E-Health Tools to Improve Antibiotic Use and Resistances: A Systematic Review.
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ABSTRACT:
SUBMITTER: Carvalho E
PROVIDER: S-EPMC7460242 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
Publications
E-Health Tools to Improve Antibiotic Use and Resistances: A Systematic Review.
Carvalho Érico É Estrela Marta M Zapata-Cachafeiro Maruxa M Figueiras Adolfo A Roque Fátima F Herdeiro Maria Teresa MT
Antibiotics (Basel, Switzerland) 20200812 8
(1) Background: e-Health tools, especially in the form of clinical decision support systems (CDSSs), have been emerging more quickly than ever before. The main objective of this systematic review is to assess the influence of these tools on antibiotic use for respiratory tract infections. (2) Methods: The scientific databases, MEDLINE-PubMed and EMBASE, were searched. The search was conducted by two independent researchers. The search strategy was mainly designed to identify relevant studies on ...[more]
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Project description:Background:Excessive use of antibiotics accelerates the acquisition/spread of antimicrobial resistance. A systematic review was conducted to identify the components of successful communication interventions targeted at the general public to improve antibiotic use. Methods:The databases MEDLINE, EMBASE, CINAHL, Web of Science and Cochrane Library were searched. Search terms were related to the population (public, community), intervention (campaign, mass media) and outcomes (antibiotic, antimicrobial resistance). References were screened for inclusion by one author with a random subset of 10% screened by a second author. No date restrictions were applied and only articles in the English language were considered. Studies had to have a control group or be an interrupted time-series. Outcomes had to measure change in antibiotic-related prescribing/consumption and/or the public's knowledge, attitudes or behaviour. Two reviewers assessed the quality of studies. Narrative synthesis was performed. Results:Fourteen studies were included with an estimated 74-75 million participants. Most studies were conducted in the United States or Europe and targeted both the general public and clinicians. Twelve of the studies measured changes in antibiotic prescribing. There was quite strong ( P? <?0·05 to ??0·01) to very strong ( P? <?0·001) evidence that interventions that targeted prescribing for RTIs were associated with decreases in antibiotic prescribing; the majority of these studies reported reductions of greater than -14% with the largest effect size reaching -30%. Conclusion:Multi-faceted communication interventions that target both the general public and clinicians can reduce antibiotic prescribing in high-income countries but the sustainability of reductions in antibiotic prescribing is unclear.
| S-EPMC7263825 | biostudies-literature
Project description:Introduction: The use of antibiotics leads to antibiotic resistance (ABR). Different methods have been used to predict and control ABR. In recent years, artificial intelligence (AI) has been explored to improve antibiotic (AB) prescribing, and thereby control and reduce ABR. This review explores whether the use of AI can improve antibiotic prescribing for human patients. Methods: Observational studies that use AI to improve antibiotic prescribing were retrieved for this review. There were no restrictions on the time, setting or language. References of the included studies were checked for additional eligible studies. Two independent authors screened the studies for inclusion and assessed the risk of bias of the included studies using the National Institute of Health (NIH) Quality Assessment Tool for observational cohort studies. Results: Out of 3692 records, fifteen studies were eligible for full-text screening. Five studies were included in this review, and a narrative synthesis was carried out to assess their findings. All of the studies used supervised machine learning (ML) models as a subfield of AI, such as logistic regression, random forest, gradient boosting decision trees, support vector machines and K-nearest neighbours. Each study showed a positive contribution of ML in improving antibiotic prescribing, either by reducing antibiotic prescriptions or predicting inappropriate prescriptions. However, none of the studies reported the engagement of AB prescribers in developing their ML models, nor their feedback on the user-friendliness and reliability of the models in different healthcare settings. Conclusion: The use of ML methods may improve antibiotic prescribing in both primary and secondary settings. None of the studies evaluated the implementation process of their models in clinical practices. Prospero Registration: (CRD42022329049).
