| 1. |
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| 2. |
- Blomström-Lundqvist, Carina, et al.
(author)
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Effect of Catheter Ablation vs Antiarrhythmic Medication on Quality of Life in Patients With Atrial Fibrillation : The CAPTAF Randomized Clinical Trial
- 2019
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In: JAMIA Journal of the American Medical Informatics Association. - Chicago : American Medical Association (AMA). - 1067-5027 .- 1527-974X .- 0098-7484 .- 1538-3598. ; 321:11, s. 1059-1068
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Journal article (peer-reviewed)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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| 3. |
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| 4. |
- Campbell, Walter S., et al.
(author)
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A computable pathology report for precision medicine: extending an observables ontology unifying SNOMED CT and LOINC
- 2018
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In: JAMIA Journal of the American Medical Informatics Association. - : OXFORD UNIV PRESS. - 1067-5027 .- 1527-974X. ; 25:3, s. 259-266
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Journal article (peer-reviewed)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. |
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| 6. |
- De Silva, Kushan, et al.
(author)
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A combined strategy of feature selection and machine learning to identify predictors of prediabetes
- 2020
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 27:3, s. 396-406
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Journal article (peer-reviewed)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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| 7. |
- Demiris, G., et al.
(author)
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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
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In: JAMIA Journal of the American Medical Informatics Association. - 1067-5027 .- 1527-974X. ; 15:1
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Journal article (peer-reviewed)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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| 8. |
- Dentler, Kathrin, et al.
(author)
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Formalization and computation of quality measures based on electronic medical records
- 2014
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In: JAMIA Journal of the American Medical Informatics Association. - : BMJ Publishing Group / Elsevier. - 1067-5027 .- 1527-974X. ; 21:2, s. 285-291
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Journal article (peer-reviewed)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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| 9. |
- Georgsson, Mattias
(author)
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Quantifying usability : an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics
- 2016
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 23:1, s. 5-11
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Journal article (peer-reviewed)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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| 10. |
- Goossen, William T. F., et al.
(author)
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Development of a provisional domain model for the nursing process for use within the Health Level 7 reference information model
- 2004
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In: JAMIA Journal of the American Medical Informatics Association. - Philadelphia, USA : Hanley & Belfus Inc.. - 1067-5027 .- 1527-974X. ; 11:3, s. 186-94
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Journal article (peer-reviewed)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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| 11. |
- Hedin, K, et al.
(author)
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Liver guide for monitoring of chronic hepatitis C
- 2000
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In: JAMIA Journal of the American Medical Informatics Association. - 1067-5027 .- 1527-974X. ; , s. 340-343
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Journal article (peer-reviewed)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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| 12. |
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| 13. |
- Hägglund, Maria, et al.
(author)
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Modeling shared care plans using CONTsys and openEHR to support shared homecare of the elderly.
- 2011
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press (OUP). - 1067-5027 .- 1527-974X. ; 18:1, s. 66-9
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Journal article (peer-reviewed)abstract
- This case report describes how two complementary standards, CONTsys (European Standard EN 13940-1 for continuity of care) and the reference model of openEHR, were applied in modeling a shared care plan for shared homecare based on requirements from the OLD@HOME project. Our study shows that these requirements are matched by CONTsys on a general level. However, certain attributes are not explicit in CONTsys, for example agents responsible for performing planned interventions, and support for monitoring outcome of interventions. We further studied how the care plan conceptual model can be implemented using the openEHR reference model. The study demonstrates the feasibility of developing shared care plans combining a standard concept model, for example CONTsys with an electronic health records (EHR) interoperability specification, that is the openEHR, while highlighting areas that need further exploration. It also explores the reusability of existing clinical archetypes as building blocks of care plans and the modeling of new shared care plan archetypes.
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| 14. |
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| 15. |
- King, Henry, et al.
