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Clinical decision-making, knowledge support systems, and theory

Section edited by Paul Taylor

This section aims to publish studies on the development, implementation and evaluation of clinical decision support systems. The section also accepts articles on the theoretical support of clinical decision-making (including shared-decision making), decision analysis, and decision aids.

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  1. Electronic health records (EHRs) with embedded clinical decision support systems (CDSSs) have the potential to improve healthcare delivery. This study was conducted to explore merits, features, and desiderata ...

    Authors: Ramzi Shawahna

    Citation: BMC Medical Informatics and Decision Making 2019 19:216

    Content type: Research article

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  2. Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models...

    Authors: Rawan AlSaad, Qutaibah Malluhi, Ibrahim Janahi and Sabri Boughorbel

    Citation: BMC Medical Informatics and Decision Making 2019 19:214

    Content type: Research Article

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  3. Smart pumps have been widely adopted but there is limited evidence to understand and support their use in pediatric populations. Our objective was to assess whether smart pumps are effective at reducing medica...

    Authors: Kristin R. Melton, Kristen Timmons, Kathleen E. Walsh, Jareen K. Meinzen-Derr and Eric Kirkendall

    Citation: BMC Medical Informatics and Decision Making 2019 19:213

    Content type: Research article

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  4. Clinical predictive tools quantify contributions of relevant patient characteristics to derive likelihood of diseases or predict clinical outcomes. When selecting predictive tools for implementation at clinica...

    Authors: Mohamed Khalifa, Farah Magrabi and Blanca Gallego

    Citation: BMC Medical Informatics and Decision Making 2019 19:207

    Content type: Research article

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  5. Radiotherapy is a standard treatment option for breast cancer, but it may lead to significant late morbidity, including radiation heart damage. Breast irradiation performed individually in the supine or prone ...

    Authors: Ferenc Rárosi, Krisztina Boda, Zsuzsanna Kahán and Zoltán Varga

    Citation: BMC Medical Informatics and Decision Making 2019 19:204

    Content type: Research article

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  6. Premenopausal breast cancer patients are at risk of treatment-related infertility. Many patients do not receive sufficient fertility information before treatment. As such, our team developed and alpha tested the

    Authors: Brittany Speller, Kelly Metcalfe, Erin D. Kennedy, Marcia Facey, Ellen Greenblatt, Adena S. Scheer, Ellen Warner, Anil Abraham Joy, Frances C. Wright and Nancy N. Baxter

    Citation: BMC Medical Informatics and Decision Making 2019 19:203

    Content type: Research article

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  7. In radiotherapy, minimizing the time between referral and start of treatment (waiting time) is important to possibly mitigate tumor growth and avoid psychological distress in cancer patients. Radiotherapy pre-...

    Authors: Bruno Vieira, Derya Demirtas, Jeroen B. van de Kamer, Erwin W. Hans and Wim van Harten

    Citation: BMC Medical Informatics and Decision Making 2019 19:199

    Content type: Research article

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  8. Type 2 Diabetes Mellitus (T2DM) is a chronic disease closely related to personal life style. Therefore, achieving effective self-management is one of the most important ways to control it. There is evidence th...

    Authors: Xiaojia Wang, Linglan He, Keyu Zhu, Shanshan Zhang, Ling Xin, Weiqun Xu and Yuxiang Guan

    Citation: BMC Medical Informatics and Decision Making 2019 19:197

    Content type: Research article

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  9. Every case of breast cancer is unique, and treatment must be personalized to incorporate a woman’s values and preferences. We developed an individually-tailored mobile patient education application for women w...

    Authors: Kirk D. Wyatt, Sarah M. Jenkins, Matthew F. Plevak, Marcia R. Venegas Pont and Sandhya Pruthi

    Citation: BMC Medical Informatics and Decision Making 2019 19:196

    Content type: Research article

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  10. Case-based reasoning is a proven method that relies on learned cases from the past for decision support of a new case. The accuracy of such a system depends on the applied similarity measure, which quantifies ...

    Authors: Christian Karmen, Matthias Gietzelt, Petra Knaup-Gregori and Matthias Ganzinger

    Citation: BMC Medical Informatics and Decision Making 2019 19:195

    Content type: Research article

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  11. A pharmacogenomic clinical decision support tool (PGx-CDS) for thiopurine medications can help physicians incorporate pharmacogenomic results into prescribing decisions by providing up-to-date, real-time decis...

