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Cancer Treatment Reviews Jan 2016Conducting regular multidisciplinary team (MDT) meetings requires significant investment of time and finances. It is thus important to assess the empirical benefits of... (Review)
Review
BACKGROUND
Conducting regular multidisciplinary team (MDT) meetings requires significant investment of time and finances. It is thus important to assess the empirical benefits of such practice. A systematic review was conducted to evaluate the literature regarding the impact of MDT meetings on patient assessment, management and outcomes in oncology settings.
METHODS
Relevant studies were identified by searching OVID MEDLINE, PsycINFO, and EMBASE databases from 1995 to April 2015, using the keywords: multidisciplinary team meeting* OR multidisciplinary discussion* OR multidisciplinary conference* OR case review meeting* OR multidisciplinary care forum* OR multidisciplinary tumour board* OR case conference* OR case discussion* AND oncology OR cancer. Studies were included if they assessed measurable outcomes, and used a comparison group and/or a pre- and post-test design.
RESULTS
Twenty-seven articles met inclusion criteria. There was limited evidence for improved survival outcomes of patients discussed at MDT meetings. Between 4% and 45% of patients discussed at MDT meetings experienced changes in diagnostic reports following the meeting. Patients discussed at MDT meetings were more likely to receive more accurate and complete pre-operative staging, and neo-adjuvant/adjuvant treatment. Quality of studies was affected by selection bias and the use of historical cohorts impacted study quality.
CONCLUSIONS
MDT meetings impact upon patient assessment and management practices. However, there was little evidence indicating that MDT meetings resulted in improvements in clinical outcomes. Future research should assess the impact of MDT meetings on patient satisfaction and quality of life, as well as, rates of cross-referral between disciplines.
Topics: Chemotherapy, Adjuvant; Cost-Benefit Analysis; Disease Management; Humans; Interdisciplinary Communication; Medical Audit; Medicine; Neoadjuvant Therapy; Neoplasm Staging; Neoplasms; Patient Care Planning; Patient Care Team; Preoperative Care; Prospective Studies; Radiotherapy, Adjuvant; Retrospective Studies; Survival Analysis; Treatment Outcome
PubMed: 26643552
DOI: 10.1016/j.ctrv.2015.11.007 -
Journal of Medical Internet Research Feb 2015Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management.
OBJECTIVE
We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management ("mAdherence"), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers.
METHODS
We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users.
RESULTS
In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%).
CONCLUSIONS
There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.
Topics: Cardiovascular Diseases; Chronic Disease; Diabetes Mellitus; Disease Management; Humans; Lung Diseases; Patient Compliance; Randomized Controlled Trials as Topic; Telemedicine; Text Messaging; Treatment Outcome
PubMed: 25803266
DOI: 10.2196/jmir.3951 -
Journal of Medical Internet Research May 2021Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides good performance in statistical tasks, such as text classification or sentiment mining.
OBJECTIVE
The primary aim of this systematic review was to summarize and characterize, in methodological and technical terms, studies that used machine learning and NLP techniques for mental health. The secondary aim was to consider the potential use of these methods in mental health clinical practice.
METHODS
This systematic review follows the PRISMA (Preferred Reporting Items for Systematic Review and Meta-analysis) guidelines and is registered with PROSPERO (Prospective Register of Systematic Reviews; number CRD42019107376). The search was conducted using 4 medical databases (PubMed, Scopus, ScienceDirect, and PsycINFO) with the following keywords: machine learning, data mining, psychiatry, mental health, and mental disorder. The exclusion criteria were as follows: languages other than English, anonymization process, case studies, conference papers, and reviews. No limitations on publication dates were imposed.
RESULTS
A total of 327 articles were identified, of which 269 (82.3%) were excluded and 58 (17.7%) were included in the review. The results were organized through a qualitative perspective. Although studies had heterogeneous topics and methods, some themes emerged. Population studies could be grouped into 3 categories: patients included in medical databases, patients who came to the emergency room, and social media users. The main objectives were to extract symptoms, classify severity of illness, compare therapy effectiveness, provide psychopathological clues, and challenge the current nosography. Medical records and social media were the 2 major data sources. With regard to the methods used, preprocessing used the standard methods of NLP and unique identifier extraction dedicated to medical texts. Efficient classifiers were preferred rather than transparent functioning classifiers. Python was the most frequently used platform.
