Outcomes from surgery are dependent upon technical performance, as demonstrated by the variability that exists in outcomes achieved by different surgeons following surgery for rectal cancer. It is possible to improve such outcomes by focused training and the adoption of specific surgical techniques, such as the total mesorectal excision (TME) training programme in Stockholm which reduced local recurrence rates of cancer by 50%. It is generally accepted that good surgical technique is the enactment of a series of positive surgical actions, and the avoidance of errors. However, the constituents of good surgical technique for rectal cancer have not yet been studied in sufficient detail to identify the specific associations between individual steps and their consequences. In this study the ergonomic principles of human reliability analysis (HRA) were applied to video recordings of rectal cancer surgery. A system of error definition and identification was developed, utilising a bespoke software solution designed for the project. Calculation of optimal camera angles and position was determined in a virtual operating theatre. Analysis of synchronised footage from multiple camera views was performed, through which over 6,000 errors were identified across 14 procedural tasks. The sequences of events contributing to these errors are reported, and a series of error reduction mechanisms formulated for rectal cancer surgery.

<p>In high-risk environments of seafaring, simulators constitute a widely used tool in preparing nauticalstudents for the challenges to be met in real-life working situations. While the technical developmentof ship bridge simulators continues at a breathtaking pace, little is known on how developments fulfiltheir intended safety critical purpose during actual simulator training exercises.In order to investigate this, a mixed-methods quasi-experimental field study (N =6) was conductedaiming at discerning the systemic causes behind committed human errors and to what extent thesecauses can be related to the technical layout of the simulator in general and a decision supportingdisplay in particular. The nautical students’ performance in terms of committed errors was analysedwhen the decision supporting display was either inactive or active during two different exercisebatches. Drawing upon eye tracking evaluation, interviews and simulator video recordings, systemiccauses leading to human errors were identified. Results indicate that all errors occur under the samekind of (stressful) interaction. Based on this design requirements aiming at promoting resilient crewbehaviour were proposed</p>

The aim of the thesis was to develop and evaluate a Computerised Decision Support System (CDSS) for use in pre-hospital care. The thesis was guided by a theoretical framework for developing and evaluating a complex intervention. The four studies used different designs and methods. The first study was a systematic review of randomised controlled trials. The second and the last studies had experimental and quasi-experimental designs, where the CDSS was evaluated in a simulation setting and in a clinical setting. The third study included in the thesis had a qualitative case study design. The main findings from the studies in the thesis were that there is a weak evidence base for the use of CDSS in pre-hospital care. No studies have previously evaluated the effect of CDSS in pre-hospital care. Due to the context, pre-hospital care is dependent on protocol-based care to be able to deliver safe, high-quality care. The physical format of the current paper based guidelines and protocols are the main obstacle to their use. There is a request for guidelines and protocols in an electronic format among both clinicians and leaders of the ambulance organisations. The use of CDSS in the pre-hospital setting has a positive effect on compliance with pre-hospital guidelines. The largest effect is in the primary survey and in the anamnesis of the patient. The CDSS also increases the amount of information collected in the basic pre-hospital assessment process. The evaluated CDSS had a limited effect on on-the-scene time. The developed and evaluated CDSS has the ability to increase pre-hospital patient safety by reducing the risks of cognitive bias. Standardising the assessment process, enabling explicit decision support in the form of checklists, assessment rules, differential diagnosis lists and rule out worst-case scenario strategies, reduces the risk of premature closure in the assessment of the pre-hospital patient.

Neste trabalho foram obtidas estimativas das Probabilidades de Erro Humano (PEH) das ações dos operadores do Reator de Pesquisa IEA-R1 do IPEN, em resposta a uma hipótese de situação de emergência, e realizada uma avaliação dos Fatores Influenciadores do Desempenho Humano (PSF) potencialmente influentes naquelas ações. A avaliação dos PSF foi realizada com a finalidade de classificá-los de acordo com o seu nível de influência nas ações e de determinar o estado atual destes PSF na instalação. Tanto a obtenção das PEH, como também a avaliação dos PSF, foram realizadas por meio do processo de Avaliação por Especialistas, através de entrevistas e questionários. O grupo especialista foi composto a partir dos próprios operadores do Reator IEA-R1. A representação do conhecimento dos especialistas em expressões lingüísticas e a geração de valores que representam o consenso das avaliações do grupo especialista deram-se pelo emprego da Lógica Fuzzy e da Teoria dos Conjuntos Fuzzy. Os valores obtidos para as PEH foram comparados com dados utilizados pela literatura afim e se mostraram satisfatórios para ações similares, corroborando a metodologia proposta como uma boa alternativa a ser empregada em métodos de Análises de Confiabilidade Humana (ACH). / This work obtains Human Error Probability (HEP) estimates from operator\'s actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator\'s actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist\'s knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA).

