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BMC Medical Informatics and Decision Making

Gilles Vandewiele, Femke De Backere, Kiani Lannoye, Maarten Vanden Berghe, Olivier Janssens, Sofie Van Hoecke, Vincent Keereman, Koen Paemeleire, Femke Ongenae, Filip De Turck
BACKGROUND: Headache disorders are an important health burden, having a large health-economic impact worldwide. Current treatment & follow-up processes are often archaic, creating opportunities for computer-aided and decision support systems to increase their efficiency. Existing systems are mostly completely data-driven, and the underlying models are a black-box, deteriorating interpretability and transparency, which are key factors in order to be deployed in a clinical setting. METHODS: In this paper, a decision support system is proposed, composed of three components: (i) a cross-platform mobile application to capture the required data from patients to formulate a diagnosis, (ii) an automated diagnosis support module that generates an interpretable decision tree, based on data semantically annotated with expert knowledge, in order to support physicians in formulating the correct diagnosis and (iii) a web application such that the physician can efficiently interpret captured data and learned insights by means of visualizations...
November 13, 2018: BMC Medical Informatics and Decision Making
Amy O'Donnell, Eileen Kaner, Caroline Shaw, Catherine Haighton
BACKGROUND: Recent decades have seen rapid growth in the implementation of Electronic Medical Records (EMRs) in healthcare settings in both developed regions as well as low and middle income countries. Yet despite substantial investment, the implementation of EMRs in some primary care systems has lagged behind other settings, with piecemeal adoption of EMR functionality by primary care physicians (PCPs) themselves. We aimed to review and synthesise international literature on the attitudes of PCPs to EMR adoption using the Clinical Adoption (CA) Framework...
November 13, 2018: BMC Medical Informatics and Decision Making
Licong Cui, Ningzhou Zeng, Matthew Kim, Remo Mueller, Emily R Hankosky, Susan Redline, Guo-Qiang Zhang
BACKGROUND: The National Sleep Research Resource (NSRR) is a large-scale, openly shared, data repository of de-identified, highly curated clinical sleep data from multiple NIH-funded epidemiological studies. Although many data repositories allow users to browse their content, few support fine-grained, cross-cohort query and exploration at study-subject level. We introduce a cross-cohort query and exploration system, called X-search, to enable researchers to query patient cohort counts across a growing number of completed, NIH-funded studies in NSRR and explore the feasibility or likelihood of reusing the data for research studies...
November 13, 2018: BMC Medical Informatics and Decision Making
Edward Meinert, Abrar Alturkistani, David Brindley, Peter Knight, Glenn Wells, Nick de Pennington
BACKGROUND: Technology can potentially enable the implementation of a value-based healthcare system, where the impact of quality of care is offered at optimised cost for maximised patient benefit. Technology can deliver value by aiding in data collection to evaluate outcomes and measure costs on a patient and population level. Healthcare organisations, however, face several challenges and risks that result almost exclusively from the use of these technologies. DISCUSSION: Some challenges associated with healthcare technology include their unsustainability, due to lack of scale-up plans and timely evaluations...
November 13, 2018: BMC Medical Informatics and Decision Making
Kiran Pohar Manhas, Shawn X Dodd, Stacey Page, Nicole Letourneau, Carol E Adair, Xinjie Cui, Suzanne C Tough
BACKGROUND: Mandates abound to share publicly-funded research data for reuse, while data platforms continue to emerge to facilitate such reuse. Birth cohorts (BC) involve longitudinal designs, significant sample sizes and rich and deep datasets. Data sharing benefits include more analyses, greater research complexity, increased opportunities for collaboration, amplification of public contributions, and reduced respondent burdens. Sharing BC data involves significant challenges including consent, privacy, access policies, communication, and vulnerability of the child...
November 12, 2018: BMC Medical Informatics and Decision Making
Lyra Halili, Rebecca Liu, Kelly Ann Hutchinson, Kevin Semeniuk, Leanne M Redman, Kristi B Adamo
BACKGROUND: Mobile technology is ubiquitous. Women of childbearing age have embraced health information technology for pregnancy-related counsel as prenatal care provider communication is increasingly scarce and brief. Pregnant women and new mothers place high value in the use of online sources to support their pregnancy information needs. In Canada, over 300,000 women are pregnant annually, with approximately 60% exceeding evidence-based weight gain recommendations. Mobile health (mHealth) tools, such as mobile applications (app), have the potential to reduce excessive gestational weight gain, offering pregnant women trustworthy guidance, ultimately improving the health outcomes of mothers and infants...
