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href="https://www.ncqa.org/digital-content-services-early-adopter-program/" class="btn btn--red">Apply Now</a></li></ul> <a href="#" class="nav__btn"> <span class="bar"></span> <span class="bar"></span> <span class="bar"></span> </a> <a href="https://www.ncqa.org/digital-content-services-early-adopter-program/" class="btn btn--red">Apply Now</a></div></div></nav><div class="container-1200"><div class="dcs-header relative"> <img src="/wp-content/uploads/DCS-Web-Page-Banner-v2.jpg" /><div class="dsc-header-content fade-from-left animate"><h1 class="header-title">Digital Content Services</h1><div class="header-tagline">Become a Digital Quality Trailblazer</div></div></div></div><div class="shell" style="margin: 0 auto 4rem auto;"><h2 class="article-header">Why Digital Quality?</h2><p>Quality workflows have become fragmented and burdensome for stakeholders across the health care landscape. Emerging standards and regulations are enabling a digital transformation that will reduce cost and burden, create better alignment, and result more relevant measures – and ultimately, better care and outcomes.</p><h2 class="article-header">How to Get Started?</h2><p>The industry is transitioning from traditional methods of measuring and reporting quality. The digitalization of quality measures is underway. Organizations can begin their digital transition by electing to receive HEDIS quality content from NCQA digitally. This digital content is delivered as a containerized software package, and is deployed within the organization’s cloud environment.</p></div><div class="callout" style="margin-bottom: 6rem;"><div class="shell shell--alt"><div class="callout__inner"><div class="callout__aside"><div class="callout__figure" style=""> <img src="https://www.ncqa.org/wp-content/themes/ncqa-org/css/education-2021/images/dots@2x.png" alt="" width="180"></div><div class="callout__image"><div class="callout__image-background" style="background-image: url(https://www.ncqa.org/wp-content/uploads/DCS-Content-Image.webp)"></div></div></div><div class="callout__content"><h2>Ready to Get Started On Your Digital Quality Transition?</h2><div class="callout__actions"> <a href="https://www.ncqa.org/digital-content-services-early-adopter-program/" class="btn callout__btn btn--blue">Complete an Application Today →</a></div></div></div></div></div><div class="wrapper mb-2"><div class="container-1200"><h2 class="text-center" style="font-size: 36px; text-transform: uppercase; color: #333;">Enjoy the Benefits of Digital Quality</h2><div class="row"><div class="card card-circle fade-from-bottom animate"><h5 class="card-title">Reduce Cost and Burden</h5><div class="card-icon"><img src="https://www.ncqa.org/wp-content/uploads/reduce-cost-blue.png" /></div><div class="card-body"><p class="card-text">Updated, configurable FHIR CQL measures and infrastructure mean less overhead on building and maintenance.</p></div></div><div class="card card-circle fade-from-bottom animate"><h5 class="card-title">Support Expanded Use Cases</h5><div class="card-icon"><img src="https://www.ncqa.org/wp-content/uploads/expanded-cases-blue.png" /></div><div class="card-body"><p class="card-text">Integrate measures for a variety of uses, including care gap closures, clinical decision support, and analytics.</p></div></div><div class="card card-circle fade-from-bottom animate"><h5 class="card-title">Accelerate Digital Transformation</h5><div class="card-icon"><img src="https://www.ncqa.org/wp-content/uploads/accelerate-digital-blue.png" /></div><div class="card-body"><p class="card-text">Be among the first to use NCQA’s measures in existing workflows-or use them to help your digital transformation efforts.</p></div></div></div></div></div><section class="section section--overview relative"><div class="shell my-2"><h2 class="article-header">ADVANCE THE DIGITAL QUALITY ECOSYSTEM OF THE FUTURE</h2></header><div class="section__body"><ul class="list-cards-overview"><li><div id="modal-trust" class="card card--overview modalOpenBtn fade-from-bottom animate"><h4>EMBRACE INNOVATION</h4><p>Support quality improvement initiatives of your clients, partners, and yourselves to help drive better patient outcomes.</p></div></li><li><div id="modal-showcase" class="card card--overview modalOpenBtn fade-from-bottom animate"><h4>MAKE YOUR MARK</h4><p>Influence NCQA product development to maximize long-term value for your program, health plan/system and/or health plan clients.</p></div></li><li><div id="modal-support" class="card card--overview modalOpenBtn fade-from-bottom animate"><h4>TAKE INITIATIVE</h4><p>Help shape the design of digital solutions that reduce the burden of quality measurement through alignment across all levels of accountability in the health care system.</p></div></li><li><div id="modal-serve" class="card card--overview modalOpenBtn fade-from-bottom animate"><h4>COMPREHENSIVE SUPPORT</h4><p>Gain access to support and training as you embark on your digital quality measurement journey. NCQA is dedicated to assisting organizations in leveraging the full potential of Digital Content Services. Our comprehensive support helps ensure a seamless transition, and training programs empower your team to maximize the benefits of configurable, FHIR CQL digital HEDIS measures.</p></div></li></ul></div> <img src="https://www.ncqa.org/wp-content/uploads/DCS-blocks.png" style="position: absolute; bottom: -22px; opacity: .3;" alt=""></section><section class="section" style="margin: 4rem auto;"><div class="shell"><div class="flex flex-wrap gap-1 justify-center items-end"> <img src="/wp-content/uploads/FHIR-Logo.webp" alt="FHIR Logo" style="width: 30%; max-width: 150px; height: auto;"><p style="width: 70%; font-size: 20px;">Organizations that are FHIR® enabled and work with a cloud provider are eligible for Digital Content Services. 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}, 2000); setTimeout(function() { document.querySelector('.mfp-wrap').setAttribute('role', 'dialog'); document.querySelector('.mfp-wrap').setAttribute('aria-modal', 'true'); document.querySelector('.mfp-img').setAttribute('alt', ''); }, 3000);</script><script type="text/javascript" id="localized-js-extra">var dqt = [{"type":"terms","title":"Data Aggregator Validation","content":"DAV"},{"type":"terms","title":"Bulk FHIR","content":""},{"type":"terms","title":"Test Resource","content":""},{"type":"linked","title":"NCQA’s Digital Quality Transition Update","content":"","link":"https:\/\/www.ncqa.org\/videos\/ncqas-digital-quality-transition-update\/"},{"type":"linked","title":"Nine Insights Into Interoperability","content":"","link":"https:\/\/www.ncqa.org\/podcast\/nine-insights-into-interoperability\/"},{"type":"linked","title":"Advancing Digital Quality: Addressing Data Challenges to Improve Performance","content":"","link":"https:\/\/www.ncqa.org\/blog\/advancing-digital-quality-addressing-data-challenges-to-improve-performance\/"},{"type":"linked","title":"Introducing the First Cohort of the Bulk FHIR Quality Coalition","content":"","link":"https:\/\/www.ncqa.org\/blog\/introducing-the-first-cohort-of-the-bulk-fhir-quality-coalition\/"},{"type":"linked","title":"NCQA Shares New Guidance for Digital HEDIS Reporting","content":"","link":"https:\/\/www.ncqa.org\/blog\/ncqa-shares-new-guidance-for-digital-hedis-reporting\/"},{"type":"linked","title":"NCQA\u2019s Proposed Timeline for Retiring and Replacing HEDIS Hybrid Measures","content":"","link":"https:\/\/www.ncqa.org\/blog\/ncqas-proposed-timeline-for-retiring-and-replacing-hedis-hybrid-measures\/"},{"type":"linked","title":"Lessons Learned From Leading Health Plans Implementing Digital Quality","content":"","link":"https:\/\/www.ncqa.org\/blog\/lessons-learned-from-leading-health-plans-implementing-digital-quality\/"},{"type":"linked","title":"NCQA Fireside Chat: Charting the Future of Health Care Interoperability","content":"","link":"https:\/\/www.ncqa.org\/blog\/ncqa-fireside-chat-charting-the-future-of-health-care-interoperability\/"},{"type":"linked","title":"NCQA Launches Coalition to Assess Bulk FHIR Data Quality","content":"","link":"https:\/\/www.ncqa.org\/blog\/ncqa-launches-coalition-to-assess-bulk-fhir-data-quality\/"},{"type":"linked","title":"How Digital Quality Can Improve the Member Experience","content":"","link":"https:\/\/www.ncqa.org\/blog\/how-digital-quality-can-improve-the-member-experience\/"},{"type":"resource","title":"Preparing Data for Digital Measurement","content":"","link":"https:\/\/www.ncqa.org\/resources\/preparing-data-for-digital-measurement\/"},{"type":"external","title":"When Exchanging (and Trusting) Data Grows Up","content":"","link":"https:\/\/www.ncqa.org\/podcast\/when-exchanging-and-trusting-data-grows-up\/"},{"type":"external","title":"The Digital Transformation-Data Quality Puzzle With NCQA’s Brad Ryan","content":"","link":"https:\/\/www.healthaffairs.org\/do\/10.1377\/hp20240926.109580\/full\/"},{"type":"external","title":"The New Rules of Data Sharing","content":"","link":"https:\/\/www.ncqa.org\/podcast\/the-new-rules-of-data-sharing\/"},{"type":"resource","title":"How Digital Measures Execute with Clinical Quality Language","content":"","link":"https:\/\/www.ncqa.org\/resources\/how-digital-measures-execute-with-clinical-quality-language\/"},{"type":"linked","title":"Updated TEFCA SOPs for Health Care Operations and NCQA","content":"","link":"https:\/\/www.ncqa.org\/blog\/updated-tefca-sops-for-health-care-operations\/"},{"type":"linked","title":"Top Three Challenges in the Transition to Digital Quality","content":"","link":"https:\/\/www.ncqa.org\/blog\/the-top-three-challenges-in-transitioning-to-digital-quality\/"},{"type":"external","title":"The Move to Digital Quality Measurement","content":"","link":"https:\/\/www.ncqa.org\/podcast\/the-move-to-digital-quality-measurement\/"},{"type":"resource","title":"Intro to CQL","content":"<h2>Understanding CQL and Its Role in Quality Measurement<\/h2>\r\n<h3>What is Clinical Quality Language (CQL)?