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BMC Medical Informatics and Decision Making

Hans Demski, Sebastian Garde, Claudia Hildebrand
BACKGROUND: Smart Health is known as a concept that enhances networking, intelligent data processing and combining patient data with other parameters. Open data models can play an important role in creating a framework for providing interoperable data services that support the development of innovative Smart Health applications profiting from data fusion and sharing. METHODS: This article describes a model-driven engineering approach based on standardized clinical information models and explores its application for the development of interoperable electronic health record systems...
October 22, 2016: BMC Medical Informatics and Decision Making
Ahmed Almashrafi, Laura Vanderbloemen
BACKGROUND: Postoperative adverse events are known to increase length of stay and cost. However, research on how adverse events affect patient flow and operational performance has been relatively limited to date. Moreover, there is paucity of studies on the use of simulation in understanding the effect of complications on care processes and resources. In hospitals with scarcity of resources, postoperative complications can exert a substantial influence on hospital throughputs. METHODS: This paper describes an evaluation method for assessing the effect of complications on patient flow within a cardiac surgical department...
October 21, 2016: BMC Medical Informatics and Decision Making
Maria Chiu, Michael Lebenbaum, Kelvin Lam, Nelson Chong, Mahmoud Azimaee, Karey Iron, Doug Manuel, Astrid Guttmann
BACKGROUND: Ontario, the most populous province in Canada, has a universal healthcare system that routinely collects health administrative data on its 13 million legal residents that is used for health research. Record linkage has become a vital tool for this research by enriching this data with the Immigration, Refugees and Citizenship Canada Permanent Resident (IRCC-PR) database and the Office of the Registrar General's Vital Statistics-Death (ORG-VSD) registry. Our objectives were to estimate linkage rates and compare characteristics of individuals in the linked versus unlinked files...
October 21, 2016: BMC Medical Informatics and Decision Making
Linda Moniz, Anna L Buczak, Ben Baugher, Erhan Guven, Jean-Paul Chretien
BACKGROUND: Prediction of influenza weeks in advance can be a useful tool in the management of cases and in the early recognition of pandemic influenza seasons. METHODS: This study explores the prediction of influenza-like-illness incidence using both epidemiological and climate data. It uses Lorenz's well-known Method of Analogues, but with two novel improvements. Firstly, it determines internal parameters using the implicit near-neighbor distances in the data, and secondly, it employs climate data (mean dew point) to screen analogue near-neighbors and capture the hidden dynamics of disease spread...
October 19, 2016: BMC Medical Informatics and Decision Making
Daniel Hausmann, Cristina Zulian, Edouard Battegay, Lukas Zimmerli
BACKGROUND: Decision-making processes in a medical setting are complex, dynamic and under time pressure, often with serious consequences for a patient's condition. OBJECTIVE: The principal aim of the present study was to trace and map the individual diagnostic process of real medical cases using a Decision Process Matrix [DPM]). METHODS: The naturalistic decision-making process of 11 residents and a total of 55 medical cases were recorded in an emergency department, and a DPM was drawn up according to a semi-structured technique following four steps: 1) observing and recording relevant information throughout the entire diagnostic process, 2) assessing options in terms of suspected diagnoses, 3) drawing up an initial version of the DPM, and 4) verifying the DPM, while adding the confidence ratings...
October 18, 2016: BMC Medical Informatics and Decision Making
Christoph Ahlgrim, Oliver Maenner, Manfred W Baumstark
BACKGROUND: Speech recognition software might increase productivity in clinical documentation. However, low user satisfaction with speech recognition software has been observed. In this case study, an approach for implementing a speech recognition software package at a university-based outpatient department is presented. METHODS: Methods to create a specific dictionary for the context "sports medicine" and a shared vocabulary learning function are demonstrated. The approach is evaluated for user satisfaction (using a questionnaire before and 10 weeks after software implementation) and its impact on the time until the final medical document was saved into the system...
