Literature DB >> 25833768

Strategies for Medical Data Extraction and Presentation Part 3: Automated Context- and User-Specific Data Extraction.

Bruce Reiner1.   

Abstract

In current medical practice, data extraction is limited by a number of factors including lack of information system integration, manual workflow, excessive workloads, and lack of standardized databases. The combined limitations result in clinically important data often being overlooked, which can adversely affect clinical outcomes through the introduction of medical error, diminished diagnostic confidence, excessive utilization of medical services, and delays in diagnosis and treatment planning. Current technology development is largely inflexible and static in nature, which adversely affects functionality and usage among the diverse and heterogeneous population of end users. In order to address existing limitations in medical data extraction, alternative technology development strategies need to be considered which incorporate the creation of end user profile groups (to account for occupational differences among end users), customization options (accounting for individual end user needs and preferences), and context specificity of data (taking into account both the task being performed and data subject matter). Creation of the proposed context- and user-specific data extraction and presentation templates offers a number of theoretical benefits including automation and improved workflow, completeness in data search, ability to track and verify data sources, creation of computerized decision support and learning tools, and establishment of data-driven best practice guidelines.

Mesh:

Year:  2015        PMID: 25833768      PMCID: PMC4501961          DOI: 10.1007/s10278-015-9795-3

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  6 in total

Review 1.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

Authors:  Amit X Garg; Neill K J Adhikari; Heather McDonald; M Patricia Rosas-Arellano; P J Devereaux; Joseph Beyene; Justina Sam; R Brian Haynes
Journal:  JAMA       Date:  2005-03-09       Impact factor: 56.272

Review 2.  One size (doesn't) fit all.

Authors:  Bruce Reiner
Journal:  J Am Coll Radiol       Date:  2008-04       Impact factor: 5.532

3.  Strategies for medical data extraction and presentation part 1: current limitations and deficiencies.

Authors:  Bruce Reiner
Journal:  J Digit Imaging       Date:  2015-04       Impact factor: 4.056

Review 4.  Strategies for medical data extraction and presentation part 2: creating a customizable context and user-specific patient reference database.

Authors:  Bruce Reiner
Journal:  J Digit Imaging       Date:  2015-06       Impact factor: 4.056

5.  Reducing the frequency of errors in medicine using information technology.

Authors:  D W Bates; M Cohen; L L Leape; J M Overhage; M M Shabot; T Sheridan
Journal:  J Am Med Inform Assoc       Date:  2001 Jul-Aug       Impact factor: 4.497

Review 6.  Criteria for diagnosis, staging, risk stratification and response assessment of multiple myeloma.

Authors:  R A Kyle; S V Rajkumar
Journal:  Leukemia       Date:  2008-10-30       Impact factor: 11.528

  6 in total

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