Approach to pre-analytical errors in a public health laboratory

Avcı, Esin; Çeken, Nihan; Kangal, Zeliha; Demi̇r, Süleyman; Emekli, Dilek Iren; Zorbozan, Nergiz

doi:10.1515/tjb-2016-0197

Cited by 5 publications

(6 citation statements)

References 10 publications

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“…Furthermore, the accuracy with which pre-analytical variables are identified by personnel working in the coagulation laboratory was not previously examined. Training workshops offered in past studies focussed primarily on non-laboratory personnel involved in specimen collection, handling and transport during the pre-analytical phase [ 24 – 26 ]. These studies identified the impact of such training by determining sample rejection rates before and after intervention.…”

Section: Discussionmentioning

confidence: 99%

The impact of laboratory staff training workshops on coagulation specimen rejection rates

2022

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Background Pre-analytical variables can have a significant adverse impact on the quality and credibility of coagulation test results. Therefore, correct and consistent identification of pre-analytical variables that compromise coagulation specimen quality is of paramount importance. Lack of standardization and heterogeneity among laboratory staff when assessing coagulation specimens can lead to inconsistent identification of these variables. Failure to recognize such pre-analytical variables results in the analysis of poor quality specimens and the authorization of spurious test results. Objectives To determine the impact of a laboratory staff training workshop on coagulation specimen rejection rates and to ascertain the level of knowledge of laboratory personnel concerning coagulation specimen rejection criteria before and after the workshop. Methods A retrospective three-month audit was performed with rejection data of incorrect blood to additive ratio, clotted, aged and haemolysed specimens collected. Training workshops and evaluation sessions were subsequently presented. A revised standard operating procedure delineating coagulation specimen rejection criteria was implemented and a repeat three-month audit was conducted. Results In total, 13 162 coagulation specimens were received during the initial audit with 1 104 specimens (8.39%) rejected. Following the workshops, the rejection rate increased by 3.49% to 11.88% with 12 743 coagulation specimens received and 1 514 specimens rejected. Evaluation sessions performed before and after the workshops revealed that 95.2% of attendees attained improved knowledge. Conclusion This study demonstrated the pivotal importance of regular laboratory staff training. The increase in specimen rejection following the workshops signifies their success in educating laboratory personnel regarding the correct identification of pre-analytical variables. Since most pre-analytical variables occur outside the laboratory, educational workshops need to be extended to non-laboratory personnel responsible for specimen collection and transport.

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Section: Discussionmentioning

confidence: 99%

The impact of laboratory staff training workshops on coagulation specimen rejection rates

2022

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“…Beş yüz doksan bir reddedilen numunenin 422'sinin hemoliz nedeni ile gerçekleşmesi kan alımı ile ilgili bir sorunun varlığını bize göstermektedir. Yapılan bu analiz sonucunda, kan alımı ile ilgili eğitimin ilgili sağlık personeline verilmesi, teknik hataların giderilmesi ve eğitimlerin sürdürebilirliğin sağlanması gerekmektedir (10) .…”

Section: Discussionunclassified

“…Yine Avcı ve ark. (10) preanalitik evreye yönelik aile hekimleri ve kan alma elemanlarına verdikleri eğitim sonucunda hataların giderek azaldığını kalite indikatörleri başlığı altında ortaya koymuşlardır.…”

Section: Hastane Bölümlerine Göreunclassified

“…Bütün preanalitik evre çalışmaları bu evredeki hataların hiçbir zaman sıfıra indirilemeyeceğini ancak azaltılabileceğini desteklemektedir. Bunun da ancak etkin ve doğru bir preanalitik evre eğitim protokolünün oluşturulması, eğitimlerin ilgili kişilere görsel teknik uygulamalar ile anlatılması ve eğitimlerin devamlılığın sağlanması ile olası kılınabilecektir (10,14) . Yine laboratuvarklinisyen-numune alan sağlık personeli arasındaki iletişimin etkin hâle getirilmesinin de ret oranlarını azaltabileceğini düşünmekteyiz.…”

Section: Hastane Bölümlerine Göreunclassified

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Sigmametric evaluation of preanalytical errors in a medical microbiology laboratory

