SummaryBackgroundAfter the introduction of modern laboratory instruments and information systems, preanalytic phase is the new field of battle. Errors in preanalytical phase account for approximately half of total errors in clinical laboratory. The objective of this study was to share an experience of an education program that was believed to be successful in decreasing the number of rejected samples received from the Emergency Department (ED).MethodsAn education program about laboratory procedures, quality requirements in the laboratory, patient and health-care worker safety was planned by the quality team to be performed on 36 people who were responsible for sample collection in the ED. A questionary which included 11 questions about the preanalytic phase was applied to all the attendees before and after training. The number of rejected samples per million was discovered with right proportion account over the number of accepted and rejected samples to laboratory after and before the training period.ResultsMost of the attendees were nurses (n: 22/55%), with over 12 years of experience in general and 2–4 years experience in the ED. Knowledge level of the attendees was calculated before training as 58.9% and after training as 91.8%. While the total rate of sample rejection before training was 2.35% (sigma value 3.37–3.50), the rate after training was 1.56% (sigma value 3.62–3.75).ConclusionsIncreasing the knowledge of staff has a direct positive impact on the preanalytic phase. The application of a pre-test was observed to be a feasible tool to shape group specific education programs.

Objectives An excessive inflammatory response to SARS-CoV-2 is thought to be a major cause of disease severity in COVID-19. The aim herein was to determine the prognostic value of IL-6, and demonstrate the comparison between IL-6 and related parameters in COVID-19. Methods Data were collected from 115 COVID-19 patients. Results The median age was 46.04 years in the mild group, 56.42 years in the moderate group, and 62.92 years in the severe group (p=0.001). There was a significant difference in the hospitalized clinic to intensive care unit ratio among the patients (p<0.001). The IL-6 values were significantly higher in the severe group than those in the mild (p=0.04) and moderate groups (p=0.043). The area under the receiver operating characteristic curve for IL-6, as predictor of severe clinical condition, was 0.864 (95% CI 0.765–0.963 p=0.000). The longitudinal analyses showed that the severe group presented with significantly increased IL-6 levels during hospitalization. Conclusions IL‐6 seemed to be a guide in the early diagnosis of severe COVID-19 and an ideal marker for monitoring negative outcome.

Bu araştırmanın amacı, Pabon Lasso Modeli ve Veri Zarflama Analizi (VZA) yöntemi ile Antalya Kamu Birliğine bağlı hastanelerin performans düzeylerini tespit etmektir. Materyal-Method: Araştırmada hastanelerin performans düzeylerini tespit edebilmek için VZA ve Pabon Lasso modeli kullanılmıştır. VZA yönteminde değişkenler dört girdiden (uzman hekim, hemşire, yatak sayısı, toplam gider) ve altı çıktıdan (poliklinik sayısı, A-B-C grubu ameliyat sayısı, yatak doluluk oranı, sağlık hizmeti geliri) oluşmaktadır. Pabon Lasso modelinde ise değişken olarak hastane performans göstergeleri olan; yatak doluluk oranı, yatak devir hızı ve ortalama yatış süresi alınmıştır. Araştırma verileri Antalya Kamu Hastane Birliği'nden temin edilmiştir. Verilerin analizinde MS Visio, MS Excel ve DEAP yazılımlarından yararlanılmıştır. Bulgular: Araştırma verilerinden elde edilen bulgulara göre Pabon Lasso modeline göre hastanelerin %51'nin tamamen verimli, VZA yöntemine göre ise hastanelerin % 67'nin verimli olduğu saptanmıştır. VZA yöntemine göre hastanelerin %33'ü orta ve düşük düzeyde verimsiz iken, Pabon Lasso modeline göre hastanelerin %49'nun verimsiz olduğu belirlenmiştir. Ayrıca araştırmada VZA yöntemine göre verimsiz olan hastanelerin Pabon Lasso modeline göre de verimsiz olduğu tespit edilmiştir. Sonuç: Paban Lasso modeli hastanelerin yatak kullanım performansı hakkında önemli bilgiler vermektedir. Bu nedenle hastanelerin performans ölçümünde VZA yönteminin yanında Pabon Lasso modelini de kullanması tavsiye edilmektedir. Antalya Kamu Hastane Birliği hastaneler arasında kaynak tahsisini rasyonel yöntemlerle sağlanmalı ve verimsiz hastaneleri verimli hale getirecek planlama ve stratejiler geliştirilmelidir.