November 12, 2018: BMC Medical Informatics and Decision Making
Solomon Shiferaw, Andualem Workneh, Robel Yirgu, Geert-Jan Dinant, Mark Spigt
BACKGROUND: Increasing mobile phone ownership, functionality and access to mobile-broad band internet services has triggered growing interest to harness the potential of mobile phone technology to improve health services in low-income settings. The present project aimed at designing an mHealth system that assists midlevel health workers to provide better maternal health care services by automating the data collection and decision-making process. This paper describes the development process and technical aspects of the system considered critical for possible replication...
November 12, 2018: BMC Medical Informatics and Decision Making
Shusuke Hiragi, Hiroshi Tamura, Rei Goto, Tomohiro Kuroda
BACKGROUND: Cost effectiveness research is emerging in the chronic kidney disease (CKD) research field. Especially, an individual-level state transition model (microsimulation) is widely used for these researches. Some researchers set CKD grades as discrete health states, and the transition probabilities between these states were dependent on the CKD grades (disease grade-based microsimulation, MSM-dg), while others set estimated glomerular filtration rate value which determines the severity of CKD as a main variable describing patients' continuous status (kidney function-based microsimulation, MSM-kf)...
November 9, 2018: BMC Medical Informatics and Decision Making
C Keyworth, J Hart, C J Armitage, M P Tully
BACKGROUND: Technological support may be crucial in optimizing healthcare professional practice and improving patient outcomes. A focus on electronic health records has left other technological supports relatively neglected. Additionally, there has been no comparison between different types of technology-based interventions, and the importance of delivery setting on the implementation of technology-based interventions to change professional practice. Consequently, there is a need to synthesise and examine intervention characteristics using a methodology suited to identifying important features of effective interventions, and the barriers and facilitators to implementation...
November 7, 2018: BMC Medical Informatics and Decision Making
Elisabeth Holen-Rabbersvik, Elin Thygesen, Tom Roar Eikebrokk, Rune Werner Fensli, Åshild Slettebø
BACKGROUND: In recent years, inter-municipal cooperation in healthcare services has been an important measure implemented to meet future demographic changes in western countries. This entails an increased focus on communication and information sharing across organisational borders. Technology enables efficient and effective solutions to enhance such cooperation. However, the systems in the healthcare sector tend not to communicate with one another. There is a lack of literature focusing on communication and information sharing in inter-municipal healthcare services...
November 7, 2018: BMC Medical Informatics and Decision Making
Daniel Xia, Chen Zhang, Va Lip, Marian Harris, Yiping Shen
BACKGROUND: Trio studies, which involve the testing of samples from a proband and both parents, are often used by clinical laboratories to help with the classification of genetic variants, including copy number variants. In order for the results of the trio study to be valid, the mother and father must be the true biological parents of the proband. As such, non-paternity and sample mix-ups are potential sources of error. To address these potential issues, we developed a computer script to accurately assess maternity and paternity using single nucleotide polymorphism (SNP) data generated by Agilent chromosomal microarrays, a platform-of-choice for clinical copy number testing...
November 6, 2018: BMC Medical Informatics and Decision Making
Talita D C Frazão, Deyse G G Camilo, Eric L S Cabral, Ricardo P Souza
BACKGROUND: The health area is one of the most affected systems on the perspective of decision-making with multiobjectives, thus becoming prone to errors in the final solution, however, multicriteria decision analysis (MDCA) appears as an aid tool for this process decision-making. Therefore,the present study aims to analyze and synthesize articles found in the literature, involing MCDA in health care, evaluating general issues and methodological aspects, structuring them in a single work...
November 1, 2018: BMC Medical Informatics and Decision Making
Franziska Singer, Anja Irmisch, Nora C Toussaint, Linda Grob, Jochen Singer, Thomas Thurnherr, Niko Beerenwinkel, Mitchell P Levesque, Reinhard Dummer, Luca Quagliata, Sacha I Rothschild, Andreas Wicki, Christian Beisel, Daniel J Stekhoven
BACKGROUND: Molecular precision oncology is an emerging practice to improve cancer therapy by decreasing the risk of choosing treatments that lack efficacy or cause adverse events. However, the challenges of integrating molecular profiling into routine clinical care are manifold. From a computational perspective these include the importance of a short analysis turnaround time, the interpretation of complex drug-gene and gene-gene interactions, and the necessity of standardized high-quality workflows...
