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    1396 results match your criteria BMC Medical Informatics and Decision Making [Journal]

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    Effective behavioral intervention strategies using mobile health applications for chronic disease management: a systematic review.
    BMC Med Inform Decis Mak 2018 Feb 20;18(1):12. Epub 2018 Feb 20.
    Program in Public Health, University of California Irvine, Irvine, CA, USA.
    Background: Mobile health (mHealth) has continuously been used as a method in behavioral research to improve self-management in patients with chronic diseases. However, the evidence of its effectiveness in chronic disease management in the adult population is still lacking. We conducted a systematic review to examine the effectiveness of mHealth interventions on process measures as well as health outcomes in randomized controlled trials (RCTs) to improve chronic disease management. Read More

    Presentation of laboratory test results in patient portals: influence of interface design on risk interpretation and visual search behaviour.
    BMC Med Inform Decis Mak 2018 02 12;18(1):11. Epub 2018 Feb 12.
    NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, The University of Manchester, Manchester, UK.
    Background: Patient portals are considered valuable instruments for self-management of long term conditions, however, there are concerns over how patients might interpret and act on the clinical information they access. We hypothesized that visual cues improve patients' abilities to correctly interpret laboratory test results presented through patient portals. We also assessed, by applying eye-tracking methods, the relationship between risk interpretation and visual search behaviour. Read More

    Leveraging healthcare utilization to explore outcomes from musculoskeletal disorders: methodology for defining relevant variables from a health services data repository.
    BMC Med Inform Decis Mak 2018 01 31;18(1):10. Epub 2018 Jan 31.
    Headquarters, U.S. Army Medical Command, Analysis & Evaluation Division, 3630 Stanley Road; Joint Base San Antonio - Fort Sam Houston, San Antonio, TX, 78234, USA.
    Background: Large healthcare databases, with their ability to collect many variables from daily medical practice, greatly enable health services research. These longitudinal databases provide large cohorts and longitudinal time frames, allowing for highly pragmatic assessment of healthcare delivery. The purpose of this paper is to discuss the methodology related to the use of the United States Military Health System Data Repository (MDR) for longitudinal assessment of musculoskeletal clinical outcomes, as well as address challenges of using this data for outcomes research. Read More

    Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records.
    BMC Med Inform Decis Mak 2018 01 24;18(1). Epub 2018 Jan 24.
    INSERM, U1099, F-35000, Rennes, France.
    Background: Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to detect comorbidities in electronic health records (EHR) by using a clinical data warehouse (CDW) and a knowledge database. Read More

    Developing a tablet computer-based application ('App') to measure self-reported alcohol consumption in Indigenous Australians.
    BMC Med Inform Decis Mak 2018 01 15;18(1). Epub 2018 Jan 15.
    University of Sydney, Discipline of Addiction Medicine, Indigenous Health and Substance Use, NHMRC Centre of Research Excellence in Indigenous Health and Alcohol, King George V Building, 83-117 Missenden Road, Camperdown, NSW, 2050, Australia.
    Background: The challenges of assessing alcohol consumption can be greater in Indigenous communities where there may be culturally distinct approaches to communication, sharing of drinking containers and episodic patterns of drinking. This paper discusses the processes used to develop a tablet computer-based application ('App') to collect a detailed assessment of drinking patterns in Indigenous Australians. The key features of the resulting App are described. Read More

    Functionality of hospital information systems: results from a survey of quality directors at Turkish hospitals.
    BMC Med Inform Decis Mak 2018 01 12;18(1). Epub 2018 Jan 12.
    Center for Applied Pediatric Quality Analytics, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
    Background: We aimed to determine availability of core Hospital Information Systems (HIS) functions implemented in Turkish hospitals and the perceived importance of these functions on quality and patient safety.

