Literature DB >> 23304296

ICDA: a platform for Intelligent Care Delivery Analytics.

David Gotz1, Harry Stavropoulos, Jimeng Sun, Fei Wang.   

Abstract

The identification of high-risk patients is a critical component in improving patient outcomes and managing costs. This paper describes the Intelligent Care Delivery Analytics platform (ICDA), a system which enables risk assessment analytics that process large collections of dynamic electronic medical data to identify at-risk patients. ICDA works by ingesting large volumes of data into a common data model, then orchestrating a collection of analytics that identify at-risk patients. It also provides an interactive environment through which users can access and review the analytics results. In addition, ICDA provides APIs via which analytics results can be retrieved to surface in external applications. A detailed review of ICDA's architecture is provided. Descriptions of four use cases are included to illustrate ICDA's application within two different data environments. These use cases showcase the system's flexibility and exemplify the types of analytics it enables.

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Year:  2012        PMID: 23304296      PMCID: PMC3540495     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  13 in total

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Journal:  J Am Med Inform Assoc       Date:  2011-11-10       Impact factor: 4.497

2.  Evidence-based medicine in the EMR era.

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Journal:  N Engl J Med       Date:  2011-11-02       Impact factor: 91.245

3.  Multimorbidity: a challenge for evidence-based medicine.

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Journal:  Evid Based Med       Date:  2010-12

4.  In chronic condition: experiences of patients with complex health care needs, in eight countries, 2008.

Authors:  Cathy Schoen; Robin Osborn; Sabrina K H How; Michelle M Doty; Jordon Peugh
Journal:  Health Aff (Millwood)       Date:  2008-11-13       Impact factor: 6.301

5.  STREPTOMYCIN treatment of pulmonary tuberculosis.

Authors: 
Journal:  Br Med J       Date:  1948-10-30

6.  Predicting Patient's Trajectory of Physiological Data using Temporal Trends in Similar Patients: A System for Near-Term Prognostics.

Authors:  Shahram Ebadollahi; Jimeng Sun; David Gotz; Jianying Hu; Daby Sow; Chalapathy Neti
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

7.  The natural history of congestive heart failure: the Framingham study.

Authors:  P A McKee; W P Castelli; P M McNamara; W B Kannel
Journal:  N Engl J Med       Date:  1971-12-23       Impact factor: 91.245

8.  Predicting three-year kidney graft survival in recipients with systemic lupus erythematosus.

Authors:  Hongying Tang; Mollie R Poynton; John F Hurdle; Bradley C Baird; James K Koford; Alexander S Goldfarb-Rumyantzev
Journal:  ASAIO J       Date:  2011 Jul-Aug       Impact factor: 2.872

9.  Data mining model using simple and readily available factors could identify patients at high risk for hepatocellular carcinoma in chronic hepatitis C.

Authors:  Masayuki Kurosaki; Naoki Hiramatsu; Minoru Sakamoto; Yoshiyuki Suzuki; Manabu Iwasaki; Akihiro Tamori; Kentaro Matsuura; Sei Kakinuma; Fuminaka Sugauchi; Naoya Sakamoto; Mina Nakagawa; Namiki Izumi
Journal:  J Hepatol       Date:  2011-10-23       Impact factor: 25.083

10.  Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: the SHARPn project.

Authors:  Susan Rea; Jyotishman Pathak; Guergana Savova; Thomas A Oniki; Les Westberg; Calvin E Beebe; Cui Tao; Craig G Parker; Peter J Haug; Stanley M Huff; Christopher G Chute
Journal:  J Biomed Inform       Date:  2012-02-04       Impact factor: 6.317

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  6 in total

1.  Predicting changes in hypertension control using electronic health records from a chronic disease management program.

Authors:  Jimeng Sun; Candace D McNaughton; Ping Zhang; Adam Perer; Aris Gkoulalas-Divanis; Joshua C Denny; Jacqueline Kirby; Thomas Lasko; Alexander Saip; Bradley A Malin
Journal:  J Am Med Inform Assoc       Date:  2013-09-17       Impact factor: 4.497

Review 2.  "Big data" and the electronic health record.

Authors:  M K Ross; W Wei; L Ohno-Machado
Journal:  Yearb Med Inform       Date:  2014-08-15

Review 3.  A review of analytics and clinical informatics in health care.

Authors:  Allan F Simpao; Luis M Ahumada; Jorge A Gálvez; Mohamed A Rehman
Journal:  J Med Syst       Date:  2014-04-03       Impact factor: 4.460

4.  PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.

Authors:  Kenney Ng; Amol Ghoting; Steven R Steinhubl; Walter F Stewart; Bradley Malin; Jimeng Sun
Journal:  J Biomed Inform       Date:  2013-12-25       Impact factor: 6.317

5.  Patient Similarity: Emerging Concepts in Systems and Precision Medicine.

Authors:  Sherry-Ann Brown
Journal:  Front Physiol       Date:  2016-11-24       Impact factor: 4.566

Review 6.  Patient Similarity in Prediction Models Based on Health Data: A Scoping Review.

Authors:  Anis Sharafoddini; Joel A Dubin; Joon Lee
Journal:  JMIR Med Inform       Date:  2017-03-03
  6 in total

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