Literature DB >> 26351216

Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings.

Bevin Cohen1, David K Vawdrey2, Jianfang Liu3, David Caplan4, E Yoko Furuya5, Frederick W Mis4, Elaine Larson3.   

Abstract

The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution's admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges.
© The Author(s) 2015.

Entities:  

Keywords:  informatics; outcomes measurement; research methodology

Mesh:

Year:  2015        PMID: 26351216      PMCID: PMC4679583          DOI: 10.1177/1527154415603358

Source DB:  PubMed          Journal:  Policy Polit Nurs Pract        ISSN: 1527-1544


  32 in total

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4.  The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting.

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Journal:  J Am Med Inform Assoc       Date:  2012-09-08       Impact factor: 4.497

5.  The inevitable application of big data to health care.

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6.  NIH's Big Data to Knowledge initiative and the advancement of biomedical informatics.

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Review 7.  Definition, structure, content, use and impacts of electronic health records: a review of the research literature.

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8.  Caveats for the use of operational electronic health record data in comparative effectiveness research.

Authors:  William R Hersh; Mark G Weiner; Peter J Embi; Judith R Logan; Philip R O Payne; Elmer V Bernstam; Harold P Lehmann; George Hripcsak; Timothy H Hartzog; James J Cimino; Joel H Saltz
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9.  The role of pre-operative and post-operative glucose control in surgical-site infections and mortality.

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Review 5.  The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness.

Authors:  Ho Ting Wong; Vico Chung Lim Chiang; Kup Sze Choi; Alice Yuen Loke
Journal:  Int J Environ Res Public Health       Date:  2016-10-17       Impact factor: 3.390

6.  Applying STOPP Guidelines in Primary Care Through Electronic Medical Record Decision Support: Randomized Control Trial Highlighting the Importance of Data Quality.

Authors:  Morgan Price; Iryna Davies; Raymond Rusk; Mary Lesperance; Jens Weber
Journal:  JMIR Med Inform       Date:  2017-06-15

7.  Incidence and physiological mechanism of carboplatin-induced electrolyte abnormality among patients with non-small cell lung cancer.

Authors:  Yushui Ma; Likun Hou; Fei Yu; Gaixia Lu; Shanshan Qin; Ruting Xie; Huiqiong Yang; Tingmiao Wu; Pei Luo; Li Chai; Zhongwei Lv; Xiaodong Peng; Chunyan Wu; Da Fu
Journal:  Oncotarget       Date:  2017-03-14

8.  Time-driven activity-based costing for patients with multiple chronic conditions: a mixed-method study to cost care in a multidisciplinary and integrated care delivery centre at a university-affiliated tertiary teaching hospital in Stockholm, Sweden.

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10.  Data extraction for epidemiological research (DExtER): a novel tool for automated clinical epidemiology studies.

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  10 in total

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