An algorithm to identify patients with treated type 2 diabetes using medico-administrative data.

abstract：BACKGROUND:With wide applications of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), statistical comparison of serum peptide profiles and management of patients information play ...

journal_title：BMC medical informatics and decision making

authors： Cao Y,Wang N,Ying X,Li A,Wang H,Zhang X,Li W

更新日期：2009-02-17 00:00:00

abstract：BACKGROUND:Diagnosis of neuromuscular diseases in primary care is often challenging. Rare diseases such as Pompe disease are easily overlooked by the general practitioner. We therefore aimed to develop a diagnostic support tool using patient-oriented questions and combined data mining algorithms recognizing answer patt...

journal_title：BMC medical informatics and decision making

authors： Grigull L,Lechner W,Petri S,Kollewe K,Dengler R,Mehmecke S,Schumacher U,Lücke T,Schneider-Gold C,Köhler C,Güttsches AK,Kortum X,Klawonn F

更新日期：2016-03-08 00:00:00

abstract：BACKGROUND:Prior studies demonstrate the suitability of natural language processing (NLP) for identifying pneumonia in chest radiograph (CXR) reports, however, few evaluate this approach in intensive care unit (ICU) patients. METHODS:From a total of 194,615 ICU reports, we empirically developed a lexicon to categorize...

journal_title：BMC medical informatics and decision making

authors： Liu V,Clark MP,Mendoza M,Saket R,Gardner MN,Turk BJ,Escobar GJ

更新日期：2013-08-15 00:00:00

abstract：BACKGROUND:Chronic diseases affect millions of children worldwide leading to substantial disease burden to the children and their families as well as escalating health care costs. The increasing trend in the prevalence of complex pediatric chronic diseases requires innovative and optimal delivery of care. Biomedical in...

journal_title：BMC medical informatics and decision making

authors： Moeinedin F,Moineddin R,Jadad AR,Hamid JS,To T,Beyene J

更新日期：2009-05-05 00:00:00

abstract：BACKGROUND:Nowadays more and more clinical guidelines for health care professionals are being developed. However, this does not automatically mean that these guidelines are actually implemented. The aim of this meta-review is twofold: firstly, to gain a better understanding of which factors affect the implementation of...

journal_title：BMC medical informatics and decision making

authors： Francke AL,Smit MC,de Veer AJ,Mistiaen P

更新日期：2008-09-12 00:00:00

abstract：BACKGROUND:Recent telehealth studies have demonstrated minor impact on patients affected by long-term conditions. The use of technology does not guarantee the compliance required for sustained collection of high-quality symptom and physiological data. Remote monitoring alone is not sufficient for successful disease man...

journal_title：BMC medical informatics and decision making

authors： Velardo C,Shah SA,Gibson O,Clifford G,Heneghan C,Rutter H,Farmer A,Tarassenko L,EDGE COPD Team.

更新日期：2017-02-20 00:00:00

abstract：BACKGROUND:Adverse drug events (ADEs) often occur as a result of drug-drug interactions (DDIs). The use of data mining for detecting effects of drug combinations on ADE has attracted growing attention and interest, however, most studies focused on analyzing pairwise DDIs. Recent efforts have been made to explore the di...

journal_title：BMC medical informatics and decision making

authors： Yao X,Tsang T,Sun Q,Quinney S,Zhang P,Ning X,Li L,Shen L

更新日期：2020-03-18 00:00:00

abstract：BACKGROUND:Information and communication technologies have become a vital infrastructural asset for use in the retention of rural health workers. However, little is known about the potential influence of ICT use, perceptions of health workers on ICT in healthcare delivery, and contribution of ICT to health care provide...

journal_title：BMC medical informatics and decision making

authors： Yagos WO,Tabo Olok G,Ovuga E

更新日期：2017-01-10 00:00:00

abstract：BACKGROUND:A common disclosure control practice for health datasets is to identify small geographic areas and either suppress records from these small areas or aggregate them into larger ones. A recent study provided a method for deciding when an area is too small based on the uniqueness criterion. The uniqueness crite...

journal_title：BMC medical informatics and decision making

authors： El Emam K,Brown A,AbdelMalik P,Neisa A,Walker M,Bottomley J,Roffey T

更新日期：2010-04-02 00:00:00

abstract：BACKGROUND:To evaluate whether or not the utilization of Health Information Technologies (HITs) in Quality Improvement Methodologies (QIMs) has impacts on QIMs' efficiency, throughput and financial outcomes at healthcare organizations and physician practices in the United States. METHODS:This is a retrospective observ...

