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Foodborne outbreak investigations often provide data for public health officials to determine how the environment contributed to the outbreak and on how to prevent future outbreaks. State and local health departments are responsible for investigating foodborne illness outbreaks in their jurisdictions and reporting the data to national-level surveillance systems, including information from the environmental assessment. This assessment is designed to describe how the environment contributed to the outbreak and identifies factors that contributed to the outbreak and environmental antecedents to the outbreak. Environmental antecedents, also referred to as root causes, are specific reasons that allow biological or chemical agents to contaminate, survive, or grow in food. From 2017 to 2019, 24 jurisdictions reported 1,430 antecedents from 393 outbreaks to the National Environmental Assessment Reporting System. The most reported antecedents were lack of oversight of employees/enforcement of policies (89.1%), lack of training of employees on specific processes (74.0%), and lack of a food safety culture/attitude towards food safety (57.5%). These findings highlight the critical role that employees play in restaurant food safety and are heavily influenced by restaurant management, who can exercise active managerial control to manage these antecedents. Identifying antecedents during investigations is essential for understanding the outbreak's root cause and implementing sustainable corrective actions to stop the immediate outbreak and future outbreaks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)

Diverse errors occur in a pathology laboratory and manual mistakes are the most common. There are various advancements to replace manual procedures with digitized automation techniques. Guidelines and protocols are available to run a standard pathology laboratory. But, even with such attempts to reinforce and strengthen the protocols, the complete elimination of errors is yet not possible. Root cause analysis (RCA) is the best way forward to develop an error-free laboratory, In this review, the importance of RCA, common errors taking place in laboratories, methods to carry out RCA, and its effectiveness are discussed in detail. The review also highlights the potential of RCA to provide long-term quality improvement and efficient laboratory management., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Srinivasaragavan et al.)

Background: Drug shortages impact multiple stakeholders and are detrimental to patient safety. Additionally, drug shortages are an extensive financial burden. In Germany, drug shortages, according to data from the federal ministry for drug and medical products (BfArM), have been increasing by 18% between 2018 and 2021. Studies show that shortages are most frequently supply side driven and that often reasons remain unknown., Objective: The aim is to develop a holistic understanding of supply side causes for drug shortages in Germany from marketing authorization holders' perspectives and to derive implications for shortage mitigation., Methods: A mixed-methods research design, with a grounded theory approach based on a structured literature review, BfArM data analysis, and semi-structured interviews, was used., Results: Input factor supply issues, manufacturing issues, logistics issues, product recalls, and product discontinuations were identified as first-level causes. Furthermore, a theory on their connection to higher-level causes related to business decision-making, as well as root causes linked to regulations, company values, internal processes, market dynamics, external shocks, and macroeconomic factors, was developed., Conclusion: Actions to mitigate drug shortages in Germany (e.g., improving business processes, diversifying tender criteria) were derived. These may thus increase patient safety and decrease the financial burden on the healthcare system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Blood grouping discrepancy in patients with hematological disorders can occur due to red cell sensitization following transfusion, transplantation, and pregnancy or pre-analytical errors. Prompt initiation of root cause analysis is vital to avoid complications of wrong blood transfusion. We present an unusual case of Rh mismatched grouping report of 24 year old female thalassemia patient being managed in our hospital since 2015. Her current type and screen were observed as O Rh D negative with negative antibody screen while the historical blood group was O Rh D positive. The pre-analytical errors were ruled out and blood grouping performed from fresh sample also demonstrated as O Rh D negative despite antigen enhancement techniques and had no recent transfusion history. We sought to reason out the possibilities for discordant Rh grouping report, historical and present group through "Funnel based problem solving 5 WHY analysis" approach. The review of the past clinical history revealed that the patient had undergone Rh mismatch bone marrow transplant (Rh D positive donor and Rh D negative recipient) at 5 years of age which soon resulted in graft failure. Yet, she continued to receive Rh D positive blood thereafter with no development of anti-D which explains the historical blood group. Recently the patient was started on thalidomide, the Hb F inducer drug, which helped in maintaining her hemoglobin level between 9 and 10 g/dl without transfusion support for two months. This allowed unmasking of native Rh D negative blood and the review of clinical history played a significant role in resolution of grouping discrepancy., Competing Interests: Conflict of Interest All the authors declare no conflict of interest in this case report., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Introduction. This study aimed to perform an in-depth analysis of a catastrophic coach crash that occurred on the Chinese expressway, and thus draw useful lessons to avoid similar mistakes. Methods. Various causes were identified from the investigation report based on a proposed accident causation model, which provides a universal pathway for accident analysis from the individual level to the organizational level. Results. Driver error in an emergency affected by fatigue and speeding led directly to the crash. Accordingly, drivers in coaches should be monitored effectively and their unsafe acts must be corrected in a timely manner to avoid the formation of unsafe habits. Based on individual flaws, weaknesses in the construction of the organizational safety management system and safety culture were further deduced and discussed. Conclusion. The work and rest system, as well as the dynamic monitoring system for drivers, should be perfected strictly according to the regulations. Additionally, external factors regarding deficiencies in the design and management of the expressway and the supervision of the transportation company also had great impact on this crash. In summary, more efforts should be taken regarding root causes at the organizational level, regardless of internal or external factors.

