Importance of Low-Density Lipoprotein Cholesterol Measurement and Control As Performance Measures

Publication Date: February 27, 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

Publication Month/Year

February 27, 2023

Last Updated Month/Year

December 20, 2023

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

Supplemental Methodology Resources

Data Supplement