October 29, 2018: BMC Medical Informatics and Decision Making
Julie M Robillard, Jessica H Jun, Jen-Ai Lai, Tanya L Feng
BACKGROUND: Online health information is unregulated and can be of highly variable quality. There is currently no singular quantitative tool that has undergone a validation process, can be used for a broad range of health information, and strikes a balance between ease of use, concision and comprehensiveness. To address this gap, we developed the QUality Evaluation Scoring Tool (QUEST). Here we report on the analysis of the reliability and validity of the QUEST in assessing the quality of online health information...
October 19, 2018: BMC Medical Informatics and Decision Making
Thibault Ledieu, Guillaume Bouzillé, Frantz Thiessard, Karine Berquet, Pascal Van Hille, Eric Renault, Elisabeth Polard, Marc Cuggia
BACKGROUND: Pharmacovigilance consists in monitoring and preventing the occurrence of adverse drug reactions (ADR). This activity requires the collection and analysis of data from the patient record or any other sources to find clues of a causality link between the drug and the ADR. This can be time-consuming because often patient data are heterogeneous and scattered in several files. To facilitate this task, we developed a timeline prototype to gather and classify patient data according to their chronology...
October 19, 2018: BMC Medical Informatics and Decision Making
Pantelis Natsiavas, Janne Rasmussen, Maja Voss-Knude, Κostas Votis, Luigi Coppolino, Paolo Campegiani, Isaac Cano, David Marí, Giuliana Faiella, Fabrizio Clemente, Marco Nalin, Evangelos Grivas, Oana Stan, Erol Gelenbe, Jos Dumortier, Jan Petersen, Dimitrios Tzovaras, Luigi Romano, Ioannis Komnios, Vassilis Koutkias
BACKGROUND: Increased digitalization of healthcare comes along with the cost of cybercrime proliferation. This results to patients' and healthcare providers' skepticism to adopt Health Information Technologies (HIT). In Europe, this shortcoming hampers efficient cross-border health data exchange, which requires a holistic, secure and interoperable framework. This study aimed to provide the foundations for designing a secure and interoperable toolkit for cross-border health data exchange within the European Union (EU), conducted in the scope of the KONFIDO project...
October 16, 2018: BMC Medical Informatics and Decision Making
Xiang Zhong, Muxuan Liang, Reynerio Sanchez, Menggang Yu, Pamela R Budd, Julie L Sprague, Marvin A Dewar
BACKGROUND: The objective of this study was to investigate the impact of patient portal adoption on patients' primary care utilization and appointment adherence. METHODS: We conducted a retrospective observational study using a panel difference-in-differences (DID) framework to investigate the use of primary care services by patients, adjusting for their disease burden and allowing for time-dependent portal effect. A large dataset with 46,544 patients of University of Florida (UF) Health during the study period July 2013 - June 2016 was used...
October 16, 2018: BMC Medical Informatics and Decision Making
Melissa T Baysari, David Lowenstein, Wu Yi Zheng, Richard O Day
BACKGROUND: Recently, attention has shifted to improving the design of computerized alerts via the incorporation of human factors design principles. The Instrument for Evaluating Human Factors Principles in Medication-Related Decision Support Alerts (I-MeDeSA) is a tool developed in the United States to guide improvements to alert design and facilitate selection of electronic systems with superior design. In this study, we aimed to determine the reliability, ease of use and usefulness of I-MeDeSA for assessing drug-drug interaction (DDI) alerts in an Australian context...
October 5, 2018: BMC Medical Informatics and Decision Making
Dari Alhuwail, Zainab AlMeraj, Fatima Boujarwah
BACKGROUND: Current advances in information and communication technology have made accessing and obtaining health-related information easier than ever before. Today, many hospital websites use a patient-centric approach to promote engagement and encourage learning for better health-related decision making. However, little is known about the current state of hospital websites in the State of Kuwait. This study aims to evaluate hospital websites in Kuwait and offer recommendations to improve patient engagement and access to health information...
September 24, 2018: BMC Medical Informatics and Decision Making
Xavier Rafael-Palou, Cecilia Turino, Alexander Steblin, Manuel Sánchez-de-la-Torre, Ferran Barbé, Eloisa Vargiu
BACKGROUND: Patients suffering obstructive sleep apnea are mainly treated with continuous positive airway pressure (CPAP). Although it is a highly effective treatment, compliance with this therapy is problematic to achieve with serious consequences for the patients' health. Unfortunately, there is a clear lack of clinical analytical tools to support the early prediction of compliant patients. METHODS: This work intends to take a further step in this direction by building compliance classifiers with CPAP therapy at three different moments of the patient follow-up, before the therapy starts (baseline) and at months 1 and 3 after the baseline...
September 18, 2018: BMC Medical Informatics and Decision Making
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