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BMC Medical Informatics and Decision Making

Sunny C Lin, Julia Adler-Milstein
BACKGROUND: Health Information Organizations (HIOs) are third party organizations that facilitate electronic health information exchange (HIE) between providers in a geographic area. Despite benefits from HIE, HIOs have struggled to form and subsequently gain broad provider participation. We sought to assess whether market-level hospital and EHR vendor dynamics are associated with presence and level of hospital participation in HIOs. METHODS: 2014 data on 4523 hospitals and their EHR vendors were aggregated to the market level...
May 8, 2018: BMC Medical Informatics and Decision Making
Kyungsook Gartrell, Caitlin W Brennan, Gwenyth R Wallen, Fang Liu, Karen G Smith, Paul Fontelo
BACKGROUND: Although evidence-based practice in healthcare has been facilitated by Internet access through wireless mobile devices, research on the effectiveness of clinical decision support for clinicians at the point of care is lacking. This study examined how evidence as abstracts and the bottom-line summaries, accessed with PubMed4Hh mobile devices, affected clinicians' decision making at the point of care. METHODS: Three iterative steps were taken to evaluate the usefulness of PubMed4Hh tools at the NIH Clinical Center...
May 8, 2018: BMC Medical Informatics and Decision Making
K S Kylie Lee, Scott Wilson, Jimmy Perry, Robin Room, Sarah Callinan, Robert Assan, Noel Hayman, Tanya Chikritzhs, Dennis Gray, Edward Wilkes, Peter Jack, Katherine M Conigrave
After publication of the original article [1] it was noted that the name of author, Peter Jack, was erroneously typeset in both the PDF and online formats of the manuscript as Peter Jack GradDipIndigH.
May 2, 2018: BMC Medical Informatics and Decision Making
Tianyong Hao, Xiaoyi Pan, Zhiying Gu, Yingying Qu, Heng Weng
After publication of the original article [1] it was noted that the captions relating to Figs. 2 and 3 had been interchanged.
April 13, 2018: BMC Medical Informatics and Decision Making
Šefket Šabanović, Majnarić Trtica Ljiljana, František Babič, Michal Vadovský, Ján Paralič, Aleksandar Včev, Andreas Holzinger
BACKGROUND: There is potential for medical research on the basis of routine data used from general practice electronic health records (GP eHRs), even in areas where there is no common GP research platform. We present a case study on menopausal women with hypertension and metabolic syndrome (MS). The aims were to explore the appropriateness of the standard definition of MS to apply to this specific, narrowly defined population group and to improve recognition of women at high CV risk. METHODS: We investigated the possible uses offered by available data from GP eHRs, completed with patients interview, in goal of the study, using a combination of methods...
April 2, 2018: BMC Medical Informatics and Decision Making
Konstantin H Franke, Ralf Krumkamp, Aliyu Mohammed, Nimako Sarpong, Ellis Owusu-Dabo, Johanna Brinkel, Julius N Fobil, Axel Bonacic Marinovic, Philip Asihene, Mark Boots, Jürgen May, Benno Kreuels
BACKGROUND: The aim of this study was the development and evaluation of an algorithm-based diagnosis-tool, applicable on mobile phones, to support guardians in providing appropriate care to sick children. METHODS: The algorithm was developed on the basis of the Integrated Management of Childhood Illness (IMCI) guidelines and evaluated at a hospital in Ghana. Two hundred and thirty-seven guardians applied the tool to assess their child's symptoms. Data recorded by the tool and health records completed by a physician were compared in terms of symptom detection, disease assessment and treatment recommendation...
March 27, 2018: BMC Medical Informatics and Decision Making
Lingtong Min, Qi Tian, Xudong Lu, Jiye An, Huilong Duan
BACKGROUND: Clinical data registry is designed to collect and manage information about the practices and outcomes of a patient population for improving the quality and safety of care and facilitating novel researches. Semantic interoperability is a challenge when integrating the data from more than one clinical data registry. The openEHR approach can represent the information and knowledge semantics by multi-level modeling, and it advocates the use of collaborative modeling to facilitate reusing existing archetypes with consistent semantics so as to be a potential solution to improve the semantic interoperability...
March 22, 2018: BMC Medical Informatics and Decision Making
Yue-Shu Zhao, Kun-Li Zhang, Hong-Chao Ma, Kun Li
BACKGROUND: De-identification is the first step to use these records for data processing or further medical investigations in electronic medical records. Consequently, a reliable automated de-identification system would be of high value. METHODS: In this paper, a method of combining text skeleton and recurrent neural network is proposed to solve the problem of de-identification. Text skeleton is the general structure of a medical record, which can help neural networks to learn better...
March 22, 2018: BMC Medical Informatics and Decision Making
Xieling Chen, Haoran Xie, Fu Lee Wang, Ziqing Liu, Juan Xu, Tianyong Hao
BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great significance to conduct a deep analysis to understand the recent development of NLP-empowered medical research field. However, limited study examining the research status of this field could be found. Therefore, this study aims to quantitatively assess the academic output of NLP in medical research field...
March 22, 2018: BMC Medical Informatics and Decision Making
Kuo Yang, Guangming Liu, Ning Wang, Runshun Zhang, Jian Yu, Jianxin Chen, Xuezhong Zhou
BACKGROUND: Identifying targets of herbs is a primary step for investigating pharmacological mechanisms of herbal drugs in Traditional Chinese medicine (TCM). Experimental targets identification of herbs is a difficult and time-consuming work. Computational method for identifying herb targets is an efficient approach. However, how to make full use of heterogeneous network data about herbs and targets to improve the performance of herb targets prediction is still a dilemma. METHODS: In our study, a random walk algorithm on the heterogeneous herb-target network (named heNetRW) has been proposed to identify protein targets of herbs...
