Literature DB >> 27170903

An Ontology for Telemedicine Systems Resiliency to Technological Context Variations in Pervasive Healthcare.

Nekane Larburu, Richard G A Bults, Marten J Van Sinderen, Ing Widya, Hermie J Hermens.   

Abstract

Clinical data are crucial for any medical case to study and understand a patient's condition and to give the patient the best possible treatment. Pervasive healthcare systems apply information and communication technology to enable the usage of ubiquitous clinical data by authorized medical persons. However, quality of clinical data in these applications is, to a large extent, determined by the technological context of the patient. A technological context is characterized by potential technological disruptions that affect optimal functioning of technological resources. The clinical data based on input from these technological resources can therefore have quality degradations. If these degradations are not noticed, the use of this clinical data can lead to wrong treatment decisions, which potentially puts the patient's safety at risk. This paper presents an ontology that specifies the relation among technological context, quality of clinical data, and patient treatment. The presented ontology provides a formal way to represent the knowledge to specify the effect of technological context variations in the clinical data quality and the impact of the clinical data quality on a patient's treatment. Accordingly, this ontology is the foundation for a quality of data framework that enables the development of telemedicine systems that are capable of adapting the treatment when the quality of the clinical data degrades, and thus guaranteeing patients' safety even when technological context varies.

Entities:  

Keywords:  Context; ontology; quality of data; telemedicine

Year:  2015        PMID: 27170903      PMCID: PMC4848059          DOI: 10.1109/JTEHM.2015.2458870

Source DB:  PubMed          Journal:  IEEE J Transl Eng Health Med        ISSN: 2168-2372            Impact factor:   3.316


  13 in total

Review 1.  Defining and improving data quality in medical registries: a literature review, case study, and generic framework.

Authors:  Danielle G T Arts; Nicolette F De Keizer; Gert-Jan Scheffer
Journal:  J Am Med Inform Assoc       Date:  2002 Nov-Dec       Impact factor: 4.497

2.  An ontology-based system for context-aware and configurable services to support home-based continuous care.

Authors:  Federica Paganelli; Dino Giuli
Journal:  IEEE Trans Inf Technol Biomed       Date:  2010-11-11

3.  Analyzing the effect of data quality on the accuracy of clinical decision support systems: a computer simulation approach.

Authors:  Sharique Hasan; Rema Padman
Journal:  AMIA Annu Symp Proc       Date:  2006

Review 4.  Decision support, knowledge representation and management in medicine.

Authors:  M Peleg; S Tu
Journal:  Yearb Med Inform       Date:  2006

5.  Uncertainty and decisions in medical informatics.

Authors:  P Szolovits
Journal:  Methods Inf Med       Date:  1995-03       Impact factor: 2.176

6.  Clinician perspectives on the quality of patient data used for clinical decision support: a qualitative study.

Authors:  James L McCormack; Joan S Ash
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

7.  Data quality in the outpatient setting: impact on clinical decision support systems.

Authors:  Eta S Berner; Ramkumar K Kasiraman; Feliciano Yu; Midge N Ray; Thomas K Houston
Journal:  AMIA Annu Symp Proc       Date:  2005

Review 8.  Grading quality of evidence and strength of recommendations in clinical practice guidelines: Part 2 of 3. The GRADE approach to grading quality of evidence about diagnostic tests and strategies.

Authors:  J L Brozek; E A Akl; R Jaeschke; D M Lang; P Bossuyt; P Glasziou; M Helfand; E Ueffing; P Alonso-Coello; J Meerpohl; B Phillips; A R Horvath; J Bousquet; G H Guyatt; H J Schünemann
Journal:  Allergy       Date:  2009-05-29       Impact factor: 13.146

Review 9.  Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research.

Authors:  Nicole Gray Weiskopf; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2012-06-25       Impact factor: 4.497

10.  Secure remote health monitoring with unreliable mobile devices.

Authors:  Minho Shin
Journal:  J Biomed Biotechnol       Date:  2012-07-15
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  1 in total

1.  A Pervasive Healthcare System for COPD Patients.

Authors:  Hicham Ajami; Hamid Mcheick; Karam Mustapha
Journal:  Diagnostics (Basel)       Date:  2019-10-01
  1 in total

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