<\/h3>\r\nThe CQL specification is an open-source standard published by HL7, designed to describe clinical rules and quality measures. It is a way to communicate complex healthcare information in a clear and consistent manner, and in a way that both humans and machines can read and understand. With CQL, complex clinical scenarios, such as patient eligibility, conditions, and interventions, can be described with a level of detail and flexibility that supports a variety of healthcare applications. This language plays a critical role in facilitating interoperability among different health IT systems and is commonly used for defining clinical quality measures in electronic form, supporting data exchange, and enabling automated decision support within healthcare systems.\r\n<h3>The Role of CQL in Clinical Data and Quality Measures<\/h3>\r\nCQL plays a critical role in helping healthcare systems maintain high-quality care by providing a common language to express clinical concepts, support interoperability, and facilitate quality measurement. It also serves as the foundation for creating automated processes that assess healthcare quality and guide clinical decisions.\r\n\r\n[GRAPHIC 1]\r\n<h3>How Does CQL Align with NCQA's Quality Standards and Goals?<\/h3>\r\nNCQA is dedicated to improving the quality of healthcare through measurement, transparency, and accountability. NCQA's primary focus is on promoting high standards in healthcare delivery, emphasizing evidence-based practices, patient-centered care, and continuous quality improvement.\r\n\r\nCQL aligns with these standards and goals in several ways:\r\n<ul>\r\n \t<li><strong>Promoting High-Quality Care:<\/strong> CQL enables NCQA to define and measure clinical quality in a way that supports evidence-based practices and consistent healthcare delivery. By adopting CQL, NCQA can ensure that its quality standards are applied uniformly across different healthcare organizations.<\/li>\r\n \t<li><strong>Enhancing Patient-Centered Care:<\/strong> The human-readable nature of CQL allows for a clearer understanding of quality measures, facilitating communication between providers and patients. This alignment with patient-centered care encourages transparency and shared decision-making in clinical settings.<\/li>\r\n \t<li><strong>Supporting Continuous Quality Improvement:<\/strong> CQL's flexibility and expressiveness allow NCQA to update and refine quality measures as healthcare best practices evolve. This feature supports NCQA's goal of fostering continuous quality improvement in healthcare.<\/li>\r\n \t<li><strong>Encouraging Accountability and Transparency:<\/strong> CQL's standardized approach to defining quality measures enhances accountability by ensuring that quality standards are clear and consistently applied. This transparency aligns with NCQA's focus on promoting accountability within healthcare organizations.<\/li>\r\n \t<li><strong>Reducing Barriers to Compliance:<\/strong> By streamlining the process of implementing and evaluating quality measures, CQL helps healthcare organizations comply with NCQA's standards. This simplification aligns with NCQA's goal of reducing barriers to achieving high-quality care.<\/li>\r\n<\/ul>\r\n<h3>Drivers of NCQA\u2019s Adoption of CQL<\/h3>\r\nNCQA's adoption of CQL is driven by the need for standardization, interoperability, and efficiency in healthcare quality measurement. CQL's advantages in these areas, particularly in the context of HEDIS digital measures, support NCQA's overarching quality standards and goals, leading to improved healthcare outcomes and enhanced accountability.\r\n\r\nDrivers include:\r\n<ul>\r\n \t<li><strong>Interoperability and Standardization:<\/strong> Designed to be interoperable across different healthcare platforms, NCQA recognizes that adopting CQL will facilitate more consistent and standardized quality measurements across diverse healthcare environments, addressing one of the key challenges in healthcare quality assessment.<\/li>\r\n \t<li><strong>Human-Readable Format:<\/strong> Unlike traditional programming languages, CQL is designed to be more accessible and human-readable. This feature allows clinicians, quality measure developers and other stakeholders to understand and work with the logic underlying clinical quality measures without extensive technical expertise.<\/li>\r\n \t<li><strong>Improved Efficiency and Automation:<\/strong> NCQA believes that CQL's standardized approach will lead to greater automation in quality measurement processes, reducing manual data collection and interpretation. This efficiency aligns with the organization\u2019s focus on promoting effective, streamlined quality assessment methods.<\/li>\r\n<\/ul>\r\nNCQA\u2019s strategy is aligned with national and global initiatives that are driving the adoption of well-structured and comprehensive data systems. Organizations like the Office of the National Coordinator for Health Information Technology (ONC) are mandating the use of Fast Healthcare Interoperability Resources (<a href=\"https:\/\/www.healthit.gov\/topic\/interoperability\/policy\/trusted-exchange-framework-and-common-agreement-tefca\">FHIR<\/a>) to improve interoperability in healthcare systems. Additionally, the Centers for Medicare & Medicaid Services (CMS) are advocating for the adoption of electronic clinical quality measures (eCQMs) within the <a href=\"https:\/\/www.cms.gov\/files\/document\/2022-ecqm-reporting-requirements.pdf\">Medicare Promoting Interoperability Program<\/a>, leading to a continued emphasis on CQL and related requirements.\r\n<h3>Advantages of Using CQL for HEDIS Digital Measures<\/h3>\r\nDeveloped and maintained by NCQA, HEDIS (Healthcare Effectiveness Data and Information Set) is a comprehensive set of standardized performance measures used to assess the quality of care and services provided by health plans and healthcare organizations.\r\n\r\nHEDIS digital measures refer to the digitalization of these performance measures, allowing them to be used in electronic health records (EHRs) and other digital health systems. These digital measures are designed to streamline data collection, reduce manual processes, and improve the accuracy and consistency of healthcare quality assessments. By using digital measures, healthcare organizations can more easily report their performance, enabling better benchmarking and comparisons across different systems and regions.\r\n\r\nThrough this process, HEDIS digital measures play a crucial role in promoting high-quality, patient-centered care by providing reliable, standardized, and efficient tools for assessing and improving healthcare performance.\r\n\r\nThe adoption of CQL offers several advantages for HEDIS digital measures:\r\n<ul>\r\n \t<li><strong>Consistency Across Measures:<\/strong> CQL allows for a consistent approach to defining clinical quality measures, ensuring that HEDIS measures are uniformly interpreted and implemented. This consistency is crucial for reliable healthcare quality assessment.<\/li>\r\n \t<li><strong>Facilitating Automation:<\/strong> By using CQL, healthcare organizations can automate the extraction and analysis of administrative (claims) and clinical data for HEDIS measures. This automation not only speeds up the process but also reduces the risk of errors associated with manual data handling.