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Cornet, Ronald
Publications (10 of 16) Show all publications
Scott, P. J., Cornet, R., McCowan, C., Peek, N., Fraccaro, P., Geifman, N., . . . Williams, R. (2017). Informatics for Health 2017: Advancing both science and practice. In: : . Paper presented at The Informatics for Health congress, 24-26 April 2017, in Manchester,UK (pp. 1-185). BCS, The Chartered Institute for IT, 24(1)
Open this publication in new window or tab >>Informatics for Health 2017: Advancing both science and practice
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2017 (English)Conference paper (Other academic)
Abstract [en]

The Informatics for Health congress, 24-26 April 2017, in Manchester, UK, brought together the Medical Informatics Europe (MIE) conference and the Farr Institute International Conference. This special issue of the Journal of Innovation in Health Informatics contains 113 presentation abstracts and 149 poster abstracts from the congress.

Place, publisher, year, edition, pages
BCS, The Chartered Institute for IT, 2017
Keywords
Computing methodologies; Informatics; Medical Records Systems, Computerized; Policy; Research
National Category
Other Health Sciences Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-146057 (URN)10.14236/jhi.v24i1.939 (DOI)28665785 (PubMedID)
Conference
The Informatics for Health congress, 24-26 April 2017, in Manchester,UK
Note

Konferensrapport

Available from: 2018-03-29 Created: 2018-03-29 Last updated: 2018-03-29
Oluoch, T., Katana, A., Kwaro, D., Santas, X., Langat, P., Mwalili, S., . . . de Keizer, N. (2016). Effect of a clinical decision support system on early action on immunological treatment failure in patients with HIV in Kenya: a cluster randomised controlled trial. LANCET HIV, 3(2), E76-E84
Open this publication in new window or tab >>Effect of a clinical decision support system on early action on immunological treatment failure in patients with HIV in Kenya: a cluster randomised controlled trial
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2016 (English)In: LANCET HIV, ISSN 2352-3018, Vol. 3, no 2, p. E76-E84Article in journal (Refereed) Published
Abstract [en]

Background A clinical decision support system (CDSS) is a computer program that applies a set of rules to data stored in electronic health records to off er actionable recommendations. We aimed to establish whether a CDSS that supports detection of immunological treatment failure among patients with HIV taking antiretroviral therapy (ART) would improve appropriate and timely action. Methods We did this prospective, cluster randomised controlled trial in adults and children (aged >= 18 months) who were eligible for, and receiving, ART at HIV clinics in Siaya County, western Kenya. Health facilities were randomly assigned (1: 1), via block randomisation (block size of two) with a computer-generated random number sequence, to use electronic health records either alone (control) or with CDSS (intervention). Facilities were matched by type and by number of patients enrolled in HIV care. The primary outcome measure was the difference between groups in the proportion of patients who experienced immunological treatment failure and had a documented clinical action. We used generalised linear mixed models with random effects to analyse clustered data. This trial is registered with ClinicalTrials.gov, number NCT01634802. Findings Between Sept 1, 2012, and Jan 31, 2014, 13 clinics, comprising 41 062 patients, were randomly assigned to the control group (n=6) or the intervention group (n=7). Data collection at each site took 12 months. Among patients eligible for ART, 10 358 (99%) of 10 478 patients were receiving ART at control sites and 10 991 (99%) of 11 028 patients were receiving ART at intervention sites. Of these patients, 1125 (11%) in the control group and 1342 (12%) in the intervention group had immunological treatment failure, of whom 332 (30%) and 727 (54%), respectively, received appropriate action. The likelihood of clinicians taking appropriate action on treatment failure was higher with CDSS alerts than with no decision support system (adjusted odds ratio 3.18, 95% CI 1.02-9.87). Interpretation CDSS significantly improved the likelihood of appropriate and timely action on immunological treatment failure. We expect our findings will be generalisable to virological monitoring of patients with HIV receiving ART once countries implement the 2015 WHO recommendation to scale up viral load monitoring.