Çeken¹,

Avcı²,

Duran³

2018

TMCD

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ÖZ Amaç: Tıbbi laboratuvar hatalarının %70'inden fazlası preanalitik evrede gerçekleşmektedir. Hataların analizi ve kayıt altına alınması, durum değerlendirilmesi ve hataların önlenebilmesi için gereklidir. Çalışmamızda mikrobiyoloji laboratuvarı preanalitik evre hataları değerlendirilerek altı sigma yaklaşımı ile değerlendirilmesi sınıflanması amaçlandı. Gereç ve Yöntem: Tıbbi Mikrobiyoloji Laboratuvarı'nda analiz için uygun olmadığı saptanan numuneler, hata kategorileri, örneklerin geldiği hastane birimleri ve analizi gerçekleştirilen laboratuvar alanları olmak üzere üç ana başlık altında sınıflandırıldı. Bunun için milyonda hata oranı saptanarak sigmametrik hesaplama yapıldı. Hesaplanan değerler ≥5.0 ise çok iyi, 4.0-<5.0 arasında ise iyi, 3.0-<4.0 arasında ise minimum ve <3.0 kabul edilemez olarak sınıflandırıldı. Bulgular: Sigmametrik değerlendirmeye göre kabul edilemez ve minimum hata yoktu. ≥5.0 sigma değerine sahip olanlar hata kategorilerine göre yapılan analizde pıhtılı, Lipemik, yetersiz, yanlış kaba alınması, hatalı barkot, laboratuvar analiz birimlerinden ise seroloji idi. 4.0-<5.0 arasında olanlar ise hata kategorilerine göre yapılan analizde hemolizli ve uygun olmayan numune, tüm örnek gelen hastane birimleri (poliklinik, servis ve yoğun bakım), laboratuvar analiz birimlerinden ise nefelometre, ELISA ve bakteriyoloji olarak saptandı. Sonuç: Sürekli veri analizi preanalitik evre hatalarının kontrol altına alınması için kaçınılmazdır. Preanalitik faz ile ilgili eğitimlerin sürekliliğinin sağlanması ve teknolojik alt yapının güçlendirilmesi bu evrenin kontrolünü sağlayacak temel faktörlerdir. ABSTRACT Sigmametric Evaluation of Preanalytical Errors in a Medical Microbiology LaboratoryObjective: More than 70% of medical laboratory errors occur in the pre-analytical phase. Analysis and recording of errors are necessary for evaluation and prevention of errors. We aimed to evaluate the phases of pre-analytical errors of microbiology laboratory and classify them according to six sigma approaches. Material and Methods:Samples which were considered inappropriate for the analysis at the medical microbiology laboratory were evaluated under the three headings as error categories, hospital units and laboratory areas where the analyses were done. Error ratio in one million was determined, and expressed on a sigma scale. The calculated sigma values were classified as follows: "very good", ≥5.0; good, 4.0-5.0; minimum, 3.0 and <4.0, and unacceptable <3.0. Results: There were no unacceptable or minimum errors according to sigmametric evaluation. Samples that were evaluated as having a sigma value of ≥5.0 according to error categories were clotted, lipemic, inadequate samples, samples collected in inappropriate containers, faulty barcodes, and those sent from units of serologic analysis. Those with a sigma value between 4.0<5.0 according to error categories were samples with hemolysis, inappropriate samples, the samples sent from all hospital units namely outpatient clinics, wards and intensive care units, laborat...

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“…In addition, the physician, health personnel (nurse, laboratory technician staff ), secretary, trainee student, and transport staff regularly receive training in laboratory processes, blood collection, and sample transport once a year. Studies in the literature have demonstrated the preliminary effects of continuing education on laboratory errors [17][18][19][20].…”

Section: Discussionmentioning

confidence: 99%

The evaluation laboratory quality indicators of biochemistry laboratory under the national Laboratory Error Classification System

Alpdemir¹

2018

Int J Med Biochem

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The national Laboratory Error Classification System (LECS) was developed by the Turkish Ministry of Health in 2015 to improve the quality processes of laboratories and enhance patient safety. This study was an evaluation of laboratory processes and quality indicators (QIs) in biochemistry laboratories according to the LECS criteria. Methods: This retrospective study included 4757 samples of a total of 649,001 samples collected between October 1, 2015 and December 30, 2016 and classified according to the LECS. The data regarding the number and type of rejected samples were obtained from the laboratory information system of Balıkesir State Hospital. Laboratory processes were also analyzed according to the LECS categories and counted on a monthly basis. The data were expressed as percentages. Results: The rate of error in the pre-, intra-, and post-analytical phase was 81.7%, 1.7%, and 16.6%, respectively. Overall, the most common error type was a clotted sample (0.28%). The primary location of error was the emergency service (25.6%). The time intervals during which the most errors occurred were 8:00-12:00 and 12:00-16:00 (30%). The professional group that made the most errors was the nurse group (64.6%). Conclusion: Different QIs have been used in clinical laboratories in Turkey and in the world in recent years to comply with the requirements of accreditation standards. In the present study, QIs were evaluated according to the LECS. These indicators provide a means to compare the performance of individual laboratories. These results may contribute to future laboratory test procedures and reduce error rates.

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Approach to pre-analytical errors in a public health laboratory

Cited by 5 publications

References 10 publications

The impact of laboratory staff training workshops on coagulation specimen rejection rates

The impact of laboratory staff training workshops on coagulation specimen rejection rates

Sigmametric evaluation of preanalytical errors in a medical microbiology laboratory

The evaluation laboratory quality indicators of biochemistry laboratory under the national Laboratory Error Classification System

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