<\/li>\r\n \t<li><strong>Scalability and Adaptability:<\/strong> CQL's flexible and expressive language allows for complex clinical logic, making it easier to update or create new HEDIS measures as healthcare needs evolve. This adaptability ensures that HEDIS remains relevant in a rapidly changing healthcare landscape.<\/li>\r\n \t<li><strong>Enhanced Interoperability:<\/strong> CQL's design is aimed at promoting interoperability among various health IT systems. This feature helps ensure that HEDIS digital measures can be implemented across different platforms, improving data sharing and collaboration between healthcare providers.<\/li>\r\n \t<li><strong>Transparency and Accessibility:<\/strong> Since CQL is human-readable, it enhances the transparency of HEDIS measures. Clinicians and other stakeholders can more easily understand the criteria behind quality assessments, promoting a clearer understanding of quality standards.<\/li>\r\n<\/ul>\r\n<h3>Examples of CQL in Action with HEDIS Measures<\/h3>\r\n<strong><em>Breast Cancer Screening:<\/em><\/strong>\r\n\r\nThis HEDIS measure evaluates the percentage of women aged 50-74 who have had a mammogram within a specific timeframe. A CQL engine would retrieve data on patient demographics, mammogram records, and the relevant time range. It would then apply the clinical logic to determine whether each patient meets the screening criteria.\r\n\r\n<strong><em>Diabetes Care - HbA1c Testing:<\/em><\/strong>\r\n\r\nThis measure assesses whether patients with diabetes have received an HbA1c test within a certain period. A CQL engine would extract data on patients diagnosed with diabetes and check for records of HbA1c tests. It would then calculate the percentage of patients who meet the criteria for the measure.\r\n<h2>About CQL Engines and How They Work<\/h2>\r\n<h3>What is a CQL Engine?<\/h3>\r\nA CQL engine is an implementation of the CQL specification that has the capability to execute clinical quality logic. This logic may initially be authored as human-readable CQL but needs to be rendered as machine-readable ELM before execution. The CQL engine processes CQL expressions to evaluate clinical data and perform automated healthcare-related tasks. Clinical and administrative data is input into the CQL engine, which uses the instructions in the CQL script to compute quality measures, apply clinical decision rules and derive outcomes.\r\n<h3>How Does the CQL Engine Calculate Measure Outcomes?<\/h3>\r\nThe process of calculating measure outcomes with a Clinical Quality Language (CQL) engine involves several steps, from interpreting the measure's criteria to deriving the final result.\r\n\r\nHere is a breakdown of the process:\r\n\r\n[GRAPHIC 2]\r\n<h3>Typical Use Cases for CQL Engines in Healthcare<\/h3>\r\nCQL engines have various use cases in healthcare, particularly in the context of quality measurement and clinical decision support. Some examples are:\r\n<ul>\r\n \t<li><strong>Quality Measurement:<\/strong> CQL engines can process quality measures, such as those found in HEDIS, to assess healthcare providers' and plans' performance against standardized metrics. For example, CQL can help determine if a patient meets specific quality measures, such as whether they received recommended screenings or vaccinations within a certain timeframe.<\/li>\r\n \t<li><strong>Clinical Decision Support:<\/strong> CQL can assist healthcare providers in making clinical decisions by analyzing patient data to identify potential risks, such as flagging drug interactions or alerting providers to potential gaps in care based on clinical guidelines.<\/li>\r\n \t<li><strong>Population Health Management:<\/strong> CQL can be used to analyze population health data to identify trends, risk factors and opportunities for intervention, such as identifying at-risk populations for targeted outreach or preventive care programs.<\/li>\r\n \t<li><strong>Risk Stratification:<\/strong> CQL can help stratify patients based on their risk levels for certain conditions or adverse outcomes, enabling providers to prioritize resources and interventions for those most in need.<\/li>\r\n \t<li><strong>Treatment Pathway Adherence:<\/strong> CQL can assess whether patients are adhering to recommended treatment pathways or protocols, such as determining if patients with chronic conditions are receiving appropriate medications and follow-up care.<\/li>\r\n \t<li>Research and Analytics: CQL engines can be used to analyze large datasets to extract insights related to patient outcomes, treatment effectiveness and other healthcare research topics.<\/li>\r\n \t<li><strong>Regulatory Compliance:<\/strong> CQL engines can help healthcare organizations demonstrate compliance with regulatory requirements by providing a standardized way to evaluate and report clinical data.<\/li>\r\n<\/ul>\r\n<h3>What is the Difference Between a Measure Engine and a CQL Engine?<\/h3>\r\nA measure engine and a Clinical Quality Language (CQL) engine serve similar functions in the context of healthcare quality assessment, but they differ in terms of their specific roles, flexibility, and underlying technology. Measure engines are tailored for specific predefined measures, while CQL engines offer greater adaptability and can be used in a broader range of healthcare applications.\r\n\r\nThe table below provides a comparison between the two:\r\n<div class=\"ncqa-table dqt-style\">\r\n<table>\r\n<thead>\r\n<tr>\r\n<th><\/th>\r\n<th>MEASURE ENGINE<\/th>\r\n<th>CQL ENGINE<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td><strong>OVERVIEW<\/strong><\/td>\r\n<td>A measure engine is a software system designed to calculate healthcare quality measures. It typically uses predefined algorithms or scripts to evaluate clinical data and generate outcomes based on specific quality metrics. Measure engines are often closely tied to specific sets of quality measures and may have limited flexibility in adapting to new or modified measures.<\/td>\r\n<td>A CQL engine is a software system specifically designed to interpret and execute CQL scripts, which define clinical logic and quality criteria. It has a broader scope, as it can process complex clinical logic and is not limited to predefined quality measures. CQL engines are more flexible and can be used for a wide range of applications beyond quality measurement, such as clinical decision support.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>FLEXIBILITY<\/strong><\/td>\r\n<td>Measure engines are generally tied to specific quality measures and may require significant reconfiguration or updates to support new measures.<\/td>\r\n<td>CQL engines are inherently more flexible because they can interpret and execute custom CQL scripts.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>SCOPE<\/strong><\/td>\r\n<td>Measure engines are primarily focused on calculating predefined quality measures.<\/td>\r\n<td>CQL engines can be used for various applications, including clinical decision support, quality measurement and research.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>PROGRAMMING LANGUAGE<\/strong><\/td>\r\n<td>Measure engines may use custom scripts, proprietary logic or hardcoded algorithms.<\/td>\r\n<td>CQL engines rely on the Clinical Quality Language, which is human-readable and standardized by Health Level Seven International (HL7).<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>TYPICAL USE CASE<\/strong><\/td>\r\n<td>Measure engines are commonly used in healthcare organizations that need to calculate specific quality measures, such as HEDIS metrics. They are well-suited for environments with a defined set of measures where flexibility is not a primary concern.<\/td>\r\n<td>CQL engines are ideal for applications requiring flexibility and customization. They are used in scenarios where complex clinical logic needs to be applied, such as clinical decision support, research and custom quality measure development. CQL engines are also suitable for organizations that need to support evolving quality measures or integrate with multiple data sources.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>INTEGRATION<\/strong><\/td>\r\n<td colspan=\"2\">Both types of engines integrate with clinical data sources, such as electronic health records (EHRs), to retrieve patient information and perform evaluations.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>CALCULATION<\/strong><\/td>\r\n<td colspan=\"2\">Both engines calculate outcomes based on defined clinical criteria, whether derived from a predefined quality measure or a custom CQL script.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>AUTOMATION<\/strong><\/td>\r\n<td colspan=\"2\">Both measure engines and CQL engines aim to automate quality assessment and clinical logic processing, providing efficient and consistent results.