journal_title：BMC medical informatics and decision making

authors： AlHazme RH,Haque SS,Wiggin H,Rana AM

更新日期：2016-12-05 00:00:00

abstract：BACKGROUND:Despite advances in diagnosis and treatment of type 2 diabetes, suboptimal metabolic control persists. Patient education in diabetes has been proved to enhance self-efficacy and guideline-driven treatment, however many people with type 2 diabetes do not have access to or do not participate in self-management...

journal_title：BMC medical informatics and decision making

authors： Odnoletkova I,Buysse H,Nobels F,Goderis G,Aertgeerts B,Annemans L,Ramaekers D

更新日期：2016-11-09 00:00:00

abstract：BACKGROUND:Most hospitals keep and update their paper-based medical records after introducing an electronic medical record or a hospital information system (HIS). This case report describes a HIS in a hospital where the paper-based medical records are scanned and eliminated. To evaluate the HIS comprehensively, the per...

journal_title：BMC medical informatics and decision making

authors： Laerum H,Karlsen TH,Faxvaag A

更新日期：2004-10-16 00:00:00

abstract：BACKGROUND:Geriatric patients frequently undergo emergency general surgery and accrue a greater risk of postoperative complications and fatal outcomes than the general population. It is highly relevant to develop the most appropriate care measures and to guide patient-centered decision-making around end-of-life care. P...

journal_title：BMC medical informatics and decision making

authors： Cao Y,Bass GA,Ahl R,Pourlotfi A,Geijer H,Montgomery S,Mohseni S

更新日期：2020-05-07 00:00:00

abstract：BACKGROUND:Patient decision aids (DAs) are support tools designed to provide patients with relevant information to help them make informed decisions about their healthcare. While DAs can be effective in improving patient knowledge and decision quality, it is unknown what types of information and evidence are used to po...

journal_title：BMC medical informatics and decision making

authors： Clifford AM,Ryan J,Walsh C,McCurtin A

更新日期：2017-02-23 00:00:00

abstract：BACKGROUND:Cardiovascular diseases (CVDs) are difficult to diagnose early and have risk factors that are easy to overlook. Early prediction and personalization of treatment through the use of artificial intelligence (AI) may help clinicians and patients manage CVDs more effectively. However, to apply AI approaches to C...

journal_title：BMC medical informatics and decision making

authors： Ahn I,Na W,Kwon O,Yang DH,Park GM,Gwon H,Kang HJ,Jeong YU,Yoo J,Kim Y,Jun TJ,Kim YH

更新日期：2021-01-28 00:00:00

abstract：BACKGROUND:Although fecal hemoglobin concentration (f-Hb) was highly associated with the risk of colorectal neoplasms, current studies on this subject are hampered by skewedness of the data and the ordinal property of f-Hb has not been well studied yet. Our aim was to develop a quantile-based method to estimate adjuste...

journal_title：BMC medical informatics and decision making

authors： Peng SM,Chiu HM,Jen HH,Hsu CY,Chen SL,Chiu SY,Yen AM,Fann JC,Lee YC,Chen HH

更新日期：2019-05-02 00:00:00

abstract：BACKGROUND:Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error...

journal_title：BMC medical informatics and decision making

authors： Ongenae F,De Backere F,Steurbaut K,Colpaert K,Kerckhove W,Decruyenaere J,De Turck F

更新日期：2010-01-18 00:00:00

abstract：BACKGROUND:SNOMED CT is being increasingly adopted as the standard clinical terminology for health care applications. Existing clinical applications that use legacy interface terminology need to migrate to the preferred SNOMED CT standard. In this paper, we describe our experience and methodology for mapping concepts f...

journal_title：BMC medical informatics and decision making

authors： Wade G,Rosenbloom ST

更新日期：2008-10-27 00:00:00

abstract：BACKGROUND:Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer and the most difficult to predict. When there are no distant metastases, the optimal therapy depends mainly on whether there are malignant lymph nodes in the mediastinum. Given the vigorous debate among specialists about which tests...

journal_title：BMC medical informatics and decision making

authors： Luque M,Díez FJ,Disdier C

更新日期：2016-01-26 00:00:00

abstract：BACKGROUND:Automated machine-learning systems are able to de-identify electronic medical records, including free-text clinical notes. Use of such systems would greatly boost the amount of data available to researchers, yet their deployment has been limited due to uncertainty about their performance when applied to new ...

