Centers for Medicare and Medicaid Services (CMS) defines clinical quality metrics (CQMs) as a “mechanism for assessing observations, treatment, processes, experience, and/or outcomes of patient care”. CQMs are intended to measure how a healthcare provider competently and safely delivers patient clinical services in a timely manner. Healthcare providers are required to report CQMs electronically (eCQMs) from certified electronic health records (EHRs) or other health information systems as formally coded sets with measure logic as mandated by CMS, covering elements such as patient safety, care coordination, and clinical process effectiveness.
From 2019 onwards, providers need to use 2015 certified EHR technology (CEHRT) that comply with Promoting Interoperability programs. The eligible providers include eligible professionals, eligible hospitals, dual- eligible hospitals, and critical access hospitals.
Why Understanding eCQMs is critical in healthcare today
Healthcare Payors today report healthcare effectiveness data and information set or HEDIS measures using a largely manual intensive process. Currently, measures include extraction of a combination of claims, EHR and other data into a HEDIS certified tool for reporting. The National Committee for Quality Assurance (NCQA) has initiated the HEDIS electronic clinical data system (ECDS) level reporting which involves a database that contains each health plan member’s details and care information.
ECDS is now being considered for standardized automated quality measurement and reporting across the sector. Towards this direction, NCQA is evaluating the need for re-specification of current HEDIS metrics, eCQMs and other measure concepts for inclusion in the HEDIS ECDS domain. With each year, the selected ECDS measures will be mandatorily approved by the NCQA’s committee on performance measurement prior to release. Thus, understanding of eCQMs is critical to the success of both providers and payors for standardized reporting today.
There are several challenges with the current metric collection and reporting:
- Healthcare quality measure format (HQMF) is used in combination with the quality data model (QDM) to write and report on CQMs. HQMF and QDM do not provide computable logic specifications. A measure developer is required to manually translate and implement the specifications based on the computing environment, thus limiting easy exchange across the healthcare organization.
- Increased risk for interpretation and variability of measures and data.
- Lack of a unified expression language to report metrics reduces the industry adoption of clinical best practices and analytics necessary for population health management.
- Dependencies on various data sources to determine source-of-truth to collect the right data
- Unstructured data interpretations can be challenging to interpret in an image format
- Loss of revenue due to inaccuracies in reporting
- The potential loss of patients due to poor ratings
- Legacy systems and expensive investments to comply with changes to CQMs in the current format due to lack of CQL implementation and continued workaround to retrofit the CQM specifications into the existing enterprise systems
Need for a Standardized Clinical Language
CQMs are currently developed and structured by each healthcare organization based on CMS requirement mandates. In order to comply with the Promoting Interoperability program mandate, the provider industry has continued to struggle with finding workarounds to exchange clinical information and reporting, taxing organizations with increased technology costs and resource burden.
There is a burning need for a single universal clinical language and CQL fits the bill perfectly. CQL is intended to resolve the clinical and health concepts fragmentation to represent quality measures, CDS, and other computable healthcare knowledge in a uniform human readable format enabling easy exchange.
New Clinical Quality Language (CQL) HL 7 Standards
CQL is endorsed by Health Level 7 International, CMS, the Office of the National Coordinator for Health Information Technology, and the Centers for Disease Control and Prevention. CQL-based eCQMs are the new mandated CMS standard for 2019 reporting. Healthcare organizations receive the measure specification, expressed in healthcare quality measure format using the quality data model and clinical quality language and then report results to CMS using the format of the quality reporting document architecture.
HL7 has listed several target entities for CQL implementation, including, clinical and public health laboratories and lab vendors, immunization registries, quality reporting agencies, payors and healthcare institutions (providers), pharmaceutical vendors, health care IT vendors, emergency services providers, local and state departments of health and medical imaging service providers.
There is an emerging yet vital need for healthcare organizations to align with the implementation of CQL whether it be the translation from SQL to CQL or exploration of enterprise technology landscape to determine changes required to enable CQL based logic which will enable a standardized and uniform exchange of information across the healthcare system.
CQL will be critical for healthcare organizations to adopt and adapt, regardless of size and scale, to drive a single language communication highway and enable effective clinical data and information exchange using standardized clinical decision-making support for successful “whole person-centric” care.
Primary Author: Dr. Jayanthi Subramanian
Advisory Reviewer: Prasad Vuyyuru
Dr. Jayanthi Subramanian
Senior Prinicpal, Infosys Consulting
Jayanthi is a healthcare and life sciences expert and a seasoned business intelligence consultant with over two decades of industry experience. She has enabled transformational initiatives in health and life sciences for leading global firms in areas such as strategy definition, practice development, solution design, and implementation. Jayanthi has a doctorate in business administration and management in healthcare and a Masters in Neuroscience. She is also a certified design thinker and dementia specialist.
Partner, Infosys Consulting
Prasad is a veteran in the company, joining us in 2004 and currently leads our Enterprise Insights practice in the U.S. He has 25 years of experience in the management consulting industry and has helped more than 20 major clients create business value from data and insights. Prasad was instrumental in opening several new accounts for Infosys through the various service offerings he grew within the organization. He has received 3 prestigious awards for excellence from Infosys. Previously, Prasad worked at Booz Allen Hamilton and in various sales and marketing leadership roles at consumer products companies.