<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\n<h3>Steps for Organizational Preparation for CQL Engine Implementation<\/h3>\r\nImplementing CQL represents a significant change for any organization, impacting workflows, processes, and systems. To navigate this transition smoothly and minimize disruptions to daily operations, it is essential to perform a comprehensive assessment, plan strategically and develop a robust change management plan.\r\n\r\nA few steps in this process are:\r\n<ul>\r\n \t<li><strong>Assess Current Systems:<\/strong> Evaluate your existing systems and workflows to identify areas where CQL implementation would be beneficial.<\/li>\r\n \t<li><strong>Training and Education:<\/strong> Provide training sessions for relevant staff to familiarize them with CQL concepts, syntax and implementation procedures.<\/li>\r\n \t<li><strong>Data Standardization:<\/strong> Ensure that your data is standardized and structured in a way that aligns with CQL requirements to facilitate smooth integration.<\/li>\r\n \t<li><strong>Testing Environment:<\/strong> Set up a testing environment to experiment with CQL queries and ensure they function as expected before deploying them in a production environment.<\/li>\r\n \t<li><strong>Change Management:<\/strong> Implement a change management plan to guide the transition to CQL and minimize disruptions to daily operations.<\/li>\r\n \t<li><strong>Documentation and Communication:<\/strong> Document all steps taken during the preparation phase and communicate them clearly to relevant stakeholders.<\/li>\r\n<\/ul>\r\n<h3>Teams and Expertise Required for Transition<\/h3>\r\nBy involving key stakeholders, ensuring the necessary expertise and providing access to training and certification resources, organizations can enhance the success of their CQL transition and maximize the benefits of using CQL for data querying and analysis.\r\n\r\nIdentifying Key Stakeholders and Teams for CQL Transition:\r\n<ul>\r\n \t<li><strong>Executive Sponsorship:<\/strong> Ensure that there is executive sponsorship from leadership to drive the CQL transition and allocate necessary resources.<\/li>\r\n \t<li><strong>IT Department:<\/strong> Involve IT professionals who are responsible for managing and maintaining the organization's systems, databases and software applications.<\/li>\r\n \t<li><strong>Data Management Team:<\/strong> Include members of the data management team who have expertise in data governance, data modeling and data architecture.<\/li>\r\n \t<li><strong>Analytics Team:<\/strong> Engage analysts and data scientists who will be utilizing CQL for querying and analyzing data to derive insights and make data-driven decisions.<\/li>\r\n \t<li><strong>Clinical and Subject Matter Experts:<\/strong> If applicable, involve clinicians or subject matter experts who can provide domain-specific knowledge and ensure that CQL queries align with clinical or operational requirements.<\/li>\r\n \t<li><strong>Quality Assurance Team:<\/strong> Incorporate members of the quality assurance team who can test CQL queries and ensure their accuracy and reliability.<\/li>\r\n<\/ul>\r\nExpertise Needed for Successful Implementation:\r\n<ul>\r\n \t<li><strong>CQL Proficiency:<\/strong> Individuals involved in CQL implementation should have a strong understanding of CQL syntax, semantics and best practices.<\/li>\r\n \t<li><strong>Database Management Skills:<\/strong> Proficiency in database management systems (DBMS) and SQL is essential for manipulating and querying data effectively.<\/li>\r\n \t<li><strong>Programming Skills:<\/strong> Basic programming skills, such as knowledge of scripting languages like Python or R, may be beneficial for automating tasks or integrating CQL with other systems.<\/li>\r\n \t<li><strong>Data Modeling:<\/strong> Expertise in data modeling concepts and techniques is important for designing databases and structuring data in a way that facilitates efficient querying with CQL.<\/li>\r\n \t<li><strong>Domain Knowledge:<\/strong> Depending on the organization's industry or sector, domain-specific knowledge may be required to understand the context and requirements for CQL queries.<\/li>\r\n<\/ul>\r\n<h2>Community Support and Vendor Selection<\/h2>\r\n<strong>Community Support for CQL Engines<\/strong>\r\n\r\nThe Clinical Quality Language (CQL) community encompasses a wide range of stakeholders, including healthcare professionals, developers, standards organizations and health IT companies. This community is focused on supporting the use of CQL for healthcare quality measurement, clinical decision support and other related applications. The community provides resources, knowledge sharing and collaborative opportunities to advance the adoption and implementation of CQL.\r\n\r\nSupport resources for CQL engines within this community typically include:\r\n<ul>\r\n \t<li><strong>Documentation and Guides:<\/strong> Comprehensive documentation, including standards, specifications and user guides, is available to help users understand and implement CQL in various contexts.<\/li>\r\n \t<li><strong>Educational Resources:<\/strong> The community offers webinars, training sessions and online courses to educate healthcare professionals and developers about CQL and its applications.<\/li>\r\n \t<li><strong>Technical Support:<\/strong> Organizations involved in developing CQL engines, whether open-source or proprietary, often provide technical support to assist with implementation and troubleshooting.<\/li>\r\n<\/ul>\r\nFor organizations interested in building, maintaining or enhancing CQL engines that support quality use cases, NCQA has established the <a href=\"https:\/\/www.ncqa.org\/digital-quality-implementers-community\/\">Digital Quality Implementers Community<\/a> to create consistency and confidence in the implementation of CQL standard engines.\r\n<h3>Do You Need to Switch Vendors?<\/h3>\r\nEvaluating the need to switch vendors is a significant decision for any organization. If your current vendor does not support CQL or lacks the necessary features for CQL implementation, it may be necessary to switch to a vendor that does. Check out the following sections for questions that you should be asking your current vendors or considerations to keep in mind when selecting a new CQL engine technology partner.\r\n<h3>Questions for Existing Vendors<\/h3>\r\nReach out to your current vendor's support or sales team directly to inquire about CQL support. Some questions that will help you assess their readiness to accommodate CQL implementations are as follows:\r\n<ul>\r\n \t<li><strong>CQL Support:<\/strong> Inquire about the level of support they offer for CQL implementation, including any dedicated resources or assistance available.<\/li>\r\n \t<li><strong>Compatibility:<\/strong> Ask if their current software versions are compatible with CQL engines.<\/li>\r\n \t<li><strong>Integration:<\/strong> Discuss how seamless the integration process will be between their products and CQL engines.<\/li>\r\n \t<li><strong>Timeline:<\/strong> Determine the estimated timeline for implementing CQL with their products and any dependencies involved.<\/li>\r\n \t<li><strong>Case Studies:<\/strong> Explore whether there are any case studies or examples of other organizations successfully implementing CQL with the same vendor's products.<\/li>\r\n \t<li><strong>Updates and Upgrades:<\/strong> Seek clarification on how future updates or upgrades from the vendor might impact CQL implementation and compatibility.<\/li>\r\n<\/ul>\r\n<h3>New Vendor Selection: Choosing the Right CQL Engine Technology Partner<\/h3>\r\nListed below are some criteria that will help organizations make an informed decision when selecting a CQL engine technology partner that aligns with their needs and goals.\r\n<ul>\r\n \t<li style=\"list-style-type: none;\">\r\n<ul>\r\n \t<li><strong>Experience:<\/strong> Look for vendors with extensive experience in developing and implementing CQL engines, preferably with a proven track record of successful implementations.<\/li>\r\n \t<li><strong>Vendor Reputation and References:<\/strong> Research the vendor's reputation in the industry and their track record with previous clients. Ask for references or case studies from the vendor to assess their capabilities and expertise in CQL technology.<\/li>\r\n \t<li><strong>Demonstrations and Prototypes:<\/strong> Request demonstrations or prototypes of the CQL engine to evaluate its features, performance and usability firsthand.<\/li>\r\n \t<li><strong>Compatibility and Ease of Integration:<\/strong> Ensure that the CQL engine is compatible with your existing systems and infrastructure, as well as with industry standards.