Banco Invest understanding how to grow in the Portuguese individual clients segment the client analysis

Field lab: Business project

The effects of cultural heritage on residential property values: Evidence from Lisbon, Portugal

This paper examines the impact of historic amenities on residential housing prices in the city of Lisbon, Portugal. Our study is directed towards identifying the spatial variation of amenity values for churches, palaces, lithic (stone) architecture and other historic amenities via the housing market, making use of both global and local spatial hedonic models. Our empirical evidence reveals that different types of historic and landmark amenities provide different housing premiums. While having a local non-landmark church within 100 meters increases housing prices by approximately 4.2%, higher concentrations of non-landmark churches within 1000 meters yield negative effects in the order of 0.1% of prices with landmark churches having a greater negative impact around 3.4%. In contrast, higher concentration of both landmark and non-landmark lithic structures positively influence housing prices in the order of 2.9% and 0.7% respectively. Global estimates indicate a negative effect of protected zones, however this significance is lost when accounting for heterogeneity within these areas. We see that the designation of historic zones may counteract negative effects on property values of nearby neglected buildings in historic neighborhoods by setting additional regulations ensuring that dilapidated buildings do not damage the city’s beauty or erode its historic heritage. Further, our results from a geographically weighted regression specification indicate the presence of spatial non-stationarity in the effects of different historic amenities across the city of Lisbon with variation between historic and more modern areas.

Aggregating community resources of care and assistance services for the elderly population

Changes in population age structure are a major concern and represent a priority in the agendas and policies of the developed world, which are demanding for renewed models of social and healthcare as well as assistance services to the elderly population. Studies indicate that as far as possible these types of services should desirably be provided at the user’s home, and that ICT-based solutions can have tremendous impact on the delivery of new services. This paper highlight and discusses some of the main results of a project undertaken in a Portuguese Municipality that demonstrates the potential contribution of an e-Marketplace of care and assistance services to the well-being of elderly people. Studies undertaken allowed identifying the main services that should be provided by such e-Marketplace (termed GuiMarket), the relevance that the population grant to this platform and, conversely, the fact that the Digital Divide phenomena influences the potential utilization of this project (and alike projects). The findings support that there is a strong relation between age and qualifications, and between access to ICT and the intended use of GuiMarket.

Child abuse monitor system model: a health care critical knowledge monitor system

The Childhood protection is a subject with high value for the society, but, the Child Abuse cases are difficult to identify. The process from suspicious to accusation is very difficult to achieve. It must configure very strong evidences. Typically, Health Care services deal with these cases from the beginning where there are evidences based on the diagnosis, but they aren’t enough to promote the accusation. Besides that, this subject it’s highly sensitive because there are legal aspects to deal with such as: the patient privacy, paternity issues, medical confidentiality, among others. We propose a Child Abuses critical knowledge monitor system model that addresses this problem. This decision support system is implemented with a multiple scientific domains: to capture of tokens from clinical documents from multiple sources; a topic model approach to identify the topics of the documents; knowledge management through the use of ontologies to support the critical knowledge sensibility concepts and relations such as: symptoms, behaviors, among other evidences in order to match with the topics inferred from the clinical documents and then alert and log when clinical evidences are present. Based on these alerts clinical personnel could analyze the situation and take the appropriate procedures.

Clustering-based approach for categorizing pregnant women in obstetrics and maternity care

When a pregnant woman is guided to a hospital for obstetrics purposes, many outcomes are possible, depending on her current conditions. An improved understanding of these conditions could provide a more direct medical approach by categorizing the different types of patients, enabling a faster response to risk situations, and therefore increasing the quality of services. In this case study, the characteristics of the patients admitted in the maternity care unit of Centro Hospitalar of Porto are acknowledged, allowing categorizing the patient women through clustering techniques. The main goal is to predict the patients’ route through the maternity care, adapting the services according to their conditions, providing the best clinical decisions and a cost-effective treatment to patients. The models developed presented very interesting results, being the best clustering evaluation index: 0.65. The evaluation of the clustering algorithms proved the viability of using clustering based data mining models to characterize pregnant patients, identifying which conditions can be used as an alert to prevent the occurrence of medical complications.