| S-EPMC10451640 | biostudies-literature
Project description:BACKGROUND:Electronic health (eHealth) tools are becoming increasingly popular for helping patients' self-manage chronic conditions. Little research, however, has examined the effect of patients using eHealth tools to self-report their medication management and use. Similarly, there is little evidence showing how eHealth tools might prompt patients and health care providers to make appropriate changes to medication use. OBJECTIVE:The objective of this systematic review was to determine the impact of patients' use of eHealth tools on self-reporting adverse effects and symptoms that promote changes to medication use. Related secondary outcomes were also evaluated. METHODS:MEDLINE, EMBASE, and CINAHL were searched from January 1, 2000, to April 25, 2018. Reference lists of relevant systematic reviews and included articles from the literature search were also screened to identify relevant studies. Title, abstract, and full-text review as well as data extraction and risk of bias assessment were performed independently by 2 reviewers. Due to high heterogeneity, results were not meta-analyzed and instead presented as a narrative synthesis. RESULTS:A total of 14 studies, including 13 randomized controlled trials (RCTs) and 1 open-label intervention, were included, from which 11 unique eHealth tools were identified. In addition, 14 RCTs found statistically significant increases in positive medication changes as a result of using eHealth tools, as did the single open-label study. Moreover, 8 RCTs found improvement in patient symptoms following eHealth tool use, especially in adolescent asthma patients. Furthermore, 3 RCTs showed that eHealth tools might improve patient self-efficacy and self-management of chronic disease. Little or no evidence was found to support the effectiveness of eHealth tools at improving medication recommendations and reconciliation by clinicians, medication-use behavior, health service utilization, adverse effects, quality of life, or patient satisfaction. eHealth tools with multifaceted functionalities and those allowing direct patient-provider communication may be more effective at improving patient self-management and self-efficacy. CONCLUSIONS:Evidence suggests that the use of eHealth tools may improve patient symptoms and lead to medication changes. Patients generally found eHealth tools useful in improving communication with health care providers. Moreover, health-related outcomes among frequent eHealth tool users improved in comparison with individuals who did not use eHealth tools frequently. Implementation issues such as poor patient engagement and poor clinician workflow integration were identified. More high-quality research is needed to explore how eHealth tools can be used to effectively manage use of medications to improve medication management and patient outcomes.
| S-EPMC6315271 | biostudies-other
Project description: Not available
| S-EPMC10512864 | biostudies-literature
Project description:Objective Accurate measurement of adult and child screen media use are needed to robustly assess its impact on health outcomes. Our objective was to systematically review screen media use measurement tools that have been validated against an objective “gold standard” tool. Methods The search strategy was initially conducted in Medline Ovid and translated to Embase, Web of Science, PsychInfo and Cochrane. A modified natural language search was conducted in Google Scholar and IEEE. The initial search was conducted in March 2021, and an updated search was conducted in June 2022. Additional studies were included from the references. Studies had to describe the validation of a tool to measure screen media use on participants of any age against a ‘gold standard’ or comparable objective measure. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) was used to assess the criterion validity. Four authors reviewed the titles in two rounds and extracted data. Results Twenty-nine articles were included in the review. Studies measured TV, computer, mobile device and social media site screen media use through: self or parent report, direct or video observation, computer and mobile device use tracking programs, and through other novel devices such as wearable devices and cameras. Correlations of self or parent report of screen media with the gold standard were lower than correlations of technology-based measures, and video observation with the gold standard. The COSMIN criterion validity ratings ranged from poor to excellent; most of the studies received a global score of fair or poor. Conclusions Technology based validated tools that more directly measure screen use are emerging that have been validated against a gold standard for measuring screen use. However, practical, objective measures of diverse types of screen media use that have been tested on diverse populations are needed to better understand the impact of screen media use on the development and physical and mental health of children and adults.
| S-EPMC10101444 | biostudies-literature
Project description:BackgroundPast studies have identified poor rates of detection of mental illness among inmates. Consequently, mental health screening is a common feature to various correctional mental health strategies and best practice guidelines. However, there is little guidance to support the selection of an appropriate tool. This systematic review compared the sensitivity and specificity of mental health screening tools among adult jail or prison populations.MethodsA systematic review of MEDLINE and PsycINFO up to 2011, with additional studies identified from a search of reference lists. Only studies involving adult jail or prison populations, with an independent measure of mental illness, were included. Studies in forensic settings to determine fitness to stand trial or criminal responsibility were excluded. Twenty-four studies met all inclusion and exclusion criteria for the review. All articles were coded by two independent authors. Study quality was coded by the lead author.ResultsTwenty-two screening tools were identified. Only six tools have replication studies: the Brief Jail Mental Health Screen (BJMHS), the Correctional Mental Health Screen for Men (CMHS-M), the Correctional Mental Health Screen for Women (CMHS-W), the England Mental Health Screen (EMHS), the Jail Screening Assessment Tool (JSAT), and the Referral Decision Scale (RDS). A descriptive summary is provided in lieu of use of meta-analytic techniques due to the lack of replication studies and methodological variations across studies.ConclusionsThe BJMHS, CMHS-M, CMHS-W, EMHS and JSAT appear to be the most promising tools. Future research should consider important contextual factors in the implementation of a screening tool that have received little attention. Randomized or quasi-randomized trials are recommended to evaluate the effectiveness of screening to improve the detection of mental illness compared to standard practices.
