Unnecessary repeated total cholesterol tests in biochemistry laboratory

Differences between repeated lipid profile measurements in a tertiary hospital over a short time period

BACKGROUND

Measurement of the plasma lipid profile, mainly low-density lipoprotein cholesterol (LDL-C), is widely used in the management of hospitalized patients as part of their cardiometabolic risk assessment. In common practice, LDL-C is calculated indirectly by the Friedewald equation. For many years, fasting of 8-14 h is needed to obtain an accurate lipid profile measurement, although recent guidelines do not necessitate it. The aim of this study was to find patients with two consecutive LDL-C measurements taken over a short time period on the same admission to see if a significant difference exists and to suggest reasons that may explain it. We also aim to define whether the difference between LDL-C calculated by the Friedewald equation is diminished while using the newer Martin/Hopkins, de Cordova or Sampson/NIH equations.

METHODS

This was a retrospective cohort study performed in one medical center in Israel. In a five-year time period, 772 patients with two repeated LDL-C measurements taken on the same admission were found. The median time gap between tests was 2 days. Correlations between laboratory results and LDL-C measurements were determined.

RESULTS

A total of 414 patients (53.6%) had a difference greater than the acceptable total error of 8.9% in LDL-C calculation using the Friedewald equation, with a mean 25.8% difference between the two tests. Newer LDL-C calculations showed less diversity. Non-HDL-C was found as the only variable with a major correlation with LDL-C results in all equations. A weaker correlation was found with HDL-C. Triglycerides showed an even weaker correlation, and glucose differences had no correlation with LDL-C differences.

CONCLUSIONS

Repeated LDL-C measurements can vary widely, even during a short period of hospitalization. In this study, more than half of the patients had a significant difference between their consecutive LDL-C results. This wide difference between two consecutive tests was diminished using newer calculations, yet not well explained. The fasting state likely has no effect on LDL-C levels. The results of this study might emphasize that many factors influence LDL-C calculation, especially in the disease state. Further research is needed, especially in looking for a more accurate LDL-C calculation from existing formulas.

Minimum retesting intervals in practice: 10 years experience

Background

Minimum retesting intervals (MRI) are a popular demand management solution for the identification and reduction of over-utilized tests. In 2011 Association of Clinical Biochemistry and Laboratory Medicines (ACB) published evidence-based recommendations for the use of MRI.

Aim

The aim of the paper was to review the use of MRI over the period since the introduction of these recommendations in 2011 to 2020 and compare it to previous published data between 2000-2010.

Methods

A multi-source literature search was performed to identify studies that reported the use of a MRI in the management or identification of inappropriate testing between the years prior to (2000–2010) and after implementation (2011–2020) of these recommendations.

Results

31 studies were identified which met the acceptance criteria (2000–2010 n=4, 2011–2020 n=27). Between 2000 and 2010 4.6% of tests (203,104/4,425,311) were identified as failing a defined MRI which rose to 11.8% of tests (2,691,591/22,777,288) in the 2011–2020 period. For those studies between 2011 and 2020 reporting predicted savings (n=20), 14.3% of tests (1,079,972/750,580) were cancelled, representing a total saving of 2.9 M Euros or 2.77 Euro/test. The most popular rejected test was Haemoglobin A1c which accounted for nearly a quarter of the total number of rejected tests. 13 out 27 studies used the ACB recommendations.

Conclusions

MRI are now an established, safe and sustainable demand management tool for the identification and management of inappropriate testing. Evidence based consensus recommendations have supported the adoption of this demand management tool into practice across multiple healthcare settings globally and harmonizing laboratory practice.

An Audit of Repeat Testing at an Academic Medical Center: Consistency of Order Patterns With Recommendations and Potential Cost Savings

OBJECTIVES

To evaluate the prevalence of potentially unnecessary repeat testing (PURT) and the associated economic burden for an inpatient population at a large academic medical facility.

METHODS

We evaluated all inpatient test orders during 2016 for PURT by comparing the intertest times to published recommendations. Potential cost savings were estimated using the Centers for Medicare & Medicaid Services maximum allowable reimbursement rate. We evaluated result positivity as a determinant of PURT through logistic regression.

RESULTS

Of the evaluated 4,242 repeated target tests, 1,849 (44%) were identified as PURT, representing an estimated cost-savings opportunity of $37,376. Collectively, the association of result positivity and PURT was statistically significant (relative risk, 1.2; 95% confidence interval, 1.1-1.3; P < .001).

CONCLUSIONS

PURT contributes to unnecessary health care costs. We found that a small percentage of providers account for the majority of PURT, and PURT is positively associated with result positivity.