Causality inference is a process to infer Cause-Effect relations between variables in, typically, complex systems, and it is commonly used for root cause analysis in large-scale process industries. Transfer entropy (TE), as a non-parametric causality inference method, is an effective method to detect Cause-Effect relations in both linear and nonlinear processes. However, a major drawback of transfer entropy lies in the high computational complexity, which hinders its real application, especially in systems that have high requirements for real-time estimation. Motivated by such a problem, this study proposes an improved method for causality inference based on transfer entropy and information granulation. The calculation of transfer entropy is improved with a new framework that integrates the information granulation as a critical preceding step; moreover, a window-length determination method is proposed based on delay estimation, so as to conduct appropriate data compression using information granulation. The effectiveness of the proposed method is demonstrated by both a numerical example and an industrial case, with a two-tank simulation model. As shown by the results, the proposed method can reduce the computational complexity significantly while holding a strong capability for accurate casuality detection.

Background: The live donor liver transplantation (LDLT) process is circuitous and requires a considerable amount of coordination and matching in multiple aspects that the literature does not completely address. From the coordinators' perspective, we systematically analyzed the time and risk factors associated with interruptions in the LDLT process. Methods: In this retrospective single center study, we reviewed the medical records of wait-listed hospitalized patients and potential live donors who arrived for evaluation. We analyzed several characteristics of transplant candidates, including landmark time points of accompanied live donation evaluation processes, time of eventual LDLT, and root causes of not implementing LDLT. Results: From January 2014 to January 2021, 417 patients (342 adults and 75 pediatric patients) were enrolled, of which 331 (79.4%) patients completed the live donor evaluation process, and 205 (49.2%) received LDLT. The median time from being wait-listed to the appearance of a potential live donor was 19.0 (interquartile range 4.0-58.0) days, and the median time from the appearance of the donor to an LDLT or a deceased donor liver transplantation was 68.0 (28.0-188.0) days. The 1-year mortality rate for patients on the waiting list was 34.3%. Presence of hepatitis B virus, encephalopathy, and hypertension as well as increased total bilirubin were risk factors associated with not implementing LDLT, and biliary atresia was a positive predictor. The primary barriers to LDLT were a patient's critical illness, donor's physical conditions, motivation for live donation, and stable condition while on the waiting list. Conclusions: Transplant candidates with potential live liver donors do not necessarily receive LDLT. The process requires time, and the most common reason for LDLT failure was critical diseases. Aggressive medical support and tailored management policies for these transplantable patients might help reduce their loss during the process.

Background . Understanding the causes of accidents plays a major role in learning from accidents and developing accident prevention and control strategies. Objective . This study aimed at application and modification of the Tripod Beta method for analyzing accident causes in the oil and gas industries. Materials and methods . A total of 68 accidents occurring in the oil and gas industries during 2005-2016 were analyzed. For this purpose, we used the Tripod Beta method and modified it using Reason's Swiss cheese model and analysis accident results. Results . The main causes that have been ignored in the Tripod Beta method were supervision factors involved in 66% of the accidents (underlying causes) and unsafe conditions that contributed to 55% of accidents (immediate causes). The former was incorporated as a sublayer of the underlying cause and the latter as a sublayer of immediate cause to the modified Tripod Beta method. Conclusions . The results of the present study added to the knowledge on the causes of accidents. These results can help increase the capabilities of the Tripod Beta method for analyzing accident causes, such as supervision factors and unsafe conditions, which have been ignored in analyses performed using the Tripod Beta method.

