Literature DB >> 23223709

Visualization of medical data based on EHR standards.

G Kopanitsa1, C Hildebrand, J Stausberg, K H Englmeier.   

Abstract

BACKGROUND: To organize an efficient interaction between a doctor and an EHR the data has to be presented in the most convenient way. Medical data presentation methods and models must be flexible in order to cover the needs of the users with different backgrounds and requirements. Most visualization methods are doctor oriented, however, there are indications that the involvement of patients can optimize healthcare.
OBJECTIVES: The research aims at specifying the state of the art of medical data visualization. The paper analyzes a number of projects and defines requirements for a generic ISO 13606 based data visualization method. In order to do so it starts with a systematic search for studies on EHR user interfaces.
METHODS: In order to identify best practices visualization methods were evaluated according to the following criteria: limits of application, customizability, re-usability. The visualization methods were compared by using specified criteria.
RESULTS: The review showed that the analyzed projects can contribute knowledge to the development of a generic visualization method. However, none of them proposed a model that meets all the necessary criteria for a re-usable standard based visualization method. The shortcomings were mostly related to the structure of current medical concept specifications.
CONCLUSION: The analysis showed that medical data visualization methods use hardcoded GUI, which gives little flexibility. So medical data visualization has to turn from a hardcoded user interface to generic methods. This requires a great effort because current standards are not suitable for organizing the management of visualization data. This contradiction between a generic method and a flexible and user-friendly data layout has to be overcome.

Entities:  

Mesh:

Year:  2012        PMID: 23223709     DOI: 10.3414/ME12-01-0016

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  8 in total

1.  Feasibility of Population Health Analytics and Data Visualization for Decision Support in the Infectious Diseases Domain: A pilot study.

Authors:  Don Roosan; Guilherme Del Fiol; Jorie Butler; Yarden Livnat; Jeanmarie Mayer; Matthew Samore; Makoto Jones; Charlene Weir
Journal:  Appl Clin Inform       Date:  2016-06-29       Impact factor: 2.342

2.  From bed to bench: bridging from informatics practice to theory: an exploratory analysis.

Authors:  R Haux; C U Lehmann
Journal:  Appl Clin Inform       Date:  2014-10-29       Impact factor: 2.342

3.  A Qualitative Study of the Barriers and Opportunities for Adoption of Web-Portals for Doctors and Patients in Russia.

Authors:  Georgy Kopanitsa
Journal:  J Med Syst       Date:  2017-03-07       Impact factor: 4.460

4.  Evaluation Study for an ISO 13606 Archetype Based Medical Data Visualization Method.

Authors:  Georgy Kopanitsa
Journal:  J Med Syst       Date:  2015-07-10       Impact factor: 4.460

5.  A complementary graphical method for reducing and analyzing large data sets. Case studies demonstrating thresholds setting and selection.

Authors:  X Jing; J J Cimino
Journal:  Methods Inf Med       Date:  2014-04-14       Impact factor: 2.176

6.  Design and development of a linked open data-based health information representation and visualization system: potentials and preliminary evaluation.

Authors:  Binyam Tilahun; Tomi Kauppinen; Carsten Keßler; Fleur Fritz
Journal:  JMIR Med Inform       Date:  2014-10-25

7.  Visualising linked health data to explore health events around preventable hospitalisations in NSW Australia.

Authors:  Michael O Falster; Louisa R Jorm; Alastair H Leyland
Journal:  BMJ Open       Date:  2016-09-07       Impact factor: 2.692

8.  Task-Data Taxonomy for Health Data Visualizations: Web-Based Survey With Experts and Older Adults.

Authors:  Sabine Theis; Peter Wilhelm Victor Rasche; Christina Bröhl; Matthias Wille; Alexander Mertens
Journal:  JMIR Med Inform       Date:  2018-07-09
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.