Software Tools for Systematic Literature Review in Medicine: A Review and Feature Analysis (Preprint)

2021 ◽  
Author(s):  
Kathryn Cowie ◽  
Asad Rahmatullah ◽  
Nicole Hardy ◽  
Karl Holub ◽  
Kevin Kallmes

BACKGROUND Systematic reviews (SRs) are central to evaluating therapies but have high costs in terms of both time and money. Many software tools exist to assist with SRs, but most tools do not support the full process, and transparency and replicability of SR depends on performing and presenting evidence according to established best practices. OBJECTIVE In order to provide a basis for comparing and selecting between software tools that support SR, we performed a feature-by-feature comparison of SR tools. METHODS We searched for SR tools by reviewing any such tool listed the Systematic Review Toolbox, previous reviews of SR tools, and qualitative Google searching. We included all SR tools that were currently functional, and require no coding and excluded reference managers, desktop applications, and statistical software. The list of features to assess was populated by combining all features assessed in four previous reviews of SR tools; we also added five features (Manual Addition, Screening Automation, Dual Extraction, Living review, Public outputs) that were independently noted as best practices or enhancements of transparency/replicability. Then, two reviewers assigned binary “present/absent” assessments to all SR tools with respect to all features, and a third reviewer adjudicated all disagreements. RESULTS Of 49 SR tools found, 27 were excluded, leaving 22 for assessment. Twenty-eight features were assessed across 6 classes, and the inter-observer agreement was 86.46%. DistillerSR, EPPI-Reviewer Web, and Nested Knowledge support the most features (24/28, 86%), followed by Covidence, SRDB.PRO, SysRev (20/28, 71%). Six tools support fewer than half of all features assessed: SyRF, Data Abstraction Assistant, SWIFT-review, SR-Accelerator, RobotReviewer, and COVID-NMA. Notably, only 9 of 22 tools (41%) support direct search, only four (18%) offer dual extraction, and only 9 (41%) offer living/updatable reviews. CONCLUSIONS DistillerSR, EPPI-Reviewer Web, and Nested Knowledge each offer a high density of SR-focused web-based tools. By transparent comparison and discussion regarding SR tool functionality, the medical community can both choose among existing software offerings and note the areas of growth needed, most notably in the support of living reviews.

COVID ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 645-665
Author(s):  
Olubukola Adenubi ◽  
Oluwawemimo Adebowale ◽  
Hezekiah Adesokan ◽  
Abimbola Oloye ◽  
Noah Bankole ◽  
...  

This study evaluated the knowledge, attitude and perception (KAP) towards COVID-19 pandemic control among veterinarians in Nigeria. A nation-wide web-based cross-sectional survey was conducted. Information on KAP towards the COVID-19 pandemic was gathered (April 23 and May 31, 2020) and multivariate logistic regression was performed to identify associated factors. A total of 368 veterinarians participated in the study. The majority of respondents were males (72.8%), between the ages of 30–39 years (39.7%). Generally, respondents displayed a good level of knowledge about COVID-19 (72.4% ± 9.9%, range 44.1–91.2%), while the general attitude level was poor (65.4% ± 10.8, range 35.3–94.1%). Various determinants for good attitude among respondents were: if they were above 60 years old (aOR = 4.49, 95% CI: 1.379–14.594, p = 0.013), possessed postgraduate qualification (aOR = 1.63, 95 CI: 1.045–2.553, p = 0.031), worked over 30 years post DVM (aOR = 5.63, 95% CI: 1.966–16.100, p = 0.001), had household members between five and 10 (aOR = 1.73, 95% CI: 1.130–2.641, p = 0.012), and if respondents’ residence was on total lockdown (aOR = 1.66, 95% CI: 1.070–2.590, p = 0.024). The pandemic had moderate impacts on social, financial and physical status of the participants. Stricter policy measures and educational programs should be implemented to keep veterinarians and the populace informed about the best practices recommended for COVID-19 management.


