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1.
Yearb Med Inform ; 9: 90-6, 2014 Aug 15.
Article in English | MEDLINE | ID: mdl-25123727

ABSTRACT

OBJECTIVES: To select best medical informatics research works published in 2013 on electronic health record (EHR) adoption, design, and impact, from the perspective of human factors and organizational issues (HFOI). METHODS: We selected 2,764 papers by querying PubMed (Mesh and TIAB) as well as using a manual search. Papers were evaluated based on pre-defined exclusion and inclusion criteria from their title, keywords, and abstract to select 15 candidate best papers, finally reviewed by 4 external reviewers using a standard evaluation grid. RESULTS: Five papers were selected as best papers to illustrate how human factors approaches can improve EHR adoption and design. Among other contributions, these works: (i) make use of the observational and analysis methodologies of social and cognitive sciences to understand clinicians' attitudes towards EHRs, EHR use patterns, and impact on care processes, workflows, information exchange, and coordination of care; (ii) take into account macro- (environmental) and meso- (organizational) level factors to analyze EHR adoption or lack thereof; (iii) highlight the need for qualitative studies to analyze the unexpected side effects of EHRs on cognitive and work processes as well as the persistent use of paper. CONCLUSION: Selected papers tend to demonstrate that HFOI approaches and methodologies are essential to bridge the gap between EHR systems and end users, and to reduce regularly reported adoption failures and unexpected consequences.


Subject(s)
Electronic Health Records , Ergonomics , Attitude of Health Personnel , Attitude to Computers , Diffusion of Innovation , Electronic Health Records/organization & administration , Electronic Health Records/statistics & numerical data , Humans , Medical Records Systems, Computerized/economics
2.
Yearb Med Inform ; 8: 86-92, 2013.
Article in English | MEDLINE | ID: mdl-23974553

ABSTRACT

OBJECTIVES: To summarize current excellent medical informatics research in the field of human factors and organizational issues. METHODS: Using PubMed, a total of 3,024 papers were selected from 17 journals. The papers were evaluated on the basis of their title, keywords, and abstract, using several exclusion and inclusion criteria. 15 preselected papers were carefully evaluated by six referees using a standard evaluation grid. RESULTS: Six best papers were selected exemplifying the central role cognitive and social sciences can play in medical informatics research. Among other contributions, those studies: (i) make use of the distributed cognition paradigm to model and understand clinical care situations; (ii) take into account organizational issues to analyse the impact of HIT on information exchange and coordination processes; (iii) illustrate how models and empirical data from cognitive psychology can be used in medical informatics; and (iv) highlight the need of qualitative studies to analyze the unexpected side effects of HIT on cognitive and work processes. CONCLUSION: The selected papers demonstrate that paradigms, methodologies, models, and results from cognitive and social sciences can help to bridge the gap between HIT and end users, and contribute to limit adoption failures that are reported regularly.


Subject(s)
Medical Informatics , Social Sciences , Cognition , Humans
3.
Stud Health Technol Inform ; 180: 88-92, 2012.
Article in English | MEDLINE | ID: mdl-22874158

ABSTRACT

In this paper, we introduce an application of Proxima and define a new measure of proximity between two concepts present in an ontology. The approach is based on the three dimensions of a conceptualization: intention with relations between concepts, expression with terms denoting concepts, and extension with instances of concepts. This preliminary work, in the field of rare diseases, involved the Orphanet Ontology of Rare Diseases (OntoOrpha) and corpus of texts extracted from Online Inheritance in Man (OMIM). The proximity measurements are consistent with an appropriate representation of groups of diseases in the ontology, which are derived from the Orphanet classifications of rare diseases. Other semantic relations are explored and new perspectives in medical knowledge curation are proposed.


Subject(s)
Databases, Factual , Databases, Genetic , Genetic Predisposition to Disease/genetics , Knowledge Management , Rare Diseases/classification , Rare Diseases/genetics , Semantics , Humans
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