Sellutehtaan toiminnan tukeminen sisäistä viestintää kehittämällä

Työssä haluttiin selvittää sellutehdasorganisaation sisäisen viestinnän nykytilaa ja siihen liittyviä haasteita. Lisäksi selvitettiin mitä viestintäkanavia ja -käytäntöjä tuotantotoimintaan liittyy ja miten niitä tulisi kehittää. Tutkimuksessa käytettiin kvalitatiivista tutkimusotetta. Tutkimusaineisto kerättiin henkilökohtaisten teemahaastattelujen sekä ryhmähaastattelujen avulla. Teemahaastattelujen aineisto litteroitiin ja analysoitiin teema-alueitten mukaisesti. Ryhmähaastattelujen aineisto saatiin kirjaamalla olennaisimmat asiat keskustelujen aikana. Lopuksi saatu materiaali luokiteltiin ryhmiin haastattelukysymyksiin perustuen. Tutkimuksessa saatiin selkeä käsitys siihen mitä kanavia pitkin ja miten tuotanto-organisaatio viestii tällä hetkellä. Eri viestintäkanavien hyötyjen ja heikkouksien määrittämisen kautta voitiin arvioida mihin suuntaan viestinnän kehittämistä tulisi suunnata. Tulosten perusteella määriteltiin toimenpiteet, joiden kautta organisaatio saa parannettua tiedon kulun läpinäkyvyyttä ja lisättyä vuorovaikutusta organisaation eri toimijoiden välillä. Toimenpidesuositusten mukaan organisaation tulisi hyödyntää tehokkaammin käytössä olevaa sähköistä raportointijärjestelmää sekä kehittää palaveritoimintoja. Palautteenantoa, eli viestinnän kaksisuuntaisuutta tulisi korostaa, koska se vahvistaa ja ohjaa haluttua toimintaa. Tänä päivänä yritysten viestinnälliset tarpeet korostavat yhä enemmän yksilöllisiä vuorovaikutus- ja kommunikointitaitoja. Näiden taitojen osaamisen ja ymmärtämisen kautta on vasta mahdollista käyttää tehokkaasti viestintäteknologian tuomia etuja työyhteisöissä. Nämä taidot ovat myös pohjana muutostilanteista selviytymiselle.

Fraud detection in the banking sector : a multi-agent approach

Fraud is an increasing phenomenon as shown in many surveys carried out by leading international consulting companies in the last years. Despite the evolution of electronic payments and hacking techniques there is still a strong human component in fraud schemes. Conflict of interest in particular is the main contributing factor to the success of internal fraud. In such cases anomaly detection tools are not always the best instruments, since the fraud schemes are based on faking documents in a context dominated by lack of controls, and the perpetrators are those ones who should control possible irregularities. In the banking sector audit team experts can count only on their experience, whistle blowing and the reports sent by their inspectors. The Fraud Interactive Decision Expert System (FIDES), which is the core of this research, is a multi-agent system built to support auditors in evaluating suspicious behaviours and to speed up the evaluation process in order to detect or prevent fraud schemes. The system combines Think-map, Delphi method and Attack trees and it has been built around audit team experts and their needs. The output of FIDES is an attack tree, a tree-based diagram to ”systematically categorize the different ways in which a system can be attacked”. Once the attack tree is built, auditors can choose the path they perceive as more suitable and decide whether or not to start the investigation. The system is meant for use in the future to retrieve old cases in order to match them with new ones and find similarities. The retrieving features of the system will be useful to simplify the risk management phase, since similar countermeasures adopted for past cases might be useful for present ones. Even though FIDES has been built with the banking sector in mind, it can be applied in all those organisations, like insurance companies or public organizations, where anti-fraud activity is based on a central anti-fraud unit and a reporting system.

