1,721,041 research outputs found

    A review of randomized controlled trials of medical record powered clinical decision support system to improve quality of diabetes care

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    BACKGROUND: A gap between current diabetes care practice and recommended diabetes care standards has consistently been reported in the literature. Many IT-based interventions have been developed to improve adherence to the quality of care standards for chronic illness like diabetes.OBJECTIVE: The widespread implementation of electronic medical/health records has catalyzed clinical decision support systems (CDSS) which may improve the quality of diabetes care. Therefore, the objective of the review is to evaluate the effectiveness of CDSS in improving quality of type II diabetes care. Moreover, the review aims to highlight the key indicators of quality improvement to assist policy makers in development of future diabetes care policies through the integration of information technology and system.SELECTION OF STUDY: Setting inclusion criteria, a systematic literature search was conducted using Medline, Web of Science and Science Direct. Critical Appraisal Skills Programme (CASP) tools were used to evaluate the quality of studies. Eight randomized controlled trials (RCTs) were selected for the review. In the selected studies, seventeen clinical markers of diabetes care were discussed. Three quality of care indicators were given more importance in monitoring the progress of diabetes care, which is consistent with National Institute for Health and Care Excellence (NICE) guidelines. The presence of these indicators in the studies helped to determine which studies were selected for review. Clinical- and process-related improvements are compared between intervention group using CDSS and control group with usual care. Glycated hemoglobin (HbA1c), low density lipid cholesterol (LDL-C) and blood pressure (BP) were the quality of care indicators studied at the levels of process of care and clinical outcome.FINDINGS: The review has found both inconsistent and variable results for quality of diabetes care measures. A significant improvement has been found in the process of care for all three measures of quality of diabetes care. However, weak to modest positive results are observed for the clinical measures of the diabetes care indicators. In addition to this, technology adoption of CDSS is found to be consistently low.CONCLUSION: The review suggests the need to conduct further empirical research using the critical diabetes care indicators (HbA1c, LDL-C and BP) to ascertain if CDSS improves the quality of diabetes care. Research designs should be improved, especially with regard to baseline characteristics, sample size and study period. With respect to implementation of CDSS, rather than a sudden change of clinical work practice, there should instead be an incremental, gradual adoption of technology that minimizes the disruption in clinical workflow

    Remote symptom monitoring integrated into electronic health records: A systematic review

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    ObjectivePeople with long-term conditions (LTCs) require serial clinical assessments. Digital patient-reported symptoms collected between visits can inform these, especially if integrated into electronic health records (EHRs) and clinical workflows. This systematic review identified and summarized EHR-integrated systems to remotely collect patient-reported symptoms and examined their anticipated and realized benefits in LTCs.Materials and MethodsWe searched Medline, Web of Science, and Embase. Inclusion criteria were symptom reporting systems in adults with LTCs; data integrated into the EHR; data collection outside of clinic; data used in clinical care. We synthesized data thematically. Benefits were assessed against a list of outcome indicators. We critically appraised studies using the Mixed Methods Appraisal Tool.ResultsWe included 12 studies representing 10 systems. Seven were in oncology. Systems were technically and functionally heterogeneous, with the majority being fully integrated (data viewable in the EHR). Half of the systems enabled regular symptom tracking between visits. We identified three symptom report-guided clinical workflows: Consultation-only (data used during consultation, n=5), alert-based (real-time alerts for providers, n=4) and patient-initiated visits (n=1). Few author-described anticipated benefits, primarily to improve communication and resultant health outcomes, were realized based on the study results, and only supported by evidence from early stage qualitative studies. Studies were primarily feasibility and pilot studies of acceptable quality.Discussion and ConclusionsEHR-integrated remote symptom monitoring is possible, but there are few published efforts to inform development of these systems. Currently there is limited evidence that this improves care and outcomes, warranting future robust, quantitative studies of efficacy and effectiveness

    Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): an exploratory analysis of a longitudinal smartwatch feasibility study

