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Patients' Perceptions of Different Information Exchange Mechanisms: An Exploratory Study in the United States Methods Inf. Med. (IF 1.574) Pub Date : 2021-02-22 Pouyan Esmaeilzadeh
Background Patients may seek health care services from various providers during treatment. These providers could serve in a network (affiliated) or practice separately (unaffiliated). Thus, using secure and reliable health information exchange (HIE) mechanisms would be critical to transfer sensitive personal health information (PHI) across distances. Studying patients' perceptions and opinions about
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MRF-RFS: A Modified Random Forest Recursive Feature Selection Algorithm for Nasopharyngeal Carcinoma Segmentation Methods Inf. Med. (IF 1.574) Pub Date : 2021-02-22 Yuchen Fei; Fengyu Zhang; Chen Zu; Mei Hong; Xingchen Peng; Jianghong Xiao; Xi Wu; Jiliu Zhou; Yan Wang
Background An accurate and reproducible method to delineate tumor margins is of great importance in clinical diagnosis and treatment. In nasopharyngeal carcinoma (NPC), due to limitations such as high variability, low contrast, and discontinuous boundaries in presenting soft tissues, tumor margin can be extremely difficult to identify in magnetic resonance imaging (MRI), increasing the challenge of
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Impact of Computerized Prescription on Medication Errors and Workflow Efficiency in Neonatal Intensive Care Units: A Quasi-Experimental Three-Phase Study Methods Inf. Med. (IF 1.574) Pub Date : 2021-01-12 Amirah Daher; Eman F. Badran; Manar Al-Lawama; Anas Al-Taee; Layla Makahleh; Mohammad Jabaiti; Amer Murtaji; Abla Bsou; Haneen Salah; Asma Tanash; Majid Al-Taee
Background Neonates are highly vulnerable to preventable medication errors due to their extensive exposure to medications in the neonatal intensive care units (NICUs). These errors, which can be made by medical, nursing, or pharmacy personnel, are costly and can be life-threatening. This study aimed to investigate the newly developed computerized neonatal pharmaceutical health care system (NPHCS) in
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International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study Methods Inf. Med. (IF 1.574) Pub Date : 2020-11-18 Elske Ammenwerth; Georg Duftschmid; Zaid Al-Hamdan; Hala Bawadi; Ngai T. Cheung; Kyung-Hee Cho; Guillermo Goldfarb; Kemal H. Gülkesen; Nissim Harel; Michio Kimura; Önder Kırca; Hiroshi Kondoh; Sabine Koch; Hadas Lewy; Dara Mize; Sari Palojoki; Hyeoun-Ae Park; Christopher Pearce; Fernan G. B. de Quirós; Kaija Saranto; Christoph Seidel; Vivian Vimarlund; Martin C. Were; Johanna Westbrook; Chung P. Wong;
Background Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional
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Leveraging the UMLS As a Data Standard for Rare Disease Data Normalization and Harmonization Methods Inf. Med. (IF 1.574) Pub Date : 2020-11-04 Qian Zhu; Dac-Trung Nguyen; Eric Sid; Anne Pariser
Objective In this study, we aimed to evaluate the capability of the Unified Medical Language System (UMLS) as one data standard to support data normalization and harmonization of datasets that have been developed for rare diseases. Through analysis of data mappings between multiple rare disease resources and the UMLS, we propose suggested extensions of the UMLS that will enable its adoption as a global
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Advantages and Limitations of Leap Motion from a Developers', Physical Therapists', and Patients' Perspective Methods Inf. Med. (IF 1.574) Pub Date : 2020-10-30 Edwin Gamboa; Andres Serrato; Juan Castro; Diana Toro; Maria Trujillo
Background Physical rehabilitation exergames (PREGs) are suitable for motivating patients toward completing treatments. Leap Motion (LM) is a motion sensor that may be useful for developing PREGs targeted at hands and fingers rehabilitation. Therefore, knowing the advantages and limitations of LM is relevant to understand under which conditions this sensor may be suitable. Objective In this article
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Electronic Health Records Aggregators (EHRagg ) Methods Inf. Med. (IF 1.574) Pub Date : 2020-10-30 Belén Prados-Suárez; Carlos Molina Fernández; Carmen Peña Yañez
Background Integration of health data systems is an open problem. Most of the active initiatives are based on the use of standards. However, achieving a widely and generalized compliment of such standards still seems a costly task that will take a long time to be completed. Even more, most of the standards are proposed for a specific use, without integrating other needs. Objectives We propose an alternative