Voimalaitoksen energiaraportoinnin kehittäminen

Diplomityössä tarkasteltiin Metsä Board Simpeleen voimalaitoksen energiaraportointi kokonaisuutta. Tarkastelun kohteena olivat lämpö-, sähkö- ja polttoaine-energiat. Tarkastelun pääpaino oli energian määritykseen tarvittavissa mittapisteissä sekä niistä muodostuvissa raporteissa. Työn tavoitteena oli saada luotettavat energiaraportit, jotka ovat jaoteltu selkeästi ja johdonmukaisesti. Tavoitteena oli myös vähentää kuukausiraportoinnin muodostamiseen tarvittavaa henkilötyöaikaa. Teoriaosuudessa käsitellään yleisesti voimalaitosprosessin toimintaa sekä siinä käytettäviä polttoaineita. Energiataseen muodostamisen perusteita tarkasteltiin voimalaitosprosessin kannalta. Energian määrityksiin käytettävät prosessimittaukset käytiin läpi. Raportointivelvollisuudet selvitettiin, niin tilastokeskuksien, kuin viranomaistenkin suuntaan. Työosuudessa perehdyttiin käytössä oleviin raportointikäytäntöihin sekä raporttipohjiin. Energialaskentayhtälöt ja parametrit tarkastettiin tarvittavilta osin. Työnaikana havaittiin nopeasti, että raportointi muodostetaan pitkälti Microsoft Excel-taulukkolaskentaohjelmiston avulla. Olemassa olevia automatisoituja raportteja ei hyödynnetty ollenkaan, koska niitä pidettiin epäluotettavina. Työn tuloksena automatisoidut kuukausiraportit tarkastettiin, virheet korjattiin ja ne otettiin käyttöön. Automaattisiin raportteihin tehtiin päivitysehdotukset uusista raporttipohjista. Viralliseen kuukausiraportointiin rakennettiin myös kokonaan uudet raportointipohjat, jotka hyödyntävät automaattisesti muodostuvia raportteja. Uudet raporttipohjat nopeuttivat raportointityötä merkittävästi. Polttoaine-energian hallintajärjestelmä todettiin vanhanaikaiseksi ja sen uusimista suositellaan. Uusinnalla raportointityö helpottuisi ja sen avulla siitä saataisiin kattavampi.

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

Genotipificación de HLA-B en pacientes colombianos afectados por el síndrome Stevens-Johnson y la Necrólisis Epidérmica Tóxica

Las reacciones alérgicas a medicamentos cutáneas severas (RAM) como el Síndrome Stevens Johnson (SJS) y la Necrólisis Epidérmica Tóxica (NET),caracterizadas por exantema, erosión de la piel y las membranas mucosas, flictenas, desprendimiento de la piel secundario a la muerte de queratinocitos y compromiso ocular. Son infrecuentes en la población pero con elevada morbi-mortalidad, se presentan luego de la administración de diferentes fármacos. En Asia se ha asociado el alelo HLA-B*15:02 como marcador genético para SJS. En Colombia no hay datos de la incidencia de estas RAM, ni de la relación con medicamentos específicos o potenciales y tampoco estudios de aproximación genómica de genes de susceptibilidad.

Análisis predictivo de los eventos adversos relacionados con los indicadores de eficiencia hospitalaria de una IPS de Bogotá

En este estudio se realizó un análisis predictivo de la aparición de eventos adversos de los pacientes de una IPS de Bogotá, Mederi Hospital Universitario de Barrios Unidos (HUBU) durante el año 2013; relacionados con los indicadores de eficiencia hospitalaria (Porcentaje de ocupación hospitalaria, número de egresos hospitalarios, promedio de estancia hospitalaria, número de egresos de urgencias, promedio de estancia en urgencias). Los datos fueron exportados a una matriz de análisis de las variables cualitativas; fueron presentadas con frecuencias absolutas y relativas, las variables cuantitativas (edad, tiempos de estancia) fueron presentadas con media, desviaciones estándar. Se agruparon los datos de eventos adversos y de eficiencia hospitalaria en una nueva matriz que permitiera el análisis predictivo la nueva matriz fue exportada al software de modelación estadístico Eviews 6.5; se especificaron modelos predictivos multivariados para la variable número de eventos adversos, respecto de los indicadores de eficiencia hospitalaria y se estimaron las probabilidades de ocurrencia, análisis de correlación y multicolinealidad; los resultados se presentaron en tablas de estimación para cada modelo, se restringieron los eventos adversos prevenibles y no prevenibles información obtenida a través de un sistema de información que registra los factores relacionados con la ocurrencia de eventos adversos en salud, a través del sistema de reporte de eventos en salud, reporte en las historias clínicas, reporte individual, reporte por servicio, análisis de datos y estudios de caso, de la misma forma fueron extraídos los datos de eficiencia hospitalaria para el mismo periodo. El análisis y gestión de eventos adversos pretende establecer estrategias de mejoramiento continuo y análisis de resultados frente a los indicadores de eficiencia que permitan intervención de los factores de riesgo operativo de los servicios del Hospital Universitario de Barrios Unidos (HUBU), relacionados con eventos adversos en la atención de los pacientes en especial se debe enfocar en la gestión de los egresos de pacientes de acuerdo a los resultados obtenidos con el fin de alinearse y fortalecer las políticas de seguridad del paciente para brindar una atención integral con calidad y eficiencia, disminuyendo las quejas en la atención, las glosas, los riesgos jurídicos, de acuerdo al modelo predictivo estudiado.