    Authors: Khoa A. Nguyen, Himalaya Patel, David A. Haggstrom, Alan J. Zillich, Thomas F. Imperiale and Alissa L. Russ

    Citation: BMC Medical Informatics and Decision Making 2019 19:194

    Content type: Research article

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  12. Chronic pain is one of the most common complaints of cancer patients. There are many pharmacological and non-pharmacological treatment modalities used for the treatment of pain. Nonetheless, non-pharmacologica...

    Authors: Ender Sir and Gül Didem Batur Sir

    Citation: BMC Medical Informatics and Decision Making 2019 19:191

    Content type: Research article

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  13. Shared decision making (SDM) is a systematic approach aimed at improving patient involvement in preference-sensitive health care decisions. Choosing between surgical or non-surgical treatment for lumbar disc h...

    Authors: Stina Brogård Andersen, Mikkel Ø. Andersen, Leah Y. Carreon, Angela Coulter and Karina Dahl Steffensen

    Citation: BMC Medical Informatics and Decision Making 2019 19:190

    Content type: Research article

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  14. The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, ...

    Authors: Rosanne Janssens, Isabelle Huys, Eline van Overbeeke, Chiara Whichello, Sarah Harding, Jürgen Kübler, Juhaeri Juhaeri, Antonio Ciaglia, Steven Simoens, Hilde Stevens, Meredith Smith, Bennett Levitan, Irina Cleemput, Esther de Bekker-Grob and Jorien Veldwijk

    Citation: BMC Medical Informatics and Decision Making 2019 19:189

    Content type: Research article

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  15. Many European countries have recently implemented national rare disease plans. Although the network is strengthening, especially on the macro and meso levels, patients still go a long way through healthcare sy...

    Authors: Ana Babac, Verena von Friedrichs, Svenja Litzkendorf, Jan Zeidler, Kathrin Damm and J.-Matthias Graf von der Schulenburg

    Citation: BMC Medical Informatics and Decision Making 2019 19:188

    Content type: Research article

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  16. An individualized approach using shared decision-making (SDM) and goal setting is a person-centred strategy that may facilitate prioritization of treatment options. SDM has not been adopted extensively in clin...

    Authors: Catherine H. Yu, Calvin Ke, Aleksandra Jovicic, Susan Hall and Sharon E. Straus

    Citation: BMC Medical Informatics and Decision Making 2019 19:186

    Content type: Research article

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  17. The incidence of cardiac implantable electronic device infection (CIEDI) is low and usually belongs to the typical imbalanced dataset. We sought to describe our experience on the management of the imbalanced C...

    Authors: Xiang-Fei Feng, Ling-Chao Yang, Li-Zhuang Tan and Yi-Gang Li

    Citation: BMC Medical Informatics and Decision Making 2019 19:185

    Content type: Research article

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  18. Kidney allocation is a multi-criteria and complex decision-making problem, which should also consider ethical issues in addition to the medical aspects. Leading countries in this field use a point scoring syst...

    Authors: Nasrin Taherkhani, Mohammad Mehdi Sepehri, Shadi Shafaghi and Toktam Khatibi

    Citation: BMC Medical Informatics and Decision Making 2019 19:182

    Content type: Research article

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  19. Even though a high demand for sector spanning communication exists, so far no eHealth platform for nephrology is established within Germany. This leads to insufficient communication between medical providers a...

    Authors: L. Pape, N. Schneider, T. Schleef, U. Junius-Walker, H. Haller, R. Brunkhorst, N. Hellrung, H. U. Prokosch, B. Haarbrandt, M. Marschollek and M. Schiffer

    Citation: BMC Medical Informatics and Decision Making 2019 19:176

    Content type: Study protocol

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  20. To evaluate the effectiveness of audit and communication strategies to reduce diagnostic errors made by clinicians.

    Authors: Julie Abimanyi-Ochom, Shalika Bohingamu Mudiyanselage, Max Catchpool, Marnie Firipis, Sithara Wanni Arachchige Dona and Jennifer J. Watts

    Citation: BMC Medical Informatics and Decision Making 2019 19:174

    Content type: Research article

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  21. Thrombophilia testing is frequently ordered in the inpatient setting despite its limited impact on clinical decision-making and unreliable results in the setting of acute thrombosis or ongoing anticoagulation....

