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Digital Health 2024Stroke survivors often experience residual impairments and motor decline post-discharge. While digital home rehabilitation combined with supervision could be a promising... (Review)
Review
OBJECTIVE
Stroke survivors often experience residual impairments and motor decline post-discharge. While digital home rehabilitation combined with supervision could be a promising approach for reducing human resources, increasing motor ability, and supporting rehabilitation persistence there is a lack of reviews synthesizing the effects. Thus, this systematic review and meta-analysis aimed to synthesize the effect of digital home rehabilitation and supervision in improving motor ability of upper limb, static balance, stroke-related quality of life, and self-reported arm function among stroke survivors.
METHODS
Six electronic databases, grey literature, ongoing studies, and reference lists were searched for relevant studies. Two investigators independently reviewed titles, abstracts, screened full texts for eligibility and performed data extraction. Meta-analysis of 13 independent studies were grouped into four separate meta-analyses. The Grading of Recommendations, Assessments, Development and Evaluations (GRADE) tool was used for evaluating the overall quality of the evidence.
RESULTS
Meta-analyses showed no statistically significant difference between intervention (digital home rehabilitation) and control groups (home training/clinic-based) of all outcomes including motor ability of upper limb, static balance, stroke-related quality of life, and self-reported arm function. In the sub-group analysis digital home rehabilitation was associated with better quality of arm use (standardized mean difference = 0.68, 95% confidence interval: [0.27, 1.09], = 0.001).
CONCLUSIONS
This result indicated that digital home rehabilitation has similar effects and could potentially replace home training or clinic-based services. This review highlights better-targeted digital motor interventions to examine the effects of interventions further. The quality of evidence was moderate to high in motor and self-reported arm outcomes, and low for balance and quality of life.
PubMed: 38832099
DOI: 10.1177/20552076241256861 -
NPJ Digital Medicine Jun 2024Digital twins represent a promising technology within the domain of precision healthcare, offering significant prospects for individualized medical interventions.... (Review)
Review
Digital twins represent a promising technology within the domain of precision healthcare, offering significant prospects for individualized medical interventions. Existing systematic reviews, however, mainly focus on the technological dimensions of digital twins, with a limited exploration of their impact on health-related outcomes. Therefore, this systematic review aims to explore the efficacy of digital twins in improving precision healthcare at the population level. The literature search for this study encompassed PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, CNKI, and Wanfang Database to retrieve potentially relevant records. Patient health-related outcomes were synthesized employing quantitative content analysis, whereas the Joanna Briggs Institute (JBI) scales were used to evaluate the quality and potential bias inherent in each selected study. Following established inclusion and exclusion criteria, 12 studies were screened from an initial 1321 records for further analysis. These studies included patients with various conditions, including cancers, type 2 diabetes, multiple sclerosis, heart failure, qi deficiency, post-hepatectomy liver failure, and dental issues. The review coded three types of interventions: personalized health management, precision individual therapy effects, and predicting individual risk, leading to a total of 45 outcomes being measured. The collective effectiveness of these outcomes at the population level was calculated at 80% (36 out of 45). No studies exhibited unacceptable differences in quality. Overall, employing digital twins in precision health demonstrates practical advantages, warranting its expanded use to facilitate the transition from the development phase to broad application.PROSPERO registry: CRD42024507256.
PubMed: 38831093
DOI: 10.1038/s41746-024-01146-0 -
The Journal of Evidence-based Dental... Jun 2024Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis. J Digit Imaging. 2023 Jun;36(3):1158-1179.... (Meta-Analysis)
Meta-Analysis
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION
Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis. J Digit Imaging. 2023 Jun;36(3):1158-1179. doi:10.1007/s10278-022-00766-w.
SOURCE OF FUNDING
The study was financed in part by the Coordenacao de Aperfeicoamentode Pessoal de Nivel Superior-Brazil (CAPES)-Finance Code 001.
TYPE OF STUDY/DESIGN
Systematic review and meta-analysis.
Topics: Cephalometry; Humans; Anatomic Landmarks; Artificial Intelligence
PubMed: 38821652
DOI: 10.1016/j.jebdp.2023.101965 -
Digital Health 2024Electronic patient-reported outcome (ePRO) systems hold promise for revolutionizing communication between cancer patients and healthcare providers across various care... (Review)
Review
OBJECTIVE
Electronic patient-reported outcome (ePRO) systems hold promise for revolutionizing communication between cancer patients and healthcare providers across various care settings. This systematic review explores the multifaceted landscape of ePROs in cancer care, encompassing their advantages, disadvantages, potential risks, and opportunities for improvement.
METHODS
In our systematic review, we conducted a rigorous search in Scopus, Web of Science, and PubMed, employing comprehensive medical subject heading terms for ePRO and cancer, with no date limitations up to 2024. Studies were critically appraised and thematically analyzed based on inclusion and exclusion criteria, including considerations of advantages, disadvantages, opportunities, and threats.
