CC BY-NC-ND 4.0 · Yearb Med Inform 2020; 29(01): 121-128
DOI: 10.1055/s-0040-1702018
Section 3: Clinical Information Systems
Synopsis
Georg Thieme Verlag KG Stuttgart

Trends in Clinical Information Systems Research in 2019

An Overview of the Clinical Information Systems Section of the International Medical Informatics Association Yearbook
W. O. Hackl*
1   Institute of Medical Informatics, UMIT - Private University of Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
,
A. Hoerbst*
2   Medical Technologies Department, MCI - The Entrepreneurial School, Innsbruck, Austria
,
Section Editors for the IMIA Yearbook Section on Clinical Information Systems › Institutsangaben
Weitere Informationen

Publikationsverlauf

Publikationsdatum:
21. August 2020 (online)

Summary

Objective: To give an overview of recent research and to propose a selection of best papers published in 2019 in the field of Clinical Information Systems (CIS).

Method: Each year, we apply a systematic process to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics. For six years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,000 papers. As CIS section editors, we categorize the retrieved articles in a multi-pass review to distill a pre-selection of 15 candidate best papers. Then, Yearbook editors and external reviewers assess the selected candidate best papers. Based on the review results, the IMIA Yearbook Editorial Committee chooses the best papers during the selection meeting. We used text mining, and term co-occurrence mapping techniques to get an overview of the content of the retrieved articles.

Results: We carried out the query in mid-January 2020 and retrieved a de-duplicated result set of 2,407 articles from 1,023 different journals. This year, we nominated 14 papers as candidate best papers, and three of them were finally selected as best papers in the CIS section. As in previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research.

Conclusions: We could observe ongoing trends, as seen in the last years. Patient benefit research is in the focus of many research activities, and trans-institutional aggregation of data remains a relevant field of work. Powerful machine-learning-based approaches, that use readily available data now often outperform human-based procedures. However, the ethical perspective of this development often comes too short in the considerations. We thus assume that ethical aspects will and should deliver much food for thought for future CIS research.

* Equal Contribution


 
  • References

  • 1 Hackl WO, Ganslandt T. New Problems - New Solutions: A Never Ending Story. Findings from the Clinical Information Systems Perspective for 2015. Yearb Med Inform 2016; ;(1): 146-51
  • 2 Hackl WO, Ganslandt T. Clinical Information Systems as the Backbone of a Complex Information Logistics Process: Findings from the Clinical Information Systems Perspective for 2016. Yearb Med Inform 2017; 26 (01) 103-9
  • 3 Hackl W, Hoerbst A. On the Way to Close the Loop in Information Logistics: Data from the Patient — Value for the Patient. Yearb Med Inform 2018; Aug 29 27 (01) 91-7
  • 4 Hackl WO, Hoerbst A. Managing Complexity. From Documentation to Knowledge Integration and Informed Decision Findings from the Clinical Information Systems Perspective for 2018. Yearb Med Inform 2019; 28 (01) 95-100
  • 5 Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev 2016; 5 (01) 210
  • 6 Shen N, Bernier T, Sequeira L, Strauss J, Silver MP, Carter-Langford A. et al. Understanding the patient privacy perspective on health information exchange: A systematic review. Int J Med Inform 2019; 125: 1-12
  • 7 Gordon WJ, Wright A, Aiyagari R, Corbo L, Glynn RJ, Kadakia J. et al. Assessment of Employee Susceptibility to Phishing Attacks at US Health Care Institutions. JAMA Netw open 2019; 2 (03) e190393
  • 8 Hill BL, Brown R, Gabel E, Rakocz N, Lee C, Cannesson M. et al. An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data. Br J Anaesth 2019; 123 (06) 877-86
  • 9 Waltman L, van Eck NJ, Noyons ECM. A unified approach to mapping and clustering of bibliometric networks. J Informetr 2010; 4 (04) 629-35
  • 10 van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010; 84 (02) 523-38
  • 11 Esmaeilzadeh P, Mirzaei T, Maddah M. The effects of data entry structure on patients’ perceptions of information quality in Health Information Exchange (HIE). Int J Med Inform 2019; 135: 104058
  • 12 Vazirani AA, O’Donoghue O, Brindley D, Meinert E. Implementing Blockchains for Efficient Health Care: Systematic Review. J Med Internet Res 2019; 21 (02) e12439
  • 13 Um TW, Lee E, Lee GM, Yoon Y. Design and Implementation of a Trust Information Management Platform for Social Internet of Things Environments. Sensors (Basel) 2019 19. (21)
  • 14 Kim HH, Park YR, Lee KH, Song YS, Kim JH. Clinical MetaData ontology: a simple classification scheme for data elements of clinical data based on semantics. BMC Med Inform Decis Mak 2019; 19 (01) 166
  • 15 Thomas JJ, Yaster M, Guffey P. The Use of Patient Digital Facial Images to Confirm Patient Identity in a Children’s Hospital’s Anesthesia Information Management System. Jt Comm J Qual patient Saf 2020; 46 (02) 118-21
  • 16 Signaevsky M, Prastawa M, Farrell K, Tabish N, Baldwin E, Han N. et al. Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy. Lab Invest 2019; Jul; 99 (07) 1019-29
  • 17 Bernard J, Sessler D, Kohlhammer J, Ruddle RA. Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Postoperative Prostate Cancer. IEEE Trans Vis Comput Graph 2019; 25 (03) 1615-28
  • 18 Blijleven V, Koelemeijer K, Jaspers M. SEWA: A framework for sociotechnical analysis of electronic health record system workarounds. Int J Med Inform 2019; 125: 71-8
  • 19 Bhatia-Lin A, Boon-Dooley A, Roberts MK, Pronai C, Fisher D, Parker L. et al. Ethical and Regulatory Considerations for Using Social Media Platforms to Locate and Track Research Participants. Am J Bioeth 2019; Jun; 19 (06) 47-61
  • 20 Steil J, Finas D, Beck S, Manzeschke A, Haux R. Robotic Systems in Operating Theaters: New Forms of Team-Machine Interaction in Health Care. Methods Inf Med 2019; 58: e14-25
  • 21 Gardner RL, Cooper E, Haskell J, Harris DA, Poplau S, Kroth PJ. et al. Physician stress and burnout: the impact of health information technology. J Am Med Inform Assoc 2019; 26 (02) 106-14
  • 22 Huebner UH, Egbert N, Schulte G. Clinical Information Systems – Seen through the Ethics Lens. Yearb Med Inform 2020; 104-14