Measure alignment includes using the same quality measures and value sets across settings and within multiple programs when possible. Alignment is achieved when a set of measures works well across settings or programs to produce meaningful information without creating extra work for those responsible for the measurement.
The Change Review Process (CRP) provides electronic clinical quality measure (eCQM) users the opportunity to review and comment on draft changes to the eCQM specifications and supporting resources under consideration by the measure steward. The CRP is conducted through the ONC Project Tracking System (Jira) website. The goal of the CRP is for eCQM implementers to comment on the potential impact of changes to measures so the Centers for Medicare & Medicaid Services (CMS) and measure stewards can make improvements to meet CMS’s intent of minimizing provider and vendor burden in the collection, capture, calculation, and reporting of eCQMs. To participate in the CRP, users must have a Jira account and log into the eCQM Issue Tracker where specific CRP tickets are posted for public comment and voting. Users can sign up for an account on the login in page.
Clinical Decision Support (CDS) is health information technology functionality that builds upon the foundation of an electronic health record (EHR) to provide persons involved in care processes with general and person-specific information, intelligently filtered and organized, at appropriate times, to enhance health and healthcare.
A Clinical Decision Support (CDS) developer is an individual or organization that translates knowledge to a structured and/or executable tool that aids in making evidence-informed decisions about a patient’s healthcare. CDS developers may or may not be the original knowledge authors (e.g., guideline developers, subject matter experts) or the final implementers. They are responsible for ensuring that the original clinical knowledge is reflected, accurately and consistently, in the appropriate standard coding schemes, e.g., Clinical Quality Language (CQL), and terminologies such as Current Procedural Terminology (CPT) and SNOMED CT, accounting appropriately for intellectual property and licensing.
A clinical quality measure (CQM) is a mechanism used for assessing the degree to which a provider competently and safely delivers clinical services that are appropriate for the patient in an optimal time frame. CQMs are a subset of the broader category of performance measures.
A code system is a managed collection of concepts with each concept represented by at least one internally unique code and a human readable description, e.g., SNOMED CT.
A comment period is the period of time the public has to respond to a request for public comment, such as a proposed rule, Request for Information, a new measure posted on the Measure Management System website, or some other document. The Administrative Procedure Act requires that federal agencies give the public an opportunity to participate in rulemaking. Executive Orders 12866 and 13563 provide that a comment period generally should be no less than 60 days, but the length of the comment period varies if not part of the rulemaking process.
A composite performance measure, also called composite measure, is a combination of two or more component measures, each of which individually reflects quality of care into a single performance measure with a single score.
A continuous variable is a measure score in which each individual value for the measure can fall anywhere along a continuous scale and can be aggregated using a variety of methods such as the calculation of a mean or median (for example, mean number of minutes between presentation of chest pain to the time of administration of thrombolytics).
The Critical Access Hospital (CAH) program is a federal program established in 1997 as part of the Balanced Budget Act and is designed to promote rural health planning, network development, and improve access to health services for rural residents of the state. CAHs represent a separate provider type with their own Medicare Conditions of Participation (CoP) as well as a separate payment method. The CoPs for CAHs are listed in the “Code of Federal Regulations” at 42 CFR 485 subpart F.
Data element validity is the extent to which the information represented by the data element or code used in the measure reflects the actual concept or event intended. See also measure validity. For example
- A medication code is used as a proxy for a diagnosis code
- Data element response categories include all values necessary to provide an accurate response
The denominator is the lower part of a fraction used to calculate a rate, proportion, or ratio. It can be the same as the initial population or a subset of the initial population to further constrain the population for the purpose of the measure. Continuous variable measures do not have a denominator, but instead define a measure population.
A denominator exception is any condition that should remove a patient, procedure, or unit of measurement from the denominator of the performance rate only if the numerator criteria are not met. A denominator exception allows for adjustment of the calculated score for those providers with higher risk populations. A denominator exception also provides for the exercise of clinical judgment and should be specifically defined where capturing the information in a structured manner fits the clinical workflow. A denominator exception is used only in proportion measures. Denominator exception cases are removed from the denominator. However, the number of patients with valid exceptions may still be reported. Allowable reasons fall into three general categories - medical reasons, patient reasons, or system reasons.
