{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T11:50:38Z","timestamp":1791287438550,"version":"4.1.0"},"reference-count":34,"publisher":"Croatian Society for Medical Biochemistry and Laboratory Medicine","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biochem. med. (Online)"],"published-print":{"date-parts":[[2026,10,15]]},"abstract":"<jats:p>Introduction: For measurands with a low index of individuality (II), delta check is crucial. If delta percentage change (DPC) values in different patients consecutively exceed the reference change value (RCV), it may indicate an analytical problem. Similarly to moving sum (MovSuM), percentage of DPCs exceeding RCV can be used as a quality control model by comparing it with a certain threshold. This study aimed to develop a novel patient-based quality control (PBQC) model using delta checks and evaluate its performance.\nMaterials and methods: The study was performed at Gazi University Biochemistry Laboratory. The model was tested on creatinine (measured on Advia Chemistry Systems using the alkaline picrate method), with pooled-CVa = 2.5%, CVi = 4.7%, and RCV = 19%. If DPC &gt; RCV, it was counted as a violation, i.e. failed delta check (FDC). The percentage of violations was calculated for every 20 consecutive patients with previous results over the past year. Similarly to MovSuM, when a new result is added, moving percentage of failed delta checks (MPFDC) removes the oldest data and calculates the percentage of violations continuously. Moving percentage of failed delta checks thresholds determined as 35%\/30% (for positive\/negative direction). After excluding dialysis patients and patients without previous results, and previous results measured with different systems, we applied truncation (truncation limits: &lt; 27 and &gt; 362 \u03bcmol\/L). The remaining 5484 results were divided into 55 batches.\nResults: After applying positive and negative errors of 15%, median number of patients affected before error detection (MNPed) was 34 and 29, respectively. Median time until error detection was 18 minutes. Sensitivity and specificity were 96% and 86%, respectively.\nConclusions: Moving percentage of failed delta checks, a novel RCV-based PBQC model, has high sensitivity and rapid error detection, suitable for measurands with low II.<\/jats:p>","DOI":"10.11613\/bm.2026.030701","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T07:07:37Z","timestamp":1786691257000},"page":"488-500","source":"Crossref","is-referenced-by-count":0,"title":["Moving percentage of failed delta checks"],"prefix":"10.11613","volume":"36","author":[{"given":"Niyazi Samet","family":"Yilmaz","sequence":"first","affiliation":[{"name":"Department of Medical Biochemistry, Gazi University Faculty of Medicine, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bayram","family":"Sen","sequence":"additional","affiliation":[{"name":"Department of Clinical Biochemistry, Recep Tayyip Erdogan University Training and Research Hospital, Rize, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sena","family":"Turkmen","sequence":"additional","affiliation":[{"name":"Department of Medical Biochemistry, Gazi University Faculty of Medicine, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hikmet Can","family":"\u00c7ubuk\u00e7u","sequence":"additional","affiliation":[{"name":"Rare Diseases Department, General Directorate of Health Services, Turkish Ministry of Health, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ozlem","family":"Gulbahar","sequence":"additional","affiliation":[{"name":"Department of Medical Biochemistry, Gazi University Faculty of Medicine, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4885","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"key":"key20260814070733_r1","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1515\/cclm-2016-0217","article-title":"Improving 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