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Usability Evaluation of User Requirement–Based Teleconsultation Robots: A Preliminary Report from South Korea Methods Inf. Med. (IF 1.574) Pub Date : 2020-10-30 Hyeongsuk Lee; Jeongeun Kim; Sukwha Kim; Hyoun-Joong Kong; Hyunjin Joo; Dongkyun Lee; Hyeongju Ryu
Background Telepresence robots used to deliver a point-of-care (POC) consultation system that may provide value to enable effective decision making by healthcare providers at care sites. Objectives This study aimed to evaluate usability of teleconsultation robots, based on endusers' needs, that can improve acceptance in future robot applications. Methods This is a single group postdesign study using
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The Dental, Oral, Medical Epidemiological (DOME) Study: Protocol and Study Methods Methods Inf. Med. (IF 1.574) Pub Date : 2020-10-20 Galit Almoznino; Ron Kedem; Ronit Turgeman; Tarif Bader; Nirit Yavnai; Dorit Zur; Boaz Shay
Abstract Objectives To develop and present the methods utilized for the Dental, Oral, Medical Epidemiological (DOME) study. Methods The DOME is an electronic record-based cross-sectional study, that was conducted to measure the dental, periodontal, and oral morbidities and their associations with systemic morbidities, among a nationally representative sample of young to middle-aged adults military
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Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing Methods Inf. Med. (IF 1.574) Pub Date : 2020-10-14 Antje Wulff; Marcel Mast; Marcus Hassler; Sara Montag; Michael Marschollek; Thomas Jack
Abstract Background Merging disparate and heterogeneous datasets from clinical routine in a standardized and semantically enriched format to enable a multiple use of data also means incorporating unstructured data such as medical free texts. Although the extraction of structured data from texts, known as natural language processing (NLP), has been researched at least for the English language extensively
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Usability Evaluation of a Distributed User Interface Application for Visuomotor Organization Assessment. Methods Inf. Med. (IF 1.574) Pub Date : 2020-09-07 Cristian Cuerda,Dulce Romero-Ayuso,Jose A Gallud,Carmen Morales,Ricardo Tesoriero,Jose-Matias Triviño-Juarez,Habib M Fardoun
Abstract Background This article describes the development and evaluation of a distributed user interface (DUI) application to assess visuomotor organization ability. This application enables therapists to evaluate the acquired brain injury (ABI) on patients, and patients, to perform the assessment on a touch screen while therapists can observe the assessment process in real time on a separated monitor
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Enhancing Traceability in Clinical Research Data through a Metadata Framework. Methods Inf. Med. (IF 1.574) Pub Date : 2020-09-07 Samuel Hume,Surendra Sarnikar,Cherie Noteboom
Abstract Background The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tools provide limited metadata traceability capabilities and are unable to query variables across
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Methods Refocused. Methods Inf. Med. (IF 1.574) Pub Date : 2020-09-07 Sabine Koch,John H Holmes
Background Methods of Information in Medicine (Methods) is the “longest running journal devoted to information in biomedicine and health care.”[1] Since its foundation in 1962, Methods has stressed the methodology and scientific fundamentals of organizing, representing, and analyzing data, information, and knowledge in biomedicine and health care. Publications covered a broad spectrum in the fields
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Using Information and Communication Technologies to Enhance Patient Rehabilitation Research Techniques. Methods Inf. Med. (IF 1.574) Pub Date : 2020-09-07 Habib M Fardoun,Daniyal M Alghazzawi,M Elena De la Guia
Introduction Physical rehabilitation is generally perceived as a face-to-face interaction between therapist and patient. However, thanks to technology developments, this picture has been changed. The massive innovation of information and communication technologies (ICTs) has brought a revolution to the view of health, people, and work.[1] Especially, the application of virtual reality (VR) and augmented
