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Sökning: L773:1067 5027 OR L773:1527 974X

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2.
  • Blomström-Lundqvist, Carina, et al. (författare)
  • Effect of Catheter Ablation vs Antiarrhythmic Medication on Quality of Life in Patients With Atrial Fibrillation : The CAPTAF Randomized Clinical Trial
  • 2019
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - Chicago : American Medical Association. - 1067-5027 .- 1527-974X .- 0098-7484 .- 1538-3598. ; 321:11, s. 1059-1068
  • Tidskriftsartikel (refereegranskat)abstract
    • IMPORTANCE Quality of life is not a standard primary outcome in ablation trials, even though symptoms drive the indication. OBJECTIVE To assess quality of life with catheter ablation vs antiarrhythmic medication at 12 months in patients with atrial fibrillation. DESIGN, SETTING, AND PARTICIPANTS Randomized clinical trial at 4 university hospitals in Sweden and 1 in Finland of 155 patients aged 30-70 years with more than 6 months of atrial fibrillation and treatment failure with 1 antiarrhythmic drug or beta-blocker, with 4-year follow-up. Study dateswere July 2008-September 2017. Major exclusionswere ejection fraction <35%, left atrial diameter > 60 mm, ventricular pacing dependency, and previous ablation. INTERVENTIONS Pulmonary vein isolation ablation (n= 79) or previously untested antiarrhythmic drugs (n= 76). MAIN OUTCOMES AND MEASURES Primary outcomewas the General Health subscale score (Medical Outcomes Study 36-Item Short-Form Health Survey) at baseline and 12 months, assessed unblinded (range, 0 [worst] to 100 [best]). There were 26 secondary outcomes, including atrial fibrillation burden (% of time) from baseline to 12 months, measured by implantable cardiac monitors. The first 3 months were excluded from rhythm analysis. RESULTS Among 155 randomized patients (mean age, 56.1 years; 22.6% women), 97% completed the trial. Of 79 patients randomized to receive ablation, 75 underwent ablation, including 2 who crossed over to medication and 14 who underwent repeated ablation procedures. Of 76 patients randomized to receive antiarrhythmic medication, 74 received it, including 8 who crossed over to ablation and 43 for whom the first drug used failed. General Health score increased from 61.8 to 73.9 points in the ablation group vs 62.7 to 65.4 points in the medication group (between-group difference, 8.9 points; 95% CI, 3.1-14.7; P=.003). Of 26 secondary end points, 5 were analyzed; 2 were null and 2 were statistically significant, including decrease in atrial fibrillation burden (from 24.9% to 5.5% in the ablation group vs 23.3% to 11.5% in the medication group; difference -6.8%[95% CI, -12.9% to -0.7%]; P=.03). Of the Health Survey subscales, 5 of 7 improved significantly. Most common adverse events were urosepsis (5.1%) in the ablation group and atrial tachycardia (3.9%) in the medication group. CONCLUSIONS AND RELEVANCE Among patients with symptomatic atrial fibrillation despite use of antiarrhythmic medication, the improvement in quality of life at 12 months was greater for those treated with catheter ablation compared with antiarrhythmic medication. Although the study was limited by absence of blinding, catheter ablation may offer an advantage for quality of life.
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  • Campbell, Walter S., et al. (författare)
  • A computable pathology report for precision medicine: extending an observables ontology unifying SNOMED CT and LOINC
  • 2018
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - : OXFORD UNIV PRESS. - 1067-5027 .- 1527-974X. ; 25:3, s. 259-266
  • Tidskriftsartikel (refereegranskat)abstract
    • The College of American Pathologists (CAP) introduced the first cancer synoptic reporting protocols in 1998. However, the objective of a fully computable and machine-readable cancer synoptic report remains elusive due to insufficient definitional content in Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) and Logical Observation Identifiers Names and Codes (LOINC). To address this terminology gap, investigators at the University of Nebraska Medical Center (UNMC) are developing, authoring, and testing a SNOMED CT observable ontology to represent the data elements identified by the synoptic worksheets of CAP. Investigators along with collaborators from the US National Library of Medicine, CAP, the International Health Terminology Standards Development Organization, and the UK Health and Social Care Information Centre analyzed and assessed required data elements for colorectal cancer and invasive breast cancer synoptic reporting. SNOMED CT concept expressions were developed at UNMC in the Nebraska LexiconA (c) SNOMED CT namespace. LOINC codes for each SNOMED CT expression were issued by the Regenstrief Institute. SNOMED CT concepts represented observation answer value sets. UNMC investigators created a total of 194 SNOMED CT observable entity concept definitions to represent required data elements for CAP colorectal and breast cancer synoptic worksheets, including biomarkers. Concepts were bound to colorectal and invasive breast cancer reports in the UNMC pathology system and successfully used to populate a UNMC biobank. The absence of a robust observables ontology represents a barrier to data capture and reuse in clinical areas founded upon observational information. Terminology developed in this project establishes the model to characterize pathology data for information exchange, public health, and research analytics.
