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CDSS- (Clinical Decision Support System)

Enrico Capobianco
Changes and transformations enabled by Big Data have direct effects on Translational Medicine. At one end, superior precision is expected from a more data-intensive and individualized medicine, thus accelerating scientific discovery and innovation (in diagnosis, therapy, disease management etc.). At the other end, the scientific method needs to adapt to the increased diversity that data present, and this can be beneficial because potentially revealing greater details of how a disease manifests and progresses...
February 12, 2019: Journal of Translational Medicine
Savita Malhotra, Subho Chakrabarti, Ruchita Shah
Background: Using digital technology to deliver mental health care can possibly serve as a viable adjunct or alternative to mainstream services in lessening the mental health gap in a large number of resource deficient and LAMI countries. Conventional models of telepsychiatric services available so far, however, have been inadequate and ineffective, as these address only a small component of care, and rely on engagement of specialists who are grossly insufficient in numbers. Aim: To describe an innovative digital model of mental health care, enabling and empowering the non-specialists to deliver high quality mental health care in remote areas...
January 2019: Indian Journal of Psychiatry
Danica S Tuden, Elizabeth M Borycki, Andre W Kushniruk
OBJECTIVE: Understand the cognitive processes of telenurses' decision making with the use of health information systems (HIS), specifically Clinical Decision Support Systems (CDSS). In addition, identify the factors that influence how telenurses use CDSS. METHODS: Eight telenurses were recruited to manage two call scenarios in a clinical simulation. The call encounters were video recorded and the phone calls were audio recorded. The screens were also recorded to capture the HIS navigation...
2019: Studies in Health Technology and Informatics
Jeong Hoon Lee, Eun Ju Ha, Jung Hwan Baek, Miyoung Choi, Seung Eun Jung, Hwan Seok Yong
OBJECTIVE: The aims of this study were to develop a mobile app-based clinical decision support system (CDSS) for implementation of Korean clinical imaging guidelines (K-CIGs) and to assess future developments therein. MATERIALS AND METHODS: K-CIGs were implemented in the form of a web-based application ( The app containing K-CIGs consists of 53 information databases, including 10 medical subspecialties and 119 guidelines, developed by the Korean Society of Radiology (KSR) between 2015 and 2017...
February 2019: Korean Journal of Radiology: Official Journal of the Korean Radiological Society
Marie Bruun, Kristian S Frederiksen, Hanneke F M Rhodius-Meester, Marta Baroni, Le Gjerum, Juha Koikkalainen, Timo Urhema, Antti Tolonen, Mark van Gils, Tong Tong, Daniel Rueckert, Nadia Dyremos, Birgitte Bo Andersen, Anja Hviid Simonsen, Afina Lemstra, Merja Hallikainen, Sudhir Kurl, Sanna-Kaisa Herukka, Anne M Remes, Gunhild Waldemar, Hilkka Soininen, Patrizia Mecocci, Wiesje M van der Flier, Jyrki Lötjönen, Steen G Hasselbalch
BACKGROUND: Determining the underlying etiology of dementia can be challenging. Computer-based clinical decision support systems (CDSS) have the potential to provide objective comparison of data and assist clinicians. OBJECTIVES: To assess the diagnostic impact of a CDSS, the PredictND tool, for differential diagnosis of dementia in memory clinics. METHOD: In this prospective multicenter study, we recruited 779 patients with either subjective cognitive decline (n=252), mild cognitive impairment (n=219) or any type of dementia (n=274) and followed them for minimum 12 months...
January 3, 2019: Current Alzheimer Research
Yexin Liu, Yan Zhang, Di Liu, Xia Tan, Xiaofang Tang, Fan Zhang, Ming Xia, Guochun Chen, Liyu He, Letian Zhou, Xuejing Zhu, Hong Liu
BACKGROUND/AIMS: There is an increasing risk of end-stage renal disease (ESRD) among Asian people with immunoglobulin A nephropathy (IgAN). A computer-aided system for ESRD prediction in Asian IgAN patients has not been well studied. METHODS: We retrospectively reviewed biopsy-proven IgAN patients treated at the Department of Nephrology of the Second Xiangya Hospital from January 2009 to November 2013. Demographic and clinicopathological data were obtained within 1 month of renal biopsy...
