Critical Value Notification Research Articles

The surveys on quality indicators for the total testing process in clinical laboratories of Fujian Province in China from 2018 to 2023.

This study investigates the application of 15 Quality Indicators (QIs) in clinical laboratories in Fujian Province, China, from 2018 to 2023. It identifies the main causes of laboratory errors and explores issues in the application of QIs, providing a reference for establishing provincial state-of-the-art and operational quality specifications (QSs). All clinical laboratories in Fujian Province were organized to submit general information and original QIs data through the online External Quality Assessment (EQA) system of the National Clinical Laboratory Center (NCCL) for a survey of 15 QIs. Data from 2018 to 2023 were downloaded for statistical analysis, and the current QSs for the 15 QIs in Fujian Province were compared and analyzed with those published by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group on Laboratory Errors and Patient Safety (WG-LEPS). QIs data from 542 clinical laboratories were collected. The survey on data sources showed that the number of laboratories recording QIs data using Laboratory Information Systems (LIS) increased annually, but the growth was modest and the proportion was less than 50 %. Among the laboratories using LIS to record QIs data, 133 continuously participated in this survey for six years, reporting different QIs. Over the six years, all reported QIs showed significant improvement or at least remained stable. The best median Sigma (σ) metrics were for the percentage of critical values notification and timely critical values notification, reaching 6σ, followed by the percentage of incorrect laboratory reports, with σ metrics ranging from 4.9σ to 5.1σ. In contrast, the percentage of tests covered by internal quality control (IQC) (1.5σ-1.7σ) and inter-laboratory comparison (0.1σ) remained consistently low. Compared to the QSs published by IFCC WG-LEPS, the QSs for the 15 QIs in Fujian Province in 2023 were stricter or roughly equivalent, except for the percentage of incorrect laboratory reports (Fujian Province: 0-0.221, IFCC WG-LEPS: 0-0.03). 1. The application of QIs has significantly improved the quality of testing in clinical laboratories in Fujian Province, but the percentage of tests covered by IQC and inter-laboratory comparison remain low; 2. Effective application of QIs requires the establishment of comprehensive LIS, unified calculation standards, and other supporting measures.

Effects of the implementation and evolution of critical value notification

Effects of the implementation and evolution of critical value notification

Critical values notification: A nationwide survey of practices among clinical laboratories across Nigeria.

Critical value notification (CVN) entails notifying doctors or other laboratory users of aberrant laboratory results that threaten the patient's life and of any values for which reporting delays could negatively impact the patient's health. Critical value notification practices in clinical laboratories in Nigeria and sub-Saharan Africa are largely unknown. We conducted a nationwide survey to obtain baseline information on CVN practice by Nigeria's laboratories. This cross-sectional study was conducted among purposively selected secondary- and tertiary-tier, public and private clinical laboratories across northern and southern Nigeria between October 2015 and December 2015. Consenting senior laboratory staff completed and returned a structured questionnaire, that gathered data on respondents' demographics, designations, and institutional characteristics and practices regarding CVN. One hundred and thirty-four laboratories responded to the questionnaires. Only 69 (51.5 %) laboratories practised CVN; only 23 (33.3%) had existing written policies guiding the practice. Most (43; 62.3%) laboratories use similar critical values (CVs) for adult and paediatric populations. Most laboratories (27; 39.1%) obtained their CVs by combining published literature and local opinions from stakeholders. Physical dispatch (42; 60.9%) followed by telephone calls (38; 55.1%) were the most common means of notification. Private laboratories, compared with public hospital laboratories, were likelier to have separate paediatric CV lists (p = 0.019) and practise telephone notifications (p < 0.001). Critical value notification practices vary and are often suboptimal in many clinical laboratories in Nigeria, which is exacerbated by the absence of guiding policies and national recommendations for post-analytical procedures. This study provides baseline information on CVN practice by Nigeria's laboratories. The study explores the causes of practice variations that can serve as a foundation for enhancing critical reporting and post-analytical services, particularly in clinical laboratories in sub-Saharan Africa.

Short-term All-cause In-hospital Mortality Prediction by Machine Learning Using Numeric Laboratory Results.

A critical value (or panic value) is a laboratory test result that significantly deviates from the normal value and represents a potentially life-threatening condition requiring immediate action. Although notification of critical values by critical value list (CVL) is a well-established method, their contribution to mortality prediction is unclear. A total of 335,430 clinical laboratory results from 92,673 patients from July 2018 to December 2019 were used. Data in the first 12 months were divided into two datasets at a ratio of 70:30, and a 7-day mortality prediction model by machine learning (eXtreme Gradient Boosting [XGB] decision tree) was created using stratified random undersampling data of the 70% dataset. Mortality predictions by the CVL and XGB model were validated using the remaining 30% of the data, as well as different 6-month datasets from July to December 2019. The true results which were the sum of correct predictions by the XGB model and CVL using the remaining 30% data were 61,535 and 61,024 tests, and the false results which were the sum of incorrect predictions were 5,492 and 6,003, respectively. Furthermore, the true results with the different datasets were 105,956 and 102,061 tests, and the false results were 6,052 and 9,947, respectively. The XGB model was significantly better than CVL (p < 0.001) in both datasets.The receiver operating characteristic-area under the curve values for the 30% and validation data by XGB were 0.9807 and 0.9646, respectively, which were significantly higher than those by CVL (0.7549 and 0.7172, respectively). Mortality prediction within 7 days by machine learning using numeric laboratory results was significantly better than that by conventional CVL. The results indicate that machine learning enables timely notification to healthcare providers and may be safer than prediction by conventional CVL.

A study of critical value analysis at hematology and biochemistry sections of laboratory in a multispeciality hospital

The issue of laboratory critical value (CV) reporting has gained importance in the recent times due to the national focus on patient safety. Critical value notification (CVN) has become an essential part of accreditation procedures for medical laboratories, including the universally accepted International Organization for Standardization (ISO) 15189: 2012. Our study aimedto analyze the critical value data in hematology and biochemistry sections of the laboratory, to compare the frequencies of critical values for different parameters and to suggest measures for improving the effectiveness and operational efficiency of the critical value notification process.Our study was a retrospective, cross-sectional, descriptive study done over a period of one year six months (January 2020 to June 2021). The parameters chosen for CVN included platelets, hemoglobin and International Normalized Ratio (INR) from hematology section and creatinine, glucose, sodium, potassium and calcium from the biochemistry section. A test result that was significantly outside the normal range and that required immediate communication was considered as a “critical value (CV)”. Both verbal (through telephone) and non-verbal [through short message service (SMS)] communication processes for CVN were implemented in our lab. We also followed the practice of CV “read-back” by the person who was informed over the phone. A total of 2199 critical values were reported. A maximum of 1224 (55.7%) critical values were recorded from the emergency department. CVs were highest from biochemistry (1898, 86.3%) section. Analyte most commonly notified was creatinine (1151, 52.3%). CVNs were maximum in the morning shifts (1378, 62.7%).Implementation of the critical alert short message service (SMS) send outs has greatly helped us in reducing the CV turn around time (TAT). Our study has successfully demonstrated the importance of both verbal and non-verbal communication processes for notification of CVs.

Baseline assessment of staff perception of critical value practices in government hospitals in Kuwait

BackgroundNotification of laboratory-determined critical values is key for effective clinical decision making and is thus a consequential step in a patient’s health care and safety. This study presents an overview of staff reporting policies and procedures concerning critical values in Kuwaiti governmental hospitals.MethodsA cross-sectional descriptive study design was adopted. Study subjects were affiliated with laboratories from five government hospitals (four general and one sub-specialty hospital). All laboratory staff in every hospital were included. The Statistical Package for the Social Sciences (version 23) was used to analyse the collected data at a significance level of ≤ 0.05. Quantitative data analysis included univariate descriptive (means, medians, standard deviations, frequencies, percentages) and bivariate (chi-squared, ANOVA and Kruskal–Wallis tests) analyses. These analyses provided associations between participating hospitals and staff perceptions towards the policies and procedures surrounding critical values.Results559 questionnaires were returned, a total response of 30.5% after those of 79 phlebotomists were excluded (eligible sample size n = 1833). The notification of critical values differs between participated laboratories in delivering protocol and time duration. Linked protocols between laboratories did not exist regarding policies and guidelines for applying the same procedures for critical value notification. There are differences in critical value limits among the participating laboratories.ConclusionThis study is the first to survey laboratory staff perceptions of critical value practices in Kuwaiti government hospitals. Enhancing critical value reporting and policy is crucial for improving patient safety and to develop high-quality health services. The findings of this study can help policy makers implement future intervention studies to enhance laboratory practices in the area of critical values and improve patient safety and the quality of government hospital systems.

Quality Tools and Strategy for Critical Alerts Process Improvements to Ensure Patient Safety.

Objectives A number of regulatory and accrediting bodies require the reporting of critical results on a timely basis (immediately or within the time frame established by the laboratory) to "the responsible, licensed caregiver" as timely notification of critical laboratory results can pivotally affect patient outcome. The aim of the study was to decrease the turnaround time (TAT) of critical result notification along with assurance of notification to the concerned caregiver or clinicians. The objectives was 30% reduction in the critical value notification TAT and identify factors associated with delayed reporting and root cause analysis for these factors by application of quality tools. Materials and Methods The study was conducted at the Institute of Human Behavior and Allied Sciences, Delhi, a tertiary center teaching Hospital, from April 2019 to June 2021. A value streamed Process Map of critical alert was prepared. The incidents related to failure were presented through Pareto chart. The possible causes were analyzed through the fishbone model. The failure mode prioritization was executed with Failure Mode and Effect Analysis (FMEA). Through extensive brainstorming, appropriate and feasible corrective actions were implemented. The effectiveness of the implemented plan was analyzed by reassessing the TAT of critical alert and feedback received by clinical caregivers. Results After implementation of corrective action plan using quality tools for 3 months, the average critical alert TAT was reduced to 21 minutes from 30 minutes (30% reduction). The median critical alert TAT for ICU, emergency, and IPD were reduced to 3 minutes (IQR: 1-7). During the pilot project, 156 critical value data were sent for feedback with treatment plan but was received only for 88 patients (56%). Conclusion Comprehensive utilization of quality tools has a potential role in patient safety by reducing the critical alert TAT as well as establishing an effective communication between laboratory personnel and clinicians.

Комп'ютерна система оповіщення критичних значень мікроклімату в приміщенні

An alert system has been studied, in which sensor data can be collected and analyzed for further processing and action. Notifications are generated when data is compared against certain criteria. The ESP8266 microcontroller has been chosen as the basic device for implementing such a system, as this Espressif controller is a highly integrated Wi-Fi SoC solution that meets the demands of the cyberphysical systems industry in low power consumption, compactness and reliability. This solution is one of the most effective for the alert system. On the basis of this microcontroller the technical means of the computer system and the functional software for realization of functions of monitoring and the notification of critical values of a microclimate indoors are designed. The architecture of the computer system is studied. The choice of the main components of the hardware part of the system is substantiated, the element base is considered. A detailed scheme of the software operation algorithm is offered, as well as the results of the developed computer system for alerting the critical values of the indoor microclimate are demonstrated.

Impact of COVID-19 on the pre and post analytical clinical laboratory testing processes- A performance evaluation study using six sigma

BackgroundThe aim of this study was to determine the impact of COVID-19 pandemic on the total testing process using six sigma metrics based on a comparison of pre and during pandemic periods. Material & methodsThe study duration was over 12 months, 6 months before and 6 months after the COVID-19 onset in Pakistan in March 2020 after the recognition of the first case, using quality indicators (QIs). QIs were chosen from a model of QIs recommended by the CAP. Analysis was performed using Six Sigma calculators and QIs were expressed in percentage (%) and Sigma value were computed. Three levels of performance quality i.e. 25th, 50th, and 75th percentile were derived, being best, common and worst performance respectively. Between-group differences were tested using the Mann-Whitney's U test. ResultsThe median defect percentages of these QIs ranged from 0% to 0.27% for the pre-pandemic period and 0% to 0.13% for the during pandemic period. Meanwhile, sigma values of the majority of the QIs were all above 4.0σ during the pre and the pandemic times. For the pre-analytical phase, sigma scores declined for 1 QI, improved for 3 QIs and remained same for 2. In the post analytical phase, no change in sigma metrics was noted for critical values notification. Considerable increase in defect percentage of inappropriate turnaround times was noted. ConclusionThe emergency preparedness proved to be fruitful as depicted by exceptional performance on the sigma metrics for most Qis both prior to and during the pandemic. The pre-analytical and the post analytical phases, being the most error sensitive requires strict vigilance.

Quality Improvement in Critical Value Delivery at a Tertiary Care Center.

Prompt notification of critical laboratory values to providers is essential for effective patient care. To improve the delivery of these critical values, a quality improvement project was initiated to determine the obstacles to prompt notification and to identify possible interventions to improve this process. Critical value call logs were retrieved, and delivery time, patient location, test name, and call time were abstracted and analyzed. All critical values with delivery times greater than 60 min were reviewed by 2 authors for 1 representative month in both the pre- and postintervention period. Based on the results of the data review, a modification to the laboratory information system call center color-coded alerts was introduced to address delays attributable to the laboratory. The overall rate of calls greater than 60 min decreased from 3.4% ± 0.8% in the preintervention study period to 1.3 ± 0.3%, postintervention. The average number of values not delivered within 60 min decreased by 64% across all locations, following with an 82% decrease for values originating from inpatient locations, and a 39% decrease for outpatient values. Low complexity interventions to critical value callback protocols can significantly increase the efficacy of communication between the laboratory and providers.

Risk assessment of the total testing process based on quality indicators with the Sigma metrics.

Background Evidence-based evaluation of laboratory performances including pre-analytical, analytical and post-analytical stages of the total testing process (TTP) is crucial to ensure patients receiving safe, efficient and effective care. To conduct risk assessment, quality management tools such as Failure Mode and Effect Analysis (FMEA) and the Failure Reporting and Corrective Action System (FRACAS) were constantly used for proactive or reactive analysis, respectively. However, FMEA and FRACAS faced big challenges in determining the scoring scales and failure prioritization in the assessment of real-world cases. Here, we developed a novel strategy, by incorporating Sigma metrics into risk assessment based on quality indicators (QIs) data, to provide a more objective assessment of risks in TTP. Methods QI data was collected for 1 year and FRACAS was applied to produce the risk rating based on three variables: (1) Sigma metrics for the frequency of defects; (2) possible consequence; (3) detection method. The risk priority number (RPN) of each QI was calculated by a 5-point scale score, where a value of RPN > 50 was rated as high-risk. Results The RPNs of two QIs in post-analytical phase (TAT of Stat biochemistry analyte and Timely critical values notification) were above 50 which required rigorous monitoring and corrective actions to eliminate the high risks. Nine QIs (RPNs between 25 and 50) required further investigation and monitoring. After 3 months of corrective action the two identified high-risk processes were successfully reduced. Conclusions The strategy can be implemented to reduce identified risk and assuring patient safety.

Improving Critical Value Notification through Secure Text Messaging

Background: To improve communication between clinical providers and the laboratory, we recently implemented secure text messaging for our critical value notifications. This was done to communicate laboratory critical values (CV) to providers faster so changes to patient care could be done faster. Our previous method of communicating CV to providers was paging and relied on a call back to receive the critical value. Methods: We implemented delivery of CV through a secure texting application in which the CV was directly communicated to the provider on their smart phone device. Results: The mean pre-implementation turnaround time (TAT) was 11.3 minutes (median: 7 minutes, range: 0 - 210 minutes). The mean post- secure text messaging implementation TAT was 3.03 minutes (median: 0.89 minutes, range: < 1 - 95 minutes).When comparing pre- and post-implementation, there was a significant reduction in the TAT from using secure text messaging (p < 0.001). Of the 234 surveys sent out, 81 providers responded (35%). Of these responses, 85% reported that critical value notification by secure text messaging has increased their efficiency and 95% reported that critical value notification is more effective than a pager-phone-call based system. 83% of providers reported that they were able to provide better, faster care to their patients. Conclusions: Using secure text messaging (STM) to deliver critical values significantly reduces the CV TAT. Furthermore, providers noted they preferred to receive CV notifications through STM and reported that they were able to provide more effective care to their patients.

Enhance the effectiveness of clinical laboratory critical values initiative notification by implementing a closed-loop system: A five-year retrospective observational study.

BackgroundAccurate and timely clinical laboratory critical values notification are crucial steps in supporting effective clinical decision making, thereby improving patient safety.MethodsA closed‐loop laboratory critical value notification system was developed by a multidisciplinary team of clinicians, laboratorians, administrators, and information technology experts. All the laboratory critical values that occurred at Beijing Tsinghua Changgung Hospital (BTCH, Beijing, China) from 2015 to 2019 were analyzed and studied retrospectively.ResultsThe total number (ratio) of institutional laboratory critical values to all reported items at BTCH from 2015 to 2019 was 38 020/7 706 962 (0.49%). Percentage distribution points of critical value boundaries based on patients’ test reports are 0.007% ~ 6.04% for low boundaries and 71.70% ~ 99.99% for high boundaries. After the intervention, the timely notification ratio, notification receipt ratio, and timely notification receipt ratio of critical values of ED, IPD, and total patients had increased, with a significant difference (P < .001). Five quality indicators, such as notification ratio, timely notification ratio, notification receipt ratio, timely notification receipt ratio, and clinician response ratio over a 5‐year period, were 100%, 94%, 97%, 92%, and 99%, respectively.ConclusionsWe enhanced the effectiveness of clinical laboratory critical values initiative notification by implementing a closed‐loop system and intervening. Clinical critical values and quality indicators should be analyzed and monitored to avoid adversely affecting patient care.

Effective Utilization of Laboratory Information System to Triage Troponin Critical Value Notification to the Emergency Department

Abstract Objectives The laboratory received a request to report abnormal troponin (ab-TnI) as critical values (CVs) for ED patients. The laboratory information system (LIS) was programmed to identify only ED patients presenting with an ab-TnI. Only the first ab-TnI on presentation was critical. Unnecessary laboratory CV communications could impair overall turnaround time. Methods Mean troponin, ab-TnI test volumes, and ab-TnI from ED patients with suspected acute coronary syndrome were determined. The LIS team constructed a best practice alert in the Beaker module (EPIC, Verona, WI). The ab-TnI CV build filtered patients based on ab-TnI values and ED location. Based on pilot data, the build was adjusted to limit ab-TnI alerts to only the first ab-TnI result. The amended build logic was to trigger the alert if an ED location TnI was abnormal. At trigger, if the lowest TnI result in the last 24 hours is ≤0.040, the return “true.” If true, then no TnI &gt;0.040 in the last 24 hours, call the ED because they currently have a result &gt;0.040. If the answer is “false,” then do not call the ED. If the patient had no TnI in the last 24 hours, then the alert would be triggered as well. The system was piloted after education to the ED and laboratory teams. Results The mean TnI per day was 150; the mean ab-TnI was 63 (42%), of which 1.1 ab-TnI originated from the ED. After pilot go-live, the actual number of ab-TnI/day was 14.3. The alert logic was amended to limit the trigger to the first ab-TnI result, reducing the CV volume to 9.6/day. Conclusion The LIS can be leveraged to develop a clinically valuable and operationally manageable critical value alert system. Clinical and laboratory teams must be open to amending the process as needed to achieve success.

Missed Critical Value Callbacks Due to Middleware Flaws

Abstract A provider notified the laboratory of a missed sodium critical value notification on a patient; during further investigation, it was noted that the laboratory had missed a second sodium critical value notification several hours later on the same patient. The two missed critical callbacks occurred on different shifts with different technologists, pointing to a systematic issue. A thorough investigation was undertaken involving review of critical callback procedures, staff interviews, and retrospective data review to determine the etiology. It was confirmed that the middleware, Siemens Centralink, had captured and displayed the critical values for review. The Centralink display highlights rows with critical results in red for easy visual identification by the laboratory technologist, and a numerical code of “8” appears in the Normal Severity (NS) column as an additional cue. Upon discussion with involved laboratory staff, a supervisor noted that sodium consistently appears in the top row of the Siemens Centralink result screen when held for review. Our Siemens Centralink display was noted to have a blue bar that by default appears in the top row and was noted to obscure the red highlight and NS Flag that provides a visual cue to staff that it is a critical value. Therefore, we hypothesized that the sodium critical values were missed due to being obscured by the default blue bar, and hypothesized that they could be preferentially affected relative to other analytes due to sodium’s default position in the top row when displayed. To investigate further, we pulled retrospective critical value callback data from our university hospitals for 2018. Our overall critical callback failure rates were ~2.0%. When broken down by individual analyte, we found that 7.2% of sodium critical values were not called back to providers, whereas only 1.0% of potassium critical values were missed. Additionally, critical callback failure rates for hemoglobin were 0.1%; our hematology analyzer has a hard stop for all critical values, whereas the chemistry analyzer does not. In conclusion, we discovered that the default display on our Siemens Centralink middleware screen places a blue bar in the top row that obscures the visual cues associated with a critical value. Because sodium results are placed in the top row on the display screen, missed sodium critical callbacks occurred seven times more often than missed potassium callbacks. To remedy the issue, a blank row has been added to the display as the top row so that no clinical data are obscured by the default blue bar. Additionally, the very low critical callback failure rate on the hematology analyzer points to a need for a hard stop on the chemistry analyzer. We will prospectively monitor critical callback data for sodium to determine whether the display change improves sodium callback rates.

Analysis of laboratory critical values at a referral Spanish tertiary university hospital.

IntroductionThe aim of this study was to analyse critical value data from our laboratory and compare our critical value reporting policy with others in the literature.Materials and methodsAnalysis of critical values was performed on data obtained over a 6-month period in a tertiary university hospital.ResultsWe identified 5723 critical values, of which approximately 80% came from STAT testing (4577), 15% from routine inpatients testing (884) and 5% from routine outpatients testing (262). The highest proportion of critical values corresponded to oxygen partial pressure (17.7%), followed by potassium ion (17.6%) concentrations. The parameters associated with the highest critical value notification percentage in emergency patients were pH, haematocrit, glucose, potassium ion and haemoglobin concentrations. In inpatients, these parameters were glucose, phosphate, haemoglobin, sodium ion and potassium ion concentrations. In outpatients, they were calcium and potassium concentrations.ConclusionsThe analysis of critical values in our hospital is in accordance with that reported in the literature. Our findings demonstrate the importance of incorporating improvement actions not only in critical value notification, but especially in the registration of this activity.

National surveys on 15 quality indicators for the total testing process in clinical laboratories of China from 2015 to 2017.

Background As effective quality management tools, quality indicators (QIs) are widely used in laboratory medicine. This study aimed to analyze the results of QIs, identify errors and provide quality specifications (QSs) based on the state-of-the-art. Methods Clinical laboratories all over China participated in the QIs survey organized by the National Health Commission of People' Republic of China from 2015 to 2017. Most of these QIs were selected from a common model of QIs (MQI) established by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All participants were asked to submit general information and original QIs data through a medical quality control data collection system. The results of QIs were reported in percentages and sigma, except turnaround time (TAT) which was measured in minutes. The 25th, 50th and 75th percentiles were, respectively, calculated as three levels of QSs, which were defined starting from the model proposed during the 1st Strategic Conference of the EFLM on "Defining analytical performance 15 years after the Stockholm Conference on Quality Specification in Laboratory Medicine". Results A total of 76 clinical laboratories from 25 provinces in China continuously participated in this survey and submitted complete data for all QIs from 2015 to 2017. In general, the performance of all reported QIs have improved or at least kept stable over time. Defect percentages of blood culture contamination were the largest in the pre-analytical phase. Intra-laboratory TAT was always larger than pre-examination TAT. Percentage of tests covered by inter-laboratory comparison was relatively low than others in the intra-analytical phase. The performances of critical values notification and timely critical values notification were the best with 6.0σ. The median sigma level of incorrect laboratory reports varied from 5.5σ to 5.7σ. Conclusions QSs of QIs provide useful guidance for laboratories to improve testing quality. Laboratories should take continuous quality improvement measures in all phases of total testing process to ensure safe and effective tests.

The application of sigma metrics quality models in quality management of clinical biochemistry laboratory

Objective To improve the quality of clinical biochemistry laboratory by quality indicators of pre-analytical, analytical, post-analytical phase and the whole process. Methods Analytical Phase: The Sigma values of items were calculated, applying the equation Sigma=(TEa%-Bias%)/CV%. Total allowable error (TEa) is from analyticalal specification defined in WS/T403-2012 of China, Bias% is from the evaluation results of National Center for Clinical Laboratory (NCCL) trueness verification PT series and CV% is from internal quality control data during the last 6 months in our lab. Normalized Sigma metrics plot was made to evaluate the analysis performance and the quality control strategies were designed accordingly. The quality goal indexes (QGI) were also calculated to propose improvement measures for items below 6 Sigma. Quality indicators of pre-, post-analytical and whole analytical phase, such as quality of specimen, critical value notification, critical value notification in time, TAT of hs-cTnT, TAT of emergency biochemical items, rewrite of laboratory reports and unacceptable performance in EQA-PT were measured in Sigma metrics too. The Sigma metrics changes before and after taking improvement measures were compared to conform the effectiveness. Results The average Sigma value of 17 biochemical tests was 5.29, of which 8 items (UA, K, ALP, CK, AMY, AST, TG, Na) achieved excellent to world class level (≥5 Sigma), 6 items (LDH, Cre, TC, ALT, Mg, Glu) achieved marginal to good level (5>Sigma≥3), BUN performed poorly (3>Sigma≥2), Ca, TP performed unacceptably (Sigma<2) with serious quality defects. The Sigma values of unacceptable specimen, critical value notification, critical value notification in time, unacceptable turn around time (TAT) of hs-cTnT, unacceptable turn around time (TAT) of emergency biochemical items, rewrite of laboratory reports, unacceptable performance in EQA-PT were 4.17, 3.60, 2.75, 1.72, 3.27, 4.52, 3.33 respectively, rising to 4.30, 4.30, 2.90, 2.45, 3.75, 4.80, 3.60 accordingly after improvement. Conclusions Sigma metrics is potentially an ideal approach for clinical biochemistry laboratories management, which is helpful to find out problems, put forward improvement measures, and confirm the effectiveness, so as to achieve the purpose of continuous quality improvement.(Chin J Lab Med, 2017, 40: 727-732) Key words: Clinical chemistry tests; Quality control; Laboratories, hospital; Quality indicators, health care; Quality improvement

Delays in reporting critical values from clinical laboratories to responsible healthcare staff

Abstract Objective We aimed to investigate the frequency of delayed notifications and probable causes of delays for critical value notification in clinical laboratory of university hospital. Materials and methods All data was obtained from critical value reporting forms and laboratory information system. The frequency and location of critical and delayed results, latencies throughout a working day and the professional status who received the critical callbacks were shown as percentages. Results A total of 2018 (1.02%) critical values were reported and 13.1% of them were delayed notifications. Most of them were observed in laboratory tests ordered from patients of service and polyclinics compared to ICU and emergency department (26.7%, 26%, 6.2% and 4.9%, respectively, p&lt;0.01). Delayed notifications were significantly higher for biochemical parameters (19.7%, p&lt;0.001) and observed particularly in morning hours (06:00 a.m.–10:00 a.m.), lunch break time (12:00–14:00) and end of the working day (16:00–18:00). Latencies of mild-delayed reporting were 18.5±4.4 min for 62.8% and advanced-delayed reporting were 47.1±11.3 min for 37.2% of total delayed notifications. Most of the critical results were reported to the health care staff other than physician (55.6%). Conclusion Laboratory professionals should work in collaboration with responsible clinician and healthcare staff in critical value reporting process.

Challenges in the Standardization of Autoantibody Testing: a Comprehensive Review.

Standardization and harmonization are complementary tools to achieve higher testing quality in laboratory medicine. Both are of great relevance and are strongly needed in autoimmune diagnostics, due to the impressive advance in basic research and technological development observed in this diagnostic field in recent years that has led to the introduction of many new tests and new analytical methods. It is, therefore, essential that this strong innovative thrust is translated into clinical practice in a coordinated way to avoid confusion and the risk of potentially harmful errors for the patient. However, while standardization of antibody assays is a very complex task, harmonization of procedures and behaviors is a more feasible target and should necessarily include all the phases of the total testing process-in the pre-analytical phase, appropriateness of test requests, harmonization of autoantibody terminology, and adoption of uniform nomenclature for laboratory tests; in the analytical phase, harmonization of measurements, and sharing of test profiles and diagnostic algorithms; and in the post-analytical phase, harmonization of data reporting, and criteria for interpreting immunoserological results, especially harmonization of units, reference intervals, decision limits, and definition and notification of critical values. We here provide and discuss some examples of harmonization initiatives related to anti-nuclear antibodies, TSH receptor, and anti-thyroid peroxidase antibodies and to antibodies associated with autoimmune hepatitis and with celiac disease. These initiatives could be the starting steps to achieve a wider consensus and a closer interaction among stakeholders in the path of autoimmune diagnostics harmonization to enhance clinical effectiveness and provide greater patient safety.