FINDINGS
Analyzing 85 articles revealed 69 themes categorized into four key areas. Advantages ( = 14) were dominated by themes like "improved quality of life and care." Disadvantages ( = 26) included "limited access and technical issues." Security concerns and lack of technical skills were prominent threats ( = 10). Opportunities ( = 19) highlighted advancements in symptom management and potential solutions for technical challenges.
CONCLUSION
This review emphasizes the crucial role of continuous exploration, integration, and innovation in ePRO systems for optimizing patient outcomes in cancer care. Beyond traditional clinical settings, ePROs hold promise for applications in survivorship, palliative care, and remote monitoring. By addressing existing limitations and capitalizing on opportunities, ePROs can empower patients, enhance communication, and ultimately improve care delivery across the entire cancer care spectrum.
PubMed: 38812853
DOI: 10.1177/20552076241257146 -
PLOS Digital Health May 2024Research on the applications of artificial intelligence (AI) tools in medicine has increased exponentially over the last few years but its implementation in clinical...
Research on the applications of artificial intelligence (AI) tools in medicine has increased exponentially over the last few years but its implementation in clinical practice has not seen a commensurate increase with a lack of consensus on implementing and maintaining such tools. This systematic review aims to summarize frameworks focusing on procuring, implementing, monitoring, and evaluating AI tools in clinical practice. A comprehensive literature search, following PRSIMA guidelines was performed on MEDLINE, Wiley Cochrane, Scopus, and EBSCO databases, to identify and include articles recommending practices, frameworks or guidelines for AI procurement, integration, monitoring, and evaluation. From the included articles, data regarding study aim, use of a framework, rationale of the framework, details regarding AI implementation involving procurement, integration, monitoring, and evaluation were extracted. The extracted details were then mapped on to the Donabedian Plan, Do, Study, Act cycle domains. The search yielded 17,537 unique articles, out of which 47 were evaluated for inclusion based on their full texts and 25 articles were included in the review. Common themes extracted included transparency, feasibility of operation within existing workflows, integrating into existing workflows, validation of the tool using predefined performance indicators and improving the algorithm and/or adjusting the tool to improve performance. Among the four domains (Plan, Do, Study, Act) the most common domain was Plan (84%, n = 21), followed by Study (60%, n = 15), Do (52%, n = 13), & Act (24%, n = 6). Among 172 authors, only 1 (0.6%) was from a low-income country (LIC) and 2 (1.2%) were from lower-middle-income countries (LMICs). Healthcare professionals cite the implementation of AI tools within clinical settings as challenging owing to low levels of evidence focusing on integration in the Do and Act domains. The current healthcare AI landscape calls for increased data sharing and knowledge translation to facilitate common goals and reap maximum clinical benefit.
PubMed: 38809946
DOI: 10.1371/journal.pdig.0000514 -
Digital Health 2024Mental health conditions are among the highest disease burden on society, affecting approximately 20% of children and adolescents at any point in time, with depression...
Mental health conditions are among the highest disease burden on society, affecting approximately 20% of children and adolescents at any point in time, with depression and anxiety being the leading causes of disability globally. To improve treatment outcomes, healthcare organizations turned to clinical decision support systems (CDSSs) that offer patient-specific diagnoses and recommendations. However, the economic impact of CDSS is limited, especially in child and adolescent mental health. This systematic literature review examined the economic impacts of CDSS implemented in mental health services. We planned to follow PRISMA reporting guidelines and found only one paper to describe health and economic outcomes. A randomized, controlled trial of 336 participants found that 60% of the intervention group and 32% of the control group achieved symptom reduction, i.e. a 50% decrease as per the Symptom Checklist-90-Revised (SCL-90-R), a method to evaluate psychological problems and identify symptoms. Analysis of the incremental cost-effectiveness ratio found that for every 1% of patients with a successful treatment result, it added €57 per year. There are not enough studies to draw conclusions about the cost-effectiveness in a mental health context. More studies on economic evaluations of the viability of CDSS within mental healthcare have the potential to contribute to patients and the larger society.
PubMed: 38798888
DOI: 10.1177/20552076241256511 -
NPJ Digital Medicine May 2024
PubMed: 38789723
DOI: 10.1038/s41746-024-01138-0 -
PLOS Digital Health May 2024Clinical discoveries largely depend on dedicated clinicians and scientists to identify and pursue unique and unusual clinical encounters with patients and communicate...
