Abstract
Prostate cancer is a common cancer worldwide and a leading cause of death. Radiotherapy is usually the first-line treatment for patients with slow-growing cancer that is confined to the prostate. In Radiation Therapy Planning (RTP), the recognition and outlining of clinical volumes in computed tomography (CT) images are one of the most time-consuming steps carried out by human experts. The aim of this review is to identify and summarize evidence of the use of automatic organ delineation of CT images for radiotherapy planning in prostate cancer. From the literature search, a total of seven studies, reported between 1994 and 2009, were selected. We associate the selected studies in order to compare results, in spite of their differences in methodology and outcome evaluators. Most of the studies conclude that the automatic approach is faster, while having equivalent accuracy to manual method. Concerning the observer's variability, automatic segmentation reaches significant gains in reproducibility. As future directions, it is recommended the improvement of the segmentation algorithms in the delineation of problematic soft tissues and future validation studies with large scale trials and possible studies of meta-analysis in the specific problems.

Abstract
Mammographic databases play an important role in the development of algorithms aiming to improve Computer-Aided Detection and Diagnosis systems (CAD). However, these often do not take into consideration all the requirements needed for a proper study, previously discussed at the Biomedical Image Processing Meeting in 1993. Case selection and annotation requirements are the most commonly referenced in literature, when describing a database used for the development of such algorithms. This work aims to assess the compliance and suitability of case selection and annotation requirements in the publicly available mammographic databases for development and optimization of CADs. A literature review has been made, applying proper selection criteria related to the research question. In the literature, we found citations to 3 publicly available mammographic databases and ten having restricted access. Through the analysis of the results attained, we noticed that none of the two requirements previously described is on its way to be fully complied in mammographic databases. We can conclude that researchers need a database that fulfils all the mentioned requirements in order to develop efficacious and effective CAD systems. We also believe that the requirements, discussed in 1993, need to be reviewed and updated. New paradigms and ideas to increase algorithms' performance are needed in order to improve CAD schemes.

Abstract
The volume of health data is rising and health information technologies which include electronic health records are a promising solution, on data management and collection, to achieve greater quality outcomes. However, they often cause errors instead of preventing them. To study the main barriers to high quality data collection from electronic health records, a qualitative review study was conducted using 5 different database engines having only considered data quality and documentation issues, opportunities and challenges for proper data collection, electronic health records data and corresponding databases quality. It were included 16 articles from which data availability, format, accuracy and data accessibility were the most focused problems to address. Still, solutions are available: early recognition of those problems, well structured and designed EHRs, standard coding use, periodic accuracy monitoring and feedback and broad use of such systems for the most daily tasks possible, among others. Altogether they can improve EHR data quality for everyday use.

Abstract
With today's hospital demands and financial constraints, hospital inpatient bed management is becoming increasingly complex. The use of decision support systems could enable hospital staff and health decision makers to perform more focused management of the hospital inpatient beds, thus potentially reducing costs and inpatient length of stay. A literature review was carry out on both PubMed and ISI Web of Knowledge in order to identify studies evaluating the use of decision support systems when applied to hospital inpatient bed management. Two different approaches were identified: one approach based on the use of mathematical models to support the planning and allocation of hospital inpatient beds and another approach consisting in the utilization of information technologies to support timely inpatient placement. It was perceived that mathematical models could be safely used to model annual patient arrival rates and bed occupancy, thus forecasting hospital/department bed demand and underlying cost structures/revenues. It was also perceived that the use of bed management information systems provides hospital staff (administrative clerk, clinicians and housekeepers) with the necessary information to timely assess performance measures based on the hospital/department activity thus increasing resource effectiveness, optimizing established clinical pathways, reducing inpatient length of stay and associated costs.

Abstract
Due to the severity of patients treated in the intensive care units, these units are commonly equipped with a variety of equipment that is handled by a multidisciplinary team. In order to identify problems, present and future, clinicians perform periodic assessments that produce huge amount of data, which availability is of vital importance. This study was performed in order to assess the impact of clinical data centralized in a clinical information system for inpatients in an intensive care unit, when compared with data disseminated in different systems. A literature search was conducted on PubMed in order to identify relevant articles published between 2000 and 2010. From a total of 48 articles, 7 articles were selected for assessment. 2 articles studied the impact of system integration, 4 articles studied the impact of computerized medical records and 1 article studied both the impact of computerized medical records and system integration. A centralized clinical information system was proved to have a positive impact for inpatients in an intensive care unit. These systems allow time savings on vital signs transcription, reduced medication errors, a quicker access to clinical data and a reduction in prescription errors.

Abstract
Radiographer abnormality detection schemes (RADS) were introduced in the early 1980s to assist emergency departments. The development of PACS systems are affecting health professionals forcing them to evolve along, reviewing images on a computer monitor rather than on radiographic film. This article reviewed published articles that evaluated the impact of the use of a Red Dot System in patient outcome of emergency trauma patients and assessed the implementation of a Red Dot System in a Radiology Department with digital radiography and PACS. Few articles addressed the implementation issues and use of a Red Dot system in Computed Radiology. Radiographer skeletal red dot studies, had sensitivity and specificity of, respectively, 0.71 and 0.96 pre-training, and 0.81 and 0.95 post-training, compared with a reference standard. The use of radiographer abnormality detection schemes such as Red Dot and reporting has the potential to improve the diagnosis and outcome of emergency patients. The arrival of Information Technologies (IT) to healthcare and the introduction of Digital Radiography have limited the functionality of RADS due to incompatibility of new technology with the standard practice. New image technology solutions in Radiology should enhance the development and utilization of radiographer skills in RADS environments.