scholarly journals PICO Portal (product review)

2021 ◽  
Vol 42 (3) ◽  
Author(s):  
Joel Minion ◽  
Oluwaseun Egunsola ◽  
Liza Mastikhina ◽  
Brenlea Farkas ◽  
Mark Hofmeister ◽  
...  
Keyword(s):  
Systematic Review ◽  
Language Processing ◽  
Review Process ◽  
Health Assessment ◽  
Management Tool ◽  
Screening Process ◽  
Review Management ◽  
Review Team ◽  
The University ◽  
User Friendly

PICO Portal is a Web-based systematic review management tool launched in September 2020 to better facilitate collaborative knowledge synthesis in biomedical research. Most notably, it uses machine learning and Natural Language Processing algorithms to continuously refine the screening process by analyzing decisions as made by the review team. PICO Portal was evaluated by researchers with the Health Assessment Technology team at the University of Calgary, who routinely undertake PICO-based systematic reviews, currently using an in-house manual system. The team appreciated many aspects of PICO Portal and felt it held considerable promise to better support the review process. At the same time, they found it wasn’t as user-friendly as expected and would benefit from additional refinement if it is to appeal to a wider range of users, particularly those less familiar with the systematic review process.

scholarly journals Use of Decision Support Tools to Empower Pregnant Women: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Elin Ngo ◽  
Maria Bich-Thuy Truong ◽  
Hedvig Nordeng
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Pregnant Women ◽  
Management Tool ◽  
Control Group ◽  
Decision Support Tools ◽  
Patient Centered ◽  
Review Management ◽  
Support Tools ◽  
Health Related

BACKGROUND Women face many health-related decisions during pregnancy. Digitalization, new technology, and a greater focus on empowering patients have driven the development of patient-centered decision support tools. OBJECTIVE This systematic review provides an overview of studies investigating the effect of patient-centered decision support tools for pregnant women. METHODS We searched 5 online databases, MEDLINE, EMBASE, Web of Science, PsycINFO, and Scopus, from inception to December 1, 2019. Two independent researchers screened titles, abstracts, and full-texts against the inclusion criteria. All studies investigating the effect of patient-centered decision support tools for health-related issues among pregnant women were included. Study characteristics and results were extracted using the review management tool Rayyan and analyzed according to topic, type of decision support tools, control group, outcome measurements, and results. RESULTS The 25 eligible studies covered a range of health topics, including prenatal screening (n=10), gestational diabetes and weight gain (n=7), lifestyle (n=3), blood pressure and preeclampsia (n=2), depression (n=1), asthma (n=1), and psychological well-being (n=1). In general, the use of decision support tools increased women's knowledge, and recording symptoms enhanced satisfaction with maternity care. CONCLUSIONS The opportunities created by digitalization and technology should be used to develop innovative patient-centered decision support tools tailored to support pregnant women. Effect on clinical outcomes should be documented.

scholarly journals Use of Decision Support Tools to Empower Pregnant Women: Systematic Review

10.2196/19436 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e19436
Author(s):  
Elin Ngo ◽  
Maria Bich-Thuy Truong ◽  
Hedvig Nordeng
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Pregnant Women ◽  
Management Tool ◽  
Control Group ◽  
Decision Support Tools ◽  
Patient Centered ◽  
Review Management ◽  
Support Tools ◽  
Health Related

Background Women face many health-related decisions during pregnancy. Digitalization, new technology, and a greater focus on empowering patients have driven the development of patient-centered decision support tools. Objective This systematic review provides an overview of studies investigating the effect of patient-centered decision support tools for pregnant women. Methods We searched 5 online databases, MEDLINE, EMBASE, Web of Science, PsycINFO, and Scopus, from inception to December 1, 2019. Two independent researchers screened titles, abstracts, and full-texts against the inclusion criteria. All studies investigating the effect of patient-centered decision support tools for health-related issues among pregnant women were included. Study characteristics and results were extracted using the review management tool Rayyan and analyzed according to topic, type of decision support tools, control group, outcome measurements, and results. Results The 25 eligible studies covered a range of health topics, including prenatal screening (n=10), gestational diabetes and weight gain (n=7), lifestyle (n=3), blood pressure and preeclampsia (n=2), depression (n=1), asthma (n=1), and psychological well-being (n=1). In general, the use of decision support tools increased women's knowledge, and recording symptoms enhanced satisfaction with maternity care. Conclusions The opportunities created by digitalization and technology should be used to develop innovative patient-centered decision support tools tailored to support pregnant women. Effect on clinical outcomes should be documented.

Success Strategies: Implementing the Professional Performance Review Process for School-Based Speech-Language Pathologists

2009 ◽  
Vol 19 (1) ◽  
pp. 4-9
Author(s):  
Jill Parmenter ◽  
Sheryl Amaral ◽  
Julia Jackson
Keyword(s):  
Review Process ◽  
Successful Implementation ◽  
Speech Language Pathologists ◽  
Self Advocacy ◽  
Professional Performance ◽  
Performance Review ◽  
Roles And Responsibilities ◽  
Speech Language Pathologist ◽  
School Based ◽  
Review Management

Abstract The Professional Performance Review Process for School-Based Speech-Language Pathologists (PPRP) (ASHA, 2006) was developed in response to the need for a performance review tool that fits school district requirements for performance review management while addressing the specific roles and responsibilities of a school-based speech-language pathologist (ASHA, 2006). This article will examine the purpose and components of the PPRP. A description of its use as a tool for self-advocacy will be discussed. Strategies for successful implementation of the PPRP will be explained using insight from speech-language pathologists and other professionals familiar with the PPRP.