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Development and Usability of a Smartphone Application for Tracking Oncology Patients in Gaborone, Botswana. Methods Inf. Med. (IF 1.574) Pub Date : 2020-08-24 Surbhi Grover,Sidrah Shah,Rohini Bhatia,Sandra Urusaro,Barati Monare,Tlotlo Ralefala,Alexander Seiphetlheng,Sherman Preet Singh,Givy Dhaliwal
Abstract Background The majority of new cancer cases are expected to be diagnosed in low- and middle-income countries (LMICs) by 2025, and 65% of cancer deaths currently occur in LMICs. Treatment adherence, patient monitoring, and follow-up are essential to cancer care but are often not possible in these settings. Out Patient (OP) Care, a smartphone application (app) developed to fill this gap, texts
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An Augmented Model with Inferred Blood Features for the Self-diagnosis of Metabolic Syndrome. Methods Inf. Med. (IF 1.574) Pub Date : 2020-08-24 Tianshu Zhou,Ying Zhang,Chengkai Wu,Chao Shen,Jingsong Li,Zhong Liu
Abstract Background and Objectives The penetration rate of physical examinations in China is substantially lower than that in developed countries. Therefore, an auxiliary approach that does not depend on hospital health checks for the diagnosis of metabolic syndrome (MetS) is needed. Methods In this study, we proposed an augmented method with inferred blood features that uses self-care inputs available
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Health-Enabling Technologies for Telerehabilitation of the Shoulder: A Feasibility and User Acceptance Study. Methods Inf. Med. (IF 1.574) Pub Date : 2020-08-10 Bianca Steiner,Lena Elgert,Birgit Saalfeld,Jonas Schwartze,Horst Peter Borrmann,Axel Kobelt-Pönicke,Andreas Figlewicz,Detlev Kasprowski,Michael Thiel,Ralf Kreikebohm,Reinhold Haux,Klaus-Hendrik Wolf
Abstract Background After discharge from a rehabilitation center the continuation of therapy is necessary to secure already achieved healing progress and sustain (re-)integration into working life. To this end, home-based exercise programs are frequently prescribed. However, many patients do not perform their exercises as frequently as prescribed or even with incorrect movements. The telerehabilitation
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APRICOT: Advanced Platform for Reproducible Infrastructures in the Cloud via Open Tools. Methods Inf. Med. (IF 1.574) Pub Date : 2020-08-10 Vicent Giménez-Alventosa,José Damián Segrelles,Germán Moltó,Mar Roca-Sogorb
Abstract Background Scientific publications are meant to exchange knowledge among researchers but the inability to properly reproduce computational experiments limits the quality of scientific research. Furthermore, bibliography shows that irreproducible preclinical research exceeds 50%, which produces a huge waste of resources on nonprofitable research at Life Sciences field. As a consequence, scientific
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Predicting Lipid-Lowering Medication Persistence after the First Cardiovascular Disease Hospitalization. Methods Inf. Med. (IF 1.574) Pub Date : 2020-07-29 Feiyu Hu,Jim Warren,Daniel J Exeter
Abstract Objectives This study analyzed patient factors in medication persistence after discharge from the first hospitalization for cardiovascular disease (CVD) with the aim of predicting persistence to lipid-lowering therapy for 1 to 2 years. Methods A subcohort having a first CVD hospitalization was selected from 313,207 patients for proportional hazard model analysis. Logistic regression, support
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A Systematic Review of the Effectiveness of Telerehabilitation Interventions for Therapeutic Purposes in the Elderly. Methods Inf. Med. (IF 1.574) Pub Date : 2020-07-06 Farnia Velayati,Haleh Ayatollahi,Morteza Hemmat
Abstract Background Many elderly people suffer from chronic health conditions and mobility limitations. Therefore, they may benefit from traditional rehabilitation or telerehabilitation interventions as an alternative for this type of services. Objective The purpose of this study was to compare the effectiveness of telerehabilitation interventions with traditional rehabilitation services for therapeutic
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From Raw Data to FAIR Data: The FAIRification Workflow for Health Research. Methods Inf. Med. (IF 1.574) Pub Date : 2020-07-03 A Anil Sinaci,Francisco J Núñez-Benjumea,Mert Gencturk,Malte-Levin Jauer,Thomas Deserno,Catherine Chronaki,Giorgio Cangioli,Carlos Cavero-Barca,Juan M Rodríguez-Pérez,Manuel M Pérez-Pérez,Gokce B Laleci Erturkmen,Tony Hernández-Pérez,Eva Méndez-Rodríguez,Carlos L Parra-Calderón