Clinical discoveries largely depend on dedicated clinicians and scientists to identify and pursue unique and unusual clinical encounters with patients and communicate these through case reports and case series. This process has remained essentially unchanged throughout the history of modern medicine. However, these traditional methods are inefficient, especially considering the modern-day availability of health-related data and the sophistication of computer processing. Outlier analysis has been used in various fields to uncover unique observations, including fraud detection in finance and quality control in manufacturing. We propose that clinical discovery can be formulated as an outlier problem within an augmented intelligence framework to be implemented on any health-related data. Such an augmented intelligence approach would accelerate the identification and pursuit of clinical discoveries, advancing our medical knowledge and uncovering new therapies and management approaches. We define clinical discoveries as contextual outliers measured through an information-based approach and with a novelty-based root cause. Our augmented intelligence framework has five steps: define a patient population with a desired clinical outcome, build a predictive model, identify outliers through appropriate measures, investigate outliers through domain content experts, and generate scientific hypotheses. Recognizing that the field of obstetrics can particularly benefit from this approach, as it is traditionally neglected in commercial research, we conducted a systematic review to explore how outlier analysis is implemented in obstetric research. We identified two obstetrics-related studies that assessed outliers at an aggregate level for purposes outside of clinical discovery. Our findings indicate that using outlier analysis in clinical research in obstetrics and clinical research, in general, requires further development.
PubMed: 38776276
DOI: 10.1371/journal.pdig.0000515 -
European Heart Journal. Digital Health May 2024Telehealth-delivered cardiac rehabilitation (CR) programmes can potentially increase participation rates while delivering equivalent outcomes to facility-based... (Review)
Review
Key features in telehealth-delivered cardiac rehabilitation required to optimize cardiovascular health in coronary heart disease: a systematic review and realist synthesis.
Telehealth-delivered cardiac rehabilitation (CR) programmes can potentially increase participation rates while delivering equivalent outcomes to facility-based programmes. However, key components of these interventions that reduce cardiovascular risk factors are not yet distinguished. This study aims to identify features of telehealth-delivered CR that improve secondary prevention outcomes, exercise capacity, participation, and participant satisfaction and develop recommendations for future telehealth-delivered CR. The protocol for our review was registered with the Prospective Register of Systematic Reviews (#CRD42021236471). We systematically searched four databases (PubMed, Scopus, EMBASE, and Cochrane Database) for randomized controlled trials comparing telehealth-delivered CR programmes to facility-based interventions or usual care. Two independent reviewers screened the abstracts and then full texts. Using a qualitative review methodology (realist synthesis), included articles were evaluated to determine contextual factors and potential mechanisms that impacted cardiovascular risk factors, exercise capacity, participation in the intervention, and increased satisfaction. We included 37 reports describing 26 randomized controlled trials published from 2010 to 2022. Studies were primarily conducted in Europe and Australia/Asia. Identified contextual factors and mechanisms were synthesized into four theories required to enhance participant outcomes and participation. These theories are as follows: (i) early and regular engagement; (ii) personalized interventions and shared goals; (iii) usable, accessible, and supported interventions; and (iv) exercise that is measured and monitored. Providing a personalized approach with frequent opportunities for bi-directional interaction was a critical feature for success across telehealth-delivered CR trials. Real-world effectiveness studies are now needed to complement our findings.
PubMed: 38774382
DOI: 10.1093/ehjdh/ztad080 -
Digital Health 2024Mobile health applications hold immense potential for enhancing health outcomes. Usability is one of the main factors for the adoption and use of mobile health... (Review)
Review
OBJECTIVE
Mobile health applications hold immense potential for enhancing health outcomes. Usability is one of the main factors for the adoption and use of mobile health applications. However, despite the growing importance of mHealth applications, clear standards for their evaluation remain elusive. The present study aimed to determine heuristics for the usability evaluation of health-related applications.
METHODS
We systematically searched multiple databases for relevant papers published between January 2008 and April 2021. Articles were reviewed, and data were extracted and categorized from those meeting inclusion criteria by two authors independently. Heuristics were identified based on statements, words, and concepts expressed in the studies. These heuristics were first mapped to Nielsen's heuristics based on their differences or similarities. The remaining heuristics that were very important for mobile applications were categorized into new heuristics.
RESULTS
Seventeen studies met the eligibility criteria. Seventy-nine heuristics were extracted from the papers. After combining the items with the same concepts and removing irrelevant items based on the exclusion criteria, 20 heuristics remained. Common heuristics such as "Visibility of system status" and "Flexibility and efficiency of use" were categorized into 10 previously established heuristics and new heuristics like "Navigation" and "User engagement" were recognized as new ones.
CONCLUSIONS
In our study, we have meticulously identified 20 heuristics that hold promise for evaluating and designing mHealth applications. These heuristics can be used by the researchers for the development of robust tools for heuristic evaluation. These tools, when adapted or tailored for health domain applications, have the potential to significantly enhance the quality of mHealth applications. Ultimately, this improvement in quality translates to enhanced patient safety.
PROTOCOL REGISTRATION
(10.17605/OSF.IO/PZJ7H).
PubMed: 38766365
DOI: 10.1177/20552076241253539