    Methods: We surveyed quality directors (QDs) at civilian hospitals in the nation of Turkey. Data were collected via web survey using an instrument with 50 items describing core functionality of HIS. Read More

    Design and evaluation of a mobile application to assist the self-monitoring of the chronic kidney disease in developing countries.
    BMC Med Inform Decis Mak 2018 01 12;18(1). Epub 2018 Jan 12.
    Federal Institute of Alagoas, R. Prof. Domingos Correia, 1207, Ouro Preto, Alagoas, 57300-010, Brazil.
    Background: The chronic kidney disease (CKD) is a worldwide critical problem, especially in developing countries. CKD patients usually begin their treatment in advanced stages, which requires dialysis and kidney transplantation, and consequently, affects mortality rates. This issue is faced by a mobile health (mHealth) application (app) that aims to assist the early diagnosis and self-monitoring of the disease progression. Read More

    Healthcare information systems: the cognitive challenge.
    BMC Med Inform Decis Mak 2018 01 11;18(1). Epub 2018 Jan 11.
    Department of Anaesthesia, The Northern Hospital, 185 Cooper St, Epping, VIC, 3076, Australia.
    Background: Healthcare work is, to a considerable extent, cognitive. Subsequently, the analysis and the design of supporting technology must be sensitive to the cognitive and adaptive demands of the work and to the cognitive strategies employed by healthcare practitioners. Despite the vital role that cognition plays in healthcare work, current technocentric design approaches for healthcare technology do not account for it, failing to observe it during analysis and failing to develop support for it during design. Read More

    The readiness of hospital pharmacists in Kuwait to practise evidence-based medicine: a cross-sectional study.
    BMC Med Inform Decis Mak 2018 01 11;18(1). Epub 2018 Jan 11.
    Faculty of Medicine, Kuwait University, PO Box 24923, Safat 13110, Al-Jabriya, Kuwait.
    Background: The evolving role of pharmacists in providing pharmaceutical care, as part of the healthcare team, challenges them to acquire up-to-date knowledge of medicines to make the best clinical decisions. The volume of medical literature is on the increase, and it is important to utilise these resources to optimise patients' therapeutic outcomes. This study aimed at assessing the readiness of government hospital pharmacists in practising evidence-based medicine (EBM) in Kuwait in regards to their attitude, knowledge and skills, as well as the perceived barriers and facilitators. Read More

    A pre-post study testing a lung cancer screening decision aid in primary care.
    BMC Med Inform Decis Mak 2018 01 12;18(1). Epub 2018 Jan 12.
    Department of Medicine, Dell Medical School, The University of Texas at Austin, 1912 Speedway, Campus Mail Code D2000, Austin, TX, 78712, USA.
    Background: The United States Preventive Services Task Force (USPSTF) issued recommendations for older, heavy lifetime smokers to complete annual low-dose computed tomography (LDCT) scans of the chest as screening for lung cancer. The USPSTF recommends and the Centers for Medicare and Medicaid Services require shared decision making using a decision aid for lung cancer screening with annual LDCT. Little is known about how decision aids affect screening knowledge, preferences, and behavior. Read More

    Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community.
    BMC Med Inform Decis Mak 2018 01 5;18(1). Epub 2018 Jan 5.
    College of Information System and Management, National University of Defense Technology, Changsha, 410073, China.
    Background: Traditional survey methods are limited in the study of hidden populations due to the hard to access properties, including lack of a sampling frame, sensitivity issue, reporting error, small sample size, etc. The rapid increase of online communities, of which members interact with others via the Internet, have generated large amounts of data, offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. In this study, we try to understand the multidimensional characteristics of a hidden population by analyzing the massive data generated in the online community. Read More

    Predicting 7-day, 30-day and 60-day all-cause unplanned readmission: a case study of a Sydney hospital.
    BMC Med Inform Decis Mak 2018 01 4;18(1). Epub 2018 Jan 4.
    Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Rd, Sydney, NSW, 2109, Australia.
    Background: The identification of patients at high risk of unplanned readmission is an important component of discharge planning strategies aimed at preventing unwanted returns to hospital. The aim of this study was to investigate the factors associated with unplanned readmission in a Sydney hospital. We developed and compared validated readmission risk scores using routinely collected hospital data to predict 7-day, 30-day and 60-day all-cause unplanned readmission. Read More

    Substance deposition assessment in obstructed pulmonary system through numerical characterization of airflow and inhaled particles attributes.
    BMC Med Inform Decis Mak 2017 12 20;17(Suppl 3):173. Epub 2017 Dec 20.
    Information Technologies Institute, Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece.
    Background: Chronic obstructive pulmonary disease (COPD) and asthma are considered as the two most widespread obstructive lung diseases, whereas they affect more than 500 million people worldwide. Unfortunately, the requirement for detailed geometric models of the lungs in combination with the increased computational resources needed for the simulation of the breathing did not allow great progress to be made in the past for the better understanding of inflammatory diseases of the airways through detailed modelling approaches. In this context, computational fluid dynamics (CFD) simulations accompanied by fluid particle tracing (FPT) analysis of the inhaled ambient particles are deemed critical for lung function assessment. Read More

    Surface structure feature matching algorithm for cardiac motion estimation.
    BMC Med Inform Decis Mak 2017 12 20;17(Suppl 3):172. Epub 2017 Dec 20.
    College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
    Background: Cardiac diseases represent the leading cause of sudden death worldwide. During the development of cardiac diseases, the left ventricle (LV) changes obviously in structure and function. LV motion estimation plays an important role for diagnosis and treatment of cardiac diseases. Read More

    Subject-independent emotion recognition based on physiological signals: a three-stage decision method.
    BMC Med Inform Decis Mak 2017 12 20;17(Suppl 3):167. Epub 2017 Dec 20.
    The Third People's Hospital of Tianshui, Tianshui, 741020, China.
    Background: Collaboration between humans and computers has become pervasive and ubiquitous, however current computer systems are limited in that they fail to address the emotional component. An accurate understanding of human emotions is necessary for these computers to trigger proper feedback. Among multiple emotional channels, physiological signals are synchronous with emotional responses; therefore, analyzing physiological changes is a recognized way to estimate human emotions. Read More

    A multiple distributed representation method based on neural network for biomedical event extraction.
    BMC Med Inform Decis Mak 2017 12 20;17(Suppl 3):171. Epub 2017 Dec 20.
    School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
    Background: Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. Read More

    Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.
    BMC Med Inform Decis Mak 2017 12 20;17(Suppl 3):166. Epub 2017 Dec 20.
    Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China.
    Background: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analysis method, doctors can only rely on the subjective experience of the data to distinguish normal people and patients, which easily lead to misdiagnosis. In recent years, functional Near-Infrared Spectroscopy (fNIRS) has been widely used in clinical diagnosis, it can get the hemoglobin concentration through the variation of optical intensity. Read More

    Disparities in the use of mobile phone for seeking childbirth services among women in the urban areas: Bangladesh Urban Health Survey.
    BMC Med Inform Decis Mak 2017 12 29;17(1):182. Epub 2017 Dec 29.
    Faculty of Social Sciences, School of International Development and Global Studies, University of Ottawa, Ottawa, Canada.
    Background: In Bangladesh, similar to its other South Asian counterparts, shortage of health workers along with inadequate infrastructure constitute some of the major obstacles for the equitable provision of reproductive healthcare services, particularly among the marginalized and underserved neighbourhoods. However, given the rapidly expanding broadband communication and mobile phone market in the country, the application of eHealth and mHealth technologies offer a window of opportunities to minimise the impact of socioeconomic barriers and promote the utilization of maternal healthcare services thereby. In the present study we aimed to investigate 1) the prevalence of usage of mobile phones for seeking childbirth services, 2) neighbourhood and socioeconomic disparities in the use, and 3) association between using mobile phones and the uptake of postnatal care among mothers and neonates. Read More

    Advancing beyond the system: telemedicine nurses' clinical reasoning using a computerised decision support system for patients with COPD - an ethnographic study.
    BMC Med Inform Decis Mak 2017 12 28;17(1):181. Epub 2017 Dec 28.
    Centre for Care Research, Southern Norway, Department of Health and Nursing Sciences, Faculty of Health and Sport Sciences, University of Agder, Post box 422, 4604, Kristiansand, Norway.
    Background: Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. Read More