    Authors: Henry Kwang, Eric Mou, Ilana Richman, Andre Kumar, Caroline Berube, Rajani Kaimal, Neera Ahuja, Stephanie Harman, Tyler Johnson, Neil Shah, Ronald Witteles, Robert Harrington, Lisa Shieh and Jason Hom

    Citation: BMC Medical Informatics and Decision Making 2019 19:167

    Content type: Research article

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  22. Most breast cancer patients undergoing mastectomy are candidates for breast reconstruction. Deciding about breast reconstruction is complex and the preference-sensitive nature of this decision requires an appr...

    Authors: Jacqueline A. ter Stege, Leonie A. E. Woerdeman, Daniela E. E. Hahn, Martine A. van Huizum, Frederieke H. van Duijnhoven, Jacobien M. Kieffer, Valesca P. Retèl, Kerry A. Sherman, Arjen J. Witkamp, Hester S. A. Oldenburg and Eveline M. A. Bleiker

    Citation: BMC Medical Informatics and Decision Making 2019 19:165

    Content type: Study protocol

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  23. To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computeriz...

    Authors: Giuseppe Fico, Liss Hernanzez, Jorge Cancela, Arianna Dagliati, Lucia Sacchi, Antonio Martinez-Millana, Jorge Posada, Lidia Manero, Jose Verdú, Andrea Facchinetti, Manuel Ottaviano, Konstantia Zarkogianni, Konstantina Nikita, Leif Groop, Rafael Gabriel-Sanchez, Luca Chiovato…

    Citation: BMC Medical Informatics and Decision Making 2019 19:163

    Content type: Research article

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  24. There is growing interest in sensor-based assessment of upper limb tremor in multiple sclerosis and other movement disorders. However, previously such assessments have not been found to offer any improvement o...

    Authors: David G. Western, Simon A. Neild, Rosemary Jones and Angela Davies-Smith

    Citation: BMC Medical Informatics and Decision Making 2019 19:162

    Content type: Research article

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  25. Healthcare professionals’ adherence to guidelines on child protection is not self-evident. This study assessed the effects of a computerised support tool on child healthcare professionals’ adherence to the sev...

    Authors: Annemieke A. J. Konijnendijk, Magda M. Boere-Boonekamp, Maria E. Haasnoot and Ariana Need

    Citation: BMC Medical Informatics and Decision Making 2019 19:161

    Content type: Research article

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  26. Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on g...

    Authors: T. Bakker, J. E. Klopotowska, S. Eslami, D. W. de Lange, R. van Marum, H. van der Sijs, E. de Jonge, D. A. Dongelmans, N. F. de Keizer and A. Abu-Hanna

    Citation: BMC Medical Informatics and Decision Making 2019 19:159

    Content type: Study protocol

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  27. Collective intelligence, facilitated by information technology or manual techniques, refers to the collective insight of groups working on a task and has the potential to generate more accurate information or ...

    Authors: Kate Radcliffe, Helena C. Lyson, Jill Barr-Walker and Urmimala Sarkar

    Citation: BMC Medical Informatics and Decision Making 2019 19:158

    Content type: Research article

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  28. Female BRCA1 and BRCA2 mutation carriers have an increased lifetime risk of developing breast and/or ovarian cancer. Hence, they face the difficult decision of choosing a preventive strategy such as risk-reducing...

    Authors: Lisa Krassuski, Vera Vennedey, Stephanie Stock and Sibylle Kautz-Freimuth

    Citation: BMC Medical Informatics and Decision Making 2019 19:154

    Content type: Research article

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  29. Although complex machine learning models are commonly outperforming the traditional simple interpretable models, clinicians find it hard to understand and trust these complex models due to the lack of intuitio...

    Authors: Radwa Elshawi, Mouaz H. Al-Mallah and Sherif Sakr

    Citation: BMC Medical Informatics and Decision Making 2019 19:146

    Content type: Research article

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  30. Approximately 20% of deaths in the US each year are attributable to smoking, yet current practices in the recording of this health risk in electronic health records (EHRs) have not led to discernable changes i...

