scholarly journals Development of a Scalable Tele-Monitoring Platform based on the Clinical Decision Support Systems

2020 ◽  
Author(s):  
azita yazdani ◽  
Reza Safdari ◽  
Roxana Sharifian ◽  
maryam zahmatkeshan
Keyword(s):  
Health Care ◽  
Performance Evaluation ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Monitoring Systems ◽  
Tele Monitoring

Abstract Background: One of the most important types of information systems that play important role today in providing quality health care services are clinical decision support systems (CDSSs). These systems are effective in overcoming human resource constraint and intelligent analysis of information generated by Tele-monitoring systems. In spite of the many advantages of this architectures, these are single-purpose, meaning that only the CDSS of a disease is located on them. If we want to use the same model of architecture in the decision-making process of another disease, all the components of this architecture should be redevelopment with a new CDSS, which is time-consuming and costly. Due to the increasing demand for health information technology at low cost and mobile access in the health care industry, in this article, a scalable software platform(Patient Tele monitoring: PATEL) based on SOA for implementing and use different CDSSs on a common platform, for use in Tele-monitoring Systems, was created.Implementation: To develop PATEL platform, the component-based software development approach and hybrid programming approach to implementing various components used. In the evaluation phase of the proposed platform, the case study, accuracy and performance evaluation (transmission delays, patient data fetch, parsing overhead and inference time) used.Results: The results of the case study evaluation confirmed the scalability and interoperability between CDSSs on the platform. Based on performance evaluation, the proposed platform has responded to 89% of the requests in less than one second. Also, based on accuracy evaluation, the platform presented in this article was successful in diagnosing 91.6% of the cases.Conclusion: The proposed platform can support CDSSs of various diseases simultaneously and provides the necessary scalability to add a new CDSS. Tele-monitoring systems will be capable of service by connecting to this platform. Using this infrastructure is expected to be a lot of duplication in the implementation of tele-monitoring systems based CDSSs will be reduced.

scholarly journals Evaluation of User-Interface Alert Displays for Clinical Decision Support Systems for Sepsis

2018 ◽  
Vol 38 (4) ◽  
pp. 46-54 ◽  
Author(s):  
Devida Long ◽  
Muge Capan ◽  
Susan Mascioli ◽  
Danielle Weldon ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
User Interface ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Care Providers

BACKGROUND Hospitals are increasingly turning to clinical decision support systems for sepsis, a life-threatening illness, to provide patient-specific assessments and recommendations to aid in evidence-based clinical decision-making. Lack of guidelines on how to present alerts has impeded optimization of alerts, specifically, effective ways to differentiate alerts while highlighting important pieces of information to create a universal standard for health care providers. OBJECTIVE To gain insight into clinical decision support systems–based alerts, specifically targeting nursing interventions for sepsis, with a focus on behaviors associated with and perceptions of alerts, as well as visual preferences. METHODS An interactive survey to display a novel user interface for clinical decision support systems for sepsis was developed and then administered to members of the nursing staff. RESULTS A total of 43 nurses participated in 2 interactive survey sessions. Participants preferred alerts that were based on an established treatment protocol, were presented in a pop-up format, and addressed the patient’s clinical condition rather than regulatory guidelines. CONCLUSIONS The results can be used in future research to optimize electronic medical record alerting and clinical practice workflow to support the efficient, effective, and timely delivery of high-quality care to patients with sepsis. The research also may advance the knowledge base of what information health care providers want and need to improve the health and safety of their patients.

Bridging challenges of clinical decision support systems with a semantic approach. A case study on breast cancer

2013 ◽  
Vol 34 (14) ◽  
pp. 1758-1768 ◽  
Author(s):  
Eider Sanchez ◽  
Carlos Toro ◽  
Arkaitz Artetxe ◽  
Manuel Graña ◽  
Cesar Sanin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Semantic Approach

scholarly journals Cost and economic benefit of clinical decision support systems for cardiovascular disease prevention: a community guide systematic review

2017 ◽  
Vol 24 (3) ◽  
pp. 669-676 ◽  
Author(s):  
Verughese Jacob ◽  
Anilkrishna B Thota ◽  
Sajal K Chattopadhyay ◽  
Gibril J Njie ◽  
Krista K Proia ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Costs And Benefits ◽  
The Cost

Objective: This review evaluates costs and benefits associated with acquiring, implementing, and operating clinical decision support systems (CDSSs) to prevent cardiovascular disease (CVD). Materials and Methods: Methods developed for the Community Guide were used to review CDSS literature covering the period from January 1976 to October 2015. Twenty-one studies were identified for inclusion. Results: It was difficult to draw a meaningful estimate for the cost of acquiring and operating CDSSs to prevent CVD from the available studies (n = 12) due to considerable heterogeneity. Several studies (n = 11) indicated that health care costs were averted by using CDSSs but many were partial assessments that did not consider all components of health care. Four cost-benefit studies reached conflicting conclusions about the net benefit of CDSSs based on incomplete assessments of costs and benefits. Three cost-utility studies indicated inconsistent conclusions regarding cost-effectiveness based on a conservative $50,000 threshold. Discussion: Intervention costs were not negligible, but specific estimates were not derived because of the heterogeneity of implementation and reporting metrics. Expected economic benefits from averted health care cost could not be determined with confidence because many studies did not fully account for all components of health care. Conclusion: We were unable to conclude whether CDSSs for CVD prevention is either cost-beneficial or cost-effective. Several evidence gaps are identified, most prominently a lack of information about major drivers of cost and benefit, a lack of standard metrics for the cost of CDSSs, and not allowing for useful life of a CDSS that generally extends beyond one accounting period.