CONCLUSIONS
Machine learning and NLP models have been highly topical issues in medicine in recent years and may be considered a new paradigm in medical research. However, these processes tend to confirm clinical hypotheses rather than developing entirely new information, and only one major category of the population (ie, social media users) is an imprecise cohort. Moreover, some language-specific features can improve the performance of NLP methods, and their extension to other languages should be more closely investigated. However, machine learning and NLP techniques provide useful information from unexplored data (ie, patients' daily habits that are usually inaccessible to care providers). Before considering It as an additional tool of mental health care, ethical issues remain and should be discussed in a timely manner. Machine learning and NLP methods may offer multiple perspectives in mental health research but should also be considered as tools to support clinical practice.
Topics: Artificial Intelligence; Data Management; Humans; Machine Learning; Mental Health; Natural Language Processing
PubMed: 33944788
DOI: 10.2196/15708 -
Journal of Medical Internet Research Jun 2021The influence of social media among adolescent peer groups can be a powerful change agent. (Review)
Review
BACKGROUND
The influence of social media among adolescent peer groups can be a powerful change agent.
OBJECTIVE
Our scoping review aimed to elucidate the ways in which social media use among adolescent peers influences eating behaviors.
METHODS
A scoping review of the literature of articles published from journal inception to 2019 was performed by searching PubMed (ie, MEDLINE), Embase, CINAHL, PsycINFO, Web of Science, and other databases. The review was conducted in three steps: (1) identification of the research question and clarification of criteria using the population, intervention, comparison, and outcome (PICO) framework; (2) selection of articles from the literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; and (3) charting and summarizing information from selected articles. PubMed's Medical Subject Headings (MeSH) and Embase's Emtree subject headings were reviewed along with specific keywords to construct a comprehensive search strategy. Subject headings and keywords were based on adolescent age groups, social media platforms, and eating behaviors. After screening 1387 peer-reviewed articles, 37 articles were assessed for eligibility. Participant age, gender, study location, social media channels utilized, user volume, and content themes related to findings were extracted from the articles.
RESULTS
Six articles met the final inclusion criteria. A final sample size of 1225 adolescents (aged 10 to 19 years) from the United States, the United Kingdom, Sweden, Norway, Denmark, Portugal, Brazil, and Australia were included in controlled and qualitative studies. Instagram and Facebook were among the most popular social media platforms that influenced healthful eating behaviors (ie, fruit and vegetable intake) as well as unhealthful eating behaviors related to fast food advertising. Online forums served as accessible channels for eating disorder relapse prevention among youth. Social media influence converged around four central themes: (1) visual appeal, (2) content dissemination, (3) socialized digital connections, and (4) adolescent marketer influencers.
CONCLUSIONS
Adolescent peer influence in social media environments spans the spectrum of healthy eating (ie, pathological) to eating disorders (ie, nonpathological). Strategic network-driven approaches should be considered for engaging adolescents in the promotion of positive dietary behaviors.
Topics: Adolescent; Data Management; Diet, Healthy; Feeding Behavior; Humans; Peer Influence; Social Media; United States
PubMed: 34081018
DOI: 10.2196/19697 -
Minerva Stomatologica Dec 2019The management of anxiety and fear of patients experiencing medical treatment is always a major issue. Dentistry is a branch of medicine that is daily in managing these...
INTRODUCTION
The management of anxiety and fear of patients experiencing medical treatment is always a major issue. Dentistry is a branch of medicine that is daily in managing these problems, especially in the case of pediatric patients. Odontophobia can be managed in different ways, and the purpose of this study is to eventually review which methods are currently accepted and which are the most effective.
EVIDENCE ACQUISITION
The literature analysis was conducted on a number of articles, suitably skimmed, after a first research, obtained from the most common scientific databases. The number of works included in the review is 28.
EVIDENCE SYNTHESIS
From the RCTs evaluated we could highlight that there are different methods in the literature, equally effective and certainly conditioned by the systemic condition of the patient. Another chapter instead turns out to be that linked to the management of the syndromic patient.
CONCLUSIONS
It is clear that there are different methods and equally different ways to manage our patients in the event of non-cooperation in the case of dental care. In addition to proper management by the clinician, in the literature methods linked to audiovisual distractions, hypnosis or pharmacological methods that produce conscious sedation are effectively reported.
Topics: Child; Data Management; Dental Anxiety; Dental Care; Fear; Humans; Syndrome
PubMed: 32052621
DOI: 10.23736/S0026-4970.19.04288-2 -
Maturitas Jun 2019Wearable trackers as research or clinical tools are increasingly used to support the care of older adults, due to their practicality in self-monitoring and potential to...
