Data mining applied to the cognitive rehabilitation of patients with acquired brain injury

Acquired brain injury (ABI) is one of the leading causes of death and disability in the world and is associated with high health care costs as a result of the acute treatment and long term rehabilitation involved. Different algorithms and methods have been proposed to predict the effectiveness of rehabilitation programs. In general, research has focused on predicting the overall improvement of patients with ABI. The purpose of this study is the novel application of data mining (DM) techniques to predict the outcomes of cognitive rehabilitation in patients with ABI. We generate three predictive models that allow us to obtain new knowledge to evaluate and improve the effectiveness of the cognitive rehabilitation process. Decision tree (DT), multilayer perceptron (MLP) and general regression neural network (GRNN) have been used to construct the prediction models. 10-fold cross validation was carried out in order to test the algorithms, using the Institut Guttmann Neurorehabilitation Hospital (IG) patients database. Performance of the models was tested through specificity, sensitivity and accuracy analysis and confusion matrix analysis. The experimental results obtained by DT are clearly superior with a prediction average accuracy of 90.38%, while MLP and GRRN obtained a 78.7% and 75.96%, respectively. This study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients.

National consumer survey of medical costs and voluntary health insurance. Summary report[s] 1-4.

Mode of access: Internet.

Health care costs and lack of access to health insurance : hearings before the Committee on Finance, United States Senate, One Hundred Second Congress, first session.

"April 9 and 16, 1991"--Pt. 1; "June 6, 1991"--Pt. 2.

Internet of healthcare (law): privacy and data protection aspects in an internet of everything

The purpose of this research study is to discuss privacy and data protection-related regulatory and compliance challenges posed by digital transformation in healthcare in the wake of the COVID-19 pandemic. The public health crisis accelerated the development of patient-centred remote/hybrid healthcare delivery models that make increased use of telehealth services and related digital solutions. The large-scale uptake of IoT-enabled medical devices and wellness applications, and the offering of healthcare services via healthcare platforms (online doctor marketplaces) have catalysed these developments. However, the use of new enabling technologies (IoT, AI) and the platformisation of healthcare pose complex challenges to the protection of patient’s privacy and personal data. This happens at a time when the EU is drawing up a new regulatory landscape for the use of data and digital technologies. Against this background, the study presents an interdisciplinary (normative and technology-oriented) critical assessment on how the new regulatory framework may affect privacy and data protection requirements regarding the deployment and use of Internet of Health Things (hardware) devices and interconnected software (AI systems). The study also assesses key privacy and data protection challenges that affect healthcare platforms (online doctor marketplaces) in their offering of video API-enabled teleconsultation services and their (anticipated) integration into the European Health Data Space. The overall conclusion of the study is that regulatory deficiencies may create integrity risks for the protection of privacy and personal data in telehealth due to uncertainties about the proper interplay, legal effects and effectiveness of (existing and proposed) EU legislation. The proliferation of normative measures may increase compliance costs, hinder innovation and ultimately, deprive European patients from state-of-the-art digital health technologies, which is paradoxically, the opposite of what the EU plans to achieve.

Patient data sharing for the improvement of healthcare and medical research: towards a moral duty of patients to share health-related data?

The project answers to the following central research question: ‘How would a moral duty of patients to transfer (health) data for the benefit of health care improvement, research, and public health in the eHealth sector sit within the existing confidentiality, privacy, and data protection legislations?’. The improvement of healthcare services, research, and public health relies on patient data, which is why one might raise the question concerning a potential moral responsibility of patients to transfer data concerning health. Such a responsibility logically would have subsequent consequences for care providers concerning the further transferring of health data with other healthcare providers or researchers and other organisations (who also possibly transfer the data further with others and other organisations). Otherwise, the purpose of the patients’ moral duty, i.e. to improve the care system and research, would be undermined. Albeit the arguments that may exist in favour of a moral responsibility of patients to share health-related data, there are also some moral hurdles that come with such a moral responsibility. Furthermore, the existing European and national confidentiality, privacy and data protection legislations appear to hamper such a possible moral duty, and they may need to be reconsidered to unlock the full use of data for healthcare and research.

Whole life health insurance

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de mestre em Matemática e Aplicações

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Rockburst laboratory tests database - Application of data mining techniques

Rockburst is characterized by a violent explosion of a block causing a sudden rupture in the rock and is quite common in deep tunnels. It is critical to understand the phenomenon of rockburst, focusing on the patterns of occurrence so these events can be avoided and/or managed saving costs and possibly lives. The failure mechanism of rockburst needs to be better understood. Laboratory experiments are undergoing at the Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUE) of Beijing and the system is described. A large number of rockburst tests were performed and their information collected, stored in a database and analyzed. Data Mining (DM) techniques were applied to the database in order to develop predictive models for the rockburst maximum stress (σRB) and rockburst risk index (IRB) that need the results of such tests to be determined. With the developed models it is possible to predict these parameters with high accuracy levels using data from the rock mass and specific project.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.