A denominator exclusion is a case that should be removed from the measure population and denominator before determining if numerator criteria are met. Denominator exclusions are used in proportion and ratio measures to help narrow the denominator. For example, patients with bilateral lower extremity amputations would be listed as a denominator exclusion for a measure requiring foot exams.
A direct reference code (DRC) is a specific code that is referenced directly in the electronic clinical quality measure (eCQM) logic to describe a data element or one of its attributes. Direct reference code metadata include the description of the code, the code system from which the code is derived, and the version of that code system.
An electronic clinical quality improvement (eCQI) implementer does many things to prepare processes and systems such as
- Putting measure data components into systems and workflow
- Using measures when conducting healthcare activities
- Providing information from measures to inform quality improvement (e.g., health information technology implementer, quality analyst, quality reporting validator).
An electronic clinical quality measure (eCQM) union is specified using the Clinical Quality Language (CQL) ‘union’ operator which is used to combine two or more data elements, arguments, or expressions onto a list such that any item contained in the combined list fulfills the criteria of the union.
An efficiency measure is a measure that evaluates the resource use (or cost) associated with a specific level of performance with respect to the aims of quality. For example, a provider in the healthcare system would be efficient if it was able to maximize output for a given set of inputs or to minimize inputs used to produce a given output.
Electronic clinical quality improvement (eCQI) is the use of health information technology, the functionality, and data in an EHR and/or other health information technology, along with clinical best practices to support, leverage, and advance quality improvement initiatives. (Adapted from the Health Information Technology Enbabled eCQI Toolkit.)
An electronic clinical quality measure (eCQM) is a clinical quality measure that is expressed and formatted to use data from electronic health records (EHR) and/or health information technology systems to measure healthcare quality, specifically data captured in structured form during the process of patient care. So they can be reported from an EHR, the Health Quality Measure Format (HQMF) is used to format the eCQM content using the Quality Data Model (QDM) to define the data elements and Clinical Quality Language (CQL) to express the logic needed to evaluate a provider or organization’s performance.
Electronic Health Record (EHR) is also known as the electronic patient record, electronic medical record, or computerized patient record. As defined by Healthcare Information Management and Systems Society, “the electronic health record (EHR) is a longitudinal electronic record of patient health information generated by one or more encounters in any care delivery setting. Included in this information are patient demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and imaging reports.”
An eligible clinician refers to a clinician who is eligible to participate in the Quality Payment Program (QPP) through the Merit-based Incentive Payment System (MIPS) and similar participants of other CMS programs using electronic clinical quality measures (eCQMs) for quality reporting such as Alternative Payment Model (APM) participants.
An eligible hospital is a medical facility that reports electronic clinical quality measures (eCQMs) and Promoting Interoperability Program data through the CMS QualityNet Secure Portal such as Medicaid-eligible hospitals, Medicare-eligible hospitals, dual-eligible hospitals (both Medicare and Medicaid), and critical access hospitals.
An eligible professional is a healthcare professional that reports eCQMs and Medicaid Promoting Interoperability Program data through their state-based systems.
eXtensible Markup Language (XML) is a markup language that defines a set of rules for encoding documents in a format which is both human-readable and machine-readable.
The Feasibility criteria are the extent to which the specifications, including measure logic, require data that are readily available or that could be captured without undue burden and can be implemented for performance measurement. Source: National Quality Forum. (2018). Measure Evaluation Criteria and Guidance for Evaluating Measures for Endorsement document.
Harmonization is the standardization of specifications for related measures with the same measure focus (for example, influenza immunization of patients in hospitals or nursing homes); related measures for the same target population (for example, eye exam and HbA1c for patients with diabetes); or definitions applicable to many measures (for example, age designation for children) so that they are uniform or compatible, unless differences are justified (in other words, dictated by the evidence). The dimensions of harmonization can include numerator, denominator, exclusions, calculation, and data source and collection instructions. The extent of harmonization depends on the relationship of the measures, the evidence for the specific measure focus, and differences in data sources. Value sets used in measures should be harmonized when the intended meaning is the same. Harmonization can also mean adoption of the same standard(s) for different purposes such as use of standards for electronic clinical quality measures (eCQMs) and clinical decision support (CDS), for example Clinical Quality Language for logic expression in eCQMs and CDS.
Per the Health Information Technology for Economic and Clinical Health (HITECH) Act, the term health information technology (IT) means hardware, software, integrated technologies or related licenses, intellectual property, upgrades, or packaged solutions provided as services that are designed for or support the use by healthcare entities or patients for the electronic creation, maintenance, access, or exchange of health information.