A Tracer Study of ICT Graduate Students at Mzuzu University, Malawi

Mousaion ◽  
2019 ◽  
Vol 36 (3) ◽  
Author(s):  
Chimango Nyasulu ◽  
Winner Chawinga ◽  
George Chipeta
Keyword(s):  
Language Processing ◽  
Mobile Application ◽  
First Century ◽  
Application Development ◽  
Job Requirements ◽  
Level Of Satisfaction ◽  
Information And Communication ◽  
Quantitative Design ◽  
The Right ◽  
The University

Governments the world over are increasingly challenging universities to produce human resources with the right skills sets and knowledge required to drive their economies in this twenty-first century. It therefore becomes important for universities to produce graduates that bring tangible and meaningful contributions to the economies. Graduate tracer studies are hailed to be one of the ways in which universities can respond and reposition themselves to the actual needs of the industry. It is against this background that this study was conducted to establish the relevance of the Department of Information and Communication Technology at Mzuzu University to the Malawian economy by systematically investigating occupations of its former students after graduating from the University. The study adopted a quantitative design by distributing an online-based questionnaire with predominantly closed-ended questions. The study focused on three key objectives: to identify key employing sectors of ICT graduates, to gauge the relevance of the ICT programme to its former students’ jobs and businesses, and to establish the level of satisfaction of the ICT curriculum from the perspectives of former ICT graduates. The key findings from the study are that the ICT programme is relevant to the industry. However, some respondents were of the view that the curriculum should be strengthened by revising it through an addition of courses such as Mobile Application Development, Machine Learning, Natural Language Processing, Data Mining, and LINUX Administration to keep abreast with the ever-changing ICT trends and job requirements. The study strongly recommends the need for regular reviews of the curriculum so that it is continually responding to and matches the needs of the industry.

WikiRecs primary care: developing rapid recommendations for primary care through effective collaboration between systematic review and guideline teams

2018 ◽  
Vol 68 (suppl 1) ◽  
pp. bjgp18X697085
Author(s):  
Trudy Bekkering ◽  
Bert Aertgeerts ◽  
Ton Kuijpers ◽  
Mieke Vermandere ◽  
Jako Burgers ◽  
...  
Keyword(s):  
Systematic Review ◽  
Primary Care ◽  
Clinical Practice ◽  
Primary Care Physicians ◽  
Urinary Stones ◽  
Care Practice ◽  
Supporting Evidence ◽  
Supervised Exercise ◽  
Review Team ◽  
New Evidence

BackgroundThe WikiRecs evidence summaries and recommendations for clinical practice are developed using trustworthy methods. The process is triggered by studies that may potentially change practice, aiming at implementing new evidence into practice fast.AimTo share our first experiences developing WikiRecs for primary care and to reflect on the possibilities and pitfalls of this method.MethodIn March 2017, we started developing WikiRecs for primary health care to speed up the process of making potentially practice-changing evidence in clinical practice. Based on a well-structured question a systematic review team summarises the evidence using the GRADE approach. Subsequently, an international panel of primary care physicians, methodological experts and patients formulates recommendations for clinical practice. The patient representatives are involved as full guideline panel members. The final recommendations and supporting evidence are disseminated using various platforms, including MAGICapp and scientific journals.ResultsWe are developing WikiRecs on two topics: alpha-blockers for urinary stones and supervised exercise therapy for intermittent claudication. We did not face major problems but will reflect on issues we had to solve so far. We anticipate having the first WikiRecs for primary care available at the end of 2017.ConclusionThe WikiRecs process is a promising method — that is still evolving — to rapidly synthesise and bring new evidence into primary care practice, while adhering to high quality standards.

scholarly journals Machine Learning in Medical Emergencies: a Systematic Review and Analysis

2021 ◽  
Vol 45 (10) ◽  
Author(s):  
Inés Robles Mendo ◽  
Gonçalo Marques ◽  
Isabel de la Torre Díez ◽  
Miguel López-Coronado ◽  
Francisco Martín-Rodríguez
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Language Processing ◽  
Emergency Services ◽  
Clinical Decision ◽  
Quality Of Healthcare ◽  
The Other ◽  
Other Hand ◽  
Increasing Demand ◽  
Commercial Applications