Aims: To identify and prioritize the root causes of adverse drug events (ADEs) in hospitals and to assess the ability of artificial intelligence (AI) capabilities to prevent ADEs., Design: A mixed method design was used., Methods: A cross-sectional study for hospitals in Spain was carried out between February and April 2019 to identify and prioritize the root causes of ADEs. A nominal group technique was also used to assess the ability of AI capabilities to prevent ADEs., Results: The main root cause of ADEs was a lack of adherence to safety protocols (64.8%), followed by identification errors (57.4%), and fragile and polymedicated patients (44.4%). An analysis of the AI capabilities to prevent the root causes of ADEs showed that identification and reading are two potentially useful capabilities., Conclusion: Identification error is one of the main root causes of drug adverse events and AI capabilities could potentially prevent drug adverse events., Impact: This study highlights the role of AI capabilities in safely identifying both patients and drugs, which is a crucial part of the medication administration process, and how this can prevent ADEs in hospitals., (© 2021 John Wiley & Sons Ltd.)

Background: Kidney transplantation success can help improve the quality of life substantially and alleviate much of the physical, social and psychological stress that comes with dialysis lifestyle. Preemptive kidney transplantation has been established to be superior with more success rates than other means of transplantation types. However, low rates of this method need more attention to address the reason and tackle the root causes affecting low preemptive kidney transplantation., Methods: This study was undertaken at a tertiary care academic hospital. We conducted a retrospective chart review of 50 living donor kidney transplants (recipient and donor charts) between January 1, 2017 and September 30, 2018 and performed a root cause analysis on the module. A three-step algorithm was developed to divide the root cause of all preemptive kidney transplantation., Results: Out of 50 patients included, only 11 (22%) achieved a successful preemptive kidney transplantation. Furthermore, an estimated glomerular filtration rate (eGFR) of 15 - 20 was a significant factor in achieving preemptive kidney transplantation (P = 0.042). Meanwhile, 22 recipients started dialysis before transplant and was a major cause of not achieving the preemptive transplantation despite them achieving the status. Moreover, the most common recipient root cause was incidental medical issues in 10 cases (20%) while in donor factors, the most common root cause was the delay in evaluating multiple donors to achieve the preemptive status (20%)., Conclusion: Even though preemptive kidney transplantation is superior when compared to other modalities, achieving such a milestone is still considered very challenging. An eGFR of 15 - 20 was a significant factor in achieving preemptive kidney transplantation, while pre-transplant dialysis was a major cause of not achieving it. Further large-scale studies are needed to identify new factors as well as validate our findings., Competing Interests: The authors declare that they have no conflict of interest., (Copyright 2021, Alsharani et al.)

Psychiatric measurement-based care has a significant role in nonpsychiatric medical and surgical settings for identifying mental illness and plays a research role in generating aggregated data. Psychiatric illnesses are multifactorial and not uniform in nature, patient distress/suffering have a complex etiology, and appropriate treatments are varied. Measures commonly used in measurement-based care are subjective ratings of symptom severity. In clinical mental health settings, measurement-based care may contribute more of a qualitative role as part of the psychiatric input to the identification and severity of illness. Psychiatrists must limit the use of measurement-based care in assisting the assessment of patient progress., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Microbiologists dread investigating results that are outside of the specifications. However, the investigation must be performed. A decision to reject the batch does not remove the requirement to investigate the failure. Unfortunately, microbiological assay samples are often consumed during the test or the results of the data are obtained several days after the sample is tested. This delay from testing to results often renders the original sample dilution not valid for further testing. Thus, this delay can hinder finding a root cause. Knowing the root cause can aid with microbial control, defining corrective actions, and defining preventative actions that are required to minimize or eliminate the potential for reoccurrence. The root cause is an essential component in understanding the patient impact, status of the product, and regulatory reporting requirements. This article discusses out of specification results obtained from the microbial examination of nonsterile product assays and the subsequent root cause investigation. The focus of this article is on aberrant results obtained from a validated assay with established acceptance criteria., (© PDA, Inc. 2020.)