2011 ◽  
pp. 3173-3178
Author(s):  
Marc Holzer ◽  
Tony Carrizales ◽  
Younhee Kim

The opportunities that arise from the practice of digital government continue to increase. Public managers responsible for adopting and implementing such new practices will be searching for existing best practices to incorporate into their respective communities. They may choose to rely on their information and communication technology (ICT) departments to develop necessary digital government applications, but an appealing option for public managers is to familiarize themselves with the most recent digital government applications through Web-based courses. Online education eliminates distances, allows for flexible scheduling and can incorporate current best practices of electronic-government on a timely basis. Public managers play a critical role in the development of digital government initiatives (Halachmi, 2004; Heeks, 1999; Ho, 2002; Melitski, 2003; Weare, Musso & Hale, 1999). Although public managers can refer to numerous individuals within government municipalities, in the case of digital government, the chief administrative officer (CAO) is often the key individual in deciding the direction of government initiatives. By completing Web-based courses, CAOs can assess and strategically plan for effective and efficient digital government in their communities. Melitski (2003) argues that there is a need for public mangers that are “familiar with both IT and the programmatic goals and missions of public organizations” (p. 389). With respect to implementing digital citizen participation in government, Holzer, Melitski, Rho, and Schwester (2004) state, as their primary recommendation, “governments should work harder to identify, study, and implement best practices” (p. 28). The means to study such best practices, however, have generally been scarce, and the literature has been limited to specialized e-government reports and articles. But Web-based courses now offer the means for a CAO or any other public manager to study digital government practices and theories in a more effective and convenient manner.


2013 ◽  
Vol 2 (1) ◽  
pp. 11-25 ◽  
Author(s):  
Elizabeth Sternke ◽  
Nicholas Burrus ◽  
Virginia Daggett ◽  
Laurie Plue ◽  
Katherine Carlson ◽  
...  

Despite many advances in stroke care treatment, there is substantial room for improvement in quality of care for stroke patients. In an attempt to disseminate up-to-date quality information and evidence-based best practices of stroke care, the Veterans Health Administration (VHA)and the VHA Stroke QUERI implemented an innovative web-based toolkit tailored for providers and program planners interested in improving stroke care quality. This study evaluated the VA Stroke QUERI Toolkit to determine its most useful aspects and those that require improvement. In-depth qualitative interviews (n = 48) were conducted with a geographically dispersed sample of clinicians and program planners throughout the VHA system. Findings suggest the Stroke QUERI toolkit was perceived as an effective, efficient and user-friendly site but knowledge of the toolkit continues to be initiated and shared mainly through individuals and small groups. To achieve greater impact a comprehensive set of strategies designed to encourage broader uptake is required.


2019 ◽  
Vol 52 (01) ◽  
pp. 134-143 ◽  
Author(s):  
Bernard O'Keeffe ◽  
Shraddha Rout

AbstractLower limb amputations form a considerable number with 5,436,000 Indians having locomotor disability. Most members of this group are young, active earning males. The major cause of amputation is trauma. Hence, this population must be rehabilitated with priority, and best concerted efforts must be made by the medical community. In this article, the authors present available modern technologies in India and share best practices from their experience of treating Indian amputees for the past 20 years. The objective is to demonstrate to the medical community the optimal outcomes that can be achieved and help them make correct decisions on behalf of patients and their families. The article discusses history of prostheses, how to select optimal amputation level, preamputation preparation, determinants of good outcomes, preprosthetic preparation, components of prosthesis, their function and significance, rehabilitation process and guidelines, prescription criteria, and also special considerations such as multiple amputees or children.


Author(s):  
Ketan Paranjape ◽  
Michiel Schinkel ◽  
Richard D Hammer ◽  
Bo Schouten ◽  
R S Nannan Panday ◽  
...  