Acute Coronary Syndrome Treatment Costs from the Perspective of the Supplementary Health System

AbstractBackground:Acute coronary syndrome (ACS) is defined as a “group of clinical symptoms compatible with acute myocardial ischemia”, representing the leading cause of death worldwide, with a high clinical and financial impact. In this sense, the development of economic studies assessing the costs related to the treatment of ACS should be considered.Objective:To evaluate costs and length of hospital stay between groups of patients treated for ACS undergoing angioplasty with or without stent implantation (stent+ / stent-), coronary artery bypass surgery (CABG) and treated only clinically (Clinical) from the perspective of the Brazilian Supplementary Health System (SHS).Methods:A retrospective analysis of medical claims of beneficiaries of health plans was performed considering hospitalization costs and length of hospital stay for management of patients undergoing different types of treatment for ACS, between Jan/2010 and Jun/2012.Results:The average costs per patient were R$ 18,261.77, R$ 30,611.07, R$ 37,454.94 and R$ 40,883.37 in the following groups: Clinical, stent-, stent+ and CABG, respectively. The average costs per day of hospitalization were R$ 1,987.03, R$ 4,024.72, R$ 6,033.40 and R$ 2,663.82, respectively. The average results for length of stay were 9.19 days, 7.61 days, 6.19 days and 15.20 days in these same groups. The differences were significant between all groups except Clinical and stent- and between stent + and CABG groups for cost analysis.Conclusion:Hospitalization costs of SCA are high in the Brazilian SHS, being significantly higher when interventional procedures are required.

White Paper on Private Health Insurance

This White Paper, which arises from commitments in the Action Programme for the New Millennium, sets out the Government’s policy objectives and proposals regarding the role of private health insurance in the overall healthcare system, the regulation of the health insurance market, and the corporate structure and status of the Voluntary Health Insurance Board Download the Report here

Not so disadvantaged: Portuguese migrants in Switzerland have a better access to healthcare and health status than Portuguese residents

Background: Most migrant studies have compared health characteristics between migrants and nationals of the host country. We aimed at comparing health characteristics of migrants with nationals from their home country. Methods: Portuguese national health survey (2005-6; 30,173 participants aged 18-75 years) and four national health surveys conducted in Switzerland (2002, 2004, 2007 and 2011, totalling 1,170 Portuguese migrants of the same age range). Self-reported data on length of stay, cardiovascular risk factors, healthcare use and health status were collected. Results: Resident Portuguese were significantly older and more educated than migrants. Resident Portuguese had a higher mean BMI and prevalence of obesity than migrants. Resident Portuguese also reported more frequently being hypertensive and having their blood pressure screened within the last year. On the contrary, migrant Portuguese were more frequently smokers, had a medical visit in the previous year more frequently and self-rated their health higher than resident Portuguese. After adjustment for age, gender, marital status and education, migrants had a higher likelihood smoking, of having a medical visit the previous year, and of self-rating their current health as good or very good than resident Portuguese. Compared to Portuguese residents, cholesterol screening in the previous year was more common only among migrants living in Switzerland for more than 17 years. Conclusion: Portuguese migrants in Switzerland do not differ substantially from resident Portuguese regarding most cardiovascular risk factors. Migrants appear to benefit from higher healthcare accessibility and consider themselves healthier than Portuguese residents.

Portuguese migrants in Switzerland: healthcare and health status compared to portuguese residents.

BACKGROUND: Most migrant studies have compared health characteristics between migrants and nationals of the host country. We aimed at comparing health characteristics of migrants with nationals from their home country. METHODS: Portuguese national health survey (2005-6; 30,173 participants aged 18-75 years) and four national health surveys conducted in Switzerland (2002, 2004, 2007 and 2011, totalling 1,170 Portuguese migrants of the same age range). Self-reported data on length of stay, cardiovascular risk factors, healthcare use and health status were collected. RESULTS: Resident Portuguese were significantly older and more educated than migrants. Resident Portuguese had a higher mean BMI and prevalence of obesity than migrants. Resident Portuguese also reported more frequently being hypertensive and having their blood pressure screened within the last year. On the contrary, migrant Portuguese were more frequently smokers, had a medical visit in the previous year more frequently and self-rated their health higher than resident Portuguese. After adjustment for age, gender, marital status and education, migrants had a higher likelihood of smoking, of having a medical visit the previous year, and of self-rating their current health as good or very good than resident Portuguese. Compared to Portuguese residents, cholesterol screening in the previous year was more common only among migrants living in Switzerland for more than 17 years. CONCLUSION: Portuguese migrants in Switzerland do not differ substantially from resident Portuguese regarding most cardiovascular risk factors. Migrants consider themselves healthier than Portuguese residents and more often had a recent medical visit.

Getting Ready to Retire: Health Insurance Issues, December 2006

Before making the decision to retire, understand the health insurance options available to you (and your spouse if you are married). Which questions you need to ask depends on: • how old you are. • how old your spouse is. • whether you or your spouse is eligible for Medicare. • whether you or your spouse will continue to be employed. • how many employees the employer has.