Internal standard (IS) plays an important role in LC-MS bioanalysis by compensating for the variability of the analyte of interest in bioanalytical workflow. Due to the complexity of biological sample compositions and bioanalytical processes, a certain level of IS response variability across a run or a study is anticipated. However, an extensive variability may raise doubts to the accuracy of the measured results and also suggest nonoptimal analytical method. In this current paper, recent publications and guidelines regarding IS response in LC-MS bioanalysis were thoroughly reviewed with focus on the evaluation, identification and impact assessment of 'abnormal' IS response variability. A systematic decision tree was proposed to facilitate investigation into abnormal IS response variability after each run.

Background: Finding the best practices for accident prevention is possible by identifying the influential factors affecting accident occurrence and their interactions as well as implementing corrective actions for the root cause factors., Objective: This study was aimed to determine the cause-effect relationships and the interaction of the influential factors affecting accident occurrence and determine the critical root factors., Methods: This study was carried out based on the opinions of a panel of experts and used the fuzzy DEMATEL method., Results: The results showed that "organization safety attitude", "safety communication", "work and safety training" and "safe design of systems" are root cause variables. Also, "work and safety knowledge" and "experience in the job" are individual cause variables., Conclusions: Organizational factors and some of individual variables are the critical factors that affect the occurrence of accidents. Therefore, corrective actions for accident prevention should primarily focus on the correction of these variables.

A clear picture of what Human Performance success looks like is now available from BioPhorum, where members of the Human Performance workstream have defined a blue-sky for the industry. This blue-sky document is both a guide and an assessment tool, which includes warning flags that help to identify significant obstacles in the way of effective human performance integration with operations that must be addressed. The effort to improve reliable operations within biopharma using elements of human performance borrowed from other industries have experienced uneven results and slow progress across the last seven years and has been bogged down for multiple significant reasons. These include a mental model that persists within the industry where workers are assumed to be the problem that needs fixing, the mistaken belief that Lean/Operational Excellence is a cure-all and nearly equivalent to human performance, neglecting the need to fundamentally rethink why and how investigations are performed, and truly underestimating the time, effort, strength of sponsor support, and strategy needed to change how work is designed, executed, and then later learned from. LAY ABSTRACT: Human Performance is an integrated risk management approach to improving systems, that includes human factors and systems safety, that leads to higher reliability and enhanced operational resilience. A clear picture of what Human Performance looks like in biopharma is available from the BioPhorum, where members of the Human Performance workstream have defined a blue-sky for the industry. This blue-sky document is both a guide and an assessment tool that will help to identify the steps to effective human performance integration with operations. The effort to improve reliable operations within biopharma using elements of human performance borrowed from other industries has experienced uneven results and slow progress across the last seven years and has been bogged down for multiple significant reasons. These include a mental model that persists within the industry where workers are assumed to be the problem that needs fixing, the mistaken belief that Lean practices (intended to improve productivity & efficiency) is a cure-all and nearly equivalent to human performance, neglecting the need to fundamentally rethink why and how investigations are performed, and truly underestimating the time, effort, strength of sponsor support needed to change how work is designed, executed, and then later learned from., (© PDA, Inc. 2019.)

Objective: Children in slums are at high risk of undernutrition, which has long-term negative consequences on their physical growth and cognitive development. Severe undernutrition can lead to the child's death. The present paper aimed to understand the causes of undernutrition in children as perceived by various groups of community members in Nairobi slums, Kenya., Design: Analysis of ten focus group discussions and ten individual interviews with key informants. The main topic discussed was the root causes of child undernutrition in the slums. The focus group discussions and key informant interviews were recorded and transcribed verbatim. The transcripts were coded in NVivo by extracting concepts and using a constant comparison of data across the different categories of respondents to draw out themes to enable a thematic analysis., Setting: Two slum communities in Nairobi, Kenya., Subjects: Women of childbearing age, community health workers, elders, leaders and other knowledgeable people in the two slum communities (n 90)., Results: Participants demonstrated an understanding of undernutrition in children., Conclusions: Findings inform target criteria at community and household level that can be used to identify children at risk of undernutrition. To tackle the immediate and underlying causes of undernutrition, interventions recommended should aim to: (i) improve maternal health and nutrition; (ii) promote optimal infant and young children feeding practices; (iii) support mothers in their working role; (iv) increase access to family planning; (v) improve water, sanitation and hygiene (WASH); (vi) address alcohol problems at all levels; and (vii) address street food issues with infant feeding counselling.