scholarly journals Interoperability of clinical decision-support systems and electronic health records using archetypes: A case study in clinical trial eligibility

2013 ◽  
Vol 46 (4) ◽  
pp. 676-689 ◽  
Author(s):  
Mar Marcos ◽  
Jose A. Maldonado ◽  
Begoña Martínez-Salvador ◽  
Diego Boscá ◽  
Montserrat Robles
Keyword(s):  
Clinical Trial ◽  
Decision Support ◽  
Electronic Health Records ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Health Records

scholarly journals Understanding the Role of Pharmacometrics‐Based Clinical Decision Support Systems in Pediatric Patient Management: A Case Study Using Lyv Software

2021 ◽  
Vol 61 (S1) ◽  
Author(s):  
Praneeth Jarugula ◽  
Sarah Scott ◽  
Vijay Ivaturi ◽  
Andreas Noack ◽  
Brady S. Moffett ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Pediatric Patient ◽  
Clinical Decision Support ◽  
Patient Management ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision

Clinical Decision Support Systems in Nursing

2010 ◽  
pp. 1056-1070
Author(s):  
Dawn Dowding ◽  
Rebecca Randell ◽  
Natasha Mitchell ◽  
Rebecca Foster ◽  
Valerie Lattimer ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Roles And Responsibilities ◽  
Technical Factors ◽  
The Impact

Increasingly, new and extended roles and responsibilities for nurses are being supported through the introduction of clinical decision support systems (CDSS). This chapter provides an overview of research on nurses’ use of CDSS, considers the impact of CDSS on nurse decision making and patient outcomes, and explores the socio-technical factors that impact the use of CDSS. In addition to summarising previous research, both on nurses’ use of CDSS and on use of CDSS more generally, the chapter presents the results of a multi-site case study that explored how CDSS are used by nurses in practice in a range of contexts. The chapter takes a socio-technical approach, exploring the barriers and facilitators to effective CDSS use at a level of the technology itself, the ways people work, and the organisations in which they operate.

Clinical Decision Support Systems in Nursing

2009 ◽  
pp. 26-40 ◽  
Author(s):  
Dawn Dowding ◽  
Rebecca Randell ◽  
Natasha Mitchell ◽  
Rebecca Foster ◽  
Valerie Lattimer ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Roles And Responsibilities ◽  
Technical Factors ◽  
The Impact

Increasingly, new and extended roles and responsibilities for nurses are being supported through the introduction of clinical decision support systems (CDSS). This chapter provides an overview of research on nurses’ use of CDSS, considers the impact of CDSS on nurse decision making and patient outcomes, and explores the socio-technical factors that impact the use of CDSS. In addition to summarising previous research, both on nurses’ use of CDSS and on use of CDSS more generally, the chapter presents the results of a multi-site case study that explored how CDSS are used by nurses in practice in a range of contexts. The chapter takes a socio-technical approach, exploring the barriers and facilitators to effective CDSS use at a level of the technology itself, the ways people work, and the organisations in which they operate.

scholarly journals Clinical Decision Support Systems for Pressure Ulcer Management: Systematic Review

10.2196/21621 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e21621
Author(s):  
Sabrina Magalhaes Araujo ◽  
Paulino Sousa ◽  
Inês Dutra
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Pressure Ulcer ◽  
Clinical Decision Making ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision

Background The clinical decision-making process in pressure ulcer management is complex, and its quality depends on both the nurse's experience and the availability of scientific knowledge. This process should follow evidence-based practices incorporating health information technologies to assist health care professionals, such as the use of clinical decision support systems. These systems, in addition to increasing the quality of care provided, can reduce errors and costs in health care. However, the widespread use of clinical decision support systems still has limited evidence, indicating the need to identify and evaluate its effects on nursing clinical practice. Objective The goal of the review was to identify the effects of nurses using clinical decision support systems on clinical decision making for pressure ulcer management. Methods The systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. The search was conducted in April 2019 on 5 electronic databases: MEDLINE, SCOPUS, Web of Science, Cochrane, and CINAHL, without publication date or study design restrictions. Articles that addressed the use of computerized clinical decision support systems in pressure ulcer care applied in clinical practice were included. The reference lists of eligible articles were searched manually. The Mixed Methods Appraisal Tool was used to assess the methodological quality of the studies. Results The search strategy resulted in 998 articles, 16 of which were included. The year of publication ranged from 1995 to 2017, with 45% of studies conducted in the United States. Most addressed the use of clinical decision support systems by nurses in pressure ulcers prevention in inpatient units. All studies described knowledge-based systems that assessed the effects on clinical decision making, clinical effects secondary to clinical decision support system use, or factors that influenced the use or intention to use clinical decision support systems by health professionals and the success of their implementation in nursing practice. Conclusions The evidence in the available literature about the effects of clinical decision support systems (used by nurses) on decision making for pressure ulcer prevention and treatment is still insufficient. No significant effects were found on nurses' knowledge following the integration of clinical decision support systems into the workflow, with assessments made for a brief period of up to 6 months. Clinical effects, such as outcomes in the incidence and prevalence of pressure ulcers, remain limited in the studies, and most found clinically but nonstatistically significant results in decreasing pressure ulcers. It is necessary to carry out studies that prioritize better adoption and interaction of nurses with clinical decision support systems, as well as studies with a representative sample of health care professionals, randomized study designs, and application of assessment instruments appropriate to the professional and institutional profile. In addition, long-term follow-up is necessary to assess the effects of clinical decision support systems that can demonstrate a more real, measurable, and significant effect on clinical decision making. Trial Registration PROSPERO International Prospective Register of Systematic Reviews CRD42019127663; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=127663

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