Abstract Background FAIR (findability, accessibility, interoperability, and reusability) guiding principles seek the reuse of data and other digital research input, output, and objects (algorithms, tools, and workflows that led to that data) making them findable, accessible, interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governed initiative - defined a seven-step FAIRification
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Exchange of Clinical and Omics Data According to FAIR Principles: A Review of Open Source Solutions. Methods Inf. Med. (IF 1.574) Pub Date : 2020-07-03 Philipp Pugliese,Christian Knell,Jan Christoph
Abstract Background Due to the ongoing increase and importance of the sustainable reusability of data, the findable, accessible, interoperable, reusable or FAIR principles were developed which are also relevant in translational research. Objectives The study aims at identification of platforms by literature search that are suitable for implementation in translational research, in particular with regard
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Professionalism of Information Management in Health Care: Development and Validation of the Construct and Its Measurement. Methods Inf. Med. (IF 1.574) Pub Date : 2020-07-03 Johannes Thye,Moritz Esdar,Jan-David Liebe,Franziska Jahn,Alfred Winter,Ursula Hübner
Abstract Background Against the background of a steadily increasing degree of digitalization in health care, a professional information management (IM) is required to successfully plan, implement, and evaluate information technology (IT). At its core, IM has to ensure a high quality of health data and health information systems to support patient care. Objectives The goal of the present study was to
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Design of a Low-Cost, Wearable Device for Kinematic Analysis in Physical Therapy Settings. Methods Inf. Med. (IF 1.574) Pub Date : 2020-06-14 Andrew Hua,Nicole Johnson,Joshua Quinton,Pratik Chaudhary,David Buchner,Manuel E Hernandez
Abstract Unsupervised home exercise is a major component of physical therapy (PT). This study proposes an inexpensive, inertial measurement unit-based wearable device to capture kinematic data to facilitate exercise. However, conveying and interpreting kinematic data to non-experts poses a challenge due to the complexity and background knowledge required that most patients lack. Objectives The objectives
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Applying FAIR Principles to Improve Data Searchability of Emergency Department Datasets: A Case Study for HCUP-SEDD. Methods Inf. Med. (IF 1.574) Pub Date : 2020-06-14 Karishma Bhatia,James Tanch,Elizabeth S Chen,Indra Neil Sarkar
Abstract Background There is a recognized need to improve how scholarly data are managed and accessed. The scientific community has proposed the findable, accessible, interoperable, and reusable (FAIR) data principles to address this issue. Objective The objective of this case study was to develop a system for improving the FAIRness of Healthcare Cost and Utilization Project's State Emergency Department
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Comparison of Two Information Sources for Cause-of-Death Follow-up in the Russian Federation: The Asbest Chrysotile Cohort Study. Methods Inf. Med. (IF 1.574) Pub Date : 2020-06-14 J Schüz,E Kovalevskiy,M Moissonnier,A Olsson,D Hashim,H Kromhout,S Kashanskiy,O Chernov,I Bukhtiyarov,E Ostroumova
Abstract Background The Asbest chrysotile cohort was set up in Asbest town, Sverdlovsk oblast, Russian Federation, among the current and former workforce of the world's largest operating chrysotile mine and its processing mills, to investigate cancer risk in relation to occupational exposure to chrysotile. Objectives The cohort of 35,837 people was followed-up for mortality using cause-of-death information
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A Method to Extract Feature Variables Contributed in Nonlinear Machine Learning Prediction. Methods Inf. Med. (IF 1.574) Pub Date : 2020-05-07 Mayumi Suzuki,Takuma Shibahara,Yoshihiro Muragaki
Abstract Background Although advances in prediction accuracy have been made with new machine learning methods, such as support vector machines and deep neural networks, these methods make nonlinear machine learning models and thus lack the ability to explain the basis of their predictions. Improving their explanatory capabilities would increase the reliability of their predictions. Objective Our objective
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Beyond Electronic Health Record Adoption. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 Conrad Krawiec