Caracterizacion de nódulos tiroideos: concordancia entre estudio citopatologico y ecografia en la detección de nódulos malignos

: Los métodos imagenológicos para evaluar los nódulos tiroideos han sido motivo de estudio en las últimas décadas, especialmente la ecografía sobresale sobre las otras modalidades diagnósticas por su accesibilidad, portabilidad, y seguridad. A pesar de ello, las características ecográficas de cada nódulo han sido objeto de controversia en cuanto a su potencial detección de malignidad o benignidad. Se presenta un estudio de concordancia entre el estudio citopatológico y la ecografía para la caracterización nódulos tiroideos de naturaleza maligna y benigna, y su análisis de pruebas diagnósticas. Metodología: Se realizó un estudio descriptivo de concordancia con estudio de pruebas diagnósticas anidado. Se escogieron todos los pacientes con nódulos tiroideos a quienes se les realizó ecografía y estudio citopatológico de la lesión y se estudiaron los hallazgos ecográficos para evaluar su potencial diagnóstico para malignidad. Se incluyeron un total de 100 pacientes con nódulos tiroideos potencialmente malignos. La concordancia entre la ecografía en modo B y el estudio citopatológico fue moderada (índice kappa 0.55). La característica con mayor potencial para detectar malignidad fue la presencia de Microcalcificaciones (sensibilidad 75%, especificidad 92%).

Descripción de eventos adversos relacionados con aplicación de vacuna contra el virus de papiloma humano en Bogotá

Estudio descriptivo de los eventos adversos atribuidos a la vacuna contra el VPH reportados ante la Secretaría Distrital de Salud de Bogotá durante los años 2012 a 2014

A design for business intelligence service in demand driven supply chain management

This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

A credibilidade do testemunho da criança vítima de abuso sexual no contexto judiciário

Violência sexual contra crianças não é um evento incomum; no entanto, há a dificuldade de denúncia, pois, além do estabelecimento da relação de dominação que o agressor exerce sobre a vítima, a maneira como tal fato é recebido pela sociedade e como é encaminhado pelas instituições judiciárias responsáveis também é determinante para as omissões. Inserida no universo dos interrogatórios, muitas vezes, a criança causa confusão ao desmentir o que havia falado antes, reforçando possíveis preconceitos em relação a si mesma. O presente trabalho traz a análise das relações entre a infância e a instituição judiciária, com principal enfoque no sistema de comunicação e de notificação dos crimes sexuais contra a criança e as consequentes intervenções profissionais que buscam a validação, ou não, de seu testemunho. Para tanto, foram pesquisados 51 processos judiciais, dos quais foram selecionados dois casos exemplares. Este trabalho evidencia a possibilidade de preservar a criança da revitimização causada pela multiplicidade de interrogatórios, sem deixar de cumprir as normas jurídicas necessárias. A fragilidade da palavra da criança está na forma como é acolhida pelos adultos, desde a revelação na família até a denúncia aos órgãos oficiais, revelando a urgência de alterações nos procedimentos judiciais relacionados a essa problemática

A regional environmental accounting matrix and integrated environmental economic analyses to support regional planning

This research deals with the deepening and use of an environmental accounting matrix in Emilia-Romagna, RAMEA air emissions (regional NAMEA), carried out by the Regional Environment Agency (Arpa) in an European project. After a depiction of the international context regarding the widespread needing to integrate economic indicators and go beyond conventional reporting system, this study explains the structure, update and development of the tool. The overall aim is to outline the matrix for environmental assessments of regional plans, draw up sustainable reports and monitor effects of regional policies in a sustainable development perspective. The work focused on an application of a Shift-Share model, on the integration with eco-taxes, industrial waste production, energy consumptions, on applications of the extended RAMEA as a policy tool, following Eurostat guidelines. The common thread is the eco-efficiency (economic-environmental efficiency) index. The first part, in English, treats the methodology used to build a more complete tool; in the second part RAMEA has been applied on two regional case studies, in Italian, to support decision makers regarding Strategic Environmental Assessments’ processes (2001/42/EC). The aim is to support an evidence-based policy making by integrating sustainable development concerns at all levels. The first case study regards integrated environmental-economic analyses in support to the SEA of the Regional Waste management plan. For the industrial waste production an extended and updated RAMEA has been developed as a useful policy tool, to help in analysing and monitoring the state of environmental-economic performances. The second case study deals with the environmental report for the SEA of the Regional Program concerning productive activities. RAMEA has been applied aiming to an integrated environmental-economic analysis of the context, to investigate the performances of the regional production chains and to depict and monitor the area where the program should be carried out, from an integrated environmental-economic perspective.

