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University of Porto, Portugal

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3 Papers

STUDY OF CLINICAL WORKFLOW AND INFORMATION FLOW OF A BREAST CARE UNIT

Topics: Medical and Nursing Informatics; Evaluation and Use of Healthcare IT; Healthcare Management Systems

Authors: Vítor Silva ¹ , Maria João Cardoso ² , João Fonseca ³ and Ricardo Cruz-Correia ³

Affiliations: ¹ Hospital São João; Center for Research in Health Technologies and Information Systems (CINTESIS), Portugal , ² Breast Center, Hospital São João; INESC, Breast Research Group; Faculdade de Medicina da Universidade do Porto (FMUP), Portugal , ³ Center for Research in Health Technologies and Information Systems (CINTESIS); Faculdade de Medicina da Universidade do Porto (FMUP), Portugal

Digital Object Identifier: 10.5220/0002744502940301

Proceedings of HEALTHINF 2010/BIOSTEC, ISBN: 978-989-674-016-0

Quick Abstract

Introduction. The study of the clinical workflows and information flows in healthcare institutions is of vital importance to improve its effectiveness and efficiency. At Hospital São João, Oporto – Portugal, a Diagnostic Breast Unit (DBU) was recently created. The implementation of a new Electronic Patient Record (EPR) called Breast.Care triggered the need to better understand the DBU processes and suggest improvements. Aim. To describe clinical workflows and information flows in DBU, detect problems and propose solutions for better communication among different actors. Methods. The study started with a direct observation period with a total of 24 hours. The observed processes and flows were transcribed into free text and then into structured text, tables and Unified Modeling Language (UML) diagrams (activity and partition-activity). The structured text and diagrams were analysed to find possible improvements. Results. Seven main processes were identified representing how different actors (humans and computers) work together. Three communication process improvements between humans were detected (e.g. changing timing of patient data insertion to facilitate reading access to others), three human–machine improvements (e.g. changing computer medical forms) and one between machines (creating specific links between information systems). Discussion. Analysing workflow and information flow in DBU allowed the detection of communication problems and the improvement of those through changes in EPR and in DBU current processes.

Related Ontology Subjects/Areas/Topics (8)

Biomedical Engineering	Evaluation and Use of Healthcare IT	Healthcare Management Systems
Cardiovascular Technologies	Health Engineering and Technology Applications	Medical and Nursing Informatics
Computing and Telecommunications in Cardiology	Health Information Systems

AUTOMATIC BREAST CONTOUR DETECTION IN DIGITAL PHOTOGRAPHS

Topics: Decision Support Systems; Expert Systems in Healthcare

Authors: Jaime S. Cardoso ¹ , Luis F. Teixeira ¹ and Maria J. Cardoso ²

Affiliations: ¹ INESC Porto, Faculdade de Engenharia, Universidade do Porto, Portugal , ² Faculdade de Medicina, Universidade do Porto, Portugal

Digital Object Identifier: 10.5220/0001039500910098

Proceedings of HEALTHINF 2008/BIOSTEC, ISBN: 978-989-8111-16-6

Quick Abstract

Breast cancer conservative treatment (BCCT), due to its proven oncological safety, is considered, when feasible, the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardized way, due to the lack of reproducibility of the subjective methods usually applied. The objective assessment methods, considered in the past as being less capable of evaluating all aspects of BCCT, are nowadays being preferred to overcome the drawbacks of the subjective evaluation. A recent computer-aided medical system was developed to objectively and automatically evaluate the aesthetic result of BCCT. In this system, the detection of the breast contour on the digital photograph of the patient is a necessary step to extract the features subsequently used in the evaluation process. In this paper an algorithm based on the shortest path on a graph is proposed to detect automatically the breast contour. The proposed method extends an existing semi-automatic algorithm for the same purpose. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method.

Related Ontology Subjects/Areas/Topics (8)

Artificial Intelligence	Expert Systems	Knowledge-Based Systems
Biomedical Engineering	Health Information Systems	Symbolic Systems
Decision Support Systems	Knowledge Engineering and Ontology Development

CONNECTING HOSPITALS AND HEALTH CENTRES COULD BENEFIT MOST OF PORTO’S CHILDREN POPULATION - Current Trends in Paedriatic Patients’ Mobility between Institutions Requires Implementation of Electronic Patient Records

Topics: Ehealth; Hospital Management Systems

Authors: Ana Edral ¹ , Ana Sofia Matos ¹ , Beatriz Soares ¹ , Carlos Leite ¹ , Joana Almeida ¹ , João Girão ¹ , João Nunes ¹ , Maria Isabel Pereira ¹ , Miguel Lobato ¹ , Mónica Silva ¹ , Rita Boaventura ¹ , Sofia Faria ¹ and Ricardo Cruz-Correia ²

Affiliations: ¹ Faculdade de Medicina, Universidade do Porto, Portugal , ² Faculdade de Medicina, Universidade do Porto; Center for Research in Health Information Systems and Technologies, Portugal

Digital Object Identifier: 10.5220/0001043903050309

Proceedings of HEALTHINF 2008/BIOSTEC, ISBN: 978-989-8111-16-6

Quick Abstract

Nowadays, data is spread across many institutions. Aim: This study aims to establish the need for the implementation of a regional Electronic Patient Record (EPR) in Porto area, to support the mobility, and the characteristics of the population that attends Porto’s Paediatric Unit (UPP) Methods: The study is crossectional with a consecutive sampling method. A questionnaire was applied during three days. The study population consisted of children attending to Paediatrics Emergency of Porto (UPP). Individuals accompanying those children were approached, in the waiting room in order to answer the designed questionnaire about the patient. Individuals who refused to answer, entered directly to the emergency room or did not complete the interview were excluded. Results: 151 patients entered the emergency room during the shifts, 126 were approached, 25 were immediately non available, 6 refused answering and 8 were incomplete – the response rate was 74%. The age mean was 4 years old, with 46% being under 2. Within children who visited UPP, 37% have been referred: 63% from health centres, 26% from other hospitals and the remaining from private care institutions; 25% of the patients went only to health centres for outpatient care; 56% attended UPP from 2 to 5 times in the last 14 months. Conclusions: Implementing an EPR accessible in health centres and the UPP is relevant for the population studied, especially those under 2 years of age.

Related Ontology Subjects/Areas/Topics (6)

Biomedical Engineering		e-Health		Hospital Management Systems
Cloud Computing		Health Information Systems		Platforms and Applications

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