BACKGROUND
Wearable trackers as research or clinical tools are increasingly used to support the care of older adults, due to their practicality in self-monitoring and potential to promote healthy lifestyle behaviours. However, there is limited understanding of appropriate data collection and analysis methods in different contexts.
AIM
To summarise evidence on wearable data generation and management in older adults, focusing on physical activity (PA), electrocardiogram (ECG), and vital signs monitoring. In addition to examine the accuracy and utility of wearable trackers in the care of older people.
METHODS
A systematic search of CINAHL, MEDLINE, PubMed and a manual search were conducted. Twenty studies on the use of wearable trackers by older adults met the inclusion criteria.
RESULTS
Methodological designs for data collection and analysis were heterogeneous, with diverse definitions of wear and no-wear time, the number and type of valid days, and proprietary algorithms. Wearable trackers had adequate accuracy for measuring step counts, moderate to vigorous physical activity (MVPA), ECG and heart rate (HR), but not for respiratory rate. Participants reported ease of use and had high-level adherence over daily long-term use. Moreover, wearable trackers encouraged users to increase their daily level of physical activity and decrease waist circumference, facilitating atrial fibrillation (AF) diagnoses and predicting length of stay.
CONCLUSION
Wearable trackers are multi-dimensional technologies offering a viable and promising approach for sustained and scaled monitoring of older people's health. Frameworks and/or guidelines, including standards for the design, data management and application of use specifically for older adults, are required to enhance validity and reliability.
Topics: Aged; Data Analysis; Data Collection; Electrocardiography; Exercise; Fitness Trackers; Heart Rate; Humans; Motivation; Patient Compliance
PubMed: 30910279
DOI: 10.1016/j.maturitas.2019.03.012 -
JMIR MHealth and UHealth Jul 2022COVID-19 digital contact-tracing apps were created to assist public health authorities in curbing the pandemic. These apps require users' permission to access specific...
BACKGROUND
COVID-19 digital contact-tracing apps were created to assist public health authorities in curbing the pandemic. These apps require users' permission to access specific functions on their mobile phones, such as geolocation, Bluetooth or Wi-Fi connections, or personal data, to work correctly. As these functions have privacy repercussions, it is essential to establish how contact-tracing apps respect users' privacy.
OBJECTIVE
This study aimed to systematically map existing contact-tracing apps and evaluate the permissions required and their privacy policies. Specifically, we evaluated the type of permissions, the privacy policies' readability, and the information included in them.
METHODS
We used custom Google searches and existing lists of contact-tracing apps to identify potentially eligible apps between May 2020 and November 2021. We included contact-tracing or exposure notification apps with a Google Play webpage from which we extracted app characteristics (eg, sponsor, number of installs, and ratings). We used Exodus Privacy to systematically extract the number of permissions and classify them as dangerous or normal. We computed a Permission Accumulated Risk Score representing the threat level to the user's privacy. We assessed the privacy policies' readability and evaluated their content using a 13-item checklist, which generated a Privacy Transparency Index. We explored the relationships between app characteristics, Permission Accumulated Risk Score, and Privacy Transparency Index using correlations, chi-square tests, or ANOVAs.
RESULTS
We identified 180 contact-tracing apps across 152 countries, states, or territories. We included 85.6% (154/180) of apps with a working Google Play page, most of which (132/154, 85.7%) had a privacy policy document. Most apps were developed by governments (116/154, 75.3%) and totaled 264.5 million installs. The average rating on Google Play was 3.5 (SD 0.7). Across the 154 apps, we identified 94 unique permissions, 18% (17/94) of which were dangerous, and 30 trackers. The average Permission Accumulated Risk Score was 22.7 (SD 17.7; range 4-74, median 16) and the average Privacy Transparency Index was 55.8 (SD 21.7; range 5-95, median 55). Overall, the privacy documents were difficult to read (median grade level 12, range 7-23); 67% (88/132) of these mentioned that the apps collected personal identifiers. The Permission Accumulated Risk Score was negatively associated with the average App Store ratings (r=-0.20; P=.03; 120/154, 77.9%) and Privacy Transparency Index (r=-0.25; P<.001; 132/154, 85.7%), suggesting that the higher the risk to one's data, the lower the apps' ratings and transparency index.