Place, publisher, year, edition, pages
ELSEVIER INC, 2016
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-126848 (URN)10.1016/S2352-3018(15)00242-8 (DOI)000371834700007 ()
Note

Funding Agencies|US Presidents Emergency Plan for AIDS Relief (PEPFAR) through the US Centers for Disease Control and Prevention (CDC), Division of Global HIV/AIDS, under a KEMRI-CDC Cooperative Agreement [GH000048-04]

Available from: 2016-04-05 Created: 2016-04-05 Last updated: 2016-04-05
Joukes, E., Cornet, R., de Bruijne, M. C. & de Keizer, N. F. (2016). Eliciting end-user expectations to guide the implementation process of a new electronic health record: A case study using concept mapping. International Journal of Medical Informatics, 87, 111-117
Open this publication in new window or tab >>Eliciting end-user expectations to guide the implementation process of a new electronic health record: A case study using concept mapping
2016 (English)In: International Journal of Medical Informatics, ISSN 1386-5056, E-ISSN 1872-8243, Vol. 87, p. 111-117Article in journal (Refereed) Published
Abstract [en]

Objective: To evaluate the usability of concept mapping to elicit the expectations of healthcare professionals regarding the implementation of a new electronic health record (EHR). These expectations need to be taken into account during the implementation process to maximize the chance of success of the EHR. Setting: Two university hospitals in Amsterdam, The Netherlands, in the preparation phase of jointly implementing a new EHR. During this study the hospitals had different methods of documenting patient information (legacy EHR vs. paper-based records). Method: Concept mapping was used to determine and classify the expectations of healthcare professionals regarding the implementation of a new EHR. A multidisciplinary group of 46 healthcare professionals from both university hospitals participated in this study. Expectations were elicited in focus groups, their relevance and feasibility were assessed through a web-questionnaire. Nonmetric multidimensional scaling and clustering methods were used to identify clusters of expectations. Results: We found nine clusters of expectations, each covering an important topic to enable the healthcare professionals to work properly with the new EHR once implemented: usability, data use and reuse, facility conditions, data registration, support, training, internal communication, patients, and collaboration. Average importance and feasibility of each of the clusters was high. Conclusion: Concept mapping is an effective method to find topics that, according to healthcare professionals, are important to consider during the implementation of a new EHR. The method helps to combine the input of a large group of stakeholders at limited efforts. (C) 2016 Elsevier Ireland Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD, 2016
Keywords
Concept mapping; Electronic health record; Implementation; Healthcare professional; Expectation
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-125291 (URN)10.1016/j.ijmedinf.2015.12.014 (DOI)000368769900013 ()26806718 (PubMedID)
Available from: 2016-02-24 Created: 2016-02-19 Last updated: 2017-11-30
Oluoch, T., de Keizer, N., Langat, P., Alaska, I., Ochieng, K., Okeyo, N., . . . Cornet, R. (2015). A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution. Journal of Biomedical Informatics, 56, 387-394
Open this publication in new window or tab >>A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution
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2015 (English)In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 56, p. 387-394Article in journal (Refereed) Published
Abstract [en]

Introduction: Several studies conducted in sub-Saharan Africa (SSA) have shown that routine clinical data in HIV clinics often have errors. Lack of structured and coded documentation of diagnosis of AIDS defining illnesses (ADIs) can compromise data quality and decisions made on clinical care. Methods: We used a structured framework to derive a reference set of concepts and terms used to describe ADIs. The four sources used were: (i) CDC/Accenture list of opportunistic infections, (ii) SNOMED Clinical Terms (SNOMED CT), (iii) Focus Group Discussion (FGD) among clinicians and nurses attending to patients at a referral provincial hospital in western Kenya, and (iv) chart abstraction from the Maternal Child Health (MCH) and HIV clinics at the same hospital. Using the January 2014 release of SNOMED CT, concepts were retrieved that matched terms abstracted from approach iii and iv, and the content coverage assessed. Post-coordination matching was applied when needed. Results: The final reference set had 1054 unique ADI concepts which were described by 1860 unique terms. Content coverage of SNOMED CT was high (99.9% with pre-coordinated concepts; 100% with post-coordination). The resulting reference set for ADIs was implemented as the interface terminology on OpenMRS data entry forms. Conclusion: Different sources demonstrate complementarity in the collection of concepts and terms for an interface terminology. SNOMED CT provides a high coverage in the domain of ADIs. Further work is needed to evaluate the effect of the interface terminology on data quality and quality of care.