March 22, 2018: BMC Medical Informatics and Decision Making
Weiqi Chen, Yong Hu, Xiangzhou Zhang, Lijuan Wu, Kang Liu, Jianqin He, Zilin Tang, Xing Song, Lemuel R Waitman, Mei Liu
BACKGROUND: Acute kidney injury (AKI), characterized by abrupt deterioration of renal function, is a common clinical event among hospitalized patients and it is associated with high morbidity and mortality. AKI is defined in three stages with stage-3 being the most severe phase which is irreversible. It is important to effectively discover the true risk factors in order to identify high-risk AKI patients and allow better targeting of tailored interventions. However, Stage-3 AKI patients are very rare (only 0...
March 22, 2018: BMC Medical Informatics and Decision Making
Tianyong Hao, Xiaoyi Pan, Zhiying Gu, Yingying Qu, Heng Weng
BACKGROUND: Temporal expression extraction and normalization is a fundamental and essential step in clinical text processing and analyzing. Though a variety of commonly used NLP tools are available for medical temporal information extraction, few work is satisfactory for multi-lingual heterogeneous clinical texts. METHODS: A novel method called TEER is proposed for both multi-lingual temporal expression extraction and normalization from various types of narrative clinical texts including clinical data requests, clinical notes, and clinical trial summaries...
March 22, 2018: BMC Medical Informatics and Decision Making
Haihong Guo, Xu Na, Jiao Li
BACKGROUND: Health question-answering (QA) systems have become a typical application scenario of Artificial Intelligent (AI). An annotated question corpus is prerequisite for training machines to understand health information needs of users. Thus, we aimed to develop an annotated classification corpus of Chinese health questions (Qcorp) and make it openly accessible. METHODS: We developed a two-layered classification schema and corresponding annotation rules on basis of our previous work...
March 22, 2018: BMC Medical Informatics and Decision Making
Tania Gutiérrez Panchana, Viviane Hidalgo Cabalín
BACKGROUND: The use of measurement instruments has become a major issue in physical therapy, but their use in daily practice is rare. The aim of this paper is to describe adherence to standardized assessments by physical therapists using a complexity-based model for categorizing rehabilitation (CMCR) at the Clínica Alemana of Santiago, an acute hospital in Chile. METHODS: This retrospective cohort study used 145,968 participant records that were stored in the inpatient database between July 2011 and December 2015...
March 12, 2018: BMC Medical Informatics and Decision Making
Ronald W Gimbel, Ronald G Pirrallo, Steven C Lowe, David W Wright, Lu Zhang, Min-Jae Woo, Paul Fontelo, Fang Liu, Zachary Connor
BACKGROUND: The frequency of head computed tomography (CT) imaging for mild head trauma patients has raised safety and cost concerns. Validated clinical decision rules exist in the published literature and on-line sources to guide medical image ordering but are often not used by emergency department (ED) clinicians. Using simulation, we explored whether the presentation of a clinical decision rule (i.e. Canadian CT Head Rule - CCHR), findings from malpractice cases related to clinicians not ordering CT imaging in mild head trauma cases, and estimated patient out-of-pocket cost might influence clinician brain CT ordering...
March 12, 2018: BMC Medical Informatics and Decision Making
Jian-Xiang Wei, Jing Wang, Yun-Xia Zhu, Jun Sun, Hou-Ming Xu, Ming Li
BACKGROUND: Traditional Chinese Medicine (TCM) is a style of traditional medicine informed by modern medicine but built on a foundation of more than 2500 years of Chinese medical practice. According to statistics, TCM accounts for approximately 14% of total adverse drug reaction (ADR) spontaneous reporting data in China. Because of the complexity of the components in TCM formula, which makes it essentially different from Western medicine, it is critical to determine whether ADR reports of TCM should be analyzed independently...
March 9, 2018: BMC Medical Informatics and Decision Making
Jung-Ah Lee, Mona Choi, Sang A Lee, Natalie Jiang
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. METHODS: Relevant randomized controlled studies that were published between January 2005 and March 2016 were searched in six databases: PubMed, CINAHL, EMBASE, the Cochrane Library, PsycINFO, and Web of Science...
February 20, 2018: BMC Medical Informatics and Decision Making
Paolo Fraccaro, Markel Vigo, Panagiotis Balatsoukas, Sabine N van der Veer, Lamiece Hassan, Richard Williams, Grahame Wood, Smeeta Sinha, Iain Buchan, Niels Peek
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. METHODS: We conducted a controlled study with 20 kidney transplant patients...
February 12, 2018: BMC Medical Informatics and Decision Making
Daniel I Rhon, Derek Clewley, Jodi L Young, Charles D Sissel, Chad E Cook
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...
January 31, 2018: BMC Medical Informatics and Decision Making
Emmanuelle Sylvestre, Guillaume Bouzillé, Emmanuel Chazard, Cécil His-Mahier, Christine Riou, Marc Cuggia
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. METHODS: We enriched the Theriaque pharmaceutical database with the French national Comorbidities List to identify drugs associated with at least one major comorbid condition and diagnoses associated with a drug indication...
January 24, 2018: BMC Medical Informatics and Decision Making
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