SORA

Advancing, promoting and sharing knowledge of health through excellence in teaching, clinical practice and research into the prevention and treatment of illness

The ALFA (Activity Log Files Aggregation) Toolkit: A Method for Precise Observation of the Consultation

de Lusignan, S; Kumarapeli, P; Chan, T; Pflug, B; van Vlymen, J; Jones, B; Freeman, GK (2008) The ALFA (Activity Log Files Aggregation) Toolkit: A Method for Precise Observation of the Consultation. JOURNAL OF MEDICAL INTERNET RESEARCH, 10 (4). e27. ISSN 1438-8871 https://doi.org/10.2196/jmir.1080
SGUL Authors: De Lusignan, Simon

Full text not available from this repository.

Abstract

Background: There is a lack of tools to evaluate and compare Electronic patient record (EPR) systems to inform a rational choice or development agenda. Objective: To develop a tool kit to measure the impact of different EPR system features on the consultation. Methods: We first developed a specification to overcome the limitations of existing methods. We divided this into work packages: (1) developing a method to display multichannel video of the consultation; (2) code and measure activities, including computer use and verbal interactions; (3) automate the capture of nonverbal interactions; (4) aggregate multiple observations into a single navigable output; and (5) produce an output interpretable by software developers. We piloted this method by filming live consultations (n = 22) by 4 general practitioners (GPs) using different EPR systems. We compared the time taken and variations during coded data entry, prescribing, and blood pressure (BP) recording. We used nonparametric tests to make statistical comparisons. We contrasted methods of BP recording using Unified Modeling Language (UML) sequence diagrams. Results: We found that 4 channels of video were optimal. We identified an existing application for manual coding of video output. We developed in-house tools for capturing use of keyboard and mouse and to time stamp speech. The transcript is then typed within this time stamp. Although we managed to capture body language using pattern recognition software, we were unable to use this data quantitatively. We loaded these observational outputs into our aggregation tool, which allows simultaneous navigation and viewing of multiple files. This also creates a single exportable file in XML format, which we used to develop UML sequence diagrams. In our pilot, the GP using the EMIS LV (Egton Medical Information Systems Limited, Leeds, UK) system took the longest time to code data (mean 11.5 s, 95% CI 8.7-14.2). Nonparametric comparison of EMIS LV with the other systems showed a significant difference, with EMIS PCS (Egton Medical Information Systems Limited, Leeds, UK) (P = .007), iSoft Synergy (iSOFT, Banbury, UK) (P = .014), and INPS Vision (INPS, London, UK) (P = .006) facilitating faster coding. In contrast, prescribing was fastest with EMIS LV (mean 23.7 s, 95% CI 20.5-26.8), but nonparametric comparison showed no statistically significant difference. UML sequence diagrams showed that the simplest BP recording interface was not the easiest to use, as users spent longer navigating or looking up previous blood pressures separately. Complex interfaces with free-text boxes left clinicians unsure of what to add. Conclusions: The ALFA method allows the precise observation of the clinical consultation. It enables rigorous comparison of core elements of EPR systems. Pilot data suggests its capacity to demonstrate differences between systems. Its outputs could provide the evidence base for making more objective choices between systems. Keywords: Video recordings, process assessment, observation, attitude to computer, professional-patient relations, general practice, family practice, decision modeling, process assessment, medical informatics, computers, medical records systems, computerized, electronic patient record (EPR), electronic medical record (EMR), evaluation methodologies, usability

Item Type: Article
Additional Information: Copyright © Simon de Lusignan, Pushpa Kumarapeli, Tom Chan, Bernhard Pflug, Jeremy van Vlymen, Beryl Jones, George K Freeman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.09.2008. Except where otherwise noted, articles published in the Journal of Medical Internet Research are distributed under the terms of the Creative Commons Attribution License (http://www.creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 1) the original work is properly cited, including full bibliographic details and the original article URL on www.jmir.org, and 2) this statement is included.
Keywords: Attitude to Computers, Computers, Family Practice, Humans, Medical Records Systems, Computerized, Programming Languages, Referral and Consultation, Sensitivity and Specificity, Software, User-Computer Interface, Science & Technology, Life Sciences & Biomedicine, Health Care Sciences & Services, Medical Informatics, HEALTH CARE SCIENCES & SERVICES, MEDICAL INFORMATICS, Video recordings, process assessment, observation, attitude to computer, professional-patient relations, general practice, family practice, decision modeling, medical informatics, computers, medical records systems, computerized, electronic patient record (EPR), electronic medical record (EMR), evaluation methodologies, usability, SYSTEMS, HEALTH, TECHNOLOGIES, FRAMEWORK, 08 Information And Computing Sciences, 11 Medical And Health Sciences, 17 Psychology And Cognitive Sciences
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: JOURNAL OF MEDICAL INTERNET RESEARCH
ISSN: 1438-8871
Related URLs:
Dates:
DateEvent
1 January 2008Published
Web of Science ID: WOS:000263213900010
Download EPMC Full text (HTML)
URI: https://openaccess.sgul.ac.uk/id/eprint/1723
Publisher's version: https://doi.org/10.2196/jmir.1080

Actions (login required)

Edit Item Edit Item