A health information technology (IT) developer/vendor is an entity that designs, develops, and/or markets health IT software application(s) for use in hospitals, ambulatory care settings, and/or specialty care delivery settings, e.g., electronic health record (EHR) developer, EHR vendor, quality reporting software developer, quality reporting software vendor.
Health Level Seven International (HL7) is a standards-developing organization that provides a framework and standards for the exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery, and evaluation of health services.
A healthcare consumer is an individual who uses the services of a healthcare provider e.g., patient receiving care in a hospital, provider's office, or a client in a community mental health center. Retrieved from the IGI Global webpage on Health consumers.
A healthcare payer is any payer of healthcare services other than the insured person, e.g., insurance company, Health Maintenance Organization, Preferred Provider Organization, or the federal government.
Healthcare Service Location (HSLOC) is a classification of locations and settings where healthcare services are provided which can be used to identify locations within a facility, such as the Emergency Department (ED) and medical intensive care unit (ICU).
A hybrid measure is a quality measure that uses both claims data and clinical data from electronic health records (EHRs) for calculating measure.
Hypertext Markup Language (HTML) is the standard markup language for creating web pages and web applications.
The Importance criterion allows for a distinction between things that are important to do (or outcomes of importance) versus those processes, structures, or outcomes that rise to the level of importance required for a national performance measure. Importance has two key sub-criteria: evidence and performance gap. Evidence is the extent to which the specific measure focus is evidence-based and can drive significant gains in healthcare quality. Performance gap denotes that there is variation in performance among measured entities or that disparities (e.g., by race or ethnicity) exist even if a "macro-level" analysis appears to show that a measure is topped out. Source: National Quality Forum. (2018). Measure Evaluation Criteria and Guidance for Evaluating Measures for Endorsement document.
The initial population refers to all events to be evaluated by a specific performance measure involving patients who share a common set of specified characteristics within a specific measurement set to which a given measure belongs. All patients counted (for example, as numerator, as denominator) are drawn from the initial population.
An intermediate outcome is a (measured) change in physiologic state that leads to a longer-term health outcome. There should be a body of evidence that the measured intermediate clinical outcome leads to a desired health outcome.
An inverse measure is a measure where a lower performance rate is better. Therefore, a zero performance rate for these measures is a good score. For example,the National Healthcare Safety Network calculates most Healthcare-Associated Infections (HAIs) as a standardized infection ratio (SIR). The SIR compares the actual number of HAIs (the numerator) with the predicted number based on the baseline U.S. experience (e.g., standard population), adjusting for several risk factors that have been found to be most associated with differences in infection rates. The goal is to have the numerator equal to or very close to zero thereby having an SIR equal to or very close to zero.
The Meaningful Measures Framework is the Centers for Medicare & Medicaid Services's initiative which identifies the highest priorities for quality measurement and improvement. It involves only assessing core issues that are the most critical to providing high-quality care and improving individual outcomes. The Meaningful Measure Areas serve as the connectors between CMS goals and individual measures/initiatives that demonstrate how high-quality outcomes for CMS beneficiaries are being achieved.
A measure developer is an individual or organization responsible for the development, implementation, and maintenance of a measure. Measure developers create, edit, and submit measures for consideration by CMS to include in programs. CMS encourages developers to use the Blueprint as a guide in creating their measures and to collaborate with other measure developers to share best practices/new learnings freely e.g., CMS measure development contractor, hospital system, medical association, or federal health agency. Adapted from the CMS Measures Management System (MMS) Measure Developers webpage.
The measure score is the numeric result that is computed by applying the measure specifications and scoring algorithm. The computed measure score represents an aggregation of all appropriate patient-level data (for example, proportion of patients who died, average lab value attained) for the entity being measured (hospital, health plan, home health agency, clinician, etc.). The measure specifications designate the entity that is being measured and to whom the measure score applies.
A measure steward is an individual or organization that owns a measure and is responsible for maintaining the measure. Measure stewards are often the same as measure developers, but not always. Measure stewards are also the ongoing point of contact for people interested in a given measure e.g., medical specialty society or federal health agency. Retrieved from the CMS MMS Blueprint.
Measure testing is empirical analysis to demonstrate the reliability and validity of a measure as specified. It includes analysis of issues that pose threats to the validity of conclusions about quality of care such as exclusions, risk adjustment/stratification for outcome and resource use measures, methods to identify differences in performance, and comparability of data sources/methods.
Measure validity is when the measure accurately represents the concept being evaluated and achieves the purpose for which it is intended (to measure quality). See also Data element validity. For example, the measure
- Cleary identifies the concept being evaluated (face validity)
- Includes all necessary data elements, codes, and tables to detect a positive occurrence when one exists (construct validity)
- Includes all necessary data sources to detect a positive occurrence when one exists (construct validity)
The Measures under Consideration (MUC) is a list of quality and efficiency measures the Department of Health & Human Services is considering adopting, through the federal rulemaking process, for use in the Medicare program. The MUC list is made publicly available by December first each year for categories of measures that are described in section 1890(b) (7) (B) (i) (I) of the Affordable Care Act.
The National Quality Forum (NQF) is a not-for-profit, nonpartisan, membership-based organization that works to catalyze improvements in healthcare.
The null performance rate is the term used if the measure is not applicable for all patients within the sample, then the performance rate would be 0/0 (null) and would be considered satisfactorily reporting.
The numerator is the upper portion of a fraction used to calculate a rate, proportion, or ratio. Also called the measure focus, it is the target process, condition, event, or outcome. Numerator criteria are the processes or outcomes expected for each patient, procedure, or other unit of measurement defined in the denominator. A numerator statement describes the clinical action that satisfies the conditions of the performance measure.
The numerator exclusion defines the instances that should not be included in the numerator data. Numerator exclusions are used in ratio and proportion measures.
An outcome measure is a measure that assesses the results of healthcare that are experienced by patients: clinical events, recovery and health status, experiences in the health system, and efficiency/cost.
A patient-reported outcome (PRO) is any report of the status of a patient’s health condition, health behavior, or experience with healthcare that comes directly from the patient, without interpretation of the patient’s response by a clinician or anyone else. This definition reflects the key domains of
- Health-related quality of life (including functional status)
- Symptoms and symptom burden (e.g., pain, fatigue)
- Experience with care
- Health behaviors (e.g., smoking, diet, exercise)
A patient-reported outcome measure (PROM) is an instrument, scale, or single-item measure used to assess the patient-reported outcome (PRO) concept as perceived by the patient, obtained by directly asking the patient to self-report.
A patient-reported outcome-based performance measure (PRO-PM) is a performance measure that is based on patient-reported outcome measure (PROM) data aggregated for an accountable healthcare entity.
A process measure is a measure that focuses on a sequence of actions or steps that should be followed to provide high quality evidence-based care. There should be a scientific basis for believing that the process, when executed well, will increase the probability of achieving a desired outcome.
A proportion is a score derived by dividing the number of cases that meet a criterion for quality (the numerator) by the number of eligible cases within a given time frame (the denominator) where the numerator cases are a subset of the denominator cases (for example, percentage of eligible women with a mammogram performed in the last year).
A Quality Data Model (QDM) attribute provides specific details about a QDM data element. QDM data elements have two types of attributes, datatype-specific and dataflow attributes. Datatype-specific attributes provide specific details on a datatype, e.g., Medication, Dispensed and Medication, Ordered contain information about dosage, route, strength, and duration of a medication, while a Medication allergy, contains information about the allergy type, allergy severity, etc. Dataflow attributes provide specific details about the location of data represented by a QDM data element e.g., Health Record Field indicates the location within an electronic record where the data should be found, Source indicates the originator of the QDM data element (an individual or a device), and a Recorder, the individual or device that enters the QDM data element into a health record field.
A Quality Data Model (QDM) category consists of a single clinical concept identified by a value set. A category is the highest level of definition for a QDM element. The QDM currently contains 21 categories. Some examples of categories are Medication, Procedure, Condition/Diagnosis/Problem, Communication, and Encounter.
A Quality Data Model (QDM) data element encapsulates a certain category with an associated datatype. It is a discrete unit of information used in quality measurement to describe part of the clinical care process, including a clinical entity and its context of use. It can include criteria for any relevant metadata about a clinical or administrative concept relevant to quality measurement. A QDM data element provides an unambiguous definition and enables consistent capture and use of data for quality measurement. It may be defined for any given measure and reused when the same information is required for another measure. Reuse encourages standardization of quality measures and reduces the generation of additional software requirements for every new measure.
A Quality Data Model (QDM) datatype is the context in which each category is used to describe a part of the clinical care process. Examples of QDM datatypes include ‘Medication, Active’ and ‘Medication, Administered’ as applied to the QDM Medication category.
A quality or performance measure is a numeric quantification of healthcare quality for a designated accountable healthcare entity, such as hospital, health plan, nursing home, clinician, etc. A healthcare performance measure is a way to calculate whether and how often the healthcare system does what it should. Measures are based on scientific evidence about processes, outcomes, perceptions, or systems that relate to high-quality care.
A ratio is a score that is derived by dividing a count of one type of data by a count of another type of data. For example, the number of patients with central lines who develop infection divided by the number of central line days.
The Reliability criterion tests whether the measure is well defined and precisely specified so that it can be implemented consistently within and across organizations and allow for comparability. Source: National Quality Forum. (2018). Measure Evaluation Criteria and Guidance for Evaluating Measures for Endorsement document.
A resource use measure, also called a cost and resource use measure, refers to broadly applicable and comparable measures of health services counts (in terms of units or dollars) applied to a population or event (broadly defined to include diagnoses, procedures, or encounters). A resource use measure counts the frequency of defined health system resources. Some measures may monetize the health service by applying a dollar amount such as allowable charges, paid amounts, or standardized prices to each unit of resource use.
A respecified measure is an existing measure that is changed to fit the current purpose or use. This may mean changing a measure to meet the needs of a different care setting, data source, or population. Or, it may mean changes to the numerator, denominator, or adding specifications to fit the current use.
Scoring is the method(s) applied to data to generate results/score. Most quality measures produce rates. However, other scoring methods include categorical value, count, continuous variable, frequency distribution, non-weighted score/composite/scale, ratio, and weighted score/composite/scales.
Semantic validation is a method of testing the validity of an electronic clinical quality measure (eCQM) whereby the formal criteria in an eCQM are compared to a manual computation of the measure from the same test database.
Sensitivity, as a statistical term, refers to the proportion of actual positives that are correctly identified as such. For example, the percentage of people with diabetes who are correctly identified as having diabetes. See Specificity.
A specification is the measure instructions that address: data elements, data sources, point of data collection, timing and frequency of data collection and reporting, specific instruments to be used (if appropriate), and implementation strategies.
Specificity, as a statistical term, refers to the proportion of negatives that are correctly identified (for example, the percentage of healthy people who are correctly identified as not having the condition). Perfect specificity would mean that the measure recognizes all actual negatives. For example, all healthy people will be recognized as healthy. See Sensitivity.
A Standard for Trial Use (STU) is used to "provide timely compliance with regulatory or other governmental mandate and/or timely response to industry or market demand." An STU, following a suitable period for evaluation and comment, is incorporated into fully balloted and accredited version of the standard. Formerly called Draft Standard for Trial Use (DSTU).
Stratification divides a population or resource services into distinct, independent groups of similar data, enabling analysis of the specific subgroups. This type of adjustment can show where disparities exist or where there is a need to expose differences in results.
A structural measure is one that assesses features of a healthcare organization or clinician relevant to its capacity to provide healthcare.
The target population is the numerator (cases) and denominator (population sample meeting specified criteria) of the measure.
The Usability and Use criteria examine the extent to which potential audiences (e.g., consumers, purchasers, providers, policymakers) are using or could use performance results for both accountability and performance improvement to achieve the goal of high-quality, efficient healthcare for individuals or populations. Source: National Quality Forum. (2018). Measure Evaluation Criteria and Guidance for Evaluating Measures for Endorsement document.
The National Quality Forum validity criterion tests whether measure specifications are consistent with the measure intent and captures the most inclusive target population. There are two main types of validity, measure validity and data element validity. Measure validity is when the measure accurately represents the concept being evaluated and achieves the purpose for which it is intended (to measure quality). Data element validity is the extent to which the information represented by the data element or code.
See measure validity and data element validity.
A value set is a list of specific values, terms, and their codes, used to describe clinical and administrative concepts in the quality measures. Value sets provide groupings of unique values along with a standard description or definition from one or more standard vocabularies used to describe the same clinical concept, e.g., diabetes, clinical visit, demographics, within quality measures.
The Virtual Medical Record (vMR) is a data model for representing the data that are analyzed and/or produced by clinical decision support (CDS) engines.