Esta pesquisa teve como objetivo principal identificar oportunidades de aperfeiçoamento de um método de classificação de tipos de erros humanos de operadores de linha de frente. Tais oportunidades foram identificadas com base no teste do método em acidentes em canteiros de obras, um ambiente no qual ele ainda não havia sido aplicado. Assim, foram investigados 19 acidentes de trabalho ocorridos em uma construtora de pequeno porte, sendo classificados os tipos de erros dos trabalhadores lesionados e de colegas de equipe que encontravam-se no cenário do acidente. Os resultados indicaram que não houve nenhum erro de 57,9% dos trabalhadores para os quais o método foi aplicado, constituindo evidência de que as causas estavam fortemente associadas a fatores organizacionais ao invés de fatores comportamentais ou cognitivos. O estudo ainda apresenta recomendações que facilitam a interpretação das perguntas que constituem o método de classificação de tipos de erros. / This study aimed to identify major opportunities for improving a method of classification of errors types of front- line workers. Such opportunities have been identified on the basis of testing the method in accidents at construction sites, an environment in which it had not yet been implemented. Thus, we investigated 19 occupational accidents occurred in a small-sized construction company, classifying the errors types of both injured workers and crew members who were at the scene of the accident. The results indicated that there was no error of 57,9% of workers for which the method was applied, providing evidence that the causes were strongly linked to organizational factors rather than cognitive or behavioral factors. The study also presents recommendations to facilitate the interpretation of questions that constitute the method of classification of types of errors.

Esta pesquisa teve como objetivo principal identificar oportunidades de aperfeiçoamento de um método de classificação de tipos de erros humanos de operadores de linha de frente. Tais oportunidades foram identificadas com base no teste do método em acidentes em canteiros de obras, um ambiente no qual ele ainda não havia sido aplicado. Assim, foram investigados 19 acidentes de trabalho ocorridos em uma construtora de pequeno porte, sendo classificados os tipos de erros dos trabalhadores lesionados e de colegas de equipe que encontravam-se no cenário do acidente. Os resultados indicaram que não houve nenhum erro de 57,9% dos trabalhadores para os quais o método foi aplicado, constituindo evidência de que as causas estavam fortemente associadas a fatores organizacionais ao invés de fatores comportamentais ou cognitivos. O estudo ainda apresenta recomendações que facilitam a interpretação das perguntas que constituem o método de classificação de tipos de erros. / This study aimed to identify major opportunities for improving a method of classification of errors types of front- line workers. Such opportunities have been identified on the basis of testing the method in accidents at construction sites, an environment in which it had not yet been implemented. Thus, we investigated 19 occupational accidents occurred in a small-sized construction company, classifying the errors types of both injured workers and crew members who were at the scene of the accident. The results indicated that there was no error of 57,9% of workers for which the method was applied, providing evidence that the causes were strongly linked to organizational factors rather than cognitive or behavioral factors. The study also presents recommendations to facilitate the interpretation of questions that constitute the method of classification of types of errors.

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Malgorzata J. Rys / According to the Centers for Disease Control and Prevention (2015), urinary tract infections (UTIs) are the most commonly reported healthcare-associated infection (HAI), of which approximately 75% of infections are attributed to the presence of a urinary catheter. Urinary catheters are commonplace within hospitals as approximately 15-25% of patients receive a urinary catheter during their hospitalization, introducing the risk of a catheter associated urinary tract infection (CAUTI) during their stay (CDC, 2015). In recent years there have been efforts to reduce CAUTI in U.S. hospitals; however, despite these efforts, CAUTI rates indicate the need to continue prevention efforts. Researchers have investigated the use of human reliability analysis (HRA) techniques to predict and prevent CAUTI (Griebel, 2016), and this research builds on that topic by applying the Human Error Assessment and Reduction Technique (HEART) to develop a model for a patient’s probability of CAUTI. HEART considers 40 different error-producing conditions (EPCs) present while performing a task, and evaluates the extent to which each EPC affects the probability of an error. This research considers the task of inserting a Foley catheter, where an error in the process could potentially lead to a CAUTI. Significant patient factors that increase a patient’s probability of CAUTI (diabetes, female gender, and catheter days) are also considered, along with obesity which is examined from a process reliability perspective. Under the HEART process, human reliability knowledge and the knowledge of eight expert healthcare professionals are combined to evaluate the probability that a patient will acquire a CAUTI. In addition to predicting the probability of CAUTI, HEART also provides a systematic way to prioritize patient safety improvement efforts by examining the most significant EPCs or process steps. The proposed CAUTI model suggests that 7 of the 26 steps in the catheter insertion process contribute to 95% of the unreliability of the process. Three of the steps are related to cleaning the patient prior to inserting the catheter, two of the steps are directly related to actually inserting the catheter, and two steps are related to maintaining the collection bag below the patient’s bladder. An analysis of the EPCs evaluated also revealed that the most significant factors affecting the process are unfamiliarity, or the possibility of novel events, personal psychological factors, shortage of time, and inexperience. By targeting reliability improvements in these steps and factors, healthcare organizations can have the greatest impact on preventing CAUTI.