It was with great interest that I read the recent article by Al-Rayes et al. Within the authors' institution, not all inpatient physicians have adopted a recently implemented electronic health record (EHR) system. This pilot cross-sectional quantitative study investigated the factors limiting adoption of EHR systems among physicians at King Fahd Military Medical Complex in Saudi Arabia. Using the theoretical
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Applying FAIRness: Redesigning a Biomedical Informatics Research Data Management Pipeline. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 Marcel Parciak,Theresa Bender,Ulrich Sax,Christian Robert Bauer
Abstract Background Managing research data in biomedical informatics research requires solid data governance rules to guarantee sustainable operation, as it generally involves several professions and multiple sites. As every discipline involved in biomedical research applies its own set of tools and methods, research data as well as applied methods tend to branch out into numerous intermediate and
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Prediction of Postoperative Length of Hospital Stay Based on Differences in Nursing Narratives in Elderly Patients with Epithelial Ovarian Cancer. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 Kidong Kim,Yoonchang Han,Suyeon Jeong,Kibbeum Doh,Hyeoun-Ae Park,Kyogu Lee,Moonsuk Cho,Soyeon Ahn
Abstract Objectives The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer. Methods A total of 33 patients, aged over 65 years, underwent curative surgery for newly diagnosed ovarian cancer between 2008 and 2012. Based on the median postoperative LOS, patients were divided into
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Analysis of Feature Extraction Methods for Prediction of 30-Day Hospital Readmissions. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 Joel Sumner,Adel Alaeddini
Abstract Objectives This article aims to determine possible improvements made by feature extraction methods to the machine learning prediction methods for predicting 30-day hospital readmissions. Methods The study evaluates five feature extraction methods including principal component analysis (PCA), kernel principal component analysis (KPCA), isomap, Laplacian eigenmaps, and locality preserving projections
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Machine Learning Classification Algorithms to Predict aGvHD following Allo-HSCT: A Systematic Review. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 Cirruse Salehnasab,Abbas Hajifathali,Farkhondeh Asadi,Elham Roshandel,Alireza Kazemi,Arash Roshanpoor
Abstract Background The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in patients receiving allogeneic hematopoietic stem cell transplantation. Given that it occurs at the stage of severe tissue damage, its diagnosis is late. With the advancement of machine learning (ML), promising real-time models to predict aGvHD have emerged. Objective This article aims to synthesize
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Development and Evaluation of Ontologies in Traditional Medicine: A Review Study. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 Hassan Shojaee-Mend,Haleh Ayatollahi,Azam Abdolahadi
Abstract Background Development of ontologies in traditional medicine can be a foundation for other applications of informatics in this field. Despite the importance of the development of ontologies in traditional medicine, there are few review studies in this area. This study aims to review different methods for ontology development and evaluation in traditional medicine. Methods This review study
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A Systematic Review of Health Dialog Systems. Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-29 William R Kearns,Nai-Ching Chi,Yong K Choi,Shih-Yin Lin,Hilaire Thompson,George Demiris
Abstract Background Health dialog systems have seen increased adoption by patients, hospitals, and universities due to the confluence of advancements in machine learning and the ubiquity of high-performance hardware that supports real-time speech recognition, high-fidelity text-to-speech, and semantic understanding of natural language. Objectives This review seeks to enumerate opportunities to apply
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Donald A. B. Lindberg (1933-2019). Methods Inf. Med. (IF 1.574) Pub Date : 2020-04-17 Alexa T McCray,Reinhold Haux,Jan H van Bemmel
We are enormously saddened by the death of our friend and colleague, Donald A.B. Lindberg, MD, on August 17, 2019. Throughout his long career, Don was a visionary leader who, earlier than most, saw the potential of technology to improve health care. He was a founder of our field, and he was a steadfast supporter of Methods. Beginning in 1970, when the journal was still a relatively new journal edited