Place, publisher, year, edition, pages
Elsevier, 2015
Keywords
AIDS; SNOMED CT; AIDS-related opportunistic infections; Developing countries; Quality of healthcare
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-121320 (URN)10.1016/j.jbi.2015.07.009 (DOI)000359752100035 ()26184057 (PubMedID)
Note

Funding Agencies|U.S. Presidents Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Centers for Disease Control and Prevention (CDC), Division of HIV/AIDS (DGHA), under KEMRI/CDC Cooperative Agreement [GH000048-04]

Available from: 2015-09-16 Created: 2015-09-14 Last updated: 2017-12-04
Rosenbeck Goeg, K., Cornet, R. & Kjaer Andersen, S. (2015). Clustering clinical models from local electronic health records based on semantic similarity. Journal of Biomedical Informatics, 54, 294-304
Open this publication in new window or tab >>Clustering clinical models from local electronic health records based on semantic similarity
2015 (English)In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 54, p. 294-304Article in journal (Refereed) Published
Abstract [en]

Background: Clinical models in electronic health records are typically expressed as templates which support the multiple clinical workflows in which the system is used. The templates are often designed using local rather than standard information models and terminology, which hinders semantic interoperability. Semantic challenges can be solved by harmonizing and standardizing clinical models. However, methods supporting harmonization based on existing clinical models are lacking. One approach is to explore semantic similarity estimation as a basis of an analytical framework. Therefore, the aim of this study is to develop and apply methods for intrinsic similarity-estimation based analysis that can compare and give an overview of multiple clinical models. Method: For a similarity estimate to be intrinsic it should be based on an established ontology, for which SNOMED CT was chosen. In this study, Lin similarity estimates and Sokal and Sneath similarity estimates were used together with two aggregation techniques (average and best-match-average respectively) resulting in a total of four methods. The similarity estimations are used to hierarchically cluster templates. The test material consists of templates from Danish and Swedish EHR systems. The test material was used to evaluate how the four different methods perform. Result and discussion: The best-match-average aggregation technique performed better in terms of clustering similar templates than the average aggregation technique. No difference could be seen in terms of the choice of similarity estimate in this study, but the finding may be different for other datasets. The dendrograms resulting from the hierarchical clustering gave an overview of the templates and a basis of further analysis. Conclusion: Hierarchical clustering of templates based on SNOMED CT and semantic similarity estimation with best-match-average aggregation technique can be used for comparison and summarization of multiple templates. Consequently, it can provide a valuable tool for harmonization and standardization of clinical models.

Place, publisher, year, edition, pages
Elsevier, 2015
Keywords
Computerized medical records; Semantics; SNOMED CT; Medical record linkage/standards; Medical record linkage/methods; Algorithms
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-118874 (URN)10.1016/j.jbi.2014.12.015 (DOI)000353932500028 ()25557885 (PubMedID)
Available from: 2015-06-04 Created: 2015-06-04 Last updated: 2017-12-04
Dentler, K. & Cornet, R. (2015). Intra-axiom redundancies in SNOMED CT. Artificial Intelligence in Medicine, 65(1), 29-34
Open this publication in new window or tab >>Intra-axiom redundancies in SNOMED CT
2015 (English)In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 65, no 1, p. 29-34Article in journal (Refereed) Published
Abstract [en]