(author)
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How, for whom, and in what contexts will artificial intelligence be adopted in pathology? A realist interview study
- 2023
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In: JAMIA Journal of the American Medical Informatics Association. - : OXFORD UNIV PRESS. - 1067-5027 .- 1527-974X. ; 30:3, s. 529-538
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Journal article (peer-reviewed)abstract
- Objective There is increasing interest in using artificial intelligence (AI) in pathology to improve accuracy and efficiency. Studies of clinicians perceptions of AI have found only moderate acceptability, suggesting further research is needed regarding integration into clinical practice. This study aimed to explore stakeholders theories concerning how and in what contexts AI is likely to become integrated into pathology. Materials and Methods A literature review provided tentative theories that were revised through a realist interview study with 20 pathologists and 5 pathology trainees. Questions sought to elicit whether, and in what ways, the tentative theories fitted with interviewees perceptions and experiences. Analysis focused on identifying the contextual factors that may support or constrain uptake of AI in pathology. Results Interviews highlighted the importance of trust in AI, with interviewees emphasizing evaluation and the opportunity for pathologists to become familiar with AI as means for establishing trust. Interviewees expressed a desire to be involved in design and implementation of AI tools, to ensure such tools address pressing needs, but needs vary by subspecialty. Workflow integration is desired but whether AI tools should work automatically will vary according to the task and the context. Conclusions It must not be assumed that AI tools that provide benefit in one subspecialty will provide benefit in others. Pathologists should be involved in the decision to introduce AI, with opportunity to assess strengths and weaknesses. Further research is needed concerning the evidence required to satisfy pathologists regarding the benefits of AI.
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| 16. |
- Kougia, Vasiliki, et al.
(author)
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RTEX : A novel framework for ranking, tagging, and explanatory diagnostic captioning of radiography exams
- 2021
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press (OUP). - 1067-5027 .- 1527-974X. ; 28:8, s. 1651-1659
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Journal article (peer-reviewed)abstract
- Objective: The study sought to assist practitioners in identifying and prioritizing radiography exams that are more likely to contain abnormalities, and provide them with a diagnosis in order to manage heavy workload more efficiently (eg, during a pandemic) or avoid mistakes due to tiredness.Materials and MethodsThis article introduces RTEx, a novel framework for (1) ranking radiography exams based on their probability to be abnormal, (2) generating abnormality tags for abnormal exams, and (3) providing a diagnostic explanation in natural language for each abnormal exam. Our framework consists of deep learning and retrieval methods and is assessed on 2 publicly available datasets.Results: For ranking, RTEx outperforms its competitors in terms of nDCG@k. The tagging component outperforms 2 strong competitor methods in terms of F1. Moreover, the diagnostic captioning component, which exploits the predicted tags to constrain the captioning process, outperforms 4 captioning competitors with respect to clinical precision and recall.Discussion: RTEx prioritizes abnormal exams toward the improvement of the healthcare workflow by introducing a ranking method. Also, for each abnormal radiography exam RTEx generates a set of abnormality tags alongside a diagnostic text to explain the tags and guide the medical expert. Human evaluation of the produced text shows that employing the generated tags offers consistency to the clinical correctness and that the sentences of each text have high clinical accuracy.Conclusions: This is the first framework that successfully combines 3 tasks: ranking, tagging, and diagnostic captioning with focus on radiography exams that contain abnormalities.
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| 17. |
- Lee, Dennis, et al.