AbstractDespite the increasing demand for artificial intelligence research in medicine, the functionalities of his methods in health emergency remain unclear. Therefore, the authors have conducted this systematic review and a global overview study which aims to identify, analyse, and evaluate the research available on different platforms, and its implementations in healthcare emergencies. The methodology applied for the identification and selection of the scientific studies and the different applications consist of two methods. On the one hand, the PRISMA methodology was carried out in Google Scholar, IEEE Xplore, PubMed ScienceDirect, and Scopus. On the other hand, a review of commercial applications found in the best-known commercial platforms (Android and iOS). A total of 20 studies were included in this review. Most of the included studies were of clinical decisions (n = 4, 20%) or medical services or emergency services (n = 4, 20%). Only 2 were focused on m-health (n = 2, 10%). On the other hand, 12 apps were chosen for full testing on different devices. These apps dealt with pre-hospital medical care (n = 3, 25%) or clinical decision support (n = 3, 25%). In total, half of these apps are based on machine learning based on natural language processing. Machine learning is increasingly applicable to healthcare and offers solutions to improve the efficiency and quality of healthcare. With the emergence of mobile health devices and applications that can use data and assess a patient's real-time health, machine learning is a growing trend in the healthcare industry.

scholarly journals Applying natural language processing and machine learning techniques to patient experience feedback: a systematic review

2021 ◽  
Vol 28 (1) ◽  
pp. e100262
Author(s):  
Mustafa Khanbhai ◽  
Patrick Anyadi ◽  
Joshua Symons ◽  
Kelsey Flott ◽  
Ara Darzi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Social Media ◽  
Natural Language Processing ◽  
Natural Language ◽  
Patient Experience ◽  
Language Processing ◽  
Performance Metrics ◽  
Free Text ◽  
Patient Feedback

ObjectivesUnstructured free-text patient feedback contains rich information, and analysing these data manually would require a lot of personnel resources which are not available in most healthcare organisations.To undertake a systematic review of the literature on the use of natural language processing (NLP) and machine learning (ML) to process and analyse free-text patient experience data.MethodsDatabases were systematically searched to identify articles published between January 2000 and December 2019 examining NLP to analyse free-text patient feedback. Due to the heterogeneous nature of the studies, a narrative synthesis was deemed most appropriate. Data related to the study purpose, corpus, methodology, performance metrics and indicators of quality were recorded.ResultsNineteen articles were included. The majority (80%) of studies applied language analysis techniques on patient feedback from social media sites (unsolicited) followed by structured surveys (solicited). Supervised learning was frequently used (n=9), followed by unsupervised (n=6) and semisupervised (n=3). Comments extracted from social media were analysed using an unsupervised approach, and free-text comments held within structured surveys were analysed using a supervised approach. Reported performance metrics included the precision, recall and F-measure, with support vector machine and Naïve Bayes being the best performing ML classifiers.ConclusionNLP and ML have emerged as an important tool for processing unstructured free text. Both supervised and unsupervised approaches have their role depending on the data source. With the advancement of data analysis tools, these techniques may be useful to healthcare organisations to generate insight from the volumes of unstructured free-text data.

scholarly journals An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolfazl Mohammadbeigi ◽  
Salman Khazaei ◽  
Hamidreza Heidari ◽  
Azadeh Asgarian ◽  
Shahram Arsangjang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Factors ◽  
Land Cover ◽  
Cutaneous Leishmaniasis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Eligibility Criteria ◽  
Screening Process ◽  
Old World ◽  
Review Study

AbstractObjectivesLeishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.ContentA systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.Summary and outlookA total of 827 relevant records in 2015–2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.ConclusionsTemperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

scholarly journals Prioritising recommendations following analyses of adverse events in healthcare: a systematic review

2020 ◽  
Vol 9 (4) ◽  
pp. e000843
Author(s):  
Kelly Bos ◽  
Maarten J van der Laan ◽  
Dave A Dongelmans
Keyword(s):  
Systematic Review ◽  
Adverse Events ◽  
Data Extraction ◽  
Data Sources ◽  
Cochrane Library ◽  
High Quality ◽  
Data Synthesis ◽  
Study Selection ◽  
Personal Opinion ◽  
User Friendly

PurposeThe purpose of this systematic review was to identify an appropriate method—a user-friendly and validated method—that prioritises recommendations following analyses of adverse events (AEs) based on objective features.Data sourcesThe electronic databases PubMed/MEDLINE, Embase (Ovid), Cochrane Library, PsycINFO (Ovid) and ERIC (Ovid) were searched.Study selectionStudies were considered eligible when reporting on methods to prioritise recommendations.Data extractionTwo teams of reviewers performed the data extraction which was defined prior to this phase.Results of data synthesisEleven methods were identified that are designed to prioritise recommendations. After completing the data extraction, none of the methods met all the predefined criteria. Nine methods were considered user-friendly. One study validated the developed method. Five methods prioritised recommendations based on objective features, not affected by personal opinion or knowledge and expected to be reproducible by different users.ConclusionThere are several methods available to prioritise recommendations following analyses of AEs. All these methods can be used to discuss and select recommendations for implementation. None of the methods is a user-friendly and validated method that prioritises recommendations based on objective features. Although there are possibilities to further improve their features, the ‘Typology of safety functions’ by de Dianous and Fiévez, and the ‘Hierarchy of hazard controls’ by McCaughan have the most potential to select high-quality recommendations as they have only a few clearly defined categories in a well-arranged ordinal sequence.

Sign in / Sign up

Export Citation Format

Share Document