2018: Kidney & Blood Pressure Research
Matthew Horrocks, Maria Michail, Aimee Aubeeluck, Nicola Wright, Richard Morriss
BACKGROUND: Suicide is a global public health concern, but it is preventable. Increased contact with primary care before the suicide or attempted suicide raises opportunities for intervention and prevention. However, suicide assessment and management are areas that many general practitioners (GPs) find particularly challenging. Previous research has indicated significant variability in how GPs understand, operationalize, and assess suicide risk, which subsequently has an impact on clinical decision making...
December 7, 2018: JMIR Research Protocols
Jiannan Liu, Chenyang Li, Jing Xu, Huanmei Wu
BACKGROUND: Colorectal Cancer (CRC) is the third leading cause of cancer death among men and women in the United States. Research has shown that the risk of CRC associates with genetic and lifestyle factors. It is possible to prevent or minimize certain CRC risks by adopting a healthy lifestyle. Existing Clinical Decision Support Systems (CDSS) mainly targeted physicians as the CDSS users. As a result, the availability of patient-oriented CDSS is limited. Our project is to develop patient-oriented CDSS for active CRC management...
December 7, 2018: BMC Medical Informatics and Decision Making
Azita Yazdani, Reza Safdari, Marjan Ghazisaeedi, Hamid Beigy, Roxana Sharifian
Introduction: In recent years, a variety of clinical decision-support systems (CDSS) have been developed to monitor the health of patients with chronic disease from far away. These systems are effective in overcoming human resource limitation and analyzing information generated by Tele-monitoring systems. These systems, however, are limited to monitoring a particular disease, which allows them to be used only in one specific disease. In reuses of these systems to monitor other diseases, we need to re-establish a new system with a new knowledge base...
October 2018: Acta Informatica Medica: AIM
Johanna Schwarz, Dominik Heider
Motivation: Clinical decision-support-systems (CDSS) have been applied in numerous fields, ranging from cancer survival towards drug resistance prediction. Nevertheless, CDSS typically have a caveat: many of them are perceived as black-boxes by non-experts and, unfortunately, the obtained scores cannot usually be interpreted as class probability estimates. In probability-focused medical applications, it is not sufficient to perform well with regards to discrimination and, consequently, various calibration methods have been developed to enable probabilistic interpretation...
November 29, 2018: Bioinformatics
Dimitrios Zikos, Nailya DeLellis
Clinical Decision Support Systems (CDSS) provide aid in clinical decision making and therefore need to take into consideration human, data interactions, and cognitive functions of clinical decision makers. The objective of this paper is to introduce a high level reference model that is intended to be used as a foundation to design successful and contextually relevant CDSS systems. The paper begins by introducing the information flow, use, and sharing characteristics in a hospital setting, and then it outlines the referential context for the model, which are clinical decisions in a hospital setting...
November 16, 2018: BMC Medical Research Methodology
S Paredes, J Henriques, T Rochar, D Mendes, P Carvalho, J Moraisl, A Bianchi, V Salcedof
The effectiveness of predictive models in supporting the Clinical Decision is closely related with their clinical interpretability, i.e.the model should provide clear information on how to reach a specific classification/decision. In fact, the development of interpretable and accurate predictive models assumes a key importance as these tools can be very useful in Clinical Decision Support Systems (CDSS). The development of those models may comprise two main perspectives; existent clinical knowledge (clinical expert knowledge, clinical guidelines, current models, etc...
July 2018: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Yung-Fu Chen, Chih-Sheng Lin, Chun-Fu Hong, D J Lee, Changming Sun, Hsuan-Hung Lin
Erectile dysfunction (ED) affects millions of men worldwide. Men with ED generally complain failure to attain or maintain an adequate erection during sexual activity. The prevalence of ED is strongly correlated with age, affecting about 40% of men at age 40 and nearly 70% at age 70. A variety of chronic diseases, including diabetes, ischemic heart disease, congestive heart failure, hypertension, depression, chronic renal failure, obstructive sleep apnea, prostate disease, gout, and sleep disorder, were reported to be associated with ED...
