Abstract
Abiding to the law is, in some cases, a delicate balance between the rights of different players. Re-using health records is such a case. While the law grants reuse rights to public administration documents, in which health records produced in public health institutions are included, it also grants privacy to personal records. To safeguard a correct usage of data, public hospitals in Portugal employ jurists that are responsible for allowing or withholding access rights to health records. To help decision making, these jurists can consult the legal opinions issued by the national committee on public administration documents usage. While these legal opinions are of undeniable value, due to their doctrine contribution, they are only available in a format best suited from printing, forcing individual consultation of each document, with no option, whatsoever of clustered search, filtering or indexing, which are standard operations nowadays in a document management system. When having to decide on tens of data requests a day, it becomes unfeasible to consult the hundreds of legal opinions already available. With the objective to create a modern document management system, we devised an open, platform agnostic system that extracts and compiles the legal opinions, ex-tracts its contents and produces metadata, allowing for a fast searching and filtering of said legal opinions.

Abstract
Obstructive sleep apnea (OSA) is a significant sleep problem with various clinical presentations that have not been formally characterized. This poses critical challenges for its recognition, resulting in missed or delayed diagnosis. Recently, cluster analysis has been used in different clinical domains, particularly within numeric variables. We applied an extension of k-means to be used in categorical variables: k-modes, to identify groups of OSA patients. Demographic, physical examination, clinical history, and comorbidities characterization variables (n=46) were collected from 318 patients; missing values were all imputed with k-nearest neighbors (k-NN). Feature selection, through Chi-square test, was executed and 17 variables were inserted in cluster analysis, resulting in three clusters. Cluster 1 having an age between 65 and 90 years (54%), 78% of males, with the presence of diabetes and gastroesophageal reflux, and high OSA prevalence; Cluster 2 presented a lower percentage of OSA (46%), with middle-aged women without comorbidities, but with gastroesophageal reflux; and Cluster 3 was very similar to cluster 1, only differing in age (45-64) and comorbidities were not present. Our results suggest that there are different groups of OSA patients, creating the need to rethink the baseline characteristics of these patients before being sent to perform polysomnography (gold standard exam for diagnosis). © 2018 IEEE.

Abstract
The aim of this scoping review is to give an overview and appraisal of the development of outcome measurement throughout time and its present importance to healthcare and specifically to palliative care clinical practice. It is based on a search and search results of a published systematic review on implementing patient reported outcome measures in palliative care clinical practice. Medline, PsycInfo, Cumulative Index to Nursing and Allied Health Literature, Embase and British Nursing Index were systematically searched from 1985. Hand searching of reference lists for all included articles and relevant review articles was performed. A total of 3,863 articles were screened. Sixty were included in this scoping review. Outcome measurement has a long history in health care and some of the strongest advocates were Florence Nightingale for using patient outcomes besides mortality rates, Codman for the "end result idea" of evaluating the patient status one year after orthopaedic surgery, and Donabedian for taking Codman's work further and developing the structure-process-outcome model. The contribution of patient-centred outcome measurement is vast and paramount in education, audit and as an informative tool for healthcare professionals and decision makers. It is possible to collect these data nationwide which would then allow for cross country comparisons, as well as, economic evaluations in palliative care interventions to contribute to appropriate resource allocation.

Abstract

Abstract
The current availability of large volumes of health care data makes it a promising data source to new views on disease interaction. Most of the times, patients have multiple diseases instead of a single one (also known as multimorbidity), but the small size of most clinical research data makes it hard to impossible to investigate this issue. In this paper, we propose a latent-based approach to expand patient evolution in temporal electronic health records, which can be uninformative due to its very general events. We introduce the notion of clusters of hidden states allowing for an expanded understanding of the multiple dynamics that underlie events in such data. Clusters are defined as part of hidden Markov models learned from such data, where the number of hidden states is not known beforehand. We evaluate the proposed approach based on a large dataset from Dutch practices of patients that had events on comorbidities related to atherosclerosis. The discovered clusters are further correlated to medical-oriented outcomes in order to show the usefulness of the proposed method.

Abstract
The varied phenotypes of obstructive sleep apnea (OSA) poses critical challenges, resulting in missed or delayed diagnosis. In this work, we applied k-modes, aiming to identify groups of OSA patients, based on demographic, physical examination, clinical history, and comorbidities characterization variables (n=41) collected from 318 patients. Missing values were imputed with k-nearest neighbours (k-NN) and chi-square test was held. Thirteen variables were inserted in cluster analysis, resulting in three clusters. Cluster 1 were middle-aged men, while Cluster 3 were the oldest men and Cluster 2 mainly middle-aged women. Cluster 3 weighted the most, whereas Cluster 1 weighted the least. The same effect was described in increased neck circumference. The percentages of variables driving sleepiness, congestive heart failure, arrhythmias and pulmonary hypertension were very low (<20%) and OSA severity was more common in mild level. Our results suggest that it is possible to phenotype OSA patients in an objective way, as also, different (although not considered innovative) visualizations improve the recognition of this common sleep pathology.