CONCLUSIONS
Many contact-tracing apps were developed covering most of the planet but with a relatively low number of installs. Privacy-preserving apps scored high in transparency and App Store ratings, suggesting that some users appreciate these apps. Nevertheless, privacy policy documents were difficult to read for an average audience. Therefore, we recommend following privacy-preserving and transparency principles to improve contact-tracing uptake while making privacy documents more readable for a wider public.
Topics: COVID-19; Contact Tracing; Data Management; Humans; Mobile Applications; Policy; Privacy
PubMed: 35709334
DOI: 10.2196/35195 -
Journal of Medical Systems Sep 2018Electronic health records (EHRs) have emerged among health information technology as "meaningful use" to improve the quality and efficiency of healthcare, and health... (Review)
Review
Electronic health records (EHRs) have emerged among health information technology as "meaningful use" to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records' use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012-10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities.
Topics: Electronic Health Records; Humans; Meaningful Use; Population Health
PubMed: 30269237
DOI: 10.1007/s10916-018-1075-6 -
Critical Care Medicine May 2021Anaphylaxis is a rapidly progressive life-threatening syndrome manifesting as pruritus, urticaria, angioedema, bronchospasm and shock. The goal of this synthetic review...
OBJECTIVES
Anaphylaxis is a rapidly progressive life-threatening syndrome manifesting as pruritus, urticaria, angioedema, bronchospasm and shock. The goal of this synthetic review is to provide a practical, updated approach to the evaluation and management of this disorder and associated complications.
DATA SOURCES
A MEDLINE search was conducted with the MeSH of anaphylaxis, anaphylactic reaction, anaphylactic shock, refractory anaphylaxis and subheadings of diagnosis, classification, epidemiology, complications and pharmacology. The level of evidence supporting an intervention was evaluated based on the availability of randomized studies, expert opinion, case studies, reviews, practice parameters and other databases (including Cochrane).
STUDY SELECTION
Selected publications describing anaphylaxis, clinical trials, diagnosis, mechanisms, risk factors and management were retrieved (reviews, guidelines, clinical trials, case series) and their bibliographies were also reviewed to identify relevant publications.
DATA EXTRACTION
Data from the relevant publications were reviewed, summarized and the information synthesized.
DATA SYNTHESIS
This is a synthetic review and the data obtained from a literature review was utilized to describe current trends in the diagnosis and management of the patient with anaphylaxis with a special emphasis on newer evolving concepts of anaphylaxis endotypes and phenotypes, management of refractory anaphylaxis in the ICU setting and review of therapeutic options for the elderly patient, or the complicated patient with severe cardiorespiratory complications. Most of the recommendations come from practice parameters, case studies or expert opinions, with a dearth of randomized trials to support specific interventions.
CONCLUSION
Anaphylaxis is a rapidly progressive life-threatening disorder. The critical care physician needs to be familiar with the diagnosis, differential diagnosis, evaluation, and management of anaphylaxis. Skilled intervention in ICUs may be required for the patient with complicated, severe, or refractory anaphylaxis.
Topics: Anaphylaxis; Anti-Inflammatory Agents; Bronchodilator Agents; Critical Care; Glucocorticoids; Humans; Intensive Care Units; Life Support Care
PubMed: 33653974
DOI: 10.1097/CCM.0000000000004893 -
Pharmacoepidemiology and Drug Safety Sep 2015To identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. (Review)
Review
PURPOSE
To identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data.
METHODS
Systematic literature searches were conducted in PubMed and Embase complemented by a manual literature search. We included pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing the study.
RESULTS
We found 3083 articles by the systematic searches and an additional 176 by the manual search. After full-text screening of 75 articles, 22 were selected for final inclusion. The number of databases used per study ranged from 2 to 17 (median = 4.0). Most studies used a cohort design (82%) instead of a case-control design (18%). Logistic regression was most often used for individual-level analyses (41%), followed by Cox regression (23%) and Poisson regression (14%). As meta-analysis method, a majority of the studies combined individual patient data (73%). Six studies performed an aggregate meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%).
CONCLUSIONS
Pharmacoepidemiological multi-database studies are a well-powered strategy to address safety issues and have increased in popularity. To be able to correctly interpret the results of these studies, it is important to systematically report on database management and analysis techniques, including central programming and heterogeneity testing.
Topics: Case-Control Studies; Cohort Studies; Databases, Factual; Humans; Pharmacoepidemiology; Statistics as Topic
PubMed: 26175179
DOI: 10.1002/pds.3828