Objective: Intra-axiom redundancies are elements of concept definitions that are redundant as they are entailed by other elements of the concept definition. While such redundancies are harmless from a logical point of view, they make concept definitions hard to maintain, and they might lead to content-related problems when concepts evolve. The objective of this study is to develop a fully automated method to detect intra-axiom redundancies in OWL 2 EL and apply it to SNOMED Clinical Terms (SNOMED CT). Materials and methods: We developed a software program in which we implemented, adapted and extended readily existing rules for redundancy elimination. With this, we analysed occurence of redundancy in 11 releases of SNOMED CT(January 2009 to January 2014). We used the ELK reasoner to classify SNOMED CT, and Pellet for explanation of equivalence. We analysed the completeness and soundness of the results by an in-depth examination of the identified redundant elements in the July 2012 release of SNOMED CT. To determine if concepts with redundant elements lead to maintenance issues, we analysed a small sample of solved redundancies. Results: Analyses showed that the amount of redundantly defined concepts in SNOMED CT is consistently around 35,000. In the July 2012 version of SNOMED CT, 35,010(12%) of the 296,433 concepts contained redundant elements in their definitions. The results of applying our method are sound and complete with respect to our evaluation. Analysis of solved redundancies suggests that redundancies in concept definitions lead to inadequate maintenance of SNOMED CT. Conclusions: Our analysis revealed that redundant elements are continuously introduced and removed, and that redundant elements may be overlooked when concept definitions are corrected. Applying our redundancy detection method to remove intra-axiom redundancies from the stated form of SNOMED CT and to point knowledge modellers to newly introduced redundancies can support creating and maintaining a redundancy-free version of SNOMED CT. (C) 2014 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV, 2015
Keywords
Automated auditing method; Intra-axiom redundancies; OWL 2 EL; Clinical terminology; SNOMED CT
National Category
Medical Biotechnology
Identifiers
urn:nbn:se:liu:diva-122213 (URN)10.1016/j.artmed.2014.10.003 (DOI)000362140700004 ()25455563 (PubMedID)
Available from: 2015-10-26 Created: 2015-10-23 Last updated: 2017-12-01
Schulz, S., Martínez-Costa, C., Karlsson, D., Cornet, R., Brochhausen, M. & Rector, A. (2014). An Ontological Analysis of Reference in Health Record Statements. In: Pawel Garbacz, Oliver Kutz (Ed.), Formal Ontology in Information Systems: . Paper presented at The 8th International Conference on Formal Ontology in Information Systems, Rio de Janeiro, Brazil, September 22-25, 2014 (pp. 289-302). Amsterdam: IOS Press, 267
Open this publication in new window or tab >>An Ontological Analysis of Reference in Health Record Statements
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2014 (English)In: Formal Ontology in Information Systems / [ed] Pawel Garbacz, Oliver Kutz, Amsterdam: IOS Press, 2014, Vol. 267, p. 289-302Conference paper, Published paper (Refereed)
Abstract [en]

The relation between an information entity and its referent can be described as a second-order statement, as long as the referent is a type. This is typical for medical discourse such as diagnostic statements in electronic health records (EHRs), which often express hypotheses or probability assertions about the existence of an instance of, e.g. a disease type. This paper presents several approximations using description logics and a query language, the entailments of which are checked against a reference standard. Their pros and cons are discussed in the light of formal ontology and logic.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2014
Series
Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389, E-ISSN 1879-8314 ; 267
Keywords
Information Entities, biomedical ontology, medical diagnosis, description logics
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-128908 (URN)10.3233/978-1-61499-438-1-289 (DOI)9781614994374 (ISBN)9781614994381 (ISBN)
Conference
The 8th International Conference on Formal Ontology in Information Systems, Rio de Janeiro, Brazil, September 22-25, 2014
Available from: 2016-06-07 Created: 2016-06-07 Last updated: 2018-01-30Bibliographically approved
Dentler, K., Numans, M. E., ten Teije, A., Cornet, R. & de Keizer, N. F. (2014). Formalization and computation of quality measures based on electronic medical records. JAMIA Journal of the American Medical Informatics Association, 21(2), 285-291
Open this publication in new window or tab >>Formalization and computation of quality measures based on electronic medical records
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2014 (English)In: JAMIA Journal of the American Medical Informatics Association, ISSN 1067-5027, E-ISSN 1527-974X, Vol. 21, no 2, p. 285-291Article in journal (Refereed) Published
Abstract [en]

Objective Ambiguous definitions of quality measures in natural language impede their automated computability and also the reproducibility, validity, timeliness, traceability, comparability, and interpretability of computed results. Therefore, quality measures should be formalized before their release. We have previously developed and successfully applied a method for clinical indicator formalization (CLIF). The objective of our present study is to test whether CLIF is generalizablethat is, applicable to a large set of heterogeneous measures of different types and from various domains. Materials and methods We formalized the entire set of 159 Dutch quality measures for general practice, which contains structure, process, and outcome measures and covers seven domains. We relied on a web-based tool to facilitate the application of our method. Subsequently, we computed the measures on the basis of a large database of real patient data. Results Our CLIF method enabled us to fully formalize 100% of the measures. Owing to missing functionality, the accompanying tool could support full formalization of only 86% of the quality measures into Structured Query Language (SQL) queries. The remaining 14% of the measures required manual application of our CLIF method by directly translating the respective criteria into SQL. The results obtained by computing the measures show a strong correlation with results computed independently by two other parties. Conclusions The CLIF method covers all quality measures after having been extended by an additional step. Our web tool requires further refinement for CLIF to be applied completely automatically. We therefore conclude that CLIF is sufficiently generalizable to be able to formalize the entire set of Dutch quality measures for general practice.