| S-EPMC4231452 | biostudies-literature
Project description:BackgroundHealth literacy (HL) is seen as an increasingly relevant issue for global public health and requires a reliable and comprehensive operationalization. By now, there is limited evidence on how the development of tools measuring HL proceeded in recent years and if scholars considered existing methodological guidance when developing an instrument.MethodsWe performed a systematic review of generic measurement tools developed to assess HL by searching PubMed, ERIC, CINAHL and Web of Knowledge (2009 forward). Two reviewers independently reviewed abstracts/ full text articles for inclusion according to predefined criteria. Additionally we conducted a reporting quality appraisal according to the survey reporting guideline SURGE.ResultsWe identified 17 articles reporting on the development and validation of 17 instruments measuring health literacy. More than two thirds of all instruments are based on a multidimensional construct of health literacy. Moreover, there is a trend towards a mixed measurement (self-report and direct test) of health literacy with 41% of instruments applying it, though results strongly indicate a weakness of coherence between the underlying constructs measured. Overall, almost every third instrument is based on assessment formats modeled on already existing functional literacy screeners such as the REALM or the TOFHLA and 30% of the included articles do not report on significant reporting features specified in the SURGE guideline.ConclusionsScholars recently developing instruments that measure health literacy mainly comply with recommendations of the academic circle by applying multidimensional constructs and mixing up measurement approaches to capture health literacy comprehensively. Nonetheless, there is still a dependence on assessment formats, rooted in functional literacy measurement contradicting the widespread call for new instruments. All things considered, there is no clear "consensus" on HL measurement but a convergence to more comprehensive tools. Giving attention to this finding can help to offer direction towards the development of comparable and reliable health literacy assessment tools that effectively respond to the informational needs of populations.
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Project description:BackgroundWomen 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.ObjectiveThis systematic review provides an overview of studies investigating the effect of patient-centered decision support tools for pregnant women.MethodsWe 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.ResultsThe 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.ConclusionsThe 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.
| S-EPMC7522732 | biostudies-literature
Project description:BackgroundThe majority of studies that link antibiotic usage and resistance focus on simple associations between the resistance against a specific antibiotic and the use of that specific antibiotic. However, the relationship between antibiotic use and resistance is more complex. Here we evaluate selection and co-selection by assessing which antibiotics, including those mainly prescribed for respiratory tract infections, are associated with increased resistance to various antibiotics among Escherichia coli isolated from urinary samples.MethodsMonthly primary care prescribing data were obtained from National Health Service (NHS) Digital. Positive E. coli records from urine samples in English primary care (n = 888,207) between April 2014 and January 2016 were obtained from the Second Generation Surveillance System. Elastic net regularization was used to evaluate associations between prescribing of different antibiotic groups and resistance against amoxicillin, cephalexin, ciprofloxacin, co-amoxiclav and nitrofurantoin at the clinical commissioning group (CCG) level. England is divided into 209 CCGs, with each NHS practice prolonging to one CCG.ResultsAmoxicillin prescribing (measured in DDD/ 1000 inhabitants / day) was positively associated with amoxicillin (RR 1.03, 95% CI 1.01-1.04) and ciprofloxacin (RR 1.09, 95% CI 1.04-1.17) resistance. In contrast, nitrofurantoin prescribing was associated with lower levels of resistance to amoxicillin (RR 0.92, 95% CI 0.84-0.97). CCGs with higher levels of trimethoprim prescribing also had higher levels of ciprofloxacin resistance (RR 1.34, 95% CI 1.10-1.59).ConclusionAmoxicillin, which is mainly (and often unnecessarily) prescribed for respiratory tract infections is associated with increased resistance against various antibiotics among E. coli causing urinary tract infections. Our findings suggest that when predicting the potential impact of interventions on antibiotic resistances it is important to account for use of other antibiotics, including those typically used for other indications.
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Project description:Urban health indicator (UHI) tools provide evidence about the health impacts of the physical urban environment which can be used in built environment policy and decision-making. Where UHI tools provide data at the neighborhood (and lower) scale they can provide valuable information about health inequalities and environmental deprivation. This review performs a census of UHI tools and explores their nature and characteristics (including how they represent, simplify or address complex systems) to increase understanding of their potential use by municipal built environment policy and decision-makers. We searched seven bibliographic databases, four key journals and six practitioner websites and conducted Google searches between January 27, 2016 and February 24, 2016 for UHI tools. We extracted data from primary studies and online indicator systems. We included 198 documents which identified 145 UHI tools comprising 8006 indicators, from which we developed a taxonomy. Our taxonomy classifies the significant diversity of UHI tools with respect to topic, spatial scale, format, scope and purpose. The proportions of UHI tools which measure data at the neighborhood and lower scale, and present data via interactive maps, have both increased over time. This is particularly relevant to built environment policy and decision-makers, reflects growing analytical capability and offers the potential for improved understanding of the complexity of influences on urban health (an aspect noted as a particular challenge by some indicator producers). The relation between urban health indicators and health impacts attributable to modifiable environmental characteristics is often indirect. Furthermore, the use of UHI tools in policy and decision-making appears to be limited, thus raising questions about the continued development of such tools by multiple organisations duplicating scarce resources. Further research is needed to understand the requirements of built environment policy and decision-makers, public health professionals and local communities regarding the form and presentation of indicators which support their varied objectives.
| S-EPMC6181826 | biostudies-literature