    Exploring factors associated with the uneven utilization of telemedicine in Norway: a mixed methods study.
    BMC Med Inform Decis Mak 2017 12 28;17(1):180. Epub 2017 Dec 28.
    Norwegian Centre for E-health Research, University Hospital of North Norway, P.O. Box 35, 9038, Tromso, Norway.
    Background: Norway has a long history of using telemedicine, especially for geographical reasons. Despite the availability of promising telemedicine applications and the implementation of national initiatives and policies, the sustainability and scaling-up of telemedicine in the health system is still far from accomplished. The main objective of this study was to explore and identify the multi-level (micro, meso and macro) factors affecting telemedicine utilization in Norway. Read More

    Multiple constraints compromise decision-making about implantable medical devices for individual patients: qualitative interviews with physicians.
    BMC Med Inform Decis Mak 2017 12 22;17(1):178. Epub 2017 Dec 22.
    University Health Network, Toronto, Canada.
    Background: Little research has examined how physicians choose medical devices for treating individual patients to reveal if interventions are needed to support decision-making and reduce device-associated morbidity and mortality. This study explored factors that influence choice of implantable device from among available options.

    Methods: A descriptive qualitative approach was used. Read More

    Economic and organizational impact of a clinical decision support system on laboratory test ordering.
    BMC Med Inform Decis Mak 2017 12 22;17(1):179. Epub 2017 Dec 22.
    Department of Engineering, University of Ferrara, Via Saragat 1, Ferrara, Italy.
    Background: We studied the impact of a clinical decision support system (CDSS) implemented in a few wards of two Italian health care organizations on the ordering of redundant laboratory tests under different perspectives: (1) analysis of the volume of tests, (2) cost analysis, (3) end-user satisfaction before and after the installation of the CDSS.

    Methods: (1) and (2) were performed by comparing the ordering of laboratory tests between an intervention group of wards where a CDSS was in use and a second (control) group where a CDSS was not in use; data were compared during a 3-month period before (2014) and a 3-month period after (2015) CDSS installation. To measure end-user satisfaction (3), a questionnaire based on POESUS was administered to the medical staff. Read More

    Using medication utilization information to develop an asthma severity classification model.
    BMC Med Inform Decis Mak 2017 Dec 20;17(1):177. Epub 2017 Dec 20.
    Institute of Health Policy and Management, College of Public Health, National Taiwan University, No. 17, Xu-Zhou Rd, Taipei, Taiwan.
    Background: Claims data are currently widely used as source data in asthma studies. However, the insufficient information in claims data related to level of asthma severity may negatively impact study findings. The present study develops and validates an asthma severity classification model that uses medication utilization in Taiwan National Health Insurance claims data. Read More

    Erratum to: An information and communication technology-based centralized clinical trial to determine the efficacy and safety of insulin dose adjustment education based on a smartphone personal health record application: a randomized controlled trial.
    BMC Med Inform Decis Mak 2017 12 12;17(1):169. Epub 2017 Dec 12.
    Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Republic of Korea.
    After publication of the original article [1] it was noted that both the figures and captions and relating to Figs. 1 and 2 had been interchanged. Read More

    Monitoring prescribing patterns using regression and electronic health records.
    BMC Med Inform Decis Mak 2017 Dec 19;17(1):175. Epub 2017 Dec 19.
    Department of Biomedical Informatics, Columbia University, 622 West 168th Street, PH-20, New York, NY, 10032, USA.
    Background: It is beneficial for health care institutions to monitor physician prescribing patterns to ensure that high-quality and cost-effective care is being provided to patients. However, detecting treatment patterns within an institution is challenging, given that medications and conditions are often not explicitly linked in the health record. Here we demonstrate the use of statistical methods together with data from the electronic health care record (EHR) to analyze prescribing patterns at an institution. Read More

