Yearb Med Inform 2012; 21(01): 113-116
DOI: 10.1055/s-0038-1639440
Synopsis
Georg Thieme Verlag KG Stuttgart

A Medical Informatics Perspective on Decision Support Systems

Findings from the Yearbook 2012 Section on Decision Support
P. Ruch
1   University of Applied Sciences Geneva, Dept. of Information and Library Sciences, Geneva, Switzerland
,
Section Editor for the IMIA Yearbook Section on Decision Support › Author Affiliations
I greatly acknowledge the support of Martina Hutter and of the reviewers in the selection process of the IMIA Yearbook.
Further Information

Correspondence to

Prof. Dr. Patrick Ruch
University of Applied Sciences Geneva
Department of Library and Information Sciences
Geneva
Switzerland
Tel: +41 22 388 17 81

Publication History

Publication Date:
10 March 2018 (online)

 

Summary

Objectives

To summarize current excellent research in the field of computer-based decision support systems in health and healthcare.

Methods

We provide a synopsis of the articles selected for the IMIA Yearbook 2012, from which we attempt to draft a synthetic overview of the activity and new trends in the field.

Results

While the state of the research in the field of medical decision support systems is illustrated by a set of fairly heterogeneous studies, it is possible to identify fundamental aspects of the fields, e.g. Decision Support Systems for Computerized Provider Order Entry, both for physicians and pharmacists, as well as more specific developments such as instruments to improve processing of data related to Clinical Trials and applications to capture family health history.

Conclusion

The best paper selection of articles on decision support shows examples of excellent research on methods concerning original development as well as quality assurance of previously reported studies. This selected set of scientific investigations clearly question the way decision support systems are deployed in clinical environments as these systems seem to have little impact on patient safety and even could harm the patient. Furthermore, while significant research efforts are invested into translational & “omics” medicine, it is interesting to observe that simple data capture applications can reasonably lead to positive changes in healthcare.


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  • References

  • 1 Rebholz-Schuhmann D, Kirsch H, Couto F. Facts from text is text mining ready to deliver?. PLoS Biol 2005; Feb; 03 (02) e65.
  • 2 Ruch P, Gobeill J, Tbahriti I, Geissbühler A. From episodes of care to diagnosis codes: automatic text categorization for medico-economic encoding. AMIA Symposium 2008; 636-40.
  • 3 Pakhomov SV, Buntrock JD, Chute CG. Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques. J Am Med Inform Assoc 2006; Sep-Oct; 13 (05) 516-25.
  • 4 Ruch P, Gobeill J, Lovis C, Geissbühler A. Automatic medical encoding with SNOMED categories. BMC Med Inform Decis Mak 2008; 08 Suppl (Suppl. 01) S6.

Correspondence to

Prof. Dr. Patrick Ruch
University of Applied Sciences Geneva
Department of Library and Information Sciences
Geneva
Switzerland
Tel: +41 22 388 17 81

  • References

  • 1 Rebholz-Schuhmann D, Kirsch H, Couto F. Facts from text is text mining ready to deliver?. PLoS Biol 2005; Feb; 03 (02) e65.
  • 2 Ruch P, Gobeill J, Tbahriti I, Geissbühler A. From episodes of care to diagnosis codes: automatic text categorization for medico-economic encoding. AMIA Symposium 2008; 636-40.
  • 3 Pakhomov SV, Buntrock JD, Chute CG. Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques. J Am Med Inform Assoc 2006; Sep-Oct; 13 (05) 516-25.
  • 4 Ruch P, Gobeill J, Lovis C, Geissbühler A. Automatic medical encoding with SNOMED categories. BMC Med Inform Decis Mak 2008; 08 Suppl (Suppl. 01) S6.