| 1. |
- Bang, Magnus, et al.
(författare)
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Cognitive design of a digital desk for the emergency room setting
- 2014
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Ingår i: AMIA Annual Symposium Proceedings. - 1942-597X. ; 2014, s. 274-281
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Tidskriftsartikel (refereegranskat)abstract
- Digital desk technology has a still mainly unexplored potential to support the everyday work of collaborating clinicians. This paper presents ER Desk - a digital desk that was designed to specifically support a team of healthcare professionals working in an emergency room setting. The underlying design requirements were elicited in a comprehensive distributed cognition study of paper-based practices in an emergency room of a middle-sized Swedish hospital. We present the user interface and visualization requirements for digital desks for small clinical emergency room teams. Moreover, we discuss key design issues more generally with a focus on supporting team awareness, cognition, and collaborative routines of healthcare personnel working in clinical environments such as emergency rooms and intensive care units.
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| 2. |
- Downs, J., et al.
(författare)
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Detection of Suicidality in Adolescents with Autism Spectrum Disorders : Developing a Natural Language Processing Approach for Use in Electronic Health Records
- 2017
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Ingår i: AMIA Annual Symposium Proceedings. - : NLM (Medline). - 1942-597X. ; 2017, s. 641-649
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Tidskriftsartikel (refereegranskat)abstract
- Over 15% of young people with autism spectrum disorders (ASD) will contemplate or attempt suicide during adolescence. Yet, there is limited evidence concerning risk factors for suicidality in childhood ASD. Electronic health records (EHRs) can be used to create retrospective clinical cohort data for large samples of children with ASD. However systems to accurately extract suicidality-related concepts need to be developed so that putative models of suicide risk in ASD can be explored. We present a systematic approach to 1) adapt Natural Language Processing (NLP) solutions to screen with high sensitivity for reference to suicidal constructs in a large clinical ASD EHR corpus (230,465 documents), and 2) evaluate within a screened subset of 500 patients, the performance of an NLP classification tool for positive and negated suicidal mentions within clinical text. When evaluated, the NLP classification tool showed high system performance for positive suicidality with precision, recall, and F1 scores all > 0.85 at a document and patient level. The application therefore provides accurate output for epidemiological research into the factors contributing to the onset and recurrence of suicidality, and potential utility within clinical settings as an automated surveillance or risk prediction tool for specialist ASD services.
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| 3. |
- Ekberg, Joakim, et al.
(författare)
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Impact of precautionary behaviors during outbreaks of pandemic influenza : modeling of regional differences
- 2009
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Ingår i: AMIA Annual Symposium Proceedings. - Rockville Pike, Bethesda MD, 20894 USA : American Medical Informatics Association. - 1942-597X. ; 2009, s. 163-167
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Tidskriftsartikel (refereegranskat)abstract
- Using time geographic theory for representation of population mixing, we set out to analyze the relative impact from precautionary behaviors on outbreaks of pandemic influenza in Europe and Asia. We extended an existing simulator environment with behavioral parameters from a population survey to model different behaviors. We found that precautionary behaviors even among a minority of the population can have a decisive effect on the probability of the outbreak to propagate. The results also display that assumptions strongly influences the outcome. Depending on the interpretation of how many "children" are kept from "school", R(0) changes from a range where outbreak progression is possible to a range where it is improbable in both European (R(0)=1.77/1.23) and Asian (R(0)=1.70/1.05) conditions. We conclude that unprompted distancing can have a decisive effect on pandemic propagation. An important response strategy can be to promote voluntary precautionary behavior shown to reduce disease transmission.
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| 4. |
- Eriksson, Henrik, et al.
(författare)
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A Flexible Simulation Architecture for Pandemic Influenza Simulation
- 2015
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Ingår i: AMIA Annual Symposium Proceedings. - : American Medical Informatics Association. - 1942-597X. ; 2015, s. 533-542
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Tidskriftsartikel (refereegranskat)abstract
- Simulation is an important resource for studying the dynamics of pandemic influenza and predicting the potential impact of interventions. However, there are several challenges for the design of such simulator architectures. Specifically, it is difficult to develop simulators that combine flexibility with run-time performance. This tradeoff is problematic in the pandemic-response setting because it makes it challenging to extend and adapt simulators for ongoing situations where rapid results are indispensable. Simulation architectures based on aspect-oriented programming can model specific concerns of the simulator and can allow developers to rapidly extend the simulator in new ways without sacrificing run-time performance. It is possible to use such aspects in conjunction with separate simulation models, which define community, disease, and intervention properties. The implication of this research for pandemic response is that aspects can add a novel layer of flexibility to simulation environments, which enables modelers to extend the simulator run-time component to new requirements that go beyond the original modeling framework.
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| 5. |
- Eriksson, Henrik, et al.
(författare)
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Assumptions management in simulation of infectious disease outbreaks
- 2009
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Ingår i: AMIA Annual Symposium Proceedings. - 1942-597X. ; 2009, s. 173-177
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Tidskriftsartikel (refereegranskat)abstract
- Simulation of outbreaks of infectious disease is an important tool for understanding the dynamics of the outbreak process, the impact of disease and population properties, and the potential effect of interventions. However, the interpretation of the simulation results requires a clear understanding of the assumptions made in the underlying model. Typical simulation tasks, such as exploring the space of different scenarios for population and disease properties, require multiple runs with varying model parameters. For such complex tasks, the management of the assumptions made becomes a daunting and potentially error-prone undertaking. We report explicit assumptions management as an approach to capture, model, and document the assumptions for simulator runs. It was found possible to extend ontology-based simulation, which uses an ontological model to parameterize the simulator, to incorporate an assumptions model in the ontology. We conclude that explicit assumptions modeling should be part of any infectious disease simulation architecture from start.