Esta pesquisa teve como objetivo principal identificar oportunidades de aperfeiçoamento de um método de classificação de tipos de erros humanos de operadores de linha de frente. Tais oportunidades foram identificadas com base no teste do método em acidentes em canteiros de obras, um ambiente no qual ele ainda não havia sido aplicado. Assim, foram investigados 19 acidentes de trabalho ocorridos em uma construtora de pequeno porte, sendo classificados os tipos de erros dos trabalhadores lesionados e de colegas de equipe que encontravam-se no cenário do acidente. Os resultados indicaram que não houve nenhum erro de 57,9% dos trabalhadores para os quais o método foi aplicado, constituindo evidência de que as causas estavam fortemente associadas a fatores organizacionais ao invés de fatores comportamentais ou cognitivos. O estudo ainda apresenta recomendações que facilitam a interpretação das perguntas que constituem o método de classificação de tipos de erros. / This study aimed to identify major opportunities for improving a method of classification of errors types of front- line workers. Such opportunities have been identified on the basis of testing the method in accidents at construction sites, an environment in which it had not yet been implemented. Thus, we investigated 19 occupational accidents occurred in a small-sized construction company, classifying the errors types of both injured workers and crew members who were at the scene of the accident. The results indicated that there was no error of 57,9% of workers for which the method was applied, providing evidence that the causes were strongly linked to organizational factors rather than cognitive or behavioral factors. The study also presents recommendations to facilitate the interpretation of questions that constitute the method of classification of types of errors.

