Predicting healthcare high-cost users using data mining methods

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe increase in healthcare costs is, perhaps, one of the most important issues that governments and organizations face nowadays. An ageing population and technological advancements are the key reasons for this phenomenon. In this scenario, proactive measures are very important. This work aimed to improve the effectiveness of the prevention by helping the identification of the most probable high-cost users of health services in future years. Data from 2015 to 2019 of approximately 30,000 Central Bank of Brazil’s Health Program’s enrollees were used to train, validate and test four types of models, considering the kind of high-cost users (simple or cost-bloomers, i.e., non-high-cost in previous periods) and the time-span between predictors and the dependent variable (none or one year), an innovation suggested by other authors. Different percentual cut-off points to define highcost were used, and up to 67% of high-risk users’ expenses could be correctly captured. Results confirmed the importance of previous costs data for this kind of prediction and showed that costbloomers and one-year time-span approaches reach good performance, creating opportunities to improve users’ health outcomes while contributing to the fiscal sustainability of private and public health systems

Advances in knowledge discovery and data mining Part II

19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p

Characterisation of a novel interaction of dystrophin with caveolae in the heart

Patients living with Duchenne and Becker muscular dystrophy are characterised respectively by the loss of a functional dystrophin protein and the expression of a mutant dystrophin protein. Dilated cardiomyopathy (DCM) is the major cause of death in these patients and the molecular mechanisms causing DCM in these patients are still not completely established. In fact, the cardiac disease is treated with cardioprotective drugs that delay but do not prevent DCM as a targeted treatment for the heart is still not available due to this lack of knowledge. Previous findings showed that exclusively in the heart, the dystrophin glycoprotein complex includes cavin-1, an essential protein for the biogenesis of caveolae. Caveolae in the heart are involved in mechanisms of cardio protection, cardiac contraction, and cardiac conduction. Key caveolae accessory proteins include cavin-2, -3 and -4. More importantly, caveolar protein mutations have been linked to cardiomyopathy. My PhD thesis investigates the molecular interactions between cardiac dystrophin and cavins that are important for cardiac function and are affected by dystrophin gene mutations. I have characterised the distribution of cavin proteins in mouse, rat and dog models of Duchenne muscular dystrophy (DMD) comparing this distribution in explanted human heart and discovered that cavin-1 and -4 cardiac localisation is conserved across these different species. I have investigated the effect of the loss of full-length dystrophin in DMD mouse, rat and dog models finding different levels of disruption of cavin-1 and -4 that could be attributed by the expression of shorter dystrophin isoforms in these animal models. I have also tested the ability of five different micro and mini-dystrophin (one of them is currently used in a clinical trial) constructs in restoring the physiological cardiac localisation of cavin-1 and -4 finding that none of them is able to do this. Overall, my findings suggest that the cardiac localisation of cavins is dependent on the expression of dystrophin at the cardiomyocyte membrane and that the cavin binding domain could reside in the distal part of the dystrophin protein. This knowledge suggests new roles of dystrophin in the heart and could be useful for the design of the next gene therapy constructs and for the development of targeted cardiac therapies

International Journal of Medical Students - Year 2015 - Volume 3 - Supplement 1

International Journal of Medical Students - Year 2015 - Volume 3 - Supplement

Development of a cardiovascular and lymphatic network model during human pregnancy

The human physiology undergoes significant adaptation during pregnancy, partic-ularly within the cardiovascular system. Insufficient cardiovascular adaptation can lead to several serious pathologies which can affect the growth of the foetus, such as hypertension, hypotension, pre-eclampsia, and placental insufficiency. Peripheral oedema occurs in the majority of woman over the course of a pregnancy, which is caused when the lymphatic system is unable to drain the excess fluid that has gathered in the interstitia.In order to provide a platform for modelling these pathologies, a comprehensive closed-loop 1D-0D cardiovascular network model of pregnancy is developed and presented in this thesis. The computational framework allows in-vivo measurement data, including pressures, cardiac output, and gestational week, to be integrated into the cardiovascular model. New numerical schemes are presented for reduced-order modelling of the cardiovascular system and the lymphatic system with a view to providing a platform for a coupled cardiovascular and lymphatic model.An automated parameter estimation technique is presented, which allows the integration of patient measurement data into the model through the iterative adap-tation of haemodynamic parameters, and could be utilised in a wide variety of cardiovascular pathology modelling.The pregnancy model is implemented using patient specific measurements and is extended to cover all gestational weeks for an idealised healthy pregnancy. The model solutions have shown good agreement with values from the literature for: the pulsatility index; pulse wave velocity; and flow rate waveforms in the uterine arteries, which includes the presence of a notch that is used in the clinic to detect pathologies. A novel aspect of the model is in predicting the blood supply to the uterus via the uterine and utero-ovarian communicating arteries, which could be useful in a clinical setting. The model is expected to provide a platform for modelling various pathologies that can develop during pregnancy