(author)
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Literature review of SNOMED CT use
- 2014
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In: JAMIA Journal of the American Medical Informatics Association. - : BMJ Group. - 1067-5027 .- 1527-974X. ; 21:E1, s. E11-E19
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Research review (peer-reviewed)abstract
- OBJECTIVE: The aim of this paper is to report on the use of the systematised nomenclature of medicine clinical terms (SNOMED CT) by providing an overview of published papers.METHODS: Published papers on SNOMED CT between 2001 and 2012 were identified using PubMed and Embase databases using the keywords 'systematised nomenclature of medicine' and 'SNOMED CT'. For each paper the following characteristics were retrieved: SNOMED CT focus category (ie, indeterminate, theoretical, pre-development/design, implementation and evaluation/commodity), usage category (eg, prospective content coverage, used to classify or code in a study), medical domain and country.RESULTS: Our search strategy identified 488 papers. A comparison between the papers published between 2001-6 and 2007-12 showed an increase in every SNOMED CT focus category. The number of papers classified as 'theoretical' increased from 46 to 78, 'pre-development/design' increased from 61 to 173 and 'implementation' increased from 10 to 34. Papers classified as 'evaluation/commodity' only started to appear from 2010.CONCLUSIONS: The majority of studies focused on 'theoretical' and 'pre-development/design'. This is still encouraging as SNOMED CT is being harmonized with other standardized terminologies and is being evaluated to determine the content coverage of local terms, which is usually one of the first steps towards adoption. Most implementations are not published in the scientific literature, requiring a look beyond the scientific literature to gain insights into SNOMED CT implementations.
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| 18. |
- Low, Yen S., et al.
(author)
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Cheminformatics-aided pharmacovigilance : application to Stevens-Johnson Syndrome
- 2016
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press (OUP). - 1067-5027 .- 1527-974X. ; 23:5, s. 968-978
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Journal article (peer-reviewed)abstract
- Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%-81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations.
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| 19. |
- Ludvigsson, Jonas F., et al.
(author)
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Use of computerized algorithm to identify individuals in need of testing for celiac disease
- 2013
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press (OUP). - 1067-5027 .- 1527-974X. ; 20:E2, s. E306-E310
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Journal article (peer-reviewed)abstract
- Background and aim Celiac disease (CD) is a lifelong immune-mediated disease with excess mortality. Early diagnosis is important to minimize disease symptoms, complications, and consumption of healthcare resources. Most patients remain undiagnosed. We developed two electronic medical record (EMR)-based algorithms to identify patients at high risk of CD and in need of CD screening. Methods (I) Using natural language processing (NLP), we searched EMRs for 16 free text (and related) terms in 216 CD patients and 280 controls. (II) EMRs were also searched for ICD9 (International Classification of Disease) codes suggesting an increased risk of CD in 202 patients with CD and 524 controls. For each approach, we determined the optimal number of hits to be assigned as CD cases. To assess performance of these algorithms, sensitivity and specificity were calculated. Results Using two hits as the cut-off, the NLP algorithm identified 72.9% of all celiac patients (sensitivity), and ruled out CD in 89.9% of the controls (specificity). In a representative US population of individuals without a prior celiac diagnosis (assuming that 0.6% had undiagnosed CD), this NLP algorithm could identify a group of individuals where 4.2% would have CD (positive predictive value). ICD9 code search using three hits as the cut-off had a sensitivity of 17.1% and a specificity of 88.5% (positive predictive value was 0.9%). Discussion and conclusions This study shows that computerized EMR-based algorithms can help identify patients at high risk of CD. NLP-based techniques demonstrate higher sensitivity and positive predictive values than algorithms based on ICD9 code searches.
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| 20. |
- Martinez-Costa, Catalina, et al.
(author)
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Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case
- 2015
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press (OUP): Policy B - Oxford Open Option B - CC-BY / Elsevier. - 1067-5027 .- 1527-974X. ; 22:3, s. 565-576
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Journal article (peer-reviewed)abstract
- Objective To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Materials and Methods Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Results Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Discussion Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. Conclusion We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question.
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| 21. |
- Roberts, Kirk, et al.
(author)
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Biomedical informatics advancing the national health agenda : the AMIA 2015 year-in-review in clinical and consumer informatics.
- 2017
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; E1, s. E185-E190
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Journal article (peer-reviewed)abstract
- The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive.
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| 22. |
- Spjuth, Ola, 1977-, et al.
(author)
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E-Science technologies in a workflow for personalized medicine using cancer screening as a case study
- 2017
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In: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 24:5, s. 950-957
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Journal article (peer-reviewed)abstract
- Objective: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings.Materials and Methods: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences.Results: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform.Discussion and Conclusion: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.