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    Introduction: people living with multiple long-term conditions (MLTC-M) (multimorbidity) experience a range of inter-related symptoms. These symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices, and then summarised to provide useful clinical insight.Aim: we aimed to perform an exploratory analysis to summarise the extent and trajectory of multiple symptom ratings tracked via a smartwatch, and to investigate the relationship between these symptom ratings and demographic factors in people living with MLTC-M in a feasibility study.Methods: ‘Watch Your Steps’ was a prospective observational feasibility study, administering multiple questions per day over a 90 day period. Adults with more than one clinician-diagnosed long-term condition rated seven core symptoms each day, plus up to eight additional symptoms personalised to their LTCs per day. Symptom ratings were summarised over the study period at the individual and group level. Symptom ratings were also plotted to describe day-to-day symptom trajectories for individuals.Results: fifty two participants submitted symptom ratings. Half were male and the majority had LTCs affecting three or more disease areas (N = 33, 64%). The symptom rated as most problematic was fatigue. Patients with increased comorbidity or female sex seemed to be associated with worse experiences of fatigue. Fatigue ratings were strongly correlated with pain and level of dysfunction.Conclusion: in this study we have shown that it is possible to collect and descriptively analyse self reported symptom data in people living with MLTC-M, collected multiple times per day on a smartwatch, to gain insights that might support future clinical care and research

    Digital manikins to self‐report pain on a smartphone: a systematic review of mobile apps

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    BACKGROUND: Chronic pain is the leading cause of disability. Improving our understanding of pain occurrence and treatment effectiveness requires robust methods to measure pain at scale. Smartphone-based pain manikins are human-shaped figures to self-report location-specific aspects of pain on people's personal mobile devices.METHODS: We searched the main app stores to explore the current state of smartphone-based pain manikins and to formulate recommendations to guide their development in the future.RESULTS: The search yielded 3,938 apps. Twenty-eight incorporated a pain manikin and were included in the analysis. For all apps, it was unclear whether they had been tested and had end-user involvement in the development. Pain intensity and quality could be recorded in 28 and 13 apps, respectively, but this was location specific in only 11 and 4. Most manikins had two or more views (n = 21) and enabled users to shade or select body areas to record pain location (n = 17). Seven apps allowed personalising the manikin appearance. Twelve apps calculated at least one metric to summarise manikin reports quantitatively. Twenty-two apps had an archive of historical manikin reports; only eight offered feedback summarising manikin reports over time.CONCLUSIONS: Several publically available apps incorporated a manikin for pain reporting, but only few enabled recording of location-specific pain aspects, calculating manikin-derived quantitative scores, or generating summary feedback. For smartphone-based manikins to become adopted more widely, future developments should harness manikins' digital nature and include robust validation studies. Involving end users in the development may increase manikins' acceptability as a tool to self-report pain.SIGNIFICANCE: This review identified and characterised 28 smartphone apps that included a pain manikin (i.e. pain drawings) as a novel approach to measure pain in large populations. Only few enabled recording of location-specific pain aspects, calculating quantitative scores based on manikin reports, or generating manikin feedback. For smartphone-based manikins to become adopted more widely, future studies should harness the digital nature of manikins, and establish the measurement properties of manikins. Furthermore, we believe that involving end users in the development process will increase acceptability of manikins as a tool for self-reporting pain.</p

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Exploring the cross-cultural acceptability of digital tools for pain self-reporting: A qualitative study

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    Background:Culture and ethnicity influence how people communicate about their pain. This makes it challenging to develop pain self-report tools that are acceptable across ethnic groups.Objective:We aimed to inform the development of cross-culturally acceptable digital pain self-report tools by better understanding the similarities and differences between ethnic groups in pain experiences and self-reporting needs.Methods:Three web-based workshops consisting of a focus group and a user requirement exercise with people who self-identified as being of Black African (n=6), South Asian (n=10), or White British (n=7) ethnicity were conducted.Results:Across ethnic groups, participants shared similar lived experiences and challenges in communicating their pain to health care professionals. However, there were differences in beliefs about the causes of pain, attitudes toward pain medication, and experiences of how stigma and gender norms influenced pain-reporting behavior. Despite these differences, they agreed on important aspects for pain self-report, but participants from non-White backgrounds had additional language requirements such as culturally appropriate pain terminologies to reduce self-reporting barriers.Conclusions:To improve the cross-cultural acceptability and equity of digital pain self-report tools, future developments should address the differences among ethnic groups on pain perceptions and beliefs, factors influencing pain reporting behavior, and language requirements
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