    Authors: Ellen L. Palmer, John Higgins, Saeed Hassanpour, James Sargent, Christina M. Robinson, Jennifer A. Doherty and Tracy Onega

    Citation: BMC Medical Informatics and Decision Making 2019 19:143

    Content type: Research article

    Published on:

    The Research article to this article has been published in BMC Medical Informatics and Decision Making 2019 19:141

  31. Usage of structured fields in Electronic Health Records (EHRs) to ascertain smoking history is important but fails in capturing the nuances of smoking behaviors. Knowledge of smoking behaviors, such as pack ye...

    Authors: Ellen L. Palmer, Saeed Hassanpour, John Higgins, Jennifer A. Doherty and Tracy Onega

    Citation: BMC Medical Informatics and Decision Making 2019 19:141

    Content type: Research article

    Published on:

    The Research article to this article has been published in BMC Medical Informatics and Decision Making 2019 19:143

  32. Medication therapy management (MTM) is a service, most commonly provided by pharmacists, intended to identify and resolve medication therapy problems (MTPs) to enhance patient care. MTM is typically documented...

    Authors: Margie E. Snyder, Heather Jaynes, Stephanie A. Gernant, Julie DiIulio, Laura G. Militello, William R. Doucette, Omolola A. Adeoye and Alissa L. Russ

    Citation: BMC Medical Informatics and Decision Making 2019 19:135

    Content type: Research article

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  33. A 2016 study standardized the definition of stillbirths. It estimated the rate as a proportion of total births. A 2015 paper addressed the problem of disability-adjusted life-years (DALY) for stillbirths. Ther...

    Authors: Chander Kant

    Citation: BMC Medical Informatics and Decision Making 2019 19:133

    Content type: Debate

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  34. Patient decision aids (PDAs) can support the treatment decision making process and empower patients to take a proactive role in their treatment pathway while using a shared decision-making (SDM) approach makin...

    Authors: Anshu Ankolekar, Ben G. L. Vanneste, Esther Bloemen-van Gurp, Joep G. van Roermund, Evert J. van Limbergen, Kees van de Beek, Tom Marcelissen, Victor Zambon, Matthias Oelke, Andre Dekker, Cheryl Roumen, Philippe Lambin, Adriana Berlanga and Rianne Fijten

    Citation: BMC Medical Informatics and Decision Making 2019 19:130

    Content type: Technical advance

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  35. Decisional conflict is associated with decision quality and may affect decision outcomes. In the health sciences literature, the Decisional Conflict Scale is widely used to measure decisional conflict, yet lim...

    Authors: Rachel A. Pozzar, Donna L. Berry and Fangxin Hong

    Citation: BMC Medical Informatics and Decision Making 2019 19:124

    Content type: Research article

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  36. The autoverification system for coagulation consists of a series of rules that allow normal data to be released without manual verification. With new advances in medical informatics, the laboratory information...

    Authors: Zhongqing Wang, Cheng Peng, Hui Kang, Xia Fan, Runqing Mu, Liping Zhou, Miao He and Bo Qu

    Citation: BMC Medical Informatics and Decision Making 2019 19:123

    Content type: Research article

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  37. Many healthcare databases have been routinely collected over the past decades, to support clinical practice and administrative services. However, their secondary use for research is often hindered by restricte...

    Authors: João Rafael Almeida, Rosa Gini, Giuseppe Roberto, Peter Rijnbeek and José Luís Oliveira

    Citation: BMC Medical Informatics and Decision Making 2019 19:121

    Content type: Software

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  38. Most of readmission prediction models are implemented at the time of patient discharge. However, interventions which include an early in-hospital component are critical in reducing readmissions and improving p...

    Authors: Natalie Flaks-Manov, Maxim Topaz, Moshe Hoshen, Ran D. Balicer and Efrat Shadmi

    Citation: BMC Medical Informatics and Decision Making 2019 19:118

    Content type: Research article

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  39. Data mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers s...

    Authors: Khanh Vu, Rebecca A. Clark, Colin Bellinger, Graham Erickson, Alvaro Osornio-Vargas, Osmar R. Zaïane and Yan Yuan

    Citation: BMC Medical Informatics and Decision Making 2019 19:112

    Content type: Research article

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  40. Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) ena...