<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\n<ul>\r\n \t<li><strong>Community and Support:<\/strong> Evaluate the size and activity level of the CQL engine's community, as well as the availability of documentation, tutorials and support resources.<\/li>\r\n<\/ul>","link":"https:\/\/www.ncqa.org\/resources\/intro-to-cql\/"},{"type":"external","title":"Joint Statement on Digital Quality Measurement Interoperability","content":"","link":"https:\/\/www.ncqa.org\/news\/joint-statement-on-digital-quality-measurement-interoperability\/"},{"type":"external","title":"NCQA Data Aggregator Validation Expands to Include FHIR Exchange","content":"","link":"https:\/\/www.ncqa.org\/news\/ncqa-data-aggregator-validation-expands-to-include-fhir-exchange\/"},{"type":"external","title":"The Future of HEDIS: Digital Measurement Midyear Review Webinar","content":"","link":"https:\/\/www.ncqa.org\/videos\/the-future-of-hedis-digital-measurement-midyear-review-webinar\/"},{"type":"external","title":"Digital Transition Update From The Health Innovation Summit","content":"","link":"https:\/\/www.ncqa.org\/wp-content\/uploads\/EngagingWithDigitalCommunity.pdf"},{"type":"faq","title":"Who pays for quality measurement?","content":"Health care organizations\u2014from individual family physicians to university health systems and health plans\u2014all shoulder the costs of quality measure reporting. A large health system spent over $5.6 million on quality reporting in 2018, with over $600,000 paid to vendors to report and share quality data, and including more than 100,000 hours of health care staff time."},{"type":"faq","title":"What does quality measurement cost today?","content":"Quality measurement and reporting requires significant staff effort and expense because of the manual processes involved in the collection, exchange, management and analysis of health care data. A report found that clinicians bear a significant proportion of the cost of quality measurement reporting\u2014an estimated $15.4 billion\u2014including for chart abstraction, data validation and measure reporting. Other industries have leveraged modern information technology to reduce these costs of data management."},{"type":"faq","title":"What is quality measurement?","content":"Quality measurement is the application of standardized quality measures to evaluate the health outcomes and experiences of care provided to individuals and populations, as well as the structures and processes used by organizations and clinicians to deliver care. The results of quality measurement guide quality improvement and can be used in accountability and value-based purchasing programs."},{"type":"faq","title":"Does CMS support the move to dQMs?","content":"Yes. After initially announcing that all quality measures would be converted to digital by 2025, CMS has moved this date to 2030. CMS recognizes that transitioning to dQMs will produce better insights about the health of populations and will increase the timeliness and relevance of information available to a \u201clearning health system.\u201d Together with ONC, CMS continues the push to standardize and harmonize health data through USCDI and USCDI+. With these data categories, FHIR (a uniform health data language) and APIs\u2014the backbone of today\u2019s internet economy\u2014lay the groundwork for efficient exchange of health data."},{"type":"faq","title":"How do dQMs promote health system alignment and coordination?","content":"Health plans are implementing \u201cgold carding,\u201d which lessens or removes some administrative work related to prior authorization. Eligibility for gold carding can depend on a provider\u2019s quality ratings, which incentivizes high-quality care. According to an AHIP 2022 survey, 58% of plans use gold carding for medical services\u2014a more than 80% increase from 2019. dQMs can help providers qualify for gold carding with plans."},{"type":"faq","title":"Why should quality measures be digital?","content":"Most quality measures are based on claims and administrative data that are used for billing, limiting the ability to measure many aspects of health care quality. Replacing the current manual approach to quality measurement with digital quality measures (dQM) can increase the precision of measurement and the relevance of quality reports for clinicians seeking to improve care. They can also increase the validity of reported results and reduce the burden and costs associated with manual data collection and management."},{"type":"faq","title":"How are dQMs related to CMS\u2019s Universal Foundation of quality measures?","content":"The Universal Foundation and dQMs are part of an overall strategy to reduce burden and maximize the power of digital measures to improve patient outcomes. The Universal Foundation establishes a high-priority, standardized set of quality measures to promote alignment across CMS\u2019s payment and quality programs, and focus the nation\u2019s health system on key areas for improvement. Universal Foundation measures also emphasize building a modern health data exchange infrastructure to deliver the highest-quality care to patients\u2014wherever they receive care."},{"type":"faq","title":"How do dQMs help health care consumers?","content":"As Congress continues to advance price transparency and value-based care, dQMs can revolutionize consumer choice. Through combined price and quality outcomes, consumers can get a true picture of the value of their care. Publicly available quality measurement information is about 2 years out of date; dQMs allow providers to view patient outcomes and needed interventions in real time."},{"type":"faq","title":"How will dQMs ensure that patients\u2019 sensitive health data are protected?","content":"dQMs pull data from certified health technology, which adheres to patient privacy and protections mandated in the 21st Century Cure Act. Additionally, health information will reside with HIPAA covered entities that safeguard the information and comply with federal and state regulations and standards for handling PHI."},{"type":"faq","title":"What are the benefits of dQMs versus traditional quality measures and eCQMs?","content":"[ninja_tables id=\"37822\"]"},{"type":"external","title":"CARIN Implementation Guide for Blue Button\u00ae","content":"Accessed through HL7, \u00a0these resources contain the version history for the CARIN Blue Button\u00ae Framework and Common Payer Consumer Data Set (CPCDS), providing a set of resources that payers can display via a FHIR API.","link":"https:\/\/hl7.org\/fhir\/us\/carin-bb\/history.html"},{"type":"external","title":"USCDI Core Data Standards","content":"Accessed through he Office of the National Coordinator for Health Information Technology (ONC), the United States Core Data for Interoperability (USCDI) is a standardized set of health data classes and constituent data elements for nationwide, interoperable health information exchange.","link":"https:\/\/www.healthit.gov\/isa\/united-states-core-data-interoperability-uscdi"},{"type":"resource","title":"Digital Quality Overview","content":"<h2>Defining Digital Quality<\/h2>\r\nDigital quality uses standardized, digital data from one or more sources of health information that is captured and exchanged via interoperable systems and applies quality measure specifications that are standards-based. Digital quality measurement leverages code packages and is computed in an integrated environment without additional effort. The solution enables:\r\n<ul>\r\n \t<li>Data queries from standards-based application programming interfaces (such as FHIR<sup>\u00ae<\/sup> APIs).<\/li>\r\n \t<li>Measure score calculation.<\/li>\r\n \t<li>Generation of outputs necessary for quality reporting.<\/li>\r\n<\/ul>\r\nIt is part of the learning health system (LHS) to improve patient care and experiences by ensuring patient and provider access to necessary information in a timely manner (rapid-cycle feedback).\r\n\r\n<b>Digital quality measures therefore are quality measures that meet these needs for digital quality measurement<\/b>","link":"https:\/\/www.ncqa.org\/resources\/digital-quality-measures-overview\/"},{"type":"resource","title":"Transforming clinical data to FHIR\u00ae","content":"New Digital measures can deliver significantly better value and be more relevant because they make use of increasingly more structured clinical data. There are multiple ways to source clinical data and they come from various sources. With the advancement of interoperability, most significantly the FHIR\u00ae standard, collection fata from various data sources will become less burdensome while the uniformity of the data will benefit better measure results and insights.\n<h3><strong>Who is involved in leveraging standardized clinical data?