    Advancing perinatal patient safety through application of safety science principles using health IT.
    BMC Med Inform Decis Mak 2017 Dec 19;17(1):176. Epub 2017 Dec 19.
    RTI International, 3040 E. Cornwallis Rd, Research Triangle Park, NC, 27709, USA.
    Background: The use of health information technology (IT) has been shown to promote patient safety in Labor and Delivery (L&D) units. The use of health IT to apply safety science principles (e.g. Read More

    Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.
    BMC Med Inform Decis Mak 2017 Dec 19;17(1):174. Epub 2017 Dec 19.
    King AbdulAziz Cardiac Center, Ministry of National Guard, Health Affairs, King Abdulaziz Medical City for National Guard - Health affairs, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Department Mail Code: 1413, P.O. Box 22490, Riyadh, 11426, Kingdom of Saudi Arabia.
    Background: Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined categories. The aim of this study is to present an evaluation and comparison of how machine learning techniques can be applied on medical records of cardiorespiratory fitness and how the various techniques differ in terms of capabilities of predicting medical outcomes (e. Read More

    A meta-model for computer executable dynamic clinical safety checklists.
    BMC Med Inform Decis Mak 2017 Dec 12;17(1):170. Epub 2017 Dec 12.
    School of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China.
    Background: Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. Read More

    Supervised learning for infection risk inference using pathology data.
    BMC Med Inform Decis Mak 2017 Dec 8;17(1):168. Epub 2017 Dec 8.
    Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, B422 Bessemer Building, South Kensington Campus, London, SW7 2AZ, UK.
    Background: Antimicrobial Resistance is threatening our ability to treat common infectious diseases and overuse of antimicrobials to treat human infections in hospitals is accelerating this process. Clinical Decision Support Systems (CDSSs) have been proven to enhance quality of care by promoting change in prescription practices through antimicrobial selection advice. However, bypassing an initial assessment to determine the existence of an underlying disease that justifies the need of antimicrobial therapy might lead to indiscriminate and often unnecessary prescriptions. Read More

    Adverse events recording in electronic health record systems in primary care.
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):163. Epub 2017 Dec 6.
    NIVEL, Netherlands Institute for Health Services Research, P.O. Box 1568, 3500 BN, Utrecht, The Netherlands.
    Background: Adequate record keeping of medication adverse events in electronic health records systems is important for patient safety. Events that remain unrecorded cannot be communicated from one health professional to another. In the absence of a gold standard, we investigate the variation between Dutch general practices in the extent to which they record medication adverse events. Read More

    Development of a video-simulation instrument for assessing cognition in older adults.
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):161. Epub 2017 Dec 6.
    Department of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, USA.
    Background: Commonly used methods to assess cognition, such as direct observation, self-report, or neuropsychological testing, have significant limitations. Therefore, a novel tablet computer-based video simulation was created with the goal of being valid, reliable, and easy to administer. The design and implementation of the SIMBAC (Simulation-Based Assessment of Cognition) instrument is described in detail, as well as informatics "lessons learned" during development. Read More

    Recognizing difficult trade-offs: values and treatment preferences for end-of-life care in a multi-site survey of adult patients in family practices.
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):164. Epub 2017 Dec 6.
    Department of Critical Care Medicine, Queen's University, Kingston, Ontario, Canada.
    Background: Decisions about care options and the use of life-sustaining treatments should be informed by a person's values and treatment preferences. The objective of this study was to examine the consistency of ratings of the importance of the values statements and the association between values statement ratings and the patient's expressed treatment preference.

    Methods: We conducted a multi-site survey in 20 family practices. Read More

    The effect of nursing participation in the design of a critical care information system: a case study in a Chinese hospital.
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):165. Epub 2017 Dec 6.
    Centre for IT-enabled Transformation, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, 2522, Australia.
    Background: Intensive care information systems (ICIS) are continuously evolving to meet the ever changing information needs of intensive care units (ICUs), providing the backbone for a safe, intelligent and efficient patient care environment. Although beneficial for the international advancement in building smart environments to transform ICU services, knowledge about the contemporary development of ICIS worldwide, their usage and impacts is limited. This study aimed to fill this knowledge gap by researching the development and implementation of an ICIS in a Chinese hospital, nurses' use of the system, and the impact of system use on critical care nursing processes and outcomes. Read More