October 23, 2018: IEEE Journal of Biomedical and Health Informatics
Esther Melinda Mahabee-Gittens, Ashley L Merianos, Judith W Dexheimer, Gabe T Meyers, Lara Stone, Meredith Tabangin, Jane C Khoury, Judith S Gordon
BACKGROUND: Clinical decision support systems (CDSS) may facilitate caregiver tobacco screening and counseling by pediatric urgent care (UC) nurses. OBJECTIVE: This study aimed to assess the feasibility of a CDSS to address caregivers' tobacco use and child tobacco smoke exposure (TSE). METHODS: We conducted a 3-month prospective study on caregivers screened using a CDSS. Nurses used the CDSS to advise, assess, and assist caregivers to quit...
October 19, 2018: Pediatric Emergency Care
M Ghoddusi Johari, M H Dabaghmanesh, H Zare, A R Safaeian, Gh Abdollahifard
Background: Diabetes is a serious chronic disease, and its increasing prevalence is a global concern. If diabetes mellitus is left untreated, poor control of blood glucose may cause long-term complications. A big challenge encountered by clinicians is the clinical management of diabetes. Many IT-based interventions such ad CDSS have been made to improve the adherence to the standard care for chronic diseases. Objective: The aim of this study is to establish a decision support system of diabetes management based on diabetes care guidelines in order to reduce medical errors and increase adherence to guidelines...
September 2018: Journal of Biomedical Physics & Engineering
Savino Spadaro, Dan Stieper Karbing, Francesca Dalla Corte, Tommaso Mauri, Federico Moro, Antonio Gioia, Carlo Alberto Volta, Stephen Edward Rees
PURPOSE: To assess whether a clinical decision support system (CDSS) suggests PS and FIO2 maintaining appropriate breathing effort, and minimizing FIO2 . MATERIALS: Prospective, cross-over study in PS ventilated ICU patients. Over support (150% baseline) and under support (50% baseline) were applied by changing PS (15 patients) or PEEP (8 patients). CDSS advice was followed. Tension time index of inspiratory muscles (TTies), respiratory and metabolic variables were measured...
December 2018: Journal of Critical Care
Nicole Hechte, Antje Wulff, Michael Marschollek
A wide range of Clinical Decision Support Systems (CDSS) have been developed. These CDSS are based on decision models, which normally have a knowledge- or data-driven approach. In this work a structured development of potential hybrid approaches was realized by the assessment of decision models and identification of their advantages and disadvantages. For the assessment of different decision models, eight criteria were identified and three of them were chosen as main criteria for CDSS: transparency, learning aptitude and handling of uncertain and vague knowledge...
2018: Studies in Health Technology and Informatics
Olakotan Olufisayo, Maryati Mohd Yusof, Sharifa Ezat Wan Puteh
Despite the widespread use of clinical decision support systems with its alert function, there has been an increase in medical errors, adverse events as well as issues regarding patient safety, quality and efficiency. The appropriateness of CDSS must be properly evaluated by ensuring that CDSS provides clinicians with useful information at the point of care. Inefficient clinical workflow affects clinical processes; hence, it is necessary to identify processes in the healthcare system that affect provider's workflow...
2018: Studies in Health Technology and Informatics
Eda Bilici, George Despotou, Theodoros N Arvanitis
Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions...
January 2018: Digital Health
Clara Schaarup, Louise Bilenberg Pape-Haugaard, Ole Kristian Hejlesen
BACKGROUND: Chronic wounds such as diabetic foot ulcers, venous leg ulcers, and pressure ulcers are a massive burden to health care facilities. Many randomized controlled trials on different wound care elements have been conducted and published in the Cochrane Library, all of which have only a low evidential basis. Thus, health care professionals are forced to rely on their own experience when making decisions regarding wound care. To progress from experience-based practice to evidence-based wound care practice, clinical decision support systems (CDSS) that help health care providers with decision-making in a clinical workflow have been developed...
June 21, 2018: JMIR diabetes
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