<\/strong><\/h3>\n<ul>\n \t<li>Your own interoperability and clinical data teams<\/li>\n \t<li>Data vendors and interoperability<\/li>\n \t<li>Data sources (provider systems, EMR vendors)<\/li>\n \t<li>Aggregators (e.g. HIEs)<\/li>\n \t<li>Registries<\/li>\n<\/ul>\nInitially, there are many cases where data is not available in FHIR\u00ae from the source. Therefore, the data need to be transformed into FHIR\u00ae at some point, but no later than just before it is used for digital quality. The two major ways to get clinical data in FHIR\u00ae are\n<p style=\"text-align: center;\"><strong>FHIR from the Source\n<\/strong>In this case the system where the data originates can provide clinical data via a FHIR API (see also BulkFHIR).<\/p>\n<img class=\"aligncenter wp-image-26706\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Data-Flow-graphics-01.png\" alt=\"\" width=\"576\" height=\"248\" \/>\n<p style=\"text-align: center;\"><strong>Just-in-Time FHIR\n<\/strong>Refers to the capability to transform non-FHIR clinical data into the FHIR format just as it is needed for processing with a digital quality use case (in digital quality software using a CQL execution engine, executing FHIR-CQL measures).<\/p>\n \n\n<img class=\"aligncenter wp-image-26707\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Data-Flow-graphics-02.png\" alt=\"\" width=\"780\" height=\"268\" \/>\n\n \n<h3><strong>Data Quality Management and Best Practices<\/strong><\/h3>\nA key consideration for clinical data, not just for digital quality, is data quality. It needs to be planned for managed proactively. While FHIR data from the source might eventually be so standardized and mature that data quality can be assumed to be sufficient, we need to expect for the foreseeable future that this is not the case.\n\nValidation programs can check or ensure data quality (e.g. PSVs performed by HEDIS auditors, NCQA DAV program) but other solutions may be needed to proactively manage data to be properly formatted, contain valid and standardized codes (value sets) and more.\n\nIn addition, there are other best practices that are important to implement clinical data operations around FHIR, which include\n<ul>\n \t<li>Using Aggregators (HIEs)<\/li>\n \t<li>Implementing standard operating models for use cases<\/li>\n \t<li>Clinical Data Integration (CDI) for Payers<\/li>\n<\/ul>\n<h3><strong>Starting Early has Benefits\u00a0<\/strong><\/h3>\nDeveloping and implementing a clinical data strategy towards FHIR takes time and needs to be implemented ahead of going live with digital quality operations. However, even if there may be time to put that off a little longer, benefits from starting right away are compelling.\n\nOften, initiatives take longer than expected and unforeseeable complications slow them down. But having more complete, timely and standardized clinical data in FHIR can benefit tradition quality use case and operations, can improve other use cases (e.g. risk adjustment) and simplify clinical data operations.\n\n ","link":"https:\/\/www.ncqa.org\/resources\/fhir-readiness-resources\/"},{"type":"resource","title":"Clinical Quality Language and CQL Engines: The Basics","content":"<h3>What is CQL or Clinical Quality Language?<\/h3>\nThe Clinical Quality Language (CQL) specification, an open-source standard published by HL7, defines a high-level domain specific language that allows a human-readable description of clinical quality logic to express clinical knowledge. The specification also defines a machine-readable, canonical representation called the Expression Logic Model (ELM) which is rendered from the authored CQL to allow for sharing of that clinical knowledge and logic in a way that is verifiable and computable. ELM serves as input to language processing applications such as transition, tooling and execution\/calculation engines.\n<h3>What is a CQL Execution or Calculation Engine?<\/h3>\nA CQL Engine is an implementation of the CQL specification that has the capability to execute clinical quality logic. A properly implemented CQL engine can \u2018run\u2019 the ELM rendering of any CQL that is authored according to the same specification.\n\nImplementations may vary, however, with differences in which versions of CQL are supported, whether or not all of the CQL syntax is supported and how well they are suited for different uses and requirements (e.g. volume, throughput, latency, required computing resources).\n<h3>Three layers to support all aspects of digital quality.<\/h3>\n<ul>\n \t<li>Applications\/Content Layer\n<ul>\n \t<li>\u00a0 Marketplace and business use case driven, digital quality applications that leverage standardized layers below to deliver innovative and scalable solutions.<\/li>\n \t<li>- Example applications include NCQA Digital Content Services.<\/li>\n<\/ul>\n<\/li>\n \t<li>Infrastructure\/Enablement Layer\n<ul>\n \t<li>Open, non-proprietary, standards-based clinical reasoning tools and platforms that execute specific prioritized quality use cases (e.g. HEDIS, eCQMs) consistently, unambiguously and without gaps, while consuming and producing results as standardized, structured data.<\/li>\n \t<li>Examples are execution engines from Smile, Mitre and, Firely.<\/li>\n<\/ul>\n<\/li>\n \t<li>Data Layer\n<ul>\n \t<li>Leverages mandated and industry adopted standardized and structured data from sources including EHR\/EMR systems, health plans, HIEs\/HINs, registries and patient applications.<\/li>\n \t<li>Examples of data standards are US Core FHIR Implementation Guide (IG), CARIN Blue-Button FHIR IG and HL7\u2019s DaVinci FHIR IGs for various use case.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<img class=\"wp-image-26709 aligncenter\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Layers-GraphicForWebsite-v1.png\" alt=\"\" width=\"842\" height=\"431\" \/>\n<h3>Why Did NCQA select CQL as the standard for digital quality?<\/h3>\n<ul>\n \t<li>It is a healthcare and quality specific, standards-based declarative language developed for quality measurement and clinical reasoning \u2013 a great fit for digitizing Quality content.<\/li>\n \t<li>It is capable of incorporating data models like FHIR as well as code and other CQL Libraries for common subroutines for consistent and easy use of common values and functions.<\/li>\n \t<li>The CMS Digital Quality Measurement Strategic Roadmap aligns with the CQL specification for Measure Calculation Tools (publicly funded and privately developed MCTs share a core set of tooling such as the CQL engine) and for EHRs reporting eCQMs (the logic needed to evaluate a provider or organization\u2019s performance is expressed using CQL)\n<ul>\n \t<li>Measure authors can use the CMS Measure Authoring Tool (MAT) to author eCQMs and the CMS Bonnie tool to test eCQMs, using CQL.<\/li>\n \t<li>Healthcare facilities can use FHIR APIs to report digital quality measures (dQMs) defined using CQL to CDC's National Healthcare Safety Network (NHSN). The NHSN dQM definition aligns with the CMS dQM definition in the CMS Digital Quality Measurement Strategic Roadmap.<\/li>\n<\/ul>\n<\/li>\n \t<li>The FHIR Data model is a great complement as it is evolving as a mandated and universally used data model for clinical data and it overcomes limitations of prior data models, enabling NCQA to create a complete roadmap for migrating HEDIS measures to dQMs and to develop new, better digital measures on a foundation of rich standardized structured clinical data.<\/li>\n \t<li>It allows NCQA to create a model for other measure programs and drive the industry-wide adoption of digital quality \u2013 only when all programs use one standard for execution logic and one standard for data, will we realize the full benefits of digital quality.<\/li>\n<\/ul>\n<h3>What is the Digital Quality Implementers Community<\/h3>\nFor organizations interested in building, maintaining or enhancing CQL engines that support quality use cases, NCQA has established the Digital Quality Implementers Community to create consistency and confidence in the implementation of CQL standards .\n\nThe Digital Quality Implementers Community, spearheaded by the National Committee for Quality Assurance (NCQA), is a collaborative effort aimed at fostering the development and standardization of digital quality measurement tools and platforms. Initially focusing on creating a developer community for vendors involved in Clinical Quality Language (CQL) engines, the Community plans to expand its scope to include additional tools, developers, and programming languages in the digital quality sector. Primary objectives include establishing standards, developing validation tools, implementing a governing model, crafting a communications strategy, and creating a federal advocacy plan. The community will focus on evolving existing CQL platforms to enable Digital Quality Measurement, ensuring consistency and innovation.