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| 6. |
- Göransson, Katarina, 1974-, et al.
(författare)
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A national survey of emergency department triage in Sweden
- 2003
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Ingår i: AMIA Annual Symposium Proceedings. - : American Medical Informatics Association. - 1942-597X. ; 2003, s. 851-851
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to identify the organisation of and knowledge about triage work in Swedish emergency departments (ED) as a first step to understanding what is necessary for decision support in ED triage systems in Sweden. A national survey using telephone interviews for data collection was used. Results showed great variety in how work regarding ED triage is organised and performed. The variety occurs in several areas including education, personnel performing triage, facilities available and scales used.
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| 7. |
- Kabukye, Johnblack K, et al.
(författare)
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User Requirements for an Electronic Medical Records System for Oncology in Developing Countries : A Case Study of Uganda.
- 2017
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Ingår i: AMIA ... Annual Symposium proceedings. AMIA Symposium. - 1942-597X. ; 2017, s. 1004-1013
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Konferensbidrag (refereegranskat)abstract
- Cancer is a major public health challenge in developing countries but the healthcare systems are not well prepared to deal with the epidemic. Health information technologies such as electronic medical records (EMRs) have the potential to improve cancer care yet their adoption remains low, in part due to EMR systems not meeting user requirements. This study aimed at analyzing the user requirements for an EMR for a cancer hospital in Uganda. A user-centered approach was taken, through focus group discussion and interviews with target end users to analyze workflow, challenges and wishes. Findings highlight the uniqueness of oncology in low-resource settings and the requirements including support for oncology-specific documentation, reuse of data for research and reporting, assistance with care coordination, computerized clinical decision support, and the need to meet the constraints in terms of technological infrastructure, stretched healthcare workforce and flexibility to allow variations and exceptions.
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| 8. |
- Li, Ying, et al.
(författare)
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Predicting Type 1 Diabetes Onset using Novel Survival Analysis with Biomarker Ontology
- 2020
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Ingår i: AMIA ... Annual Symposium proceedings. AMIA Symposium. - 1942-597X. ; 2020, s. 727-736
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Tidskriftsartikel (refereegranskat)abstract
- Type 1 diabetes (T1D) is a chronic autoimmune disease that affects about 1 in 300 children and up to 1 in 100 adults during their life-time1. Improvements in early prediction of T1D onset may help prevent diagnosis for diabetic ketoacidosis, a serious complication often associated with a missed or delayed T1D diagnosis. In addition to genetic factors, progression to T1D is strongly associated with immunologic factors that can be measured during clinical visits. We developed a T1D-specific ontology that captures the dynamic patterns of these biomarkers and used it together with a survival model, RankSvx, proposed in our prior work2. We applied this approach to a T1D dataset harmonized from three birth cohort studies from the United States, Finland, and Sweden. Results show that the dynamic biomarker patterns captured in the proposed ontology are able to improve prediction performance (in concordance index) by 5.3%, 3.3%, 2.8%, and 1.0% over baseline for 3, 6, 9, and 12 month duration windows, respectively.
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| 9. |
- Li, Zhiguo, et al.
(författare)
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Imputing Longitudinal Growth Data in International Pediatric Studies : Does CDC Reference Suffice?
- 2021
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Ingår i: AMIA ... Annual Symposium proceedings. AMIA Symposium. - 1942-597X. ; 2021, s. 754-762
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Tidskriftsartikel (refereegranskat)abstract
- This study investigates a missing value imputation approach for longitudinal growth data in pediatric studies from multiple countries. We analyzed a combined cohort from five natural history studies of type 1 diabetes (T1D) in the US and EU with longitudinal growth measurements for 23,201 subjects. We developed a multiple imputation methodology using LMS parameters of CDC reference data. We measured imputation errors on both combined and individual cohorts using mean absolute percentage error (MAPE) and normalized root-mean-square error (NRMSE). Our results show low imputation errors using CDC reference. Overall height imputation errors were lower than for weight. The largest MAPE for weight and height among all age groups was 4.8% and 1.7%, respectively. When comparing performance between CDC reference and country-specific growth charts, we found no significant differences for height (CDC vs. German: p =0.993, CDC vs. Swedish: p=0.368) and for weight (CDC vs. Swedish: p=0.513) for all ages.
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| 10. |
- Timpka, Toomas, et al.
(författare)
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A neighborhood susceptibility index for planning of local physical interventions in response to pandemic influenza outbreaks
- 2010
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Ingår i: AMIA Annual Symposium Proceedings. - 1942-597X. ; 2010, s. 792-796
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Tidskriftsartikel (refereegranskat)abstract
- The global spread of a novel A (H1N1) influenza virus in 2009 has highlighted the possibility of a devastating pandemic similar to the 'Spanish flu' of 1917-1918. Responding to such pandemics requires careful planning for the early phases where there is no availability of pandemic vaccine. We set out to compute a Neighborhood Influenza Susceptibility Index (NISI) describing the vulnerability of local communities of different geo-socio-physical structure to a pandemic influenza outbreak. We used a spatially explicit geo-physical model of Linköping municipality (pop. 136,240) in Sweden, and employed an ontology-modeling tool to define simulation models and transmission settings. We found considerable differences in NISI between neighborhoods corresponding to primary care areas with regard to early progress of the outbreak, as well as in terms of the total accumulated share of infected residents counted after the outbreak. The NISI can be used in local preparations of physical response measures during pandemics.
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