October 18, 2016: BMC Medical Informatics and Decision Making
Wendy Shulver, Maggie Killington, Maria Crotty
BACKGROUND: Telehealth technologies, which enable delivery of healthcare services at distance, offer promise for responding to the challenges created by an ageing population. However, successful implementation of telehealth into mainstream healthcare systems has been slow and fraught with failure. Understanding of frontline providers' experiences and attitudes regarding telehealth is a crucial aspect of successful implementation. This study aims to examine healthcare worker views on telehealth, and their implications for implementation to mainstream healthcare services for older people...
October 12, 2016: BMC Medical Informatics and Decision Making
Tsair-Wei Chien, Weir-Sen Lin
BACKGROUND: Computer adaptive testing (CAT) of the activities of daily living (ADL) functions is required (i) to reveal the advantages of using an efficient and accurate estimation method, (ii) to determine the cutpoint for classifying ADL strata in patients with stroke, and (iii) to evaluate the feasibility of online CAT used in clinical settings for smartphones. METHODS: Normally standardized distributions of ADL measurements were simulated using item parameters from published papers...
October 10, 2016: BMC Medical Informatics and Decision Making
Maxence Guesdon, Eric Benzenine, Kamel Gadouche, Catherine Quantin
Administrative records in France, especially medical and social records, have huge potential for statistical studies. The NIR (a national identifier) is widely used in medico-social administrations, and this would theoretically provide considerable scope for data matching, on condition that the legislation on such matters was respected.The law, however, forbids the processing of non-anonymized medical data, thus making it difficult to carry out studies that require several sources of social and medical data...
October 6, 2016: BMC Medical Informatics and Decision Making
Hector R Perez, Michael W Nick, Katrina F Mateo, Allison Squires, Scott E Sherman, Adina Kalet, Melanie Jay
BACKGROUND: Obesity disproportionately affects Latina women, but few targeted, technology-assisted interventions that incorporate tailored health information exist for this population. The Veterans Health Administration (VHA) uses an online weight management tool (MOVE!23) which is publicly available, but was not designed for use in non-VHA populations. METHODS: We conducted a qualitative study to determine how interactions between the tool and other contextual elements impacted task performance when the target Latina users interacted with MOVE!23...
October 5, 2016: BMC Medical Informatics and Decision Making
Amelia Barwise, Lisbeth Garcia-Arguello, Yue Dong, Manasi Hulyalkar, Marija Vukoja, Marcus J Schultz, Neill K J Adhikari, Benjamin Bonneton, Oguz Kilickaya, Rahul Kashyap, Ognjen Gajic, Christopher N Schmickl
BACKGROUND: The Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN) is an international collaborative project with the overall objective of standardizing the approach to the evaluation and treatment of critically ill patients world-wide, in accordance with best-practice principles. One of CERTAIN's key features is clinical decision support providing point-of-care information about common acute illness syndromes, procedures, and medications in an index card format...
October 3, 2016: BMC Medical Informatics and Decision Making
Marie-Louise Mares, David H Gustafson, Joseph E Glass, Andrew Quanbeck, Helene McDowell, Fiona McTavish, Amy K Atwood, Lisa A Marsch, Chantelle Thomas, Dhavan Shah, Randall Brown, Andrew Isham, Mary Jane Nealon, Victoria Ward
BACKGROUND: Millions of Americans need but don't receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs' implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients' health tracking and relapses...
September 29, 2016: BMC Medical Informatics and Decision Making
Brigid A Knight, H David McIntyre, Ingrid J Hickman, Marina Noud
BACKGROUND: Modern flexible multiple daily injection (MDI) therapy requires people with diabetes to manage complex mathematical calculations to determine insulin doses on a day to day basis. Automated bolus calculators assist with these calculations, add additional functionality to protect against hypoglycaemia and enhance the record keeping process, however uptake and use depends on the devices meeting the needs of the user. We aimed to obtain user feedback on the usability of a mobile phone bolus calculator application in adults with T1DM to inform future development of mobile phone diabetes support applications...
