Analytical Phase Research Articles

Econometric Measurement of the Relationship between Tourism Revenues and Economic Growth. Study Case of Kazakhstan and Kyrgyzstan

The purpose of this research is to establish the link between Kazakhstan's and Kyrgyzstan's international tourist income and economic development from 1998 to 2019. The Linear Regression Model was used to see whether there was a significant link between the dependent and independent variables, as well as how the variables influenced economic growth. The World Bank provided the data for the research, which included yearly data. A set of assumption tests were performed throughout the analytical phase to determine the model's relevance. The logarithm of the dependent variable was used to create the model. The inflation factors of variance (WIF) test were used to determine if the independent variables were unrelated to one another. Another assumption was used to determine the normal distribution of error terms: the Shapiro-Wilk W test.
 A positive linear association was found between economic development and foreign tourist revenues in the nations studied, according to the results of a series of assumption tests and regression analysis. According to the results of the most recent regression study, the variables in both nations have a positive linear connection.

Seismic assessment of the XX century masonry buildings in Florence: Vulnerability insights based on urban data acquisition and nonlinear static analysis

This paper deals with the seismic vulnerability assessment of modern masonry buildings in Florence, Italy. The work focuses on the XX century masonry structures realized before seismic codes. The research is divided into two main distinct phases: i) the acquisition of the main geometrical and structural information at the urban scale; ii) the selection of a representative model to execute an analytical assessment. The first part of the work represents a cognitive phase based on archive research and the collection of the buildings, which allowed the architectural and structural identification of over 300 structures. The second part of the work represents an analytical phase targeted at deriving fragility curves. A real case study representative of the simple block typology with two apartments per floor and a central stairwell has been selected and a probabilistic framework based on nonlinear static analysis has been performed. The analytical conclusions of the research point out a significant vulnerability of these structures, mainly ruled by a weak-piers-strong-spandrels behaviour. For the Life Safety limit state (SLV), around 40% of probability to having DL4 and 40% reaching DL5 are expected. The paper presents the results in terms of generic outcomes providing indications useful for the uncertainty's treatment and the engineering practice.

Replay spoof detection using energy separation based instantaneous frequency estimation from quadrature and in-phase components

Replay attacks in speech are becoming easier to mount with the advent of high quality of recording and playback devices. This makes these replay attacks a major concern for the security of Automatic Speaker Verification (ASV) systems and voice assistants. In the past, auditory transform-based as well as Instantaneous Frequency (IF)-based features have been proposed for replay spoofed speech detection (SSD). In this context, IF has been estimated either by derivative of analytic phase via Hilbert transform, or by using high temporal resolution Teager Energy Operator (TEO)-based Energy Separation Algorithm (ESA). However, excellent temporal resolution of ESA comes with lacking in using relative phase information and vice-versa. To that effect, we propose novel Cochlear Filter Cepstral Coefficients-based Instantaneous Frequency using Quadrature Energy Separation Algorithm (CFCCIF-QESA) features, with excellent temporal resolution as well as relative phase information. CFCCIF-QESA is designed by exploiting relative phase shift to estimate IF, without estimating phase explicitly from the signal. To motivate and validate effectiveness of proposed QESA approach for IF estimation, we have employed information-theoretic measures, such as Mutual Information (MI), Kullback–Leibler (KL) divergence, and Jensen–Shannon (JS) divergence. The proposed CFCCIF-QESA feature set is extensively evaluated on standard statistically meaningful ASVSpoof 2017 version2.0 dataset. When evaluated on the ASVSpoof 2017 v2.0 dataset, CFCCIF-QESA achieves improved performance as compared to CFCCIF-ESA and CQCC feature sets on GMM, CNN, and LCNN classifiers. Furthermore, in the case of cross-database evaluation using ASVSpoof 2017 v2.0 and VSDC, CFCCIF-QESA also performs relatively better as compared to CFCCIF-ESA and CQCC on GMM classifier. However, for the case of self-classification on the ASVSpoof 2019 PA data, CFCCIF-QESA only outperforms CFCCIF-ESA. Whereas, on BTAS 2016 dataset, it performs relatively close to CFCCIF-ESA. Finally, results are presented for the case when the ASV system is not under attack.

Development and Validation of Analytical RP HPLC Method for Benidipine Hydrochloride

The aim of the present study is development and validation of analytical reverse phase (RP) high performance liquid chromatography (HPLC) from Benidipine Hydrochloride. HPLC method is used for quantification, identification and purification of particular analyte or compound. The developed HPLC chromatographic technique was validated based on international conference on harmonization (ICH) Q2 guidelines for accuracy, precision, linearity, range and robustness. High performance liquid chromatography technique is rapid and precise technique. Advance for the validated of Benidipine Hydrochloride in pure and tablet dosage form. Diethyl ether was extracted from plasma in the presence of 5M NaOH (Sodium Hydroxide) Diethyl ether is used as internal standard like Benidipine and Benidipine d5. Benidipine is dihydropyridine calcium channel blocker, which is used in the treatment of hypertension and angina pectoris and is used to examine the efficacy and safety of therapy with Benidipine in elderly hypertensive patients.

Dual EEG alignment between participants during shared intentionality experiments

Electroencephalograph (EEG) analysis from human subjects have demonstrated that beta oscillations carried perceptual information across the cortex featuring amplitude and phase modulation occurrences when subjects are engaged in task-oriented activities. A hypothesis was tested that synchronized patterns could be found in the scalp EEG of two human subjects engaged in similar intentional activity. Signals were recorded from scalp electrodes and band-pass filtered. The Hilbert transform decomposes the EEG signals into the analytic phase and amplitude. With these components of the EEG signal, a systematic search of the alpha, beta, delta, gamma, and theta spectrum is executed to locate temporal patterns. The amplitude and phase modulation were classified with respect to task intervals. Temporal patterns were found in the alpha-beta range (15–30 Hz). Our results suggest that the scalp EEG can yield information about the timing of episodically synchronized brain activity in higher cognitive function between two individuals engaged in similar task-oriented activities.

Improved Analytic Expansions in Hybrid A-Star Path Planning for Non-Holonomic Robots

In this study, we concisely investigate two phases in the hybrid A-star algorithm for non-holonomic robots: the forward search phase and analytic expansion phase. The forward search phase considers the kinematics of the robot model in order to plan continuous motion of the robot in discrete grid maps. Reeds-Shepp (RS) curve in the analytic expansion phase augments the accuracy and the speed of the algorithm. However, RS curves are often produced close to obstacles, especially at corners. Consequently, the robot may collide with obstacles through the process of movement at these corners because of the measurement errors or errors of motor controllers. Therefore, we propose an improved RS method to eventually improve the hybrid A-star algorithm’s performance in terms of safety for robots to move in indoor environments. The advantage of the proposed method is that the non-holonomic robot has multiple options of curvature or turning radius to move safer on pathways. To select a safer route among multiple routes to a goal configuration, we introduce a cost function to evaluate the cost of risk of robot collision, and the cost of movement of the robot along the route. In addition, generated paths by the forward search phase always consist of unnecessary turning points. To overcome this issue, we present a fine-tuning of motion primitive in the forward search phase to make the route smoother without using complex path smoothing techniques. In the end, the effectiveness of the improved method is verified via its performance in simulations using benchmark maps where cost of risk of collision and number of turning points are reduced by up to around 20%.

Sigma metric analysis of quality indicators across the testing process as an effective tool for the evaluation of laboratory performance

BackgroundLaboratories across the world are successfully using quality indicators (QIs) to monitor their performance. We aimed to analyze the effectiveness of using the peer group comparison and statistical tools such as sigma metrics for periodic evaluation of QIs and identify potential errors in the preanalytical, analytical, and postanalytical phases. MethodsWe evaluated the monthly QIs for 1 year. A total of 11 QIs were evaluated across the three phases of the total testing process, using percentage variance, and sigma metric analysis. ResultsOur study observed that based on sigma metric analysis, the performance was good for all the QIs except for the number of samples with the inappropriate specimen hemolyzed samples, clotted samples, and turnaround time (Sigma value < 3). The percentage variance of QIs in all the phases was plotted in a Pareto chart, which helped us in identifying turnaround time and internal quality control performance are the key areas that contribute to almost 80% of the errors among all the QIs. ConclusionLaboratory performance evaluation using QIs and sigma metric analysis helped us in identifying and prioritizing the corrective actions in the key areas of the total testing process.

Survey of Deep-Learning Techniques in Big-Data Analytics

Big-data research studies relying upon Deep-learning methods are revitalized the decision-making mechanism in the business sectors and the enterprise domains. The firms’ operational parameters also have the dependency of the Big-data analytics phase, their way of managing the data, and to evolve the outcomes of Big-data implementation by using the Deep-learning algorithms. Deep-learning approaches enhancements in Big-data applications facilitate the decision-making process such as the information-processing to the employees, analytical potentials augmentation, and in the transition of more innovative work. In this DL-approach, the robust-patterns of the data-predictions resulted from the unstructured information by conceptualizing the Decision-making methods. Hence this paper reviewed the impact of the Deep-learning process utilizing the Big-data in the enterprise and Business sectors. Also this study provides a comprehensive survey of all the Deep-learning techniques illustrating the efficiency of Big-Data processing and their impacts of operational parameters. Further it concentrating the data-dimensionality factors and the Big-data complications rectifying by utilizing the DL-algorithms, usage of Machine-learning or deep-learning process for the decision-making mechanism in the Enterprise sectors and business sectors. This research discussed the predictions of the Big-data analytics resulting to the decision parameters within the organisations, and in the management of larger scale of datasets in Big-data analytics processing by utilizing the Deep-learning implementations. The comparative analysis of the reviewed studies has also been described by comparing existing approaches of Deep-learning methodologies in employing Big-data analytics.

Modeling success: How to work effectively with your biostatistician.

Modeling success: How to work effectively with your biostatistician.

A Concept Analysis of Illness Intrusiveness in Chronic Disease: Application of the Hybrid Model Method.

This study clarifies the concept of illness intrusiveness in patients with a chronic disease using the hybrid model method. To clarify the dimension, attributes, and definition of illness intrusiveness in chronic disease, three phases of analysis were conducted. In the theoretical phase, a working definition was devised through a systematic review. In the fieldwork phase, individual in-depth interviews were conducted with nine participants with chronic diseases. In the final analytic phase, the results were integrated through comparison and review. There are four domains and eleven attributes of illness intrusiveness in chronic disease. The domains include physical, psychological, social/contextual, and spiritual. The physical domain consists of four attributes: pain, fatigue, physical malfunction, and change of body image. The psychological domain consists of three attributes: psychological weakness, uncertainty, and stigma. The social/contextual domain is made up of three attributes: withdrawal of role play, limit of daily life, and burden of changing health habits. Finally, the spiritual domain had one attribute: unstable spiritual state. Thus, based on the study findings, it is necessary to develop a suitable illness intrusiveness in chronic disease assessment scale to assess chronic disease patients.

MONITORING QUALITY INDICATORS IN A MEDIUM-SIZED LABORATORY OF SOUTH BENGAL: MOVING TOWARDS ACCREDITATION

Introduction: Documenting and monitoring quality indicators are important to improve the quality of a laboratory. The objective of this study was to record the quality indicators of a clinical laboratory and prepare it for accreditation by National Accreditation Board of Laboratories (NABL) as per ISO 15189. Materials And Methods: A total of 9 quality indicators in different phases of sample analyses viz. pre-analytical, analytical and post-analytical were monitored for 21459 samples over a period of one year. Results: Incomplete requisition forms were the most common outlier (2.5%) in the pre-analytical phase followed by samples not maintaining cold chain during transport (2.1%). Internal non-conformance with quality control was seen in 0.6% of samples in analytical phase. In post analytical phase, turnaround time (TAT) could not be maintained for 8% of the samples. Conclusion: Monitoring and recording quality indicators give us an idea about the performance of a medical laboratory. Therefore, working with a goal to reduce quality indicator outliers will improve the quality of a laboratory and ultimately enhance patient care. Moreover, it can help comparing different laboratories in a particular area based on performance.

Best Practices for the Analytic Phase of Anaerobic Bacteriology

The analytic process for identification of anaerobic bacteria involves direct specimen Gram stains and workup of growth in culture. Direct Gram stains help to develop the initial differential, aiding in guiding both the extent of laboratory workup and clinician decision making for patient management. Workup of anaerobic growth should involve an aerotolerance test to assess aerobic growth and to compare growth rates in anaerobic versus aerobic environments. While matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has become a routine means of anaerobe identification for many clinical laboratories, spot biochemical tests, such as indole and catalase, should be available in every laboratory that identifies anaerobes. If MALDI-TOF MS and biochemical methods are unsuccessful at providing an identification, 16S rRNA gene PCR and/or sequencing may be performed if the information impacts clinical care. The extent of culture workup to the level of presumptive identification versus definitive identification depends upon several factors, including the specimen source, direct Gram stain results, and the presence or absence of mixed microbiota. In addition to discussing the current best practices for anaerobic culture workup, commonly encountered anaerobic organism Gram stains and culture growth are detailed.

Electrolytes internal quality control by using ISO 15189 version 2007: Particular requirements for quality and competence for biomedical laboratories

Background: the blood electrolytes analysis is a routine laboratory test which proper execution would help in the diagnosis of hydro-electrolytes disorders. The objective of this work was to assess the internal quality control of the sodium and potassium tests from the pre-pre-analytical phase to the post-analytical phase. Material and Methods: This was a cross-sectional study which took in the laboratory of biochemistry at the Institute of Cardiology, Abidjan, Ivory Coast from March 1st to March 31, 2009. We used the flame photometer to measure the sodium and potassium electrolytes level in the internal control Exatrol-Normal from Biolabo®. Clinical samples were also taken for the determination of the same electrolytes levels. The pre-pre-analytical quality indicators depending on the physicians order, the pre-analytical quality, the analytical quality and the post-analytical indicators under the control of the laboratory were assessed by using “NF en ISO 15189 version 2007” check list: Particular requirements for quality and competence for biomedical laboratories paragraph 5.4.1, 5.4.2, 5.5 and 5.7. Data were captured into Microsoft Excel [Microsoft Corporation, Redmond, WA] and then imported and analyzed using QI Macros SPC Software for Excel®. The levels of Na+ and K+ in the control material Exatrol Normal from Biolabo® were represented as follow: mean (m), Standard deviation (SD). The values of the monthly distribution of Na+ and K+ concentrations around the mean were used to draw the Levey-Jennings diagram and Wesgard’s rules were used to evaluate the performances of the analytical process. Results: a total of 112 electrolytes analysis order were received at the biochemistry laboratory. For the pre-pre-analytical phase, the analysis of these requests forms revealed that 81 (72.3%) requests forms carried no clinical information. The non-compliance of the samples were mainly represented by the sampling under tight tourniquet 4 (3.6%), followed by the non-respect of the succession of tubes during multiple sampling process 3 (2.7%). For the analytical phase, the monthly Levey-Jennings diagram showed a dispersion of the two electrolytes Exatrol-Normal Biolabo® levels ​​between the mean plus or minus 2 standard deviations [m ± 2SD]: 139.34 ± 2.84 mmol/L for Na+ and for K+, between [m± SD]: 4.2 ± 0.78 mmol/L. The analytical performances assessment for the two Levey-Jennings diagrams by using Wesgard’s rules did not found any significant critical deviations with regard to the distribution of Na+ and K+ levels. For clinical samples, isolated hyponatremia was the most common disturbance (30.4%) followed by isolated hypokalemia (12.5%). At the post-analytical phase we observed for test execution a mean turnaround time of 34 ± 5.2 minutes with extremes ranging from 23 to 95 minutes. One case (0.9%) of transcription error was noted. Conclusion: the internal quality control process is applied in the clinical biochemistry laboratory at the Institute of Cardiology, Abidjan. A systematic verification system of the different phases of the analytical process helped to follow quality indicators at all levels of the pre, analytical and post analytical process and corrective actions were taken if necessary. Better collaboration between clinicians requesting electrolytes analysis and biologists performing the analysis is necessary to improve the pre-pre-analytical phase and, beyond that, improve the patient outcome throughout a comprehensive care.

The diagnostic pitfalls and challenges associated with basic hematological tests

Several generations of automated hematology analyzers are currently being used to determine a wide range of hematological parameters. As their results form the basis of many medical interventions, it is required that they undergo analytical validation. Samples flagged as being pathological or non-diagnostic require re-testing in a different mode, revision, or additional diagnostic workup (e.g. microscopic smear). In order to avoid mistakes, close cooperation and continuous communication are needed between laboratory and medical staff. To address this, in this review we discuss the most frequent errors and pitfalls associated with the preanalytical and analytical phases of basic hematological tests. While not all diagnostic pitfalls are avoidable, this guidance regarding potentially problematic diagnostic situations will allow for their quick verification at the laboratory stage. An awareness of the causes of errors and of the existence of pitfalls can lower the costs of analytical procedures by minimizing the need to repeat analyses of potentially pathological samples, and have a positive impact on patient safety. In addition, reducing the potential for laboratory errors can improve the accuracy of medical diagnoses and avoid unnecessary treatment.

Form Follows Parameter: Algorithmic-Thinking-Oriented Course for Early-stage Architectural Education.

The digital paradigm requires efficient methods of teaching CAAD tools in architecture schools. With the trend of enhancing the design process with parametric methods, linking architecture with other knowledge areas, such as mathematics, is gaining in importance. Equipping future architects with skills in algorithmic thinking is yet another challenge for education. This paper describes the workflow of an early-stage course addressing this challenge, conducted at the Warsaw University of Technology’s Faculty of Architecture. The course focuses on the students’ ability to construct complex geometric forms in the digital environment by introducing an extensive analytic phase. The students study the geometric foundations of real-world architectural cases and translate them into parametric models. Later, they explore the potential of the generated solutions space. The results compare the course’s teaching efficiency with the outcomes of past courses covering similar subjects.

Development of a virtual classroom for pre-analytical phase of laboratory medicine for undergraduate medical students using the Delphi technique.

Amongst the pre-analytical, analytical, and post-analytical phase of laboratory testing, pre-analytical phase is the most error-prone. Knowledge gaps in understanding of pre-analytical factors are identified in the clinical years amongst undergraduate students due to lack of formal teaching modules on the pre-analytical phase. This study was conducted to seek experts' consensus in Clinical Chemistry on learning objectives and contents using the Delphi technique with an aim to develop an asynchronous virtual classroom for teaching pre-analytical factors of laboratory testing. A mixed method study was conducted at the Aga Khan University. A questionnaire comprising of 16 learning objectives and their associated triggers was developed on Google Docs for developing the case vignettes. A four-point Likert Scale, which included strongly agree, agree, disagree and strongly disagree, was utilized for the learning objectives. An open-ended question was included for experts to suggest new items for inclusion. A cut off of at least 75% agreement was set to establish consensus on each item. A total of 17 Chemical Pathology faculty from 13 institutions across Pakistan were invited to participate in the first round of Delphi. Similar method of response was used in round two to establish consensus on the newly identified items suggested by the faculty in round 1. Later, the agreed-upon objectives and triggers were used to develop interactive scenarios over Moodle to concurrently test and teach medical students in a nonchalant manner. A total of 17 responses were received in Round 1 of the Delphi process (response rate = 100%), while 12 responses were received in Round 2 (response rate = 71%). In round 1, all 16 learning objectives reached the required consensus (≥ 75%) with no additional learning objectives suggested by the experts. Out of 75 triggers in round 1, 61 (81.3%) reached the consensus to be included while 39 were additionally suggested. In 2nd round, 17 out of 39 newly suggested triggers met the desired consensus. 14 triggers did not reach the consensus after two rounds, and were therefore eliminated. The virtual classroom developed using the agreed-upon learning objectives and triggers consisted of 20 items with a total score of 31 marks. The questions included multiple choice questions, fill in the blanks, drag and drop sequences and read-and-answer comprehensions. Specific learning points were included after each item and graphs and pictures were included for a vibrant experience. We developed an effective and interactive virtual session with expert consensus on the pre-analytical phase of laboratory testing for undergraduate medical students which can be used for medical technologist, graduate students and fellows in Chemical Pathology.

Quantification of twenty pharmacologically active dyes in water samples using UPLC-MS/MS

This study presents a multi-compound method for the determination of 20 pharmacologically active dyes from 5 different chemical classes in environmental water samples. These compounds, including triphenylmethane dyes (malachite green, crystal violet, brilliant green, ethyl violet, methyl violet 2B, pararosaniline, victoria blue B, victoria blue R, victoria pure blue BO), phenothiazine dyes (methylene blue, azure A, azure B, azure C, new methylene blue, thionine), phenoxazine dye (nile blue A), acridine dyes (acriflavine, proflavine) and xanthene dyes (rhodamine B, rhodamine 6G) constitute pharmacologically active substances (PASs). For the optimisation of sample preparation, different solid-phase extraction (SPE) sorbents and a wide range of pH (from 2 to 12) of water samples were tested. Finally, water samples were preconcentrated and cleaned up on diol SPE cartridges. Extracts were analysed by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) operating in the positive electrospray ionisation (ESI+) mode. The chromatographic separation of the 20 pharmacologically active dyes was achieved within 5 min by using a pentafluorophenyl (F5) analytical column and mobile phases of ammonium acetate buffer (0.05 M, pH = 3.5) and acetonitrile with gradient elution. The developed method was validated proving to be suitable for the determination of all tested compounds. Limits of quantification were 0.01–0.1 μg/l, are sensitive enough to quantify very low concentration levels of the dyes in environmental water samples. The obtained recovery values for all tested analytes were between 71.2 and 104.9% with a good RSD, less than 14 % at all fortification levels. The application of the developed method to water samples allows the detection of dyes such as crystal violet, rhodamine B, and methyl violet in two wastewater samples in concentration range from 0.017 to 0.0043 μg/l).

Medication Literacy in Hospitalized Older Adults: Concept Development.

Background:Medication literacy encompasses the cognitive and social skills necessary for individuals to obtain, comprehend, communicate, calculate, and process medication-related information necessary to make informed decisions. Personal and contextual factors are widely recognized to influence the way that individuals acquire and maintain medication literacy skills. Despite a growing number of studies on medication literacy, current definitions remain general, lacking consideration for the specificities of older adults and hospitalization.Objective:The project was conducted to identify, compare, and summarize the attributes, antecedents, and consequences of medication literacy in hospitalized older adults and to propose a refined definition.Methods:A three-phase hybrid model of concept development was performed that included a literature review and focus groups with hospital nurses. In the final analytic phase, findings from the literature and focus groups were compared, and a refined definition of the concept was elaborated.Key Results:From the synthesis of 24 publications and the narrative data of 14 hospital nurses, 19 themes were described: 4 related to attributes, 8 to antecedents, and 7 to consequences. Medication literacy of hospitalized older adults has been further defined as the degree to which older adults and/or their natural caregivers can develop and maintain multidimensional skills, namely functional, interactive, and critical medication literacy skills. Adjustment of these skills is characterized by a dynamic and potentially complex process. In practice, optimal medication literacy might be achieved through control of and involvement in the medication regimen and the decisions related to it, and/or by using practical means to facilitate medication self-management (e.g., using lists, notes, reminders).Conclusions:The proposed refined definition might enhance professionals' common understanding of the concept and its application in practice, policy, and research. Managing a medication regimen is a complex activity that requires a high level of integration and coordination of cognitive and social skills. [HLRP: Health Literacy Research and Practice. 2022;6(2):e70–e83.]Plain Language Summary:Based on the literature on medication literacy and the experiences of nurses working in hospitals, this article defines medication literacy in hospitalized older adults. This definition will help professionals to better understand challenges related to medication literacy in older patients and to propose adequate support (i.e., provide education, simplify medication prescriptions, propose practical aids such as a pillbox).

Maintaining laboratory quality assurance and safety in a pandemic: Experiences from the KEMRI-Wellcome Trust Research Programme laboratory’s COVID-19 response

Laboratory diagnosis plays a critical role in the containment of a pandemic. Strong laboratory quality management systems (QMS) are essential for laboratory diagnostic services. However, low laboratory capacities in resource-limited countries has made the maintenance of laboratory quality assurance, especially during a pandemic, a daunting task. In this paper, we describe our experience of how we went about providing diagnostic testing services for SARS-CoV-2 through laboratory reorganization, redefining of the laboratory workflow, and training and development of COVID-19 documented procedures, all while maintaining the quality assurance processes during the COVID-19 pandemic at the Kenya Medical Research Institute (KEMRI) Wellcome Trust Research Programme (KWTRP) laboratory. The KWTRP laboratory managed to respond to the COVID-19 outbreak in Kenya by providing diagnostic testing for the coastal region of the country, while maintaining its research standard quality assurance processes. A COVID-19 team comprising of seven sub-teams with assigned specific responsibilities and an organizational chart with established reporting lines were developed. Additionally, a total of four training sessions were conducted for county Rapid Response Teams (RRTs) and laboratory personnel. A total of 11 documented procedures were developed to support the COVID-19 testing processes, with three for the pre-analytical phases, seven for the analytical phase, and one for the post-analytical phase. With the workflow re-organization, the development of appropriate standard operating procedures, and training, research laboratories can effectively respond to pandemic outbreaks while maintaining research standard QMS procedures.

The use of deliberate reflection to reduce confirmation bias among orthopedic surgery residents

Introduction: cognitive biases might affect decision-making processes such as clinical reasoning and confirmation bias is among the most important ones. The use of strategies that stimulate deliberate reflection during the diagnostic process seems to reduce availability bias, but its effect in reducing confirmation bias needs to be evaluated.Aims: to examine whether deliberate reflection reduces confirmation bias and increases the diagnostic accuracy of orthopedic residents solving written clinical cases.Methods: experimental study comparing the diagnostic accuracy of orthopedic residents in the resolution of eight written clinical cases containing a referral diagnosis. Half of the written cases had a wrong referral diagnosis. One group of residents used deliberate reflection (RG), which stimulates comparison and contrast of clinical hypotheses in a systematic manner, and a control group (CG), was asked to provide differential diagnoses with no further instruction. The study included 55 third-year orthopedic residents, 27 allocated to the RG and 28 to the CG.Results: residents on the RG had higher diagnostic scores than the CG for clinical cases with a correct referral diagnosis (62.0±20.1 vs. 49.1±21.0 respectively; p = 0.021). For clinical cases with incorrect referral diagnosis, diagnostic accuracy was similar between residents on the RG and those on the CG (39.8±24.3 vs. 44.6±26.7 respectively; p = 0.662). We observed an overall confirmation bias in 26.3% of initial diagnoses (non-analytic phase) and 19.5% of final diagnoses (analytic phase) when solving clinical cases with incorrect referral diagnosis. Residents from RG showed a reduction in confirmation of incorrect referral diagnosis when comparing the initial diagnosis given in the non-analytic phase with the one provided as the final diagnosis (25.9±17.7 vs. 17.6±18.1, respectively; Cohen d: 0.46; p = 0.003). In the CG, the reduction in the confirmation of incorrect diagnosis was not statistically significant.Conclusions: confirmation bias was present when residents solved written clinical cases with incorrect referral diagnoses, and deliberate reflection reduced such bias. Despite the reduction in confirmation bias, diagnostic accuracy of residents from the RG was similar to those from the CG when solving the set of clinical cases with a wrong referral diagnosis.