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5.
  • De Silva, Kushan, et al. (författare)
  • A combined strategy of feature selection and machine learning to identify predictors of prediabetes
  • 2020
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 27:3, s. 396-406
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVE: To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population.MATERIALS AND METHODS: We analyzed n = 6346 men and women enrolled in the National Health and Nutrition Examination Survey 2013-2014. Prediabetes was defined using American Diabetes Association guidelines. The sample was randomly partitioned to training (n = 3174) and internal validation (n = 3172) sets. Feature selection algorithms were run on training data containing 156 preselected exposure variables. Four machine learning algorithms were applied on 46 exposure variables in original and resampled training datasets built using 4 resampling methods. Predictive models were tested on internal validation data (n = 3172) and external validation data (n = 3000) prepared from National Health and Nutrition Examination Survey 2011-2012. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC). Predictors were assessed by odds ratios in logistic models and variable importance in others. The Centers for Disease Control (CDC) prediabetes screening tool was the benchmark to compare model performance.RESULTS: Prediabetes prevalence was 23.43%. The CDC prediabetes screening tool produced 64.40% AUROC. Seven optimal (≥ 70% AUROC) models identified 25 predictors including 4 potentially novel associations; 20 by both logistic and other nonlinear/ensemble models and 5 solely by the latter. All optimal models outperformed the CDC prediabetes screening tool (P < 0.05).DISCUSSION: Combined use of feature selection and machine learning increased predictive performance outperforming the recommended screening tool. A range of predictors of prediabetes was identified.CONCLUSION: This work demonstrated the value of combining feature selection with machine learning to identify a wide range of predictors that could enhance prediabetes prediction and clinical decision-making.
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6.
  • Demiris, G., et al. (författare)
  • Patient-centered Applications : Use of Information Technology to Promote Disease Management and Wellness. A White Paper by the AMIA Knowledge in Motion Working Group
  • 2008
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - 1067-5027 .- 1527-974X. ; 15:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Advances in information technology (IT) enable a fundamental redesign of health care processes based on the use and integration of electronic communication at all levels. New communication technologies can support a transition from institution centric to patient-centric applications. This white paper defines key principles and challenges for designers, policy makers, and evaluators of patient-centered technologies for disease management and prevention. It reviews current and emerging trends, highlights challenges related to design, evaluation, reimbursement and usability, and reaches conclusions for next steps that will advance the domain. © 2008 J Am Med Inform Assoc.
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7.
  • Dentler, Kathrin, et al. (författare)
  • Formalization and computation of quality measures based on electronic medical records
  • 2014
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - : BMJ Publishing Group / Elsevier. - 1067-5027 .- 1527-974X. ; 21:2, s. 285-291
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a method for clinical indicator formalization (CLIF). The objective of our present study is to test whether CLIF is generalizablethat is, applicable to a large set of heterogeneous measures of different types and from various domains. Materials and methods We formalized the entire set of 159 Dutch quality measures for general practice, which contains structure, process, and outcome measures and covers seven domains. We relied on a web-based tool to facilitate the application of our method. Subsequently, we computed the measures on the basis of a large database of real patient data. Results Our CLIF method enabled us to fully formalize 100% of the measures. Owing to missing functionality, the accompanying tool could support full formalization of only 86% of the quality measures into Structured Query Language (SQL) queries. The remaining 14% of the measures required manual application of our CLIF method by directly translating the respective criteria into SQL. The results obtained by computing the measures show a strong correlation with results computed independently by two other parties. Conclusions The CLIF method covers all quality measures after having been extended by an additional step. Our web tool requires further refinement for CLIF to be applied completely automatically. We therefore conclude that CLIF is sufficiently generalizable to be able to formalize the entire set of Dutch quality measures for general practice.
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8.
