PMID- 25089026
OWN - NLM
STAT- MEDLINE
DCOM- 20150824
LR  - 20141208
IS  - 1532-0480 (Electronic)
IS  - 1532-0464 (Linking)
VI  - 52
DP  - 2014 Dec
TI  - Integrating electronic health record information to support integrated care: 
      practical application of ontologies to improve the accuracy of diabetes disease 
      registers.
PG  - 364-72
LID - S1532-0464(14)00179-8 [pii]
LID - 10.1016/j.jbi.2014.07.016 [doi]
AB  - BACKGROUND: Information in Electronic Health Records (EHRs) are being promoted 
      for use in clinical decision support, patient registers, measurement and 
      improvement of integration and quality of care, and translational research. To do 
      this EHR-derived data product creators need to logically integrate patient data 
      with information and knowledge from diverse sources and contexts. OBJECTIVE: To 
      examine the accuracy of an ontological multi-attribute approach to create a Type 
      2 Diabetes Mellitus (T2DM) register to support integrated care. METHODS: Guided 
      by Australian best practice guidelines, the T2DM diagnosis and management 
      ontology was conceptualized, contextualized and validated by clinicians; it was 
      then specified, formalized and implemented. The algorithm was standardized 
      against the domain ontology in SNOMED CT-AU. Accuracy of the implementation was 
      measured in 4 datasets of varying sizes (927-12,057 patients) and an integrated 
      dataset (23,793 patients). Results were cross-checked with sensitivity and 
      specificity calculated with 95% confidence intervals. RESULTS: Incrementally 
      integrating Reason for Visit (RFV), medication (Rx), and pathology in the 
      algorithm identified nearly100% of T2DM cases. Incrementally integrating the four 
      datasets improved accuracy; controlling for sample size, data incompleteness and 
      duplicates. Manual validation confirmed the accuracy of the algorithm. 
      CONCLUSION: Integrating multiple data elements within an EHR using ontology-based 
      case-finding algorithms can improve the accuracy of the diagnosis and compensate 
      for suboptimal data quality, and hence creating a dataset that is more 
      fit-for-purpose. This clinical and pragmatic application of ontologies to EHR 
      data improves the integration of data and the potential for better use of data to 
      improve the quality of care.
CI  - Copyright (c) 2014 Elsevier Inc. All rights reserved.
FAU - Liaw, Siaw-Teng
AU  - Liaw ST
AD  - School of Public Health and Community Medicine, UNSW Medicine, Sydney, Australia; 
      Centre for PHC & Equity, UNSW Medicine, Sydney, Australia; Academic General 
      Practice Unit, South Western Sydney Local Health District, NSW, Australia. 
      Electronic address: siaw@unsw.edu.au.
FAU - Taggart, Jane
AU  - Taggart J
AD  - Centre for PHC & Equity, UNSW Medicine, Sydney, Australia.
FAU - Yu, Hairong
AU  - Yu H
AD  - Centre for PHC & Equity, UNSW Medicine, Sydney, Australia.
FAU - de Lusignan, Simon
AU  - de Lusignan S
AD  - University of Surrey, Guildford, UK.
FAU - Kuziemsky, Craig
AU  - Kuziemsky C
AD  - Telfer School of Management, University of Ottawa, Ottawa, Canada.
FAU - Hayen, Andrew
AU  - Hayen A
AD  - School of Public Health and Community Medicine, UNSW Medicine, Sydney, Australia.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140801
PL  - United States
TA  - J Biomed Inform
JT  - Journal of biomedical informatics
JID - 100970413
SB  - IM
MH  - Algorithms
MH  - Australia
MH  - *Biological Ontologies
MH  - Delivery of Health Care, Integrated/*methods
MH  - Diabetes Mellitus, Type 2/*diagnosis
MH  - Electronic Health Records/*classification
MH  - Humans
OTO - NOTNLM
OT  - Case finding
OT  - EHR
OT  - Integration
OT  - Knowledge engineering
OT  - Ontology
OT  - Patient register
EDAT- 2014/08/05 06:00
MHDA- 2015/08/25 06:00
CRDT- 2014/08/05 06:00
PHST- 2014/03/17 00:00 [received]
PHST- 2014/07/21 00:00 [revised]
PHST- 2014/07/23 00:00 [accepted]
PHST- 2014/08/05 06:00 [entrez]
PHST- 2014/08/05 06:00 [pubmed]
PHST- 2015/08/25 06:00 [medline]
AID - S1532-0464(14)00179-8 [pii]
AID - 10.1016/j.jbi.2014.07.016 [doi]
PST - ppublish
SO  - J Biomed Inform. 2014 Dec;52:364-72. doi: 10.1016/j.jbi.2014.07.016. Epub 2014 
      Aug 1.