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One Step Away from Technology but One Step Towards Domain Experts—MDRBridge: A Template-Based ISO 11179-Compliant Metadata Processing Pipeline Methods Inf. Med. (IF 1.574) Pub Date : 2019-12-01 Ann-Kristin Kock-Schoppenhauer; B. Kroll; M. Lambarki; H. Ulrich; S. Stahl-Toyota; J.K. Habermann; P. Duhm-Harbeck; J. Ingenerf; M. Lablans
BACKGROUND Secondary use of routine medical data relies on a shared understanding of given information. This understanding is achieved through metadata and their interconnections, which can be stored in metadata repositories (MDRs). The necessity of an MDR is well understood, but the local work on metadata is a time-consuming and challenging process for domain experts. OBJECTIVE To support the identification
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Overrating Classifier Performance in ROC Analysis in the Absence of a Test Set: Evidence from Simulation and Italian CARATkids Validation. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-19 Giovanna Cilluffo,Salvatore Fasola,Giuliana Ferrante,Laura Montalbano,Ilaria Baiardini,Luciana Indinnimeo,Giovanni Viegi,Joao A Fonseca,Stefania La Grutta
BACKGROUND The use of receiver operating characteristic curves, or "ROC analysis," has become quite common in biomedical research to support decisions. However, sensitivity, specificity, and misclassification rates are still often estimated using the training sample, overlooking the risk of overrating the test performance. METHODS A simulation study was performed to highlight the inferential implications
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A Statistical Approach for the Learning Curve of Physicians in Utilization of Electronic Order Sets Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 Jaehoon Lee; Nathan C. Hulse
BACKGROUND Understanding a physician's behavior toward learning order sets is important as it is a key information to design order sets with optimized contents. OBJECTIVE The objective of this article is to test a hypothesis: for a physician using a new order set repeatedly, the utilization rate of order set contents has a pattern of either increase or decrease. METHODS To test the hypothesis, we retrieved
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Modeling Care Team Structures in the Neonatal Intensive Care Unit through Network Analysis of EHR Audit Logs. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 You Chen,Christoph U Lehmann,Leon D Hatch,Emma Schremp,Bradley A Malin,Daniel J France
BACKGROUND In the neonatal intensive care unit (NICU), predefined acuity-based team care models are restricted to core roles and neglect interactions with providers outside of the team, such as interactions that transpire via electronic health record (EHR) systems. These unaccounted interactions may be related to the efficiency of resource allocation, information flow, communication, and thus impact
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Evaluating Manual Mappings of Russian Proprietary Formats and Terminologies to FHIR. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 Iuliia D Lenivtceva,Georgy Kopanitsa
BACKGROUND Evaluating potential data losses from mapping proprietary medical data formats to standards is essential for decision making. The article implements a method to evaluate the preliminary content overlap of proprietary medical formats, including national terminologies and Fast Healthcare Interoperability Resources (FHIR)-international medical standard. METHODS Three types of mappings were
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Identification and Validation of Requirements for a Registry System of Children's Developmental Motor Disorders in Iran. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 Elahe Gozali,Reza Safdari,Marjan Ghazisaeedi,Bahlol Rahimi,Hamidreza Farrokh Eslamlou,Esmaeil Mehraeen
BACKGROUND Despite recent advances in the field of medical sciences, children's developmental motor disorders (DMDs) are considered as one of the challenges in this area. Establishment of electronic systems for recording and monitoring children's DMDs can play an effective role in identifying patients and reducing the costs and consequences of the disease management. The aim of this study was to identify
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Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 Ali Garavand,Mahnaz Samadbeik,Hamed Nadri,Bahlol Rahimi,Heshmatollah Asadi
