Measuring the impact of different brands of computer systems on the clinical consultation: a pilot study

Background UK general practitioners largely conduct computer-mediated consultations. Although historically there were many small general practice (GP) computer suppliers there are now around five widely used electronic patient record (EPR) systems. A new method has been developed for assessing the impact of the computer on doctor_patient interaction through detailed observation of the consultation and computer use. Objective To pilot the latest version of a method to measure the difference in coding and prescribing times on two different brands of general practice EPR system. Method We compared two GP EPR systems by observing use in real life consultations. Three video cameras recorded the consultation and screen capture software recorded computer activity.We piloted semi-automated user action recording (UAR) software to record mouse and keyboard use, to overcome limitations in manual measurement. Six trained raters analysed the videos using data capture software to measure the doctor_patient_computer interactions; we used interclass correlation coefficients (ICC) to measure reliability. Results Raters demonstrated high inter-rater reliability for verbal interactions and prescribing (ICC 0.74 to 0.99), but for measures of computer use they were not reliable. We used UAR to capture computer use and found it more reliable.Coded data entry time varied between the systems: 6.8 compared with 11.5 seconds (P = 0.006). However, the EPR with the shortest coding time had a longer prescribing time: 27.5 compared with 23.7 seconds (P = 0.64). Conclusion This methodological development improves the reliability of our method for measuring the impact of different computer systems on the GP consultation. UAR added more objectivity to the observationof doctor_computer interactions. If larger studies were to reproduce the differences between computer systems demonstrated in this pilot it might be possible to make objective comparisons between systems

Modelling the computerised clinical consultations: a multi-channel video study

This study aims to understand the use of a computer during GP consultations and to enable the development of EPR systems which are easier to review, enter data into, use to take action, and is more sensitive to the clinical context. This thesis reports the development of a multi-channel video and data capture toolkit, the ALFA (Activity Log File Aggregation) because existing observation techniques have limitations. None of the existing tools are designed to assess human-computer interaction in the context of the clinical consultation, where the social interaction is the prime focus. The ALFA tool-kit has been used to observe and study 163 live primary care consultations supported by computer systems with four different designs. A detailed analysis of consultation interactions was then performed focusing on doctor-patient communication and the integration of the computer into the consultation workflow. The data collection elements of the ALFA supported recording of consultation activities by providing rating techniques attuned with the characteristics of those interactions. The Log File Aggregation (LFA) component of the ALFA toolkit aggregated those multitudes of data files into a single navigable output that can be studied both quantitatively and qualitatively. A set of Unified Modelling Language (UML) sequence diagrams were then created as they could be used by software engineers to develop better systems. This research proposes a framework with three elements to analyse the computerised clinical consultation; (1) the overview of the context within which the consultation was carried out, (2) time taken to perform key consultation tasks and (3) the process used. Traditional analysis with its emphasis on the technology often misses crucial features of the complex work environments in which the technology is implemented. Direct observation could inform software designers in developing systems that are more readily integrated into clinical workflow. Direct observation of the consultation, using the ALFA toolkit is acceptable to patients; captures the context of the consultation the precise timing and duration of key tasks; and produces an output a software engineer can understand. ALFA offers a range of possibilities for research in the consulting room. The computer should be considered as an active element of the consultation; room layout and consultation models should let the computer in, while software engineers take in the capacity to sustain patient centred social interactions as a core facet of their design agenda

Getting seamless care right from the beginning – Integrating computers into the human interaction

The digital age is coming to the health space, behind many other fields of society. In part this is because health remains heavily reliant on human interaction. The doctor-patient relationship remains a significant factor in determining patient outcomes. Whilst there are many benefits to E-Health, there are also significant risks if computers are not adequately integrated into this interaction and accurate data are consequently not available on the patient's journey through the health system

"Effects of exam room EHR use on doctor-patient communication: a systematic literature review" - Triadic and other key terms may have identified additional literature.

Kazmi’s systemic review concludes on the positive influence of the computer use on the biomedical aspect of the consultation interaction, and the adverse effect on the psychosocial dimension. It broaches concerns about the availability of high-quality studies focusing on the doctor–patient interactions. However, there are visible limitations associated with the search strategy employed, which indeed can be considered as a common challenge for reviews in this field of interaction research involving doctor, patient, and computer

Addressing modifiable risk factors for coronary heart disease in primary care: an evidence-base lost in translation

Risk factors for cardiovascular disease can be modified in primary care. Electronic patient record (EPR) systems include embedded cardiovascular risk factor calculators and should facilitate this process

Measuring the impact of the computer on the consultation: an open source application to combine multiple observational outputs

A diverse range of tools and techniques can be used to observe the clinical consultation and the use of information technology. These technologies range from transcripts; to video observation with one or more cameras; to voice and pattern recognition applications. Currently, these have to be observed separately and there is limited capacity to combine them. Consequently, when multiple methods are used to analyse the consultation a significant proportion of time is spent linking events in one log file (e.g. mouse movements and keyboard use when prescribing alerts appear) with what was happening in the consultation at that time. The objective of this study was to develop an application capable of combining and comparing activity log-files and with facilities to view simultaneously all data relating to any time point or activity. Interviews, observations and design prototypes were used to develop a specification. Class diagram of the application design was used to make further development decisions. The application development used object-orientated design principles. We used open source tools; Java as the programming language and JDeveloper as the development environment. The final output is log file aggregation (LFA) tool which forms part of the wider aggregation of log files for analysis (ALFA) open source toolkit ( www.biomedicalinformatics.info/alfa/ ). Testing was done using sample log files and reviewed the application's utility for analysis of the consultation activities. Separation of the presentation and functionality in the design stage enabled us to develop a modular and extensible application. The application is capable of converting and aggregating several log files of different formats and displays them in different presentation layouts. We used the Java Media Framework to aggregate video channels. Java extensible mark-up language (XML) package facilitated the conversion of aggregated output into XML format. Analysts can now move easily between observation tools and find all the data related to an activity. The LFA application makes new analysis tasks feasible and established tasks much more efficient. Researchers can now store multiple log file data as a single file isolate and investigate different doctor-computer-patient interaction