Real-World Performance of Longitudinal Barriers Struck by Large Trucks

Outside of relatively limited crash testing with large trucks, very little is known regarding the performance of traffic barriers subjected to real-world large truck impacts. The purpose of this study was to investigate real-world large truck impacts into traffic barriers to determine barrier crash involvement rates, the impact performance of barriers not specifically designed to redirect large trucks, and the real-world performance of large-truck-specific barriers. Data sources included the Fatality Analysis Reporting System (2000-2009), the General Estimates System (2000-2009) and 155 in-depth large truck-to-barrier crashes from the Large Truck Crash Causation Study. Large truck impacts with a longitudinal barrier were found to comprise 3 percent of all police-reported longitudinal barrier impacts and roughly the same proportion of barrier fatalities. Based on a logistic regression model predicting barrier penetration, large truck barrier penetration risk was found to increase by a factor of 6 for impacts with barriers designed primarily for passenger vehicles. Although large-truck-specific barriers were found to perform better than non-heavy vehicle specific barriers, the penetration rate of these barriers were found to be 17 percent. This penetration rate is especially a concern because the higher test level barriers are designed to protect other road users, not the occupants of the large truck. Surprisingly, barriers not specifically designed for large truck impacts were found to prevent large truck penetration approximately half of the time. This suggests that adding costlier higher test level barriers may not always be warranted, especially on roadways with lower truck volumes.

Medication errors in a swiss cardiovascular surgery department: a cross-sectional study based on a novel medication error report method

The purpose of this study was (1) to determine frequency and type of medication errors (MEs), (2) to assess the number of MEs prevented by registered nurses, (3) to assess the consequences of ME for patients, and (4) to compare the number of MEs reported by a newly developed medication error self-reporting tool to the number reported by the traditional incident reporting system. We conducted a cross-sectional study on ME in the Cardiovascular Surgery Department of Bern University Hospital in Switzerland. Eligible registered nurses (n = 119) involving in the medication process were included. Data on ME were collected using an investigator-developed medication error self reporting tool (MESRT) that asked about the occurrence and characteristics of ME. Registered nurses were instructed to complete a MESRT at the end of each shift even if there was no ME. All MESRTs were completed anonymously. During the one-month study period, a total of 987 MESRTs were returned. Of the 987 completed MESRTs, 288 (29%) indicated that there had been an ME. Registered nurses reported preventing 49 (5%) MEs. Overall, eight (2.8%) MEs had patient consequences. The high response rate suggests that this new method may be a very effective approach to detect, report, and describe ME in hospitals.

LEARNING FROM NEAR MISSES IN MEDICATION ERRORS: A BAYESIAN APPROACH

Medical errors originating in health care facilities are a significant source of preventable morbidity, mortality, and healthcare costs. Voluntary error report systems that collect information on the causes and contributing factors of medi- cal errors regardless of the resulting harm may be useful for developing effective harm prevention strategies. Some patient safety experts question the utility of data from errors that did not lead to harm to the patient, also called near misses. A near miss (a.k.a. close call) is an unplanned event that did not result in injury to the patient. Only a fortunate break in the chain of events prevented injury. We use data from a large voluntary reporting system of 836,174 medication errors from 1999 to 2005 to provide evidence that the causes and contributing factors of errors that result in harm are similar to the causes and contributing factors of near misses. We develop Bayesian hierarchical models for estimating the log odds of selecting a given cause (or contributing factor) of error given harm has occurred and the log odds of selecting the same cause given that harm did not occur. The posterior distribution of the correlation between these two vectors of log-odds is used as a measure of the evidence supporting the use of data from near misses and their causes and contributing factors to prevent medical errors. In addition, we identify the causes and contributing factors that have the highest or lowest log-odds ratio of harm versus no harm. These causes and contributing factors should also be a focus in the design of prevention strategies. This paper provides important evidence on the utility of data from near misses, which constitute the vast majority of errors in our data.