BACKGROUND Students with complex health care services process face constant challenges with regard to health education. The mobile devices are an important tool that can install various applications for using information such as clinical guidelines, drug resources, clinical calculations, and the latest scientific evidence without any time and place limitations. And this happens only when students accept
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Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 Henry Joutsijoki,Kirsi Penttinen,Martti Juhola,Katriina Aalto-Setälä
BACKGROUND Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previously observed that a few genetic cardiac diseases can be separated from each other and healthy controls by applying machine learning to Ca2+ transient signals
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Information Extraction from Echocardiography Reports for a Clinical Follow-up Study-Comparison of Extracted Variables Intended for General Use in a Data Warehouse with Those Intended Specifically for the Study. Methods Inf. Med. (IF 1.574) Pub Date : 2019-11-01 Mathias Kaspar,Caroline Morbach,Georg Fette,Maximilian Ertl,Lea K Seidlmayer,Jonathan Krebs,Georg Dietrich,Leon Liman,Frank Puppe,Stefan Störk
BACKGROUND The interest in information extraction from clinical reports for secondary data use is increasing. But experience with the productive use of information extraction processes over time is scarce. A clinical data warehouse has been in use at our university hospital for several years, which also provides an information extraction of echocardiography reports developed for general use. OBJECTIVES
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Current Trends in Biomedical and Health Informatics. Methods Inf. Med. (IF 1.574) Pub Date : 2019-09-13 Sabine Koch
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Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony. Methods Inf. Med. (IF 1.574) Pub Date : 2019-03-29 Gregory B Rehm,Jinyoung Han,Brooks T Kuhn,Jean-Pierre Delplanque,Nicholas R Anderson,Jason Y Adams,Chen-Nee Chuah
BACKGROUND As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (ICU) existing automated alarm systems typically rely on simple thresholding that result in frequent false positives. Recurrent false positive alerts create
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Is Multiclass Automatic Text De-Identification Worth the Effort? Methods Inf. Med. (IF 1.574) Pub Date : 2019-03-29 Duy Duc An Bui,David T Redden,James J Cimino
OBJECTIVES Automatic de-identification to remove protected health information (PHI) from clinical text can use a "binary" model that replaces redacted text with a generic tag (e.g., ""), or can use a "multiclass" model that retains more class information (e.g., ""). Binary models are easier to develop, but result in text that is potentially less informative. We investigated whether building a multiclass
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Computational Intelligence Re-meets Medical Image Processing. Methods Inf. Med. (IF 1.574) Pub Date : 2019-03-16 Hariton N Costin,Thomas M Deserno
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Erratum to: Machine Learning and Data Analytics in Pervasive Health. Methods Inf. Med. (IF 1.574) Pub Date : 2019-02-15 Nuria Oliver,Oscar Mayora,Michael Marschollek
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Addendum to: Approaches to Regularized Regression - A Comparison between Gradient Boosting and the Lasso. Methods Inf. Med. (IF 1.574) Pub Date : 2019-01-12 Tobias Hepp,Matthias Schmid,Olaf Gefeller,Elisabeth Waldmann,Andreas Mayr
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Prehospital Telemedical Emergency Management of Severely Injured Trauma Patients. Methods Inf. Med. (IF 1.574) Pub Date : 2018-10-09 Patrick A Eder,Birgit Reime,Thomas Wurmb,Uwe Kippnich,Layal Shammas,Asarnusch Rashid
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Analysis of Machine Learning Algorithms for Diagnosis of Diffuse Lung Diseases. Methods Inf. Med. (IF 1.574) Pub Date : 2018-10-09 Isadora Cardoso,Eliana Almeida,Hector Allende-Cid,Alejandro C Frery,Rangaraj M Rangayyan,Paulo M Azevedo-Marques,Heitor S Ramos
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Considering Relationship of Proteins for Radiotherapy Prognosis of Bladder Cancer Cells in Small Data Set. Methods Inf. Med. (IF 1.574) Pub Date : 2018-09-25 Tung-I Tsai,Yaofeng Zhang,Zhigang Zhang,Gy-Yi Chao,Cheng-Chieh Tsai
BACKGROUND Radiotherapy has serious side effects and thus requires prudent and cautious evaluation. However, obtaining protein expression profiles is expensive and timeconsuming, making it necessary to develop a theoretical and rational procedure for predicting the radiotherapy outcome for bladder cancer when working with limited data. OBJECTIVE A procedure for estimating the performance of radiotherapy
