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Yearb Med Inform 2011; 20(01): 39-47
DOI: 10.1055/s-0038-1638735
Working Group Contributions
Georg Thieme Verlag KG Stuttgart

Reporting Observational Studies of the Use of Information Technology in the Clinical Consultation

A Position Statement from the IMIA Primary Health Care Informatics Working Group (IMIA PCI WG)
S. de Lusignan
1   IMIA Primary Healthcare Working Group Co-Chair, Department of Health Care Management and Policy University of Surrey, UK
,
C. Pearce
2   Department of General Practice, Monash University, Australia
,
P. Kumarapeli
3   Faculty of Computing, Information Systems and Mathematics, Kingston University, UK
,
C. Stavropoulou
1   IMIA Primary Healthcare Working Group Co-Chair, Department of Health Care Management and Policy University of Surrey, UK
,
A. Kushniruk
4   School of Health Information Science, University of Victoria, Canada
,
A. Sheikh
5   eHealth Research Group, Centre for Population Health Sciences, University of Edinburgh, UK
,
A. Shachak
6   Department of Health Policy, Management and Evaluation, University of Toronto, Canada
,
K. Mendis
7   IMIA Primary Healthcare Working Group Chair, School of Rural Health, University of Sydney, Australia
› Author AffiliationsPatients and colleagues who have participated in this research; multiple funding agencies have supported the work of the authors, AS is supported by NHS Connecting for Health Evaluation Programme; IMIA and EFMI for supporting their PCI working groups.
Further Information

Publication History

Publication Date:
06 March 2018 (online)

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Summary

Objectives

To develop a classification system to improve the reporting of observational studies of the use of information technology (IT) in clinical consultations.

Methods

Literature review, workshops, and development of a position statement. We grouped the important aspects for consistent reporting into a “faceted classification”; the components relevant to a particular study to be used independently.

Results

The eightfacetsof ourclassification are: (1) Theoretical and methodological approach: e.g. dramaturgical, cognitive; (2) Data collection: Type and method of observation; (3) Room layout and environment: How this affects interaction between clinician, patient and computer. (4) Initiation and Interaction: Who starts the consultation, and how the participants interact; (5) Information and knowledge utilisation: What sources of information or decision support are used or provided; (6) Timing and type of consultation variables: Standard descriptors that can be used to allow comparison of duration and description of continuous activities (e.g. speech, eye contact) and episodic ones, such as prescribing; (7) Post-consultation impact measures: Satisfaction surveys and health economic assessment based on the perceived quality of the clinician-patient interaction; and (8) Data capture, storage, and export formats: How to archive and curate data to facilitate further analysis.

Conclusions

Adoption of this classification should make it easier to interpret research findings and facilitate the synthesis of evidence across studies. Those engaged in IT-consultation research shouldconsider adopting this reporting guide.

Keywords

Healthcare research - observation - information science - medical informatics - medical records systems - computerized
 

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