\n<h3>Why is the Digital Implementers Community Important<\/h3>\n<ul>\n \t<li>Standardization and Consistency<\/li>\n \t<li>Innovation & Adoption<\/li>\n \t<li>Addressing Implementation Challenges<\/li>\n \t<li>Validation & Quality Assurance<\/li>\n \t<li>Community Governance<\/li>\n \t<li>Communication and Advocacy<\/li>\n \t<li>Consensus Building<\/li>\n \t<li>Scalability<\/li>\n<\/ul>","link":"https:\/\/www.ncqa.org\/resources\/clinical-quality-language-and-cql-engines-the-basics\/"},{"type":"resource","title":"HEDIS Implementation Guide: An Overview","content":"<h1>What Is the HEDIS<sup>\u00ae<\/sup> Implementation Guide?<\/h1>\r\nNCQA\u2019s HEDIS IG is published as web pages that include both <strong>human-readable<\/strong> and <strong>machine-readable<\/strong> versions of the data model constraints. The IG also contains a narrative description of the rules and background on the challenges the IG addresses.\r\n\r\nThe implementation guide will allow implementers to understand exactly how to source and prepare data (clinical and administrative) in FHIR<sup>\u00ae<\/sup> to ensure it is a fit for digital quality, more specifically for digital quality measures for the HEDIS measure program.\r\n<div style=\"text-align: center; margin: 1rem auto;\">[ncqa_btn href=\"https:\/\/www.ncqa.org\/hedis-core-implementation-guide-request\/\" target=\"_blank\" type=\"blue\"]Request access to the HEDIS Core IG[\/ncqa_btn]<\/div>\r\nStakeholders may be familiar with the concept of the implementation guides as they are used in other use case domains around FHIR<sup>\u00ae<\/sup>. However, if you are new to IGs the following sections are intended to introduce you to use in the HEDIS IG.\r\n\r\n<span data-contrast=\"auto\">The HEDIS IG structure diagram depicted below highlights the components of the HEDIS IG web page and represents the items that compose the IG (e.g., page, concepts).\u00a0\u00a0 <\/span><span data-ccp-props=\"{"201341983":0,"335559738":80,"335559739":80,"335559740":240}\">\u00a0<\/span>\r\n\r\n<img class=\"aligncenter wp-image-26650 size-full\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Graphic-6-hedisigstructure.png\" alt=\"\" width=\"640\" height=\"275\" \/>\r\n\r\n<span data-ccp-props=\"{"201341983":0,"335559738":80,"335559739":80,"335559740":240}\">\u00a0<\/span>\r\n\r\n<span data-ccp-props=\"{"201341983":0,"335559738":80,"335559739":80,"335559740":240}\">\u00a0<\/span>\r\n<h2>How to Read the IG<\/h2>\r\n<span data-contrast=\"auto\">NCQA\u2019s HEDIS IG is published as web pages that include both <\/span><b><span data-contrast=\"auto\">human-readable<\/span><\/b><span data-contrast=\"auto\"> and <\/span><b><span data-contrast=\"auto\">machine-readable<\/span><\/b><span data-contrast=\"auto\"> versions of the data model constraints. The IG also contains narrative descriptions of the rules and background on the challenges the IG addresses.<\/span>\r\n\r\n<img class=\"size-full wp-image-26656 aligncenter\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Graphic-Placeholder-1-implementation-name-and-version.png\" alt=\"\" width=\"640\" height=\"219\" \/>\r\n\r\nTo read the IG, start with the home page, which contains important information. Next, examine the computable content: The artifact page provides the technical definition of all the profiles published in a specific version of the IG. Each profile has its own pages in the IG, where you will find conformance rules specified by the profile.\r\n\r\nEach profile, extension, value set and CodeSystem has a unique canonical URL:\r\n\r\n<img class=\"aligncenter size-full wp-image-26655\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Graphic-Placeholder-2-canonical-URL.png\" alt=\"\" width=\"640\" height=\"293\" \/>\r\n\r\nThe IG comprises different menus. Navigate through the menus and submenus to access content.\r\n\r\nProfile elements may be nested; for example, Patient.telecom\r\n\r\n<img class=\"aligncenter size-full wp-image-26651\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Graphic-5-nested-components.png\" alt=\"\" width=\"640\" height=\"335\" \/>\r\n\r\n<span data-ccp-props=\"{"201341983":0,"335559738":80,"335559739":80,"335559740":240}\">\u00a0<\/span>\r\n\r\n<span data-ccp-props=\"{"201341983":0,"335559738":80,"335559739":80,"335559740":240}\">\u00a0<\/span>\r\n\r\nThe HEDIS IG is composed of both US Core and HEDIS Core principles.\r\n\r\nConformance resources in the HEDIS Core IG derive from and extend the US Core IG v3.1.1(USCDI v1) profiles and CARIN IG for Blue Button v1.1.0 profiles for clinical data and payer data, respectively.\r\n\r\nA profile allows for simplification or inclusion of elements (constraints, extension) to a standard data model. The differential between the parent profile and the derived profile can be viewed via the\u00a0diff view\u00a0tab.\r\n\r\n<b><span data-contrast=\"auto\">View of Profile Content Tabs<\/span><\/b><span data-ccp-props=\"{"201341983":0,"335559738":80,"335559739":80,"335559740":240}\">\u00a0<\/span>\r\n\r\n<strong>The<\/strong>\u00a0<strong>Differential Tab<\/strong>\u00a0shows only the rules added by a specific profile. The tab compares the profile you are viewing with its parent profile.\r\n\r\n<strong>The\u00a0Hybrid Tab<\/strong>\u00a0shows all the rules in the profile. Parent profile rules are grayed out.\r\n\r\n<strong>The\u00a0Snapshot Tab<\/strong>\u00a0shows all the rules in the profile, including those inherited from the parent profile.\r\n\r\n \r\n\r\n \r\n\r\n<img class=\"aligncenter size-full wp-image-26653\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Graphic-3-profile-content-tabs.png\" alt=\"\" width=\"640\" height=\"416\" \/>\r\n\r\n<strong>Profile Definition Concepts\u00a0<\/strong>\r\n\r\nCardinality flags\r\n\r\nThe cardinality of an attribute within a profile is in the format {minimum}..{maximum}\r\n\r\nFor instance :\r\n\r\n0..*: Optional array(multiple codes, different systems)\r\n\r\n0..1: optional element (zero or one)\r\n\r\n1..1: Required element (one and only one)\r\n\r\nS: Must support\r\n\r\n?!: Modifier element\r\n\r\nI : Invariant\r\n\r\n\u03a3: Summary set\r\n\r\nC: Constraints\r\n\r\nValue set bindings\r\n\r\nrequired: You SHALL use the specified codes\r\n\r\nextensible: You SHALL use the specified codes\r\n\r\npreferred: You SHOULD use the specified codes\r\n\r\nexample: You MAY use these codes\u2014suggested, but not required\r\n\r\n \r\n\r\nThe annotated screenshot below shows a profile\u2019s key components:\r\n\r\n<img class=\"aligncenter size-full wp-image-26654\" src=\"https:\/\/www.ncqa.org\/wp-content\/uploads\/Graphic-4-profile-key-components.png\" alt=\"\" width=\"640\" height=\"376\" \/>\r\n\r\n \r\n<h2>FHIR<sup>\u00ae<\/sup> Resources Used in the HEDIS IG<\/h2>\r\n<span class=\"NormalTextRun BCX0 SCXP106756321\">What are the FHIR<sup>\u00ae<\/sup> Resources (and definitions) used\u00a0in the HEDIS IG (<\/span><span class=\"AdvancedProofingIssueZoomed BCX0 SCXP106756321\">i.e.<\/span><span class=\"NormalTextRun BCX0 SCXP106756321\">\u00a0Observation, Resource, Result,\u00a0Coverage, etc.)\u00a0<\/span>\r\n<div class=\"ncqa-table dqt-style\">\r\n<table>\r\n<thead>\r\n<tr>\r\n<th>Resources<\/th>\r\n<th>Definition<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>Claim<\/td>\r\n<td>A provider-issued list of professional services and products which have been provided, or are to be provided, to a patient which is sent to an insurer for reimbursement.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>ClaimResponse<\/td>\r\n<td>This resource provides the adjudication details from the processing of a Claim resource.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Condition ( Condition Encounter Diagnosis, Condition Problems Health Concerns )<\/td>\r\n<td>A clinical condition, problem, diagnosis, or other event, situation, issue, or clinical concept that has risen to a level of concern.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Coverage<\/td>\r\n<td>Financial instrument which may be used to reimburse or pay for health care products and services. Includes both insurance and self-payment.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>DocumentReference<\/td>\r\n<td>A reference to a document of any kind for any purpose. Provides metadata about the document so that the document can be discovered and managed. The scope of a document is any serialized object with a mime-type, so includes formal patient-centric documents (CDA), clinical notes, scanned paper, and non-patient-specific documents like policy text. \u200b\r\n\r\nThis is a basic constraint on DocumentReference for use in the US Core IG.\u200b<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Encounter<\/td>\r\n<td>An interaction between a patient and healthcare provider(s) for the purpose of providing healthcare service(s) or assessing the health status of a patient.