Place, publisher, year, edition, pages
BMJ Publishing Group / Elsevier, 2014
Keywords
Quality Measures; Quality Indicators; Electronic Medical Record; Secondary Use of Patient Data; Identification of Patient Cohorts; EMR-driven Phenotyping
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-105749 (URN)10.1136/amiajnl-2013-001921 (DOI)000331263600015 ()
Available from: 2014-04-07 Created: 2014-04-04 Last updated: 2017-12-05
Lee, D., de Keizer, N., Lau, F. & Cornet, R. (2014). Literature review of SNOMED CT use. JAMIA Journal of the American Medical Informatics Association, 21(E1), E11-E19
Open this publication in new window or tab >>Literature review of SNOMED CT use
2014 (English)In: JAMIA Journal of the American Medical Informatics Association, ISSN 1067-5027, E-ISSN 1527-974X, Vol. 21, no E1, p. E11-E19Article, review/survey (Refereed) Published
Abstract [en]

OBJECTIVE: The aim of this paper is to report on the use of the systematised nomenclature of medicine clinical terms (SNOMED CT) by providing an overview of published papers.

METHODS: Published papers on SNOMED CT between 2001 and 2012 were identified using PubMed and Embase databases using the keywords 'systematised nomenclature of medicine' and 'SNOMED CT'. For each paper the following characteristics were retrieved: SNOMED CT focus category (ie, indeterminate, theoretical, pre-development/design, implementation and evaluation/commodity), usage category (eg, prospective content coverage, used to classify or code in a study), medical domain and country.

RESULTS: Our search strategy identified 488 papers. A comparison between the papers published between 2001-6 and 2007-12 showed an increase in every SNOMED CT focus category. The number of papers classified as 'theoretical' increased from 46 to 78, 'pre-development/design' increased from 61 to 173 and 'implementation' increased from 10 to 34. Papers classified as 'evaluation/commodity' only started to appear from 2010.

CONCLUSIONS: The majority of studies focused on 'theoretical' and 'pre-development/design'. This is still encouraging as SNOMED CT is being harmonized with other standardized terminologies and is being evaluated to determine the content coverage of local terms, which is usually one of the first steps towards adoption. Most implementations are not published in the scientific literature, requiring a look beyond the scientific literature to gain insights into SNOMED CT implementations.

Place, publisher, year, edition, pages
BMJ Group, 2014
Keywords
Controlled vocabularies, Implementation, Literature Review, SNOMED CT
National Category
Other Medical Engineering
Identifiers
urn:nbn:se:liu:diva-100435 (URN)10.1136/amiajnl-2013-001636 (DOI)000337672800004 ()23828173 (PubMedID)
Available from: 2013-11-07 Created: 2013-11-07 Last updated: 2017-12-06
Dentler, K., Ten Teije, A., de Keizer, N. & Cornet, R. (2013). Barriers to the reuse of routinely recorded clinical data: a field report. In: Proceedings of Studies in Health Technology & Informatics, vol.192: . Paper presented at Medinfo 2013, 20-23 Aug Copenhagen, Denmark (pp. 313-317). IOS Press, 192
Open this publication in new window or tab >>Barriers to the reuse of routinely recorded clinical data: a field report
2013 (English)In: Proceedings of Studies in Health Technology & Informatics, vol.192, IOS Press, 2013, Vol. 192, p. 313-317Conference paper, Published paper (Refereed)
Abstract [en]

Today, clinical data is routinely recorded in vast amounts, but its reuse can be challenging. A secondary use that should ideally be based on previously collected clinical data is the computation of clinical quality indicators. In the present study, we attempted to retrieve all data from our hospital that is required to compute a set of quality indicators in the domain of colorectal cancer surgery. We categorised the barriers that we encountered in the scope of this project according to an existing framework, and provide recommendations on how to prevent or surmount these barriers. Assuming that our case is not unique, these recommendations might be applicable for the design, evaluation and optimisation of Electronic Health Records.

Place, publisher, year, edition, pages
IOS Press, 2013
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 192
National Category
Other Medical Engineering
Identifiers
urn:nbn:se:liu:diva-100779 (URN)10.3233/978-1-61499-289-9-313 (DOI)000341021700064 ()23920567 (PubMedID)978-1-61499-288-2 (ISBN)978-1-61499-289-9 (ISBN)
Conference
Medinfo 2013, 20-23 Aug Copenhagen, Denmark
Available from: 2013-11-12 Created: 2013-11-12 Last updated: 2015-06-10
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