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Quality of institutional care and early childhood development

Institutional rearing adversely affects children’s development, but the extent to which specific characteristics of the institutional context and the quality of care provided contribute to problematic development remains unclear. In this study, 72 preschoolers institutionalised for at least 6 months were evaluated by their caregiver using the Child Behavior Checklist and the Disturbances of Attachment Interview. Distal and proximate indices of institutional caregiving quality were assessed using both staff reports and direct observation. Results revealed that greater caregiver sensitivity predicted reduced indiscriminate behaviour and secure-base distortions. A closer relationship with the caregiver predicted reduced inhibited attachment behaviour. Emotional and behavioural problems proved unrelated to caregiving quality. Results are discussed in terms of (non)-shared caregiving factors that influence institutionalised children’s development.

Analysis of portuguese residential buildings’ needs and proposed solutions

The Portuguese housing sector experienced a significant growth throughout the 20th century, particularly in the last quarter, after the democratic revolution in 1974. In fact, the number of buildings built between 1970 and 1990 is more than one third of the buildings actually existing in Portugal. Therefore most of them were built before the publication of the first regulation concerning the energy efficiency in buildings. Regarding this scenario, it would be expected that rehabilitation activities would represent most of the current construction activities. However, given some remaining barriers from old social policies, this situation is not observed; actually building retrofitting is the least significant sector, accentuating the degradation level of major part of the Portuguese housing stock. Several studies show that the main problems are found in the buildings envelope elements, such as roofs and façades. Based on this context, the aim of this paper is to introduce some examples of building retrofitting systems that, adapted to the Portuguese main needs and requirements may represent sustainable solutions to overcome the identified needs of Portuguese buildings' envelope.

Cost optimal strategies for the renovation of residential neighbourhoods towards energy and emissions neutrality – Rainha Dona Leonor case study

Buildings are one of the major consumers of energy in Europe. This makes them an important target when aiming to reduce the energy consumptions and carbon emissions. The majority of the European building stock has already some decades and so it needs renovation in order to keep its functionality. Taking advantage of these interventions, the energy performance of the buildings may also be improved. In Portugal the renovation techniques, both regarding energy efficiency measures as well as measures for the use of renewable energy sources, are normally planned at the building scale. It is important to explore the possibility of having large scale interventions, has it has been done in other countries, namely at neighbourhood scale with district energy system in order to optimize the results in terms of costs and environmental impact.

Optimal behavior of responsive residential demand considering hybrid phase change materials

Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customerâ s cost in different DRPs but also to guaranty the habitantsâ  satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customerâ s electricity cost can be reduced up to 48% by utilizing the proposed model.

Alcohol-dependent patients receiving specialised outpatient care: an overview of gender issues

OBJECTIVE: The objective of the present study, with focus on gender, was aimed at evaluating alcohol-dependent individual in terms of socio-demographic variables related to alcohol consumption and therapeutic interventions. METHODS: This is a retrospective cross-sectional study of 1,051 patients (833 men and 218 women), with diagnosis of alcohol dependence syndrome, according to ICD-10 criteria, who had sought treatment for the first time at a specialised health centre between 2000 and 2006. RESULTS: The results showed that women, compared to men, are more likely to be unemployed and without partner, in addition to having higher educational level, latter age of alcohol initiation, needing less outpatient alcohol detoxification program, consuming more fermented beverage, presenting less psychiatric comorbidities, and using less coadjutant medications during treatment. CONCLUSION: We can state that some peculiarities exist permeating both gender and alcohol consumption. A further focus on the characteristics of each population is needed to facilitate the adequate use of therapeutic interventions according to gender specificities.

Quality of life assessment of patients with schizophrenic spectrum disorders from Psychosocial Care Centers

OBJECTIVE: Assessing the quality of life and the clinical and social-demographic factors associated in schizophrenic spectrum patients (ICD-10 F20-F29) attending CAPS at the programmatic area 3.0. METHODS: A cross-sectional study was carried out in a sample of schizophrenic spectrum patients who have been enrolled in 2008 in CAPS in programmatic area (AP) 3 at Rio de Janeiro city, using MINIPLUS to assess schizophrenia spectrum disorder and use of psychoactive substances, Positive and Negative Symptoms Scale (PANSS) to assess psychiatric symptoms and Quality of Life Scale (QLS-BR) to assess the quality of life. RESULTS: Seventy nine patients were included, of whom 74 (93.7%) presented some impairment in quality of life. The most frequently affected area was occupational performance. Variables that showed a significant association with severe impairment of quality of life were: marital status, race, occupation, who patients lived with, homelessness, having children, previous psychiatric hospitalization, negative symptoms and symptoms designated as not applicable (being characterized by a lack of typical positive and negative symptoms). CONCLUSION: The knowledge of these factors should be crucial to implement health policies and psychosocial rehabilitation programs focused on improving the quality of life of these patients.