  • Georgsson, Mattias (författare)
  • Quantifying usability : an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics
  • 2016
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 23:1, s. 5-11
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective Mobile health (mHealth) systems are becoming more common for chronic disease management, but usability studies are still needed on patients' perspectives and mHealth interaction performance. This deficiency is addressed by our quantitative usability study of a mHealth diabetes system evaluating patients' task performance, satisfaction, and the relationship of these measures to user characteristics. Materials and Methods We used metrics in the International Organization for Standardization (ISO) 9241-11 standard. After standardized training, 10 patients performed representative tasks and were assessed on individual task success, errors, efficiency (time on task), satisfaction (System Usability Scale [SUS]) and user characteristics. Results Tasks of exporting and correcting values proved the most difficult, had the most errors, the lowest task success rates, and consumed the longest times on task. The average SUS satisfaction score was 80.5, indicating good but not excellent system usability. Data trends showed males were more successful in task completion, and younger participants had higher performance scores. Educational level did not influence performance, but a more recent diabetes diagnosis did. Patients with more experience in information technology (IT) also had higher performance rates. Discussion Difficult task performance indicated areas for redesign. Our methods can assist others in identifying areas in need of improvement. Data about user background and IT skills also showed how user characteristics influence performance and can provide future considerations for targeted mHealth designs. Conclusion Using the ISO 9241-11 usability standard, the SUS instrument for satisfaction and measuring user characteristics provided objective measures of patients' experienced usability. These could serve as an exemplar for standardized, quantitative methods for usability studies on mHealth systems.
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9.
  • Goossen, William T. F., et al. (författare)
  • Development of a provisional domain model for the nursing process for use within the Health Level 7 reference information model
  • 2004
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - Philadelphia, USA : Hanley & Belfus Inc.. - 1067-5027 .- 1527-974X. ; 11:3, s. 186-94
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: Since 1999, the Nursing Terminology Summits have promoted the development, evaluation, and use of reference terminology for nursing and its integration into comprehensive health care data standards. The use of such standards to represent nursing knowledge, terminology, processes, and information in electronic health records will enhance continuity of care, decision support, and the exchange of comparable patient information. As part of this activity, working groups at the 2001, 2002, and 2003 Summit Conferences examined how to represent nursing information in the Health Level 7 (HL7) Reference Information Model (RIM).Design: The working groups represented the nursing process as a dynamic sequence of phases, each containing information specific to the activities of the phase. They used Universal Modeling Language (UML) to represent this domain knowledge in models. An Activity Diagram was used to create a dynamic model of the nursing process. After creating a structural model of the information used at each stage of the nursing process, the working groups mapped that information to the HL7 RIM. They used a hierarchical structure for the organization of nursing knowledge as the basis for a hierarchical model for "Findings about the patient." The modeling and mapping reported here were exploratory and preliminary, not exhaustive or definitive. The intent was to evaluate the feasibility of representing some types of nursing information consistently with HL7 standards.Measurements: The working groups conducted a small-scale validation by testing examples of nursing terminology against the HL7 RIM class "Observation."Results: It was feasible to map patient information from the proposed models to the RIM class "Observation." Examples illustrate the models and the mapping of nursing terminology to the HL7 RIM.Conclusion: It is possible to model and map nursing information into the comprehensive health care information model, the HL7 RIM. These models must evolve and undergo further validation by clinicians. The integration of nursing information, terminology, and processes in information models is a first step toward rendering nursing information machine-readable in electronic patient records and messages. An eventual practical result, after much more development, would be to create computable, structured information for nursing documentation.
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10.
  • Hedin, K, et al. (författare)
  • Liver guide for monitoring of chronic hepatitis C
  • 2000
  • Ingår i: JAMIA Journal of the American Medical Informatics Association. - 1067-5027 .- 1527-974X. ; , s. 340-343
  • Tidskriftsartikel (refereegranskat)abstract
    • The severity of chronic hepatitis C infection in the Individual patient is monitored using blood laboratory findings and liver biopsy. Lf blood test results could be shown to provide sufficient information concerning the disease, the invasive procedure of liver biopsy could perhaps be avoided in some instances. This study assessed the clinical relevance of blood laboratory tests for detecting disease-related changes. in the liver. Histopathological classification was used ta assign class membership of the patients and data mining operations were performed in an elaborate way on 19 different data sets. Disease activity could be detected by a small set of blood tests. Extended sets could identify more severe changes, but failed to distinguish them. The extracted rules are implemented as a part of the knowledge base of a corresponding decision support system aimed at specialists and general practitioners.
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