September 15, 2016: BMC Medical Informatics and Decision Making
Anca Bucur, Jasper van Leeuwen, Nikolaos Christodoulou, Kamana Sigdel, Katerina Argyri, Lefteris Koumakis, Norbert Graf, Georgios Stamatakos
BACKGROUND: The adoption in oncology of Clinical Decision Support (CDS) may help clinical users to efficiently deal with the high complexity of the domain, lead to improved patient outcomes, and reduce the current knowledge gap between clinical research and practice. While significant effort has been invested in the implementation of CDS, the uptake in the clinic has been limited. The barriers to adoption have been extensively discussed in the literature. In oncology, current CDS solutions are not able to support the complex decisions required for stratification and personalized treatment of patients and to keep up with the high rate of change in therapeutic options and knowledge...
July 21, 2016: BMC Medical Informatics and Decision Making
Wolfgang Kuchinke, Christian Krauth, René Bergmann, Töresin Karakoyun, Astrid Woollard, Irene Schluender, Benjamin Braasch, Martin Eckert, Christian Ohmann
BACKGROUND: In an unprecedented rate data in the life sciences is generated and stored in many different databases. An ever increasing part of this data is human health data and therefore falls under data protected by legal regulations. As part of the BioMedBridges project, which created infrastructures that connect more than 10 ESFRI research infrastructures (RI), the legal and ethical prerequisites of data sharing were examined employing a novel and pragmatic approach. METHODS: We employed concepts from computer science to create legal requirement clusters that enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data...
July 7, 2016: BMC Medical Informatics and Decision Making
Timothy Bonnici, Stephen Gerry, David Wong, Julia Knight, Peter Watkinson
BACKGROUND: An Early Warning Score is a clinical risk score based upon vital signs intended to aid recognition of patients in need of urgent medical attention. The use of an escalation of care policy based upon an Early Warning Score is mandated as the standard of practice in British hospitals. Electronic systems for recording vital sign observations and Early Warning Score calculation offer theoretical benefits over paper-based systems. However, the evidence for their clinical benefit is limited...
February 9, 2016: BMC Medical Informatics and Decision Making
Rachel B Seymour, Daniel Leas, Meghan K Wally, Joseph R Hsu
No abstract text is available yet for this article.
2016: BMC Medical Informatics and Decision Making
Yuanyang Zhang, Tie Bo Wu, Bernie J Daigle, Mitchell Cohen, Linda Petzold
BACKGROUND: Trauma is the leading cause of death between the ages of 1 to 44 in the United States. Blood loss is the primary cause of these deaths. The discrimination of states through which patients transition would be helpful in understanding the disease process, and in identification of critical states and appropriate interventions. Even though these states are strongly associated with patients' blood composition data, there has not been a way to directly identify them. Statistical tools such as hidden Markov models can be used to infer the discrete latent states from the blood composition data...
2016: BMC Medical Informatics and Decision Making
Kevin J O'Leary, Rashmi K Sharma, Audrey Killarney, Lyndsey S O'Hara, Mary E Lohman, Eckford Culver, David M Liebovitz, Kenzie A Cameron
BACKGROUND: Hospital-based patient portals have the potential to better inform and engage patients in their care. We sought to assess patients' and healthcare providers' perceptions of a hospital-based portal and identify opportunities for design enhancements. METHODS: We developed a mobile patient portal application including information about the care team, scheduled tests and procedures, and a list of active medications. Patients were offered use of tablet computers, with the portal application, during their hospitalization...
2016: BMC Medical Informatics and Decision Making
Anne C Rahn, Imke Backhus, Franz Fuest, Karin Riemann-Lorenz, Sascha Köpke, Adrianus van de Roemer, Ingrid Mühlhauser, Christoph Heesen
BACKGROUND: Presentation of confidence intervals alongside information about treatment effects can support informed treatment choices in people with multiple sclerosis. We aimed to develop and pilot-test different written patient information materials explaining confidence intervals in people with relapsing-remitting multiple sclerosis. Further, a questionnaire on comprehension of confidence intervals was developed and piloted. METHODS: We developed different patient information versions aiming to explain confidence intervals...
2016: BMC Medical Informatics and Decision Making
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