Objectives—To identify the technologies that are being used in the remote care of patients with chronic conditions, and their most relevant outcomes. Methods—A systematic review of reviews and meta-analyses. Results—Fifty-one systematic reviews and meta-analyses related to diabetes, congestive heart failure, chronic obstructive pulmonary disease, mental and behavioral diseases, cancer, hypertension, asthma, multiple sclerosis, chronic renal disease, and obesity were retrieved; these studies compared the use of remote care technology with usual care. Conclusion—Remote care technology has positive effects in various health-related outcomes, but further research is required to allow its use in clinical practice.

The study reported in this article aimed to identify: i) the most relevant application domains of mHealth to support older adults in their domiciles; ii) the most relevant chronic conditions of older adults, whose management is being supported by mHealth; iii) the characteristics, outcomes and impacts of mHealth tools that might support older adults in their domiciles. The method of a systematic review of reviews and meta-analyses was performed based on a search of the literature. The result of a total of 66 reviews and meta-analyses across several chronic diseases were retrieved. These studies compare mHealth interventions with usual care. The conclusion is that mHealth interventions have positive effects on various health related outcomes, but further research is required to allow their incorporation in the clinical practice.

In a clinical environment are produced on daily basis huge volumes of information. In the radiology context, the realization of an increasing number of studies, in particular those associated with modalities that produce huge amounts of images, has given rise to large PACS archives. Proprietary tools available for the analysis of the stored information are limited and usually do not allow efficient analysis of the radiology department performance.In this work we demonstrate that with seamless access to DICOM metadata we can provide a consolidated view of departmental production data regardless of the heterogeneous imaging sources and subsidiary information systems. With our non-proprietary approach it is therefore feasible to conceive indicators that may be included in wider scope institutional performance evaluation.The results from the consolidated DICOM information analysis of more than 20 million images, belonging to more than 467 thousand studies performed on more than 162 thousand patients, justify the relevance of the implementation of similar methodologies in order to optimize the management of Radiology departments

In clinical environments the information resulting from the provision of healthcare is increasingly used to improve the delivery of healthcare. In the radiology context, the data analysis used to characterize the population that accesses different radiology departments is often supported by software applications from different manufacturers, which makes data integration very difficult. And it makes very difficult to characterize, in a centralized manner, the studies performed on each patient. In this context, is there a way to perform population characterization and patient centered studies by analyzing the DICOM metadata stored on Picture Archiving and Communication Systems (PACS) from different healthcare facilities?This paper presents the results of population characterization with chest radiographic studies performed on Computed Radiography (CR) and Digital Radiography (DX) modalities in three healthcare facilities. It also identifies the studies conducted on the patient that, in each healthcare facility, in addition to chest radiographic studies, had a higher number of radiological studies involving ionizing radiation. The final sample consists of 95.433 images, corresponding to 89.980 studies belonging to 56.547 patients. The methodology used made it possible to characterize the population by age group, gender and modality, the average number of studies per patient in each age group, as well as the patient with the highest number of chest radiographic studies per modality in each of the healthcare facilities. The results clearly demonstrate the relevance of the use of DICOM metadata stored in disperse PACS archives for population characterization, as well as to identify resources utilization trends and situations that may represent patient radiation over-exposure

Technological developments in the medical imaging acquisition and storage process have triggered the use of PACS (Picture Archiving and Communication Systems) with gradually larger archives. Nowadays, there is data stored in the DICOM (Digital Imaging and Communication in Medicine) file that is not searchable using the traditional PACS database. However, it may represent an important source of information for continuous professional practice improvement. The use of DICOM Data Mining tools has been a valuable asset to analyze the information stored in the DICOM file and can result in gathering important data for the professional practice improvement. These tools can also contribute to the PACS information audit and facilitate access to relevant clinical data within programs for quality continuous improvement. By allowing the construction of multiple views over data repository in a flexible and quickly way and with the possibility to export data for further statistical analysis, Dicoogle permits the identification of data and process inconsistencies that can contribute to radiology department improvement, such as in dose surveillance and patient safety programs and image quality control initiatives. However, the assessment of relevant data for practice improvement must take into account several factors related to the informational environment, professional reality, and healthcare goals and mission. This chapter describes a method to examine and perform studies over a medical imaging repository. Moreover, a case study of a small hospital where the obtained results are discussed is shown.