Abstract Objectives As laboratory medicine continues to undergo digitalization and automation, clinical laboratorians will likely be confronted with the challenges associated with artificial intelligence (AI). Understanding what AI is good for, how to evaluate it, what are its limitations, and how it can be implemented are not well understood. With a survey, we aimed to evaluate the thoughts of stakeholders in laboratory medicine on the value of AI in the diagnostics space and identify anticipated challenges and solutions to introducing AI. Methods We conducted a web-based survey on the use of AI with participants from Roche’s Strategic Advisory Network that included key stakeholders in laboratory medicine. Results In total, 128 of 302 stakeholders responded to the survey. Most of the participants were medical practitioners (26%) or laboratory managers (22%). AI is currently used in the organizations of 15.6%, while 66.4% felt they might use it in the future. Most had an unsure attitude on what they would need to adopt AI in the diagnostics space. High investment costs, lack of proven clinical benefits, number of decision makers, and privacy concerns were identified as barriers to adoption. Education in the value of AI, streamlined implementation and integration into existing workflows, and research to prove clinical utility were identified as solutions needed to mainstream AI in laboratory medicine. Conclusions This survey demonstrates that specific knowledge of AI in the medical community is poor and that AI education is much needed. One strategy could be to implement new AI tools alongside existing tools.


Author(s):  
Yuli Levtov

This chapter explores algorithmic music and the software tools used to create it from the perspective of media that allow it to be distributed to mass audiences, such as smartphone apps, web-based experiences, and dedicated software packages. Different types of listener input and interaction for various algorithmic music formats are analysed, and examples of each are given. Advantages and disadvantages of various distribution platforms, both present and historic, are explored, and critical reaction to this wide body of work is also reviewed. Conclusions are drawn that the field is still relatively nascent, with advances in consumer technology being a main driver for innovation in this area of music distribution and creation.


Author(s):  
Charlie C. L. Wang ◽  
Matthew M. F. Yuen ◽  
Yu Wang

Abstract Internet technology in particular opens up another domain for building future CAD/CAM environment. This environment will be a global, network-centric environment with various members providing different software tools, manufacturing facilities, and analysis services for distributed design and fabrication. Web-based CAD tools play a prominent role in the environment. Two kinds of clients can be used to develop a web-based CAD tool now, one is “thin” client, and another is “fat” client. This paper compares the advantage of “thin” and “fat” client, and explains the advantage of using low-cost, configurable, CAD components.


2019 ◽  
Vol 111 (2) ◽  
pp. 256-265 ◽  
Author(s):  
Diana M Thomas ◽  
Nicholas Clark ◽  
Dusty Turner ◽  
Cynthia Siu ◽  
Tanya M Halliday ◽  
...  

ABSTRACT Background Regression to the mean (RTM) is a statistical phenomenon where initial measurements of a variable in a nonrandom sample at the extreme ends of a distribution tend to be closer to the mean upon a second measurement. Unfortunately, failing to account for the effects of RTM can lead to incorrect conclusions on the observed mean difference between the 2 repeated measurements in a nonrandom sample that is preferentially selected for deviating from the population mean of the measured variable in a particular direction. Study designs that are susceptible to misattributing RTM as intervention effects have been prevalent in nutrition and obesity research. This field often conducts secondary analyses of existing intervention data or evaluates intervention effects in those most at risk (i.e., those with observations at the extreme ends of a distribution). Objectives To provide best practices to avoid unsubstantiated conclusions as a result of ignoring RTM in nutrition and obesity research. Methods We outlined best practices for identifying whether RTM is likely to be leading to biased inferences, using a flowchart that is available as a web-based app at https://dustyturner.shinyapps.io/DecisionTreeMeanRegression/. We also provided multiple methods to quantify the degree of RTM. Results Investigators can adjust analyses to include the RTM effect, thereby plausibly removing its biasing influence on estimating the true intervention effect. Conclusions The identification of RTM and implementation of proper statistical practices will help advance the field by improving scientific rigor and the accuracy of conclusions. This trial was registered at clinicaltrials.gov as NCT00427193.


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