journal_title：BMC medical informatics and decision making

authors： Hartman T,Howell MD,Dean J,Hoory S,Slyper R,Laish I,Gilon O,Vainstein D,Corrado G,Chou K,Po MJ,Williams J,Ellis S,Bee G,Hassidim A,Amira R,Beryozkin G,Szpektor I,Matias Y

更新日期：2020-01-30 00:00:00

abstract：BACKGROUND:Adopting mobile electronic medical record (MEMR) systems is expected to be one of the superior approaches for improving nurses' bedside and point of care services. However, nurses may use the functions for far fewer tasks than the MEMR supports. This may depend on their technological personality associated t...

journal_title：BMC medical informatics and decision making

authors： Kuo KM,Liu CF,Ma CC

更新日期：2013-08-12 00:00:00

abstract：BACKGROUND:Electronic health records provide access to an unprecedented amount of clinical data for research that can accelerate the development of effective medical practices. However it is important to protect patient confidentiality, as many medical conditions are stigmatized and disclosure could result in personal ...

journal_title：BMC medical informatics and decision making

authors： Morse RE,Nadkarni P,Schoenfeld DA,Finkelstein DM

更新日期：2011-11-10 00:00:00

abstract：BACKGROUND:Drug therapy has become increasingly efficient, with more drugs available for treatment of an ever-growing number of conditions. Yet, drug use is reported to be sub optimal in several aspects, such as dosage, patient's adherence and outcome of therapy. The aim of the current study was to investigate the poss...

journal_title：BMC medical informatics and decision making

authors： Wanger P,Martin L

更新日期：2004-07-20 00:00:00

abstract：BACKGROUND:Cost effectiveness research is emerging in the chronic kidney disease (CKD) research field. Especially, an individual-level state transition model (microsimulation) is widely used for these researches. Some researchers set CKD grades as discrete health states, and the transition probabilities between these s...

journal_title：BMC medical informatics and decision making

authors： Hiragi S,Tamura H,Goto R,Kuroda T

更新日期：2018-11-09 00:00:00

abstract：BACKGROUND:In recent years, a significant change has taken place in the health care delivery systems due to the availability of smartphones and mobile software applications. The use of mobile technology can help to reduce a number of barriers for mental health care such as providers' workload, lack of qualified personn...

journal_title：BMC medical informatics and decision making

authors： Pokhrel P,Karmacharya R,Taylor Salisbury T,Carswell K,Kohrt BA,Jordans MJD,Lempp H,Thornicroft G,Luitel NP

更新日期：2021-01-19 00:00:00

abstract：BACKGROUND:New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the...

journal_title：BMC medical informatics and decision making

authors： Buczak AL,Babin S,Moniz L

更新日期：2010-10-14 00:00:00

abstract：BACKGROUND:A major problem patients encounter when reading about health related issues is document interpretation, which limits reading comprehension and therefore negatively impacts health care. Currently, searching for medical definitions from an external source is time consuming, distracting, and negatively impacts ...

journal_title：BMC medical informatics and decision making

authors： Gradie PR,Litster M,Thomas R,Vyas J,Schiller MR

更新日期：2011-01-25 00:00:00

abstract：BACKGROUND:Problems may arise during the approval process of treatment after a compensable work injury, which include excess paperwork, delays in approving services, disputes, and allegations of over-servicing. This is perceived as undesirable for injured people, health care professionals and claims managers, and costl...

journal_title：BMC medical informatics and decision making

authors： Elbers NA,Chase R,Craig A,Guy L,Harris IA,Middleton JW,Nicholas MK,Rebbeck T,Walsh J,Willcock S,Lockwood K,Cameron ID

更新日期：2017-05-22 00:00:00

abstract：BACKGROUND:Efficient planning of hospital bed usage is a necessary condition to minimize the hospital costs. In the presented work we deal with the problem of occupancy forecasting in the scale of several months, with a focus on personnel's holiday planning. METHODS:We construct a model based on a set of recursive neu...

journal_title：BMC medical informatics and decision making

authors： Kutafina E,Bechtold I,Kabino K,Jonas SM

更新日期：2019-03-07 00:00:00

abstract：BACKGROUND:Machine learning is a branch of Artificial Intelligence that is concerned with the design and development of algorithms, and it enables today's computers to have the property of learning. Machine learning is gradually growing and becoming a critical approach in many domains such as health, education, and bus...

journal_title：BMC medical informatics and decision making

authors： Alloghani M,Aljaaf A,Hussain A,Baker T,Mustafina J,Al-Jumeily D,Khalaf M

更新日期：2019-12-12 00:00:00