Summary Background Phlebotomy is one of the most important steps in the preanalytical phase of a clinical laboratory process. In order to decrease phlebotomy errors, this specific procedure should be taught in detail by laboratory organizations. Our study aims to practice the training program on venous blood sampling and observe the close follow-up results. Methods In this observational study, 127 students who started their summer internship in Antalya Education and Research Hospital were given a one-day theoretical phlebotomy training in accordance with the Venous Blood Sampling Guidelines. After the theoretical training, phlebotomy applications of 10 students who were working in the field of out-patient blood sampling were observed both with and without their knowledge. A comprehensive checklist related to phlebotomy was created by the trainers in Antalya Education and Research Hospital and the observers answered each question as yes or no. For the statistical analysis, IBM SPSS Statistics 21.0 was used. Results After the theoretical education, the trainees were observed but no significant difference was found between the first and the second informed observations (p = 0.125). The students were observed three times more in the following week without their knowledge. There was a statistically significant difference between the first and the third unannounced observations (p=0.001). Conclusions In order to perform phlebotomy correctly, apart from theoretical education, a close follow-up is necessary too.

Background/aim: COVID-19 cases originated in Wuhan and it has become a global problem. The purpose of study to examine the rate of re-hospitalisation within 30 days after the completion of medical treatments for patients suffering from COVID-19. Materials and methods: In this study, the results of COVID-19 patients who were re-admitted to the hospital within 30 days were examined. The general and clinical characteristics of the patients and laboratory results were evaluated using parametric and nonparametric tests. Results: Included in this study were 22 patients, comprising 14 males and 8 females, with re-hospitalisation rate within 30 days and a diagnosis of COVID-19 that was 0.6%. The mean age of the patients who were re-hospitalised was 56.45 years. The major clinical symptoms of the patients who were re-hospitalised, respectively, were cough, shortness of breath, fever. When the levels from the first hospitalisation and the second hospitalisation were compared, an increase in the LYM count and N/L ratio was detected and the difference was statistically significant. Conclusion: A holistic patient assessment and care approach should be adopted by evaluating the symptomatic complaints as well as the comorbidities of the patients, so as to reduce the number of re-hospitalisations.

Objective: The rate of readmissions to the emergency room is an important indicator of measuring hospital performance and quality of care. This study aimed to determine the demographic and clinical characteristics of the patients with confirmed COVID-19, who presented to the emergency room of a training and research tertiary hospital and received medical treatment, but were readmitted to the hospital within 72 hours after being discharged. Materials and Methods: This is a retrospective, descriptive, cross-sectional, and single-centre trial. The data of patients who presented to the emergency room with the diagnosis of COVID-19 were obtained retrospectively from the Hospital Information Management System. Patient data comprised adult patients readmitted to the hospital between 01 March and 31 December 2020. Results: Between 01 March and 31 December 2020, a total of 56,497 patients with the diagnosis of COVID-19 presented to our emergency room, and 0.04% of them returned to the emergency room with similar complaints within 72 hours. Among those who returned, 51.4% were female and the mean age was 41.67, mostly in the 30-49 age range. The present study found that 30.8%, who were readmitted, had at least one comorbidity, and those with comorbidities had lower saturation values at the readmission. On the other hand, the most common reason for admission in patients without comorbidities was found to be diarrhoea and loss of taste, while nausea and cough were the most common complaints in patients with comorbidities. Conclusion: There is a need for the design of further studies in order to establish the criteria for the safe return of COVID-19 patients to home, and to reduce the re-admission rates and increase the quality of care.

Bu araştırmanın amacı, Akdeniz Bölgesi'nde faaliyet gösteren kamu hastanelerinin göreceli teknik etkinlik düzeylerini belirlemektir. Yöntem: Araştırmada, hastanelerin performanslarının belirlenmesinde Veri Zarflama Analizi (VZA), Analitik Hiyerarşi Prosesi (AHP) ve Pabon Lasso Modeli (PLM) kullanılmıştır. İlk olarak ağırlık kısıtlaması olmadan VZA, daha sonra AHP ile elde edilen ağırlıklı VZA modeli uygulanmıştır. En son aşamada yatak kullanım performasını belirlemede PLM kullanılmıştır. Bulgular: VZA modeline göre hastanelerin %34'ü teknik düzeyde verimlidir. Girdi ve çıktıların ağırlıkları dikkate alınarak yapılan VZA'ya göre hastanelerin %12,8'inin teknik düzeyde verimli olduğu tespit edilmiştir. PLM'ye göre hastanelerin %31,9'unun en verimli bölgede (3. Bölge) yer aldığı saptanmıştır. Özgünlük: Bu araştırmada hastane verimliliklerini belirlemede hibrit yöntem olan Veri Zarflama Analitik Hiyarşi Prosesi (VZAHP) ve PLM yöntemleri birlikte ele alınmıştır. Hibrit yöntemlerin birlikte kullanılarak hastanelerin performansına yönelik kanıta dayalı bilgiler sunulması, yapılan çalışmanın özgünlüğü ortaya koymakta ve literatürdeki eksikliği dolduracağı öngörülmektedir.

n the book chapter, the basic structure, features, axioms, advantages and disadvantages of AHP will be given. Then, AHP application steps will be explained with a sample application in the exell program, and screen shots will be included in the lecture. As an example application, how the personnel selection in the field of health is made with AHP will be explained in detail. If the results are not consistent, what should be done will be explained. As a result, the readers will have an idea about solving the AHP problem through the excel program and will be able to apply it easily.