    Implementation of shared decision-making in oncology: development and pilot study of a nurse-led decision-coaching programme for women with ductal carcinoma in situ.
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):160. Epub 2017 Dec 6.
    MIN-Faculty, Unit of Health Sciences and Education, University of Hamburg, Martin-Luther-King-Platz 6, D-20146, Hamburg, Germany.
    Background: To implement informed shared decision-making (ISDM) in breast care centres, we developed and piloted an inter-professional complex intervention.

    Methods: We developed an intervention consisting of three components: an evidence-based patient decision aid (DA) for women with ductal carcinoma in situ, a decision-coaching led by specialised nurses (breast care nurses and oncology nurses) and structured physician encounters. In order to enable professionals to gain ISDM competencies, we developed and tested a curriculum-based training programme for specialised nurses and a workshop for physicians. Read More

    Autism risk classification using placental chorionic surface vascular network features.
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):162. Epub 2017 Dec 6.
    NIH National Children's Study Placenta Consortium, Bethesda, MD, USA.
    Background: Autism Spectrum Disorder (ASD) is one of the fastest-growing developmental disorders in the United States. It was hypothesized that variations in the placental chorionic surface vascular network (PCSVN) structure may reflect both the overall effects of genetic and environmentally regulated variations in branching morphogenesis within the conceptus and the fetus' vital organs. This paper provides sound evidences to support the study of ASD risks with PCSVN through a combination of feature-selection and classification algorithms. Read More

    An ontology-aware integration of clinical models, terminologies and guidelines: an exploratory study of the Scale for the Assessment and Rating of Ataxia (SARA).
    BMC Med Inform Decis Mak 2017 Dec 6;17(1):159. Epub 2017 Dec 6.
    Instituto de Investigación Sanitaria (IDIS), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Santiago de Compostela, Spain.
    Background: Electronic rating scales represent an important resource for standardized data collection. However, the ability to exploit reasoning on rating scale data is still limited. The objective of this work is to facilitate the integration of the semantics required to automatically interpret collections of standardized clinical data. Read More

    The development of a nursing subset of patient problems to support interoperability.
    BMC Med Inform Decis Mak 2017 Dec 4;17(1):158. Epub 2017 Dec 4.
    National Health Care Institute, PO Box 320, 1110, Diemen, AH, Netherlands.
    Background: Since the emergence of electronic health records, nursing information is increasingly being recorded and stored digitally. Several studies have shown that a wide range of nursing information is not interoperable and cannot be re-used in different health contexts. Difficulties arise when nurses share information with others involved in the delivery of nursing care. Read More

    Validation of an algorithm that determines stroke diagnostic code accuracy in a Japanese hospital-based cancer registry using electronic medical records.
    BMC Med Inform Decis Mak 2017 Dec 4;17(1):157. Epub 2017 Dec 4.
    Department of Neurology, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka, 565-0871, Japan.
    Background: This study aimed to validate an algorithm that determines stroke diagnostic code accuracy, in a hospital-based cancer registry, using electronic medical records (EMRs) in Japan.

    Methods: The subjects were 27,932 patients enrolled in the hospital-based cancer registry of Osaka University Hospital, between January 1, 2007 and December 31, 2015. The ICD-10 (international classification of diseases, 10th revision) diagnostic codes for stroke were extracted from the EMR database. Read More

    Exploring the feasibility of eHealth solutions to decrease delays in maternal healthcare in remote communities of Ghana.
    BMC Med Inform Decis Mak 2017 Dec 2;17(1):156. Epub 2017 Dec 2.
    Department of Signals and System, Chalmers University of Technology, -412 96, Göteborg, SE, Sweden.
    Background: Despite the introduction of the Millennium Development Goal to reduce maternal deaths from 400 to 100 per 100,000 live births, the proportion of maternal deaths is still much higher in most developing countries like Ghana. Various interventions have been implemented in Ghana that focus on increasing skilled maternal care. These are especially needed in rural areas. Read More

    Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.
    BMC Med Inform Decis Mak 2017 Dec 1;17(1):155. Epub 2017 Dec 1.
    Laboratory of Computer Science, Massachusetts General Hospital, 50 Staniford Street, Suite 750, Boston, MA, 02114, USA.
    Background: The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constructed a machine learning-based natural language processing (NLP) pipeline and developed medical subdomain classifiers based on the content of the note.

    Methods: We constructed the pipeline using the clinical NLP system, clinical Text Analysis and Knowledge Extraction System (cTAKES), the Unified Medical Language System (UMLS) Metathesaurus, Semantic Network, and learning algorithms to extract features from two datasets - clinical notes from Integrating Data for Analysis, Anonymization, and Sharing (iDASH) data repository (n = 431) and Massachusetts General Hospital (MGH) (n = 91,237), and built medical subdomain classifiers with different combinations of data representation methods and supervised learning algorithms. Read More

    A mobile and web-based clinical decision support and monitoring system for diabetes mellitus patients in primary care: a study protocol for a randomized controlled trial.
    BMC Med Inform Decis Mak 2017 Nov 29;17(1):154. Epub 2017 Nov 29.
    Department of Family Medicine, Dokuz Eylül University, İzmir, Turkey.
    Background: Physicians' guideline use rates for diagnosis, treatment and monitoring of diabetes mellitus (DM) is very low. Time constraints, patient overpopulation, and complex guidelines require alternative solutions for real time patient monitoring. Rapidly evolving e-health technology combined with clinical decision support and monitoring systems (CDSMS) provides an effective solution to these problems. Read More

    Patient perspectives on engagement in decision-making in early management of non-ST elevation acute coronary syndrome: a qualitative study.
    BMC Med Inform Decis Mak 2017 Nov 28;17(1):153. Epub 2017 Nov 28.
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
    Background: Surveys of patients suggest many want to be actively involved in treatment decisions for acute coronary syndromes. However, patient experiences of their engagement and participation in early phase decision-making have not been well described.

    Methods: We performed a patient led qualitative study to explore patient experiences with decision-making processes when admitted to hospital with non-ST elevation acute coronary syndrome. Read More

    Association between borderline dysnatremia and mortality insight into a new data mining approach.
    BMC Med Inform Decis Mak 2017 Nov 22;17(1):152. Epub 2017 Nov 22.
    Division of Geriatrics, Hôpital Européen G. Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France.
    Background: Even small variations of serum sodium concentration may be associated with mortality. Our objective was to confirm the impact of borderline dysnatremia for patients admitted to hospital on in-hospital mortality using real life care data from our electronic health record (EHR) and a phenome-wide association analysis (PheWAS).

    Methods: Retrospective observational study based on patient data admitted to Hôpital Européen George Pompidou, between 01/01/2008 and 31/06/2014; including 45,834 patients with serum sodium determinations on admission. Read More

    Experimental application of Business Process Management technology to manage clinical pathways: a pediatric kidney transplantation follow up case.
    BMC Med Inform Decis Mak 2017 Nov 3;17(1):151. Epub 2017 Nov 3.
    IT Department, Bambino Gesù Children's Hospital, Rome, Italy.
    Background: To test the application of Business Process Management technology to manage clinical pathways, using a pediatric kidney transplantation as case study, and to identify the benefits obtained from using this technology.

    Methods: Using a Business Process Management platform, we implemented a specific application to manage the clinical pathway of pediatric patients, and monitored the activities of the coordinator in charge of the case management during a 6-month period (from June 2015 to November 2015) using two methodologies: the traditional procedure and the one under study.

    Results: The application helped physicians and nurses to optimize the amount of time and resources devoted to management purposes. Read More

    Evaluation of data quality of interRAI assessments in home and community care.
    BMC Med Inform Decis Mak 2017 Oct 30;17(1):150. Epub 2017 Oct 30.
    School of Public Health and Health Systems, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada.
    Background: The aim of this project is to describe the quality of assessment data regularly collected in home and community, with techniques adapted from an evaluation of the quality of long-term care data in Canada.

    Methods: Data collected using the Resident Assessment Instrument - Home Care (RAI-HC) in Ontario and British Columbia (BC) as well as the interRAI Community Health Assessment (CHA) in Ontario were analyzed using descriptive statistics, Pearson's r correlation, and Cronbach's alpha in order to assess trends in population characteristics, convergent validity, and scale reliability.

    Results: Results indicate that RAI-HC data from Ontario and BC behave in a consistent manner, with stable trends in internal consistency providing evidence of good reliability (alpha values range from 0. Read More

    Multiple criteria decision analysis in the context of health technology assessment: a simulation exercise on metastatic colorectal cancer with multiple stakeholders in the English setting.
    BMC Med Inform Decis Mak 2017 Oct 26;17(1):149. Epub 2017 Oct 26.
    Department of Health Policy and Medical Technology Research Group, LSE Health, London School of Economics and Political Science, London, UK.
    Background: Multiple criteria decision analysis (MCDA) has appeared as a methodology to address limitations of economic evaluation in health technology assessment (HTA), however there are limited empirical evidence from real world applications. The aim of this study is to test in practice a recently developed MCDA methodological framework known as Advance Value Framework (AVF) through a proof-of-concept case study engaging multiple stakeholders.

    Methods: A multi-attribute value theory methodological process was adopted involving problem structuring, model building, model assessment and model appraisal phases. Read More

    EsPRit: ethics committee proposals for Long Term Medical Data Registries in rapidly evolving research fields - a future-proof best practice approach.
    BMC Med Inform Decis Mak 2017 Oct 18;17(1):148. Epub 2017 Oct 18.
    eHealth Research and Innovation Unit, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria.
    Background: Long-term data collection is a challenging task in the domain of medical research. Many effects in medicine require long periods of time to become traceable e.g. Read More

    Finnish physicians' stress related to information systems keeps increasing: a longitudinal three-wave survey study.
    BMC Med Inform Decis Mak 2017 Oct 17;17(1):147. Epub 2017 Oct 17.
    National Institute for Health and Welfare, P.O. Box 30, 00271, Helsinki, Finland.
    Background: Poorly functioning, time-consuming, and inadequate information systems are among the most important work-related psychosocial factors causing stress in physicians. The present study examined the trend in the perceived stress that was related to information systems (SRIS) among Finnish physicians during a nine-year follow-up. In addition, we examined the associations of gender, age, employment sector, specialization status, leadership position, on-call burden, and time pressure with SRIS change and levels. Read More

    Assessment of a Business-to-Consumer (B2C) model for Telemonitoring patients with Chronic Heart Failure (CHF).
    BMC Med Inform Decis Mak 2017 Oct 11;17(1):145. Epub 2017 Oct 11.
    Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, Netherlands.
    Background: The purpose of this study is to assess the Business-to-Consumer (B2C) model for telemonitoring patients with Chronic Heart Failure (CHF) by analysing the value it creates, both for organizations or ventures that provide telemonitoring services based on it, and for society.

    Methods: The business model assessment was based on the following categories: caveats, venture type, six-factor alignment, strategic market assessment, financial viability, valuation analysis, sustainability, societal impact, and technology assessment. The venture valuation was performed for three jurisdictions (countries) - Singapore, the Netherlands and the United States - in order to show the opportunities in a small, medium-sized, and large country (i. Read More

    Paramedic literature search filters: optimised for clinicians and academics.
    BMC Med Inform Decis Mak 2017 Oct 11;17(1):146. Epub 2017 Oct 11.
    Department of Community Emergency Health and Paramedic Practice, Monash University, Melbourne, Australia.
    Background: Search filters aid clinicians and academics to accurately locate literature. Despite this, there is no search filter or Medical Subject Headings (MeSH) term pertaining to paramedics. Therefore, the aim of this study was to create two filters to meet to different needs of paramedic clinicians and academics. Read More

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