\r\n\r\nThis is a basic constraint on Encounter for use in US Core resources.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>ExplanationOfBenefit ( Inpatient Institutional, Outpatient Institutional, Pharmacy, Professional NonClinician )<\/td>\r\n<td>This resource provides: the claim details; adjudication details from the processing of a Claim; and optionally account balance information, for informing the subscriber of the benefits provided.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Immunization<\/td>\r\n<td>Describes the event of a patient being administered a vaccine or a record of immunization as reported by a patient, a clinician or another party.\u200b\r\n\r\nThe US Core Immunization Profile is based upon the core FHIR<sup>\u00ae<\/sup> Immunization Resource and created to meet the 2015 Edition Common Clinical Data Set 'Immunizations' requirements.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>MedicationAdministration<\/td>\r\n<td>Describes the event of a patient consuming or otherwise being administered a medication. This may be as simple as swallowing a tablet or it may be a long-running infusion. Related resources tie this event to the authorizing prescription and the specific encounter between patient and health care practitioner.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>MedicationDispense<\/td>\r\n<td>Indicates that a medication product is to be or has been dispensed for a named person\/patient. This includes a description of the medication product (supply) provided and the instructions for administering the medication. The medication dispense is the result of a pharmacy system responding to a medication order.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Observation<\/td>\r\n<td>Measurements and simple assertions made about a patient, device or other subject.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Organization<\/td>\r\n<td>A formally or informally recognized grouping of people or organizations formed for the purpose of achieving some form of collective action. Includes companies, institutions, corporations, departments, community groups, healthcare practice groups, payers\/insurers, etc.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Patient<\/td>\r\n<td>Demographics and other administrative information about an individual or animal receiving care or other health-related services\u200b.\r\n\r\nThe US Core Patient Profile is based upon the core FHIR<sup>\u00ae<\/sup> Patient Resource and designed to meet the applicable patient demographic data elements from the 2015 Edition Common Clinical Data Set.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Practitioner<\/td>\r\n<td>A person who is directly or indirectly involved in the provisioning of healthcare.\u200b\r\n\r\nThis is a basic constraint on the provider for use in US Core resources.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>PractitionerRole<\/td>\r\n<td>A specific set of Roles\/Locations\/specialties\/services that a practitioner may perform at an organization for a period of time.\u200b\r\n\r\nThis is a basic constraint on PractitionerRole for use in US Core resources.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Procedure<\/td>\r\n<td>An action that is or was performed on or for a patient. This can be a physical intervention like an operation, or less invasive like long-term services, counseling, or hypnotherapy.\u200b\r\n\r\nThe US Core Condition Profile is based upon the core FHIR<sup>\u00ae<\/sup> Procedure Resource and created to meet the 2015 Edition Common Clinical Data Set 'Procedures' requirements.<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>QuestionnaireResponse<\/td>\r\n<td>A structured set of questions and their answers. The questions are ordered and grouped into coherent subsets, corresponding to the structure of the grouping of the questionnaire being responded to.<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<div style=\"text-align: center; margin: 1rem auto;\">[ncqa_btn href=\"https:\/\/www.ncqa.org\/hedis-core-implementation-guide-request\/\" target=\"_blank\" type=\"blue\"]Request access to the HEDIS Core IG[\/ncqa_btn]<\/div>\r\n<\/div>","link":"https:\/\/www.ncqa.org\/resources\/hedis-ig-resource-page\/"},{"type":"external","title":"SDOH and Health Equity Standards: Gravity Project","content":"","link":"https:\/\/build.fhir.org\/ig\/HL7\/fhir-sdoh-clinicalcare\/sdoh_challenges_gravity.html"},{"type":"resource","title":"Clinical Data For Quality Use: The Basics","content":"New Digital measures can deliver significantly better value and be more relevant because they make use of increasingly more structured clinical data. There are multiple ways to source clinical data and they come from various sources. With the advancement of interoperability, most significantly the FHIR\u00ae standard, collection data from various data sources will become less burdensome while the uniformity of the data will benefit better measure results and insights.\n\n<strong>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Who is involved in leveraging standardized clinical data?<\/strong>\n<ul>\n \t<li>Your own interoperability and clinical data teams<\/li>\n \t<li>Data vendors and interoperability<\/li>\n \t<li>Data sources (provider systems, EMR vendors)<\/li>\n \t<li>Aggregators (e.g. HIEs)<\/li>\n \t<li>Registries<\/li>\n<\/ul>\n<strong>How to access clinical data via FHIR\u00ae<\/strong>\n\nA common thread in engaging with stakeholders around clinical data enablement is FHIR\u00ae. Interoperability teams at the abovementioned data partners and enablers need to work with a shared understanding of the 21<sup>st<\/sup> Century Cures Act provisions in Title IV, which among other things mandates that clinical data needs to be accessible with \u2018No Special Effort.\u2019 ONC and CMS rules further define the implementation of FHIR\u00ae APIs, data elements via USCDI and more.\n\nData quality is another key aspect. Standard best practices are expected to evolve as the digital quality transition progresses.\n\n<strong>Enabling Digital Quality with FHIR\u00ae<\/strong>\n\nNot all clinical data will be available in the FHIR\u00ae format right away. During the transition to digital quality, significant amounts of data will only be available in other formats. To ensure that digital quality systems received the FHIR\u00ae formatted data they need, two approaches need to be considered and typically deployed side-by-side. Engaging with interoperability and data management teams to determine an approach and available options for FHIR\u00ae enabling clinical data is important.\n\n<strong>Data Sources for dQMs <\/strong>\n\nWhile administrative data sources remain important for HEDIS \u2013 and they need to be converted to FHIR\u00ae for digital quality, additional data sources are important to meet the needs for clinical data as existing measures evolve and new measures become available.\n\nAs a general guideline, data sources defined as allowable by ECDS will become the standard even as supplemental data and chart reviews get deprecated during the transition to digital quality. The following graphic shows data sources relevant to digital quality:\n\n<img class=\"aligncenter size-full wp-image-26711\" src=\"https:\/\/dev.ncqa.org\/wp-content\/uploads\/NCQA-DigitalDataSources-web-version.png\" alt=\"\" width=\"1200\" height=\"171\" \/>\n\nThese sources (and measure design for dQMs) also consider the need for leveraging clinical data that is being generated from routine workflows, i.e. in the course of delivering care to patients. The data is no (and should not be) use-case specific to digital quality measurement and can be used to support other use cases, like pubic health and patient care treatment. Such broader useability of structured clinical data is key to getting maximum value from clinical data in the future.","link":"https:\/\/www.ncqa.org\/resources\/clinical-data-for-quality-use-the-basics\/"}];</script> <script type="text/javascript" src="https://www.ncqa.org/wp-content/cache/autoptimize/js/autoptimize_single_2b9c6bee0a4bfd951a4bc645c5bcd627.js?ver=1.0.0" id="localized-js"></script> <script type="text/javascript" src="https://www.ncqa.org/wp-includes/js/jquery/ui/mouse.min.js?ver=1.13.3" id="jquery-ui-mouse-js"></script> <script type="text/javascript" src="https://www.ncqa.org/wp-includes/js/jquery/ui/draggable.min.js?ver=1.13.3" id="jquery-ui-draggable-js"></script> <script type="text/javascript" src="https://www.ncqa.org/wp-content/cache/autoptimize/js/autoptimize_single_19876fc818584aa6268eb84e33dce241.js?ver=20220421" id="components-js"></script> </body></html>