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Learning to Detect Cognitive Impairment through Digital Games and Machine Learning Techniques. Methods Inf. Med. (IF 1.574) Pub Date : 2018-09-25 Sonia Valladares-Rodriguez,Roberto Pérez-Rodriguez,J Manuel Fernandez-Iglesias,Luis E Anido-Rifón,David Facal,Carlos Rivas-Costa
OBJECTIVE Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population. The early detection of Mild Cognitive Impairment (MCI), which may trigger AD, is essential to slow down the cognitive decline process. METHODS This paper presents a suit of serious games that aims at detecting AD and MCI overcoming the limitations of traditional tests, as they are time-consuming, affected
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Prediction of Sepsis and In-Hospital Mortality Using Electronic Health Records. Methods Inf. Med. (IF 1.574) Pub Date : 2018-09-25 Anahita Khojandi,Varisara Tansakul,Xueping Li,Rebecca S Koszalinski,William Paiva
OBJECTIVES Our goal was to develop predictive models for sepsis and in-hospital mortality using electronic health records (EHRs). We showcased the efficiency of these algorithms in patients diagnosed with pneumonia, a group that is highly susceptible to sepsis. METHODS We retrospectively analyzed the Health Facts® (HF) dataset to develop models to predict mortality and sepsis using the data from the
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Quality of the ICD-11 Beta Draft from the German Perspective: Evaluation Based on the Alphabet of ICD-10-GM 2017. Methods Inf. Med. (IF 1.574) Pub Date : 2018-09-25 Jürgen Stausberg
OBJECTIVES The German Association for Medical Informatics, Biometry and Epidemiology implemented a field test for the ICD-11 Beta Draft. Aim was to analyze completeness and appropriateness of the ICD-11 Beta Draft in its entire breadth. METHODS Starting point was the synonym thesaurus ("Alphabet") of the German modification of ICD-10. The Alphabet included a list of diagnoses terms that supports the
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Development of an Open Metadata Schema for Clinical Pathway (openCP) in China. Methods Inf. Med. (IF 1.574) Pub Date : 2018-09-25 Wei Xu,Yanxin Zhu,Yibing Geng
BACKGROUND By the end of the first quarter of 2017, 1212 standard Clinical Pathways (CPs) had been developed and implemented in China since 2009, however, Chinese standard CPs are still paper-based CPs. OBJECTIVES To optimize the data structure and content of Chinese standard CPs based on Chinese health standards by two-level modeling approach and archetype method, and develop an Open Metadata Schema
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Health Information Systems - from Present to Future? Methods Inf. Med. (IF 1.574) Pub Date : 2018-07-18 Reinhold Haux
This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Funded by the German Federal Ministry of Education and Research with about 150 million Euro in its currently starting development and networking phase this initiative has already a significant impact on the development of health information systems in Germany. In this Focus Theme
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German Medical Informatics Initiative. Methods Inf. Med. (IF 1.574) Pub Date : 2018-07-18 Sebastian C Semler,Frank Wissing,Ralf Heyder
This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. The Medical Informatics Initiative (MII) was launched within the scope of the German Federal Ministry of Education and Research's (BMBF) Medical Informatics Funding Scheme, with the goal of developing infrastructure for the integration of clinical data from patient care and medical
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Smart Medical Information Technology for Healthcare (SMITH). Methods Inf. Med. (IF 1.574) Pub Date : 2018-07-18 Alfred Winter,Sebastian Stäubert,Danny Ammon,Stephan Aiche,Oya Beyan,Verena Bischoff,Philipp Daumke,Stefan Decker,Gert Funkat,Jan E Gewehr,Armin de Greiff,Silke Haferkamp,Udo Hahn,Andreas Henkel,Toralf Kirsten,Thomas Klöss,Jörg Lippert,Matthias Löbe,Volker Lowitsch,Oliver Maassen,Jens Maschmann,Sven Meister,Rafael Mikolajczyk,Matthias Nüchter,Mathias W Pletz,Erhard Rahm,Morris Riedel,Kutaiba Saleh
INTRODUCTION This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. "Smart Medical Information Technology for Healthcare (SMITH)" is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH's goals are
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