Objectives There is bountiful evidence of ambulatory patient over-testing, both in terms of the tests ordered and their frequency. To be thorough and efficient, many physicians pay short shrift to sustainable test ordering. We have developed a calculus that transforms sequential intra-patient test results into total variation comprising its preanalytical, analytical and biological components. We have used this approach to compare the analytical and clinical performance of multiple analytical systems. Here, we determine the total test variation in patients with test separation intervals of 90, 180, 270 and 365 days. We demonstrate that annual testing with phlebotomies scheduled at the same time of day minimizes the variation of the sequential test results and permits optimal discrimination of a statistically significant change in the test results.
Method We studied 5 years (2014-2019) of Ottawa Hospital adult outpatient general chemistry test pairs of albumin, alanine aminotransferase, aspartate aminotransferase, calcium, chloride, bicarbonate, creatinine, potassium, magnesium, sodium, phosphate, total bilirubin and urea. Intrapatient data pairs (separated by 88-92, 178-182, 268-272 and 363-367 days), were divided into 2 groups: those sampled on weekdays at the same time of day (+ 2 hr) and those with 3 to 8 hr sampling differences . The between pair variations were derived calculated with Dahlberg’s formula.
Results The median numbers of patient pairs/analyte for the matched sampling times were 1034 (90 days), 696 (180 days), 84 (270 days) and 364 (365 days). For the unmatched sampling times, the median numbers of patient pairs were much smaller, ranging between 38 to 290 and their average variations exceeded the matched pair variations by as much as 30% (phosphate and creatinine). The matched pair 90, 180, 270 and 365 day variations were highly correlated (r ranged from 0.965 to 0.977). Compared to the other periods, the 180 day variations were smaller (-7.5%) and the 270 day variations were larger (+11.9%). Overall, the 365 day magnitudes of variations were closest to the magnitudes of variation of the other periods.
Conclusions At least £2.2 billion are spent annually on UK pathology services, a significant portion wasted on suboptimal testing including: 1) tests are ordered too closely, providing little new information 2) tests that are ordered 9 months later and have been influenced by seasonal factors or 3) sequential tests that are ordered at different times of the day and are influenced by diurnal variation. Biological variation can be a guide to reducing test wastage and setting a standard for testing intervals that are minimally one year with the patient being sampled at the same time of day. Simple algorithms incorporating minimal sequential data would be able to discern real laboratory trends far more readily than ‘thorough and efficient’ but over-testing clinicians.
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