Pushpa Kumarapeli

Using the computer in the clinical consultation; setting the stage, reviewing, recording, and taking actions: multi-channel video study

BACKGROUND AND OBJECTIVE Electronic patient record (EPR) systems are widely used. This study explores the context and use of systems to provide insights into improving their use in clinical practice. METHODS We used video to observe 163 consultations by 16 clinicians using four EPR brands. We made a visual study of the consultation room and coded interactions between clinician, patient, and computer. Few patients (6.9%, n=12) declined to participate. RESULTS Patients looked at the computer twice as much (47.6 s vs 20.6 s, p<0.001) when it was within their gaze. A quarter of consultations were interrupted (27.6%, n=45); and in half the clinician left the room (12.3%, n=20). The core consultation takes about 87% of the total session time; 5% of time is spent pre-consultation, reading the record and calling the patient in; and 8% of time is spent post-consultation, largely entering notes. Consultations with more than one person and where prescribing took place were longer (R(2) adj=22.5%, p<0.001). The core consultation can be divided into 61% of direct clinician-patient interaction, of which 15% is examination, 25% computer use with no patient involvement, and 14% simultaneous clinician-computer-patient interplay. The proportions of computer use are similar between consultations (mean=40.6%, SD=13.7%). There was more data coding in problem-orientated EPR systems, though clinicians often used vague codes. CONCLUSIONS The EPR system is used for a consistent proportion of the consultation and should be designed to facilitate multi-tasking. Clinicians who want to promote screen sharing should change their consulting room layout.

A study of cardiovascular risk in overweight and obese people in England

Objectives: To report current levels of obesity and associated cardiac risk using routinely collected primary care computer data. Methods: 67 practices took part in an educational intervention to improve computer data quality and care in cardiovascular disease. Data were extracted from 435 102 general practice computer records. 64.3% (229 108/362 861) of people age 15 y and older had a body mass index (BMI) recording or a valid height and weight record that enabled BMI to be derived. Data about cardiovascular disease and risk factors were also extracted. The prevalence of disease and the control of risk factors in the overweight and obese population were compared with those of normal body weight. Results: 56.8% of men and 69.3% of women aged over 15 y had a BMI record. 22% of men and 32.3% of women aged 15 to 24 y were overweight or obese; rising each decade to a peak of 65.6% of men and 57.5% of women aged 55 to 64 y. Thereafter, the proportion who were overweight or obese declined. The prevalence of ischaemic heart disease, diabetes mellitus and hypertension rose with increasing levels of obesity; their prevalence in those who are moderately obese was between two and three times that of the general population. Systolic and diastolic blood pressure, blood glucose even in non-diabetics, cholesterol and triglycerides were all elevated in the overweight and obese population. Conclusion: Based on the recorded data over half of men and nearly half of women are overweight or obese. They have increased cardiovascular risk, which is not adequately controlled by current practice.

The ALFA (Activity Log Files Aggregation) toolkit: a method for precise observation of the consultation.

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.

Using Unified Modelling Language (UML) as a process-modelling technique for clinical-research process improvement

The Primary Care Data Quality programme (PCDQ) is a quality-improvement programme which processes routinely collected general practice computer data. Patient data collected from a wide range of different brands of clinical computer systems are aggregated, processed, and fed back to practices in an educational context to improve the quality of care. Process modelling is a well-established approach used to gain understanding and systematic appraisal, and identify areas of improvement of a business process. Unified modelling language (UML) is a general purpose modelling technique used for this purpose. We used UML to appraise the PCDQ process to see if the efficiency and predictability of the process could be improved. Activity analysis and thinking-aloud sessions were used to collect data to generate UML diagrams. The UML model highlighted the sequential nature of the current process as a barrier for efficiency gains. It also identified the uneven distribution of process controls, lack of symmetric communication channels, critical dependencies among processing stages, and failure to implement all the lessons learned in the piloting phase. It also suggested that improved structured reporting at each stage—especially from the pilot phase, parallel processing of data and correctly positioned process controls—should improve the efficiency and predictability of research projects. Process modelling provided a rational basis for the critical appraisal of a clinical data processing system; its potential maybe underutilized within health care.

Disparities in testing for renal function in UK primary care: cross-sectional study.

BACKGROUND In the UK, explicit quality standards for chronic disease management, including for diabetes and chronic kidney disease (CKD), are set out National Service Frameworks and pay-for-performance indicators. These conditions are common with a prevalence of 4% and 5.4%, respectively. CKD is largely asymptomatic, detