Importance of Low-Density Lipoprotein Cholesterol Measurement and Control As Performance Measures
Publication Date: February 26, 2023
Last Updated: March 1, 2023
Conclusions
Achievement of LDL-C levels <100 mg/dL in individuals with ASCVD or equivalent risk has been associated with improvements in ASCVD event rates and mortality, making it a Class IA recommendation and an established quality measure in the well-respected HEDIS tool in the past. The transition by the NCQA to a HEDIS process measure focused on statin use in 2015 reflected new data in support of higher-intensity statin treatment but did not incentivize LDL-C monitoring and/or improvement. Many data now support the re-establishment of LDL-C testing in high-risk subsets as a performance measure, especially in patients with established ASCVD:
- Recent data from the NCQA and independent surveys show minimal improvement in statin use in individuals with ASCVD in recent years
- Significant heterogeneity in LDL-C response from statin therapy
- New evidence-based guidelines that support LDL-C monitoring to assess efficacy and adherence to statin therapy and assess the need for add-on therapies (e.g., if certain LDL-C thresholds are not met on statin therapy alone)
- New clinical trial evidence with nonstatin therapies that supports the benefits of additional LDL-C lowering in high-risk patients already on maximal statin therapy
- Advances in the use of advanced data analytics in the EHR that allow health systems and providers not only to monitor LDL-C levels but also to improve care quality and outcomes
Evidence that LDL-C measurement fulfills performance measure attributes
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| ACC/AHA Task Force on Performance Measures Attributes for Performance Measures | Does LDL-C Measurement Meet This Attribute? | |
| Characteristic | Description | |
| 1. Evidence Based | ||
| High-impact area that is useful in improving patient outcomes | a. For structural measures, the structure should be closely linked to a meaningful process of care that in turn is linked to a meaningful patient outcome. | Not applicable |
| b. For process measures, the scientific basis for the measure is well established and the process should be closely linked to a meaningful patient outcome. | Yes, ACC/AHA guidelines clearly outline the evidence for improvement in outcomes meaningful to patients with lowering high LDL-C levels. Measurement of lipids is a Class I recommendation. | |
| c. For outcome measures, the outcome should be clinically meaningful. If appropriate, performance measures based on outcomes should adjust for relevant clinical characteristics by using appropriate methodology and high-quality data sources. | Not applicable | |
| 2. Measure Selection | ||
| Measure definition | a. The patient group to whom the measure applies (denominator) and for whom conformance is achieved is clearly defined and clinically meaningful. | This patient group for measurement can be clearly defined as in the past. |
| Measure exceptions and exclusions | b. Exceptions and exclusions are supported by evidence. | Exceptions and exclusions can be easily defined. |
| Reliability | c. The measure is reproducible across organizations and delivery settings. | It is highly likely that LDL-C measurement rates can be reproduced in all settings using electronic health records. |
| Face validity | d. The measure appears to assess what it is intended to assess. | The measure clearly measures what is intended. |
| Content validity | e. The measure captures most meaningful aspects of care. | LDL-C measurement is the primary method of determining appropriateness and effectiveness of LDL-C treatment. |
| Construct validity | f. The measure correlates well with other measures of the same aspect of care. | LDL-C measurement will have some correlation with drug prescriptions and adherence for drugs to lower LDL-C, which are known to improve care in appropriate individuals. |
| 3. Measure Feasibility | ||
| Reasonable effort and cost | a. Data required for the measure can be obtained with reasonable effort and cost. | The cost of measuring data using the electronic health record is small compared with other measurements. |
| Reasonable period | b. Data required for the measure can be obtained within the period allowed for data collection. | The data from laboratory records and pharmacy prescription records are readily available in a timely manner. |
| 4. Accountability | ||
| Actionable | a. Those held accountable can affect the care process or outcome. | Those doing poorly on the measure can be held accountable for their care and have clear paths to improving care through guideline-directed changes in medical therapy. |
| Unintended consequences avoided | b. The likelihood of negative unintended consequences with the measure is low. | An unintended consequence of the measure may be increased prescription rates among inappropriate patients. However, the probability of poor outcomes related to inappropriate use is exceedingly low based on the favorable safety profile of LDL-C lowering treatments. Restricting the measure to those who are high risk will reduce the probability of unintended consequences. |
Recommendation Grading
Disclaimer
The information in this patient summary should not be used as a substitute for professional medical care or advice. Contact a health care provider if you have questions about your health.
Overview
Title
Importance of Low-Density Lipoprotein Cholesterol Measurement and Control As Performance Measures
Authoring Organization
National Lipid Association
Publication Month/Year
February 26, 2023
Last Updated Month/Year
April 1, 2024
Document Type
Consensus
Country of Publication
US
Inclusion Criteria
Male, Female, Adult, Older adult
Health Care Settings
Ambulatory, Laboratory services
Intended Users
Nurse, nurse practitioner, physician, physician assistant
Scope
Diagnosis, Assessment and screening, Prevention
Diseases/Conditions (MeSH)
D008074 - Lipoproteins, D008077 - Lipoproteins, LDL
Keywords
LDL-cholesterol, low-density lipoprotein, lipoprotein, LDL