.

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Paper to Software: Reduced Cost and BurdenMoving From People and Paper to Software

1.Democratizes access to organizations with less capabilities by enabling centralized code control and “push” updates

2.Improves quality and speed for launches and updates

Computable Specifications

Reduces duplicative interpretation, development, implementation, and maintenance of measures and content

Reduces redundant systems and infrastructure costs

Executable Software

Designed from the start for digital clinical data collection, mapping, and use across levels of measurement and source systems

Reduces burden and enables data quality reporting solutions

Data Collection and Reporting

Enables users to easily adapt, configure, and stratify measures and content for use in their applications

Reduces administrative effort for changes while preserving integrity

Modular Configuration

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The Path to A Better Measurement Ecosystem

Measures that support multiple

use cases

• High interest in use for accountability

• Value-based purchasing

Measures that address priority

populations

• Prevention and population health

• High need, high cost

• Health equity

Measures that align across levels

• Misalignment contributes to burden

• Uncoordinated approach to quality improvement

Measures that encourage

electronic data use

• Care coordination requires data sharing

• Infrastructure improved but could be better

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Digital Measures For Multiple Quality Uses

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By supporting broader use cases, we can enable higher value, lower-burden quality solutions

Adjudicate and manage contractual and incentive-based payments

Payment

Provide trusted visibility and periodic reporting between stakeholders

Reporting

Identify and prioritize improvement opportunities

Optimization

Choose, develop, and deploy measures

Performance Measurement

See performance and understand drivers

Performance Management

Operations and decision support for QI/PI

Performance Improvement

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Supporting Multiple Levels of Accountability Through Alignment

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CollaborationCooperationCoordination

Connecting the dots across the delivery system

A measurement framework to focus reporting on what matters at each level of the delivery system

Managed Care: Meso LevelManage delivery of evidence-based care

State & Federal: Macro LevelSet priorities and direct resources through regulations and financial support

Facility/Provider: Micro LevelProvide evidence-based treatment and services to support whole-person care

Reference: Olin, S., Freed, G., Hudson, S., Applegate, M. (n.d.) Aligning to Improve Pediatric Healthcare Quality. Academic Pediatrics- Under Review.

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Aligning bundles of measures across levels: Example

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Goal is harmonization, not replication

Lauren Niles & Serene Olin (May 2021)https://www.ncqa.org/wp-content/uploads/2021/07/20210701_Behavioral_Health_Quality_Framework_NCQA_White_Paper.pdf

Measure Bundle for Population Goal: Reducing Opioid-Related Mortality

Federal &State

Outcome: Opioid-related death

Process: Follow-up post emergency department for OUD

Structure: Prior authorization for MOUD, reimbursement for telehealth

Managed Care

Facility/Provider

Outcome: Repeat opioid overdose/poisoning events

Process: Treatment continuity, care coordination for high-risk members

Structure: BH network adequacy, coverage of non-opioid pain therapy

Member experience

Outcome: Treatment dropout/show rates

Process: Access to MOUD, treatment engagement, preventive and chronic care management for patients with OUD, care coordination

Structure: Waivered providers, telehealth infrastructure, care team communication infrastructure

Patient experience

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This evolution is necessary but not sufficient

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The technology is the “easy” part

Incentives drive adoption

Quality is a good business case- Value-based payments and incentives- Need for stakeholder alignment- Data already flowing

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Questions

BUILDING A DIGITAL QUALITY ECOSYSTEM

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Thank you!Michael S Barr, MD, MBA, MACP, FRCPExecutive Vice President, Quality Measurement & Research GroupNational Committee for Quality AssuranceEmail: barr@ncqa.orgTwitter: @barrmsLinkedIn: www.linkedin.com/in/michaelsbarr

Brad Ryan, MDChief Product OfficerNational Committee for Quality AssuranceEmail: bryan@ncqa.orgLinkedIn: www.linkedin.com/in/bradryanmd/

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Acronyms and Terms Used

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Those you might be less familiar with

API An application programming interface (API) is a computing interface that defines interactions between multiple software or mixed hardware-software intermediaries.

ASP Average Selling Price, the price at which a certain class of good or service is typically sold.

CCD Continuity of Care Document, based on the HL7 CDA architecture is a "document standard“ for transferring clinical data between organizations.

CDS Clinical Decision Support (Rules, etc.)

CPG, CPG Hub

Clinical Practice Guideline. CPG Hub refers to a repository or database of CPGs.

DAV Data Aggregator Validation, a new NCQA product validating HIEs and related entities.

DMC Digital Measurement Community

DMR Digital Measurement Roadmap, NCQA’s plan to move to digitized measure specifications.

dQM Digital Quality Measure

eCQM Electronic Clinical Quality Measure

ECPG Electronic Clinical Practice Guideline

eCR electronic Case Report

ETL (Data ETL) Extract/Transform/Load. This is a process to extract data from the source systems, enforce data quality and consistency standards, conform data so that separate sources can be used together, and deliver data in a presentation-ready format so that application developers can build applications and end users can make decisions.

FHIR (FHIR/QI Core)

The HL7® FHIR® (Fast Healthcare Interoperability Resources 1 ) standard defines how healthcare information can be exchanged between different computer systems regardless of how it is stored in those systems. QICore defines a set of FHIR profiles with extensions and bindings needed to create interoperable, quality-focused applications.

IMAS Internal Measure Authoring System

MaaS Measures-as-a-Service, a proposed NCQA product

NLP Natural Language Processing, but also refers to a pilot NCQA program for validating NLP in the context of HEDIS measurement

Reporting Solutions A proposed NCQA product

VBC Value-based care

VBP Value-based payment

VS Value Set, a list of codes and corresponding terms, from standard clinical vocabularies (such as SNOMED CT®, RxNorm, LOINC® and others), often representing a clinical concept such as “Heart Failure” or “Primary Care Visit”