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Relevant bibliographies by topics / Temporal clinical data warehouse

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Journal articles

Academic literature on the topic 'Temporal clinical data warehouse'

Author: Grafiati

Published: 11 March 2023

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Journal articles on the topic "Temporal clinical data warehouse"

1

Garani, Georgia, and Canan Eren Atay. "Encountering Incomplete Temporal Information in Clinical Data Warehouses." International Journal of Applied Research on Public Health Management 5, no. 1 (2020): 32–48. http://dx.doi.org/10.4018/ijarphm.2020010103.

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A clinical data warehouse (CDW) can be an important tool for the purposes of analysis and critical decision making in the medical field. Such a data repository integrates heterogeneous health data, including clinical, treatment and diagnostic data and laboratory test results from a variety of sources. Accurate data need to be stored and processed in a CDW with adequate computation capabilities and thus, time plays a crucial factor. A slowly changing dimension (SCD) is a dimension that changes slowly over time, either gradually or intermittently. This article introduces a new SCD type, Type BTA

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2

Looten, Vincent, Liliane Kong Win Chang, Antoine Neuraz, et al. "What can millions of laboratory test results tell us about the temporal aspect of data quality? Study of data spanning 17 years in a clinical data warehouse." Computer Methods and Programs in Biomedicine 181 (November 2019): 104825. http://dx.doi.org/10.1016/j.cmpb.2018.12.030.

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3

Dagliati, Arianna, Lucia Sacchi, Valentina Tibollo, et al. "A dashboard-based system for supporting diabetes care." Journal of the American Medical Informatics Association 25, no. 5 (2018): 538–47. http://dx.doi.org/10.1093/jamia/ocx159.

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Abstract Objective To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice. Methods The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, c

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4

Taweel, A., S. Miles, B. C. Delaney, and R. Bache. "An Eligibility Criteria Query Language for Heterogeneous Data Warehouses." Methods of Information in Medicine 54, no. 01 (2015): 41–44. http://dx.doi.org/10.3414/me13-02-0027.

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SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Managing Interoperability and Complexity in Health Systems”.Objectives: The increasing availability of electronic clinical data provides great potential for finding eligible patients for clinical research. However, data heterogeneity makes it difficult for clinical researchers to interrogate sources consistently. Existing standard query languages are often not sufficient to query across diverse representations. Thus, a higher- level domain language is needed so that queries become data-repres

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Suzuki, Hiroyuki, Eli Perencevich, Daniel Diekema, et al. "1031. Nationwide Temporal Trends of Candidemia Incidence Over 18 Years Within the Veteran Health Administration System." Open Forum Infectious Diseases 5, suppl_1 (2018): S307. http://dx.doi.org/10.1093/ofid/ofy210.868.

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Abstract Background Bloodstream infection due to Candida spp. is common and associated with significant mortality and morbidity. Previous population-based studies in 2000s and early 2010s have suggested that the incidence of candidemia might be increasing, presumably due to widespread use of central lines and broad-spectrum antibiotics. However, recent trends of candidemia incidence have not been not well described. Methods We conducted a retrospective cohort study of all veterans cared for in the Veterans Health Administration (VHA) system from January 2000 to December 2017 to determine the i

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6

Lee, Kyeryoung, Zongzhi Liu, Meng Ma, et al. "Analyzing treatment patterns and time to the next treatment in chronic lymphocytic leukemia real-world data using automated temporal phenotyping." Journal of Clinical Oncology 39, no. 15_suppl (2021): e19512-e19512. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e19512.

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e19512 Background: Targeted therapy is an important treatment for chronic lymphocytic leukemia (CLL). However, optimal strategies for deploying small molecule inhibitors or antibody therapies in the real world are not well understood, largely due to a lack of outcomes data. We implemented a novel temporal phenotyping algorithm pipeline to derive lines of therapy (LOT) and disease progression in CLL patients. Here, the CLL treatment pattern and time to the next treatment (TTNT) were analyzed in real-world data (RWD) using patient electronic health records. Methods: We identified a CLL cohort wi

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7

Ross, Mindy K., Henry Zheng, Bing Zhu, et al. "Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution." Methods of Information in Medicine 59, no. 06 (2020): 219–26. http://dx.doi.org/10.1055/s-0041-1729951.

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Abstract Objectives Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients from the electronic health record is consequently challenging as current algorithms (computable phenotypes) rely on diagnostic codes (e.g., International Classification of Disease, ICD) in addition to other criteria (e.g., inhaler medications)—but presume an accurate diagnosis. As such, there is no universally accepted or rigorously tested co

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8

Morgan, Ethan, Sam Hohmann, Jessica P. Ridgway, Robert S. Daum, and Michael Z. David. "Decreasing Incidence of Skin and Soft-tissue Infections in 86 US Emergency Departments, 2009–2014." Clinical Infectious Diseases 68, no. 3 (2018): 453–59. http://dx.doi.org/10.1093/cid/ciy509.

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Abstract Background The incidence of skin and soft-tissue infections (SSTIs), for which human immunodeficiency virus (HIV) is a significant risk factor, in United States emergency departments (EDs) increased dramatically after 2000 with the emergence of community-associated methicillin-resistant Staphylococcus aureus. Few studies have examined SSTI incidence among HIV-infected and non–HIV-infected patients in the United States after 2010. Methods Data were obtained for patient encounters at all academic medical center EDs affiliated with the Vizient clinical data warehouse assigned an SSTI-ass

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9

Ma, Meng, Arielle Redfern, Xiang Zhou, et al. "Automated abstraction of real-world clinical outcome in lung cancer: A natural language processing and artificial intelligence approach from electronic health records." Journal of Clinical Oncology 38, no. 15_suppl (2020): e14062-e14062. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e14062.

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e14062 Background: Real world evidence generated from electronic health records (EHRs) is playing an increasing role in health care decisions. It has been recognized as an essential element to assess cancer outcomes in real-world settings. Automatically abstracting outcomes from notes is becoming a fundamental challenge in medical informatics. In this study, we aim to develop a system to automatically abstract outcomes (Progression, Response, Stable Disease) from notes in lung cancer. Methods: A lung cancer cohort (n = 5,003) was obtained from the Mount Sinai Data Warehouse. The progress, path

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10

Garani, Georgia, George K. Adam, and Dimitrios Ventzas. "Temporal data warehouse logical modelling." International Journal of Data Mining, Modelling and Management 8, no. 2 (2016): 144. http://dx.doi.org/10.1504/ijdmmm.2016.077156.

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