Submitted by Pedro Barros (pedro.silvabarros@ufpe.br) on 2018-06-20T22:54:11Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) TESE Marilia Abílio Ramos.pdf: 6997571 bytes, checksum: 1514e881a0919bde7d2b45038eed3a91 (MD5) / Made available in DSpace on 2018-06-20T22:54:11Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) TESE Marilia Abílio Ramos.pdf: 6997571 bytes, checksum: 1514e881a0919bde7d2b45038eed3a91 (MD5) Previous issue date: 2017-04-07 / ANP (Agência Nacional do Petróleo) / Petrobras / The oil industry has grown in recent decades in terms of quantity of facilities and process complexity. However, human and material losses still occur due to major accidents at the facility. The analysis of these accidents reveals that many involve human failures that, if prevented, could avoid such accidents. These failures, in turn, can be identified, modeled and quantified through Human Reliability Analysis (HRA), which forms a basis for prioritization and development of safeguards for preventing or reducing the frequency of accidents. The most advanced and reliable HRA methods have been developed and applied in nuclear power plant operations, while the petroleum industry has usually applied Quantitative Risk Analysis (QRA) focusing on process safety in terms of technical aspects of the operation and equipment. This thesis demonstrates that the use of HRA in oil refining and petrochemical operations allows the identification and analysis of factors that can influence the behavior of operators as well as the potential human errors that can contribute to the occurrence of an accident. Existing HRA methodologies, however, were mainly developed for the nuclear industry. Thus, they may not reflect the specificities of refining and petrochemical plants regarding the interaction of the operators with the plant, the failure modes of the operators and the factors that influence their actions. Thus, this thesis presents an HRA methodology developed specifically for use in this industry, HERO - Human Error in Refinery Operations HRA Methodology. The Phoenix HRA methodology was used as a basis, which has three layers i) a crew response tree (CRT), which models the interaction between the crew and the plant; ii) a human response model, modeled through fault trees, that identifies the possible crew failures modes (CFMs); and (iii) "contextual factors" known as performance influencing factors (PIFs), modeled through Bayesian networks. In addition to building on such a structure, HERO's development relied on interviews with HRA specialists, visitations to a refinery and its control room, and analysis of past oil refineries accidents - four accidents were analyzed in detail. The methodology developed maintains the three-layer structure and has a guideline flowchart for the construction of the CRT, in order to model the team-plant interactions in oil refining and petrochemical operations; it also features CFMs and PIFs developed specifically for this industry, with definitions that make them easily relatable by an analyst. Finally, the methodology was applied to three potential accidental scenarios of refinery operations. In one of these scenarios, it was combined with a QRA to illustrate how an HRA can be applied to a traditional QRA and to demonstrate the influence of PIFs and of human error probability on the final risk. The use of this methodology for HRA of refineries and petrochemical plants operations can enhance this industry safety and allow for solid riskbased decisions. / A indústria de petróleo teve grande crescimento nas últimas décadas em termos de quantidade de instalações e complexidade de processo. No entanto, perdas humanas e materiais ainda ocorrem devido a acidentes graves nas instalações. A análise desses acidentes revela que muitos envolvem falhas humanas que poderiam ser prevenidas de forma a evitar tais acidentes. Estas falhas, por sua vez, podem ser identificadas, modeladas e quantificadas através da Análise de Confiabilidade Humana (ACH), que forma uma base para priorização e desenvolvimento de salvaguardas na prevenção ou redução da frequência de acidentes. Os métodos de ACH mais avançados e confiáveis têm sido desenvolvidos e aplicados nas operações de controle de plantas nucleares; já a indústria de petróleo tem usualmente aplicado a Análise Quantitativa de Risco (AQR) com foco na segurança de processo em termos técnicos da operação e equipamentos. Esta tese demonstra que o uso da ACH em operações de refino e petroquímica possibilita a identificação e análise dos fatores que podem influenciar o comportamento do operador bem como as potenciais falhas humanas que podem contribuir para a ocorrência de um acidente. As metodologias de ACH existentes, no entanto, foram desenvolvidas para a indústria nuclear. Desta forma, elas não refletem as especificidades de refino e petroquímica no que se refere à interação dos operadores com a planta, aos modos de falha dos operadores e aos fatores que influenciam suas ações. Assim, esta tese apresenta uma metodologia de ACH desenvolvida especificamente para uso nessa indústria, a HERO - Human Error in Refinery Operations HRA Methodology. Como base, utilizou-se a Metodologia Phoenix, que possui três camadas i) uma árvore de resposta da equipe (crew response tree - CRT), que modela a interação da equipe com a planta; ii) um modelo de resposta humana, modelado através de árvores de falhas, que identifica os possíveis modos de falhas da equipe (crew failures modes - CFMs); e iii) os “fatores contextuais” conhecidos como fatores de desempenho ou performance influencing factors (PIFs), modelados através de redes Bayesianas. Além de basear-se em tal estrutura, o desenvolvimento da HERO apoiou-se em entrevistas com especialistas em ACH, visitas a uma refinaria e sua sala de controle e na análise de estudos de acidentes passados em refinarias – foram analisados em detalhe quatro acidentes. A metodologia desenvolvida mantém a estrutura de três camadas e possui um fluxograma-guia para construção da CRT, de forma a modelar as interações equipe-planta na operação de refino e petroquímicas; ela também apresenta CFMs e PIFs desenvolvidos especificamente para esta indústria, com definições que os tornam facilmente identificáveis por um analista. Por fim, a metodologia foi aplicada a três cenários acidentais de operações de refinaria. Em um destes cenários, ela foi conjugada a uma AQR de forma a ilustrar como uma ACH pode ser aplicada a uma tradicional AQR e para demonstrar a influência dos PIFs e da Probabilidade de Erro Humano no risco final. Espera-se que o uso da metodologia proposta nesta tese poderá aumentar a segurança em refinarias e petroquímicas e permitir sólidas decisões baseadas no risco.

[pt] Os modelos para a melhoria da qualidade de operações logísticas são fundamentados na tríade processo-pessoas-tecnologia. Este trabalho busca a relação entre dois desses pilares da qualidade: o processo e o ser humano. Ele avalia como os modelos de gestão consideram o ser humano e caracteriza a inserção de falhas como erros humanos cometidos no processo. Fatores humanos condicionantes do desempenho são identificados e, com base em pesquisa de campo cujo objetivo é explorar a realidade de operações logísticas, analisam-se os fatores humanos que podem afetar a qualidade do processo, principalmente no que diz respeito às características de funcionalidade e confiabilidade. / [en] Os modelos para a melhoria da qualidade de operações logísticas são fundamentados na tríade processo-pessoas-tecnologia. Este trabalho busca a relação entre dois desses pilares da qualidade: o processo e o ser humano. Ele avalia como os modelos de gestão consideram o ser humano e caracteriza a inserção de falhas como erros humanos cometidos no processo. Fatores humanos condicionantes do desempenho são identificados e, com base em pesquisa de campo cujo objetivo é explorar a realidade de operações logísticas, analisam-se os fatores humanos que podem afetar a qualidade do processo, principalmente no que diz respeito às características de funcionalidade e confiabilidade.