    Authors: T. Katrien J. Groenhof, Folkert W. Asselbergs, Rolf H. H. Groenwold, Diederick E. Grobbee, Frank L. J. Visseren and Michiel L. Bots

    Citation: BMC Medical Informatics and Decision Making 2019 19:108

    Content type: Research article

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  41. Evidence-Based Medicine (EBM) is the process of systematically locating, searching, evaluating, and using contemporaneous research findings as the basis for clinical decision making. The systematic review show...

    Authors: Teshager Worku, Meron Yeshitila, Tilaye Feto, Shiferaw Leta, Frehiwot Mesfin and Haymanot Mezmur

    Citation: BMC Medical Informatics and Decision Making 2019 19:107

    Content type: Research article

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  42. Inappropriate prescribing of psychotropics is a persistent and prevalent problem in nursing homes. The present study compared inappropriate prescribing of psychotropics in nursing homes 16 years apart with pre...

    Authors: Jan Schjøtt and Jörg Aßmus

    Citation: BMC Medical Informatics and Decision Making 2019 19:102

    Content type: Research article

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  43. Multiple predictive scores using Electronic Patient Record data have been developed for hospitalised patients at risk of clinical deterioration. Methods used to select patient centred variables for inclusion i...

    Authors: James Malycha, Timothy Bonnici, David A. Clifton, Guy Ludbrook, J. Duncan Young and Peter J. Watkinson

    Citation: BMC Medical Informatics and Decision Making 2019 19:98

    Content type: Research article

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  44. Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historic...

    Authors: Shaker El-Sappagh, Farman Ali, Abdeltawab Hendawi, Jun-Hyeog Jang and Kyung-Sup Kwak

    Citation: BMC Medical Informatics and Decision Making 2019 19:97

    Content type: Research article

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  45. 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-...

    Authors: Szu-Min Peng, Han-Mo Chiu, Hsiao-Hsuan Jen, Chen-Yang Hsu, Sam Li-Sheng Chen, Sherry Yueh-Hsia Chiu, Amy Ming-Fang Yen, Jean Ching-Yuan Fann, Yi-Chia Lee and Hsiu-Hsi Chen

    Citation: BMC Medical Informatics and Decision Making 2019 19:94

    Content type: Research article

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  46. While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will rem...

    Authors: Lars Müller, Rashmi Gangadharaiah, Simone C. Klein, James Perry, Greg Bernstein, David Nurkse, Dustin Wailes, Rishi Graham, Robert El-Kareh, Sanjay Mehta, Staal A. Vinterbo and Eliah Aronoff-Spencer

    Citation: BMC Medical Informatics and Decision Making 2019 19:93

    Content type: Database

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  47. Maintaining physical fitness is a crucial component of the therapeutic process for patients with cardiovascular disease (CVD). Despite the known importance of being physically active, patient adherence to exer...

    Authors: Kristina Livitckaia, Vassilis Koutkias, Evangelia Kouidi, Mark van Gils, Nikolaos Maglaveras and Ioanna Chouvarda

    Citation: BMC Medical Informatics and Decision Making 2019 19:92

    Content type: Research article

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  48. Many clinical concepts are standardized under a categorical and hierarchical taxonomy such as ICD-10, ATC, etc. These taxonomic clinical concepts provide insight into semantic meaning and similarity among clin...

    Authors: Zheng Jia, Xudong Lu, Huilong Duan and Haomin Li

    Citation: BMC Medical Informatics and Decision Making 2019 19:91

    Content type: Research article

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  49. Shared decision making is associated with improved patient outcomes in radiation oncology. Our study aimed to capture how shared decision-making practices–namely, communicating potential harms and benefits and...

    Authors: Laurie Pilote, Luc Côté, Selma Chipenda Dansokho, Émilie Brouillard, Anik M. C. Giguère, France Légaré, Roland Grad and Holly O. Witteman

    Citation: BMC Medical Informatics and Decision Making 2019 19:84

    Content type: Research article

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  50. While doctors should analyze a large amount of electronic medical record (EMR) data to conduct clinical research, the analyzing process requires information technology (IT) skills, which is difficult for most ...

    Authors: Tong Ruan, Yueqi Huang, Xuli Liu, Yuhang Xia and Ju Gao

    Citation: BMC Medical Informatics and Decision Making 2019 19:82

    Content type: Research article

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