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| 23. |
- Terner, Annika, et al.
(author)
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Predefined headings in a multiprofessional electronic health record system
- 2012
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In: JAMIA Journal of the American Medical Informatics Association. - Linköping : Oxford University Press (OUP). - 1067-5027 .- 1527-974X. ; 19:6, s. 1032-1038, s. 61-61
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Journal article (peer-reviewed)abstract
- BackgroundApplying multiprofessional electronic health records (EHRs) is expected to improve the quality of patient care and patient safety. Both EHR systems and system users depend on semantic interoperability to function efficiently. A shared clinical terminology comprising unambiguous terms is required for semantic interoperability. Empirical studies of clinical terminology, such as predefined headings, in EHR systems are scarce and limited to one profession or one clinical specialty.ObjectiveTo study predefined headings applied by users in a Swedish multiprofessional EHR system.Materials and methodsThis was a descriptive study of predefined headings (n=3596) applied by 5509 users in a Swedish multiprofessional EHR system. The predefined headings were classified into four term and word categories.ResultsLess than half of the predefined headings were shared by two or more professional groups. All eight professionals groups shared 1.7% of the predefined headings. The distribution of predefined headings across categories yielded two-thirds "terms for special purposes" and "specialist terms" and one-third "common words" and "unclassified headings".DiscussionThe indicated presence of profession-specific predefined headings and the conflict between ambiguity and comprehension of terms and words used as headings are discussed.ConclusionsThe predefined headings in the multiprofessional EHR system studied did not constitute a joint language for specific purposes. The improvement of the quality and usability of multiprofessional EHR systems requires attention.
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| 24. |
- Vimarlund, Vivian, et al.
(author)
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Information technology and knowledge exchange in health-care organizations
- 1999
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In: JAMIA Journal of the American Medical Informatics Association. - 1067-5027 .- 1527-974X. ; , s. 632-636
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Journal article (peer-reviewed)abstract
- Despite the increasing global interest in information technology among health care institutions, little has been discussed about its importance for the effectiveness of knowledge management. In this study, economic theories are used to analyze and describe a theoretical framework for the use of information technology in the exchange of knowledge. The analyses show that health care institutions would benefit from developing global problem-solving collaboration, which allows practitioners to exchange knowledge unrestricted by time and geographical barriers. The use of information technology for vertical integration of health-care institutions would reduce knowledge transaction costs, Le. decrease costs for negotiating and creating communication channels, and facilitating the determination of what, when, and how to produce knowledge. A global network would allow organizations to increase existing knowledge, and thus total productivity, while also supporting an environment where the generation of new ideas is unrestricted Using all the intellectual potential of market actors and thereby releasing economic resources can reduce today's global budget conflicts in the public sector, Le. the necessity to choose between health care services and for instance, schools and support for the elderly. In conclusion, global collaboration and coordination would reduce the transaction costs inherent in knowledge administration and allow a more effective total use of scarce health-care resources.
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- Åhlfeldt, Hans, et al.
(author)
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Towards a multi-professional patient record - A study of the headings used in clinical practice
- 1999
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In: JAMIA Journal of the American Medical Informatics Association. - 1067-5027 .- 1527-974X.
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Journal article (peer-reviewed)abstract
- This paper reports on the differences and similarities of headings used in patient records by Swedish health care professionals, nurses, occupational therapists, physiotherapists, dietitians, speech therapists, medical social workers and general practitioners. The background to the study is a national project where representatives from the different health care professions have worked together for two years in an effort to develop a multi-professional database of terms for the health care sector. The study reports on an analysis of the existing multi-professional lists of headings with respect to structure, degree of specialization, synonyms and homonyms. The study is descriptive in nature, gives a status report on the variety of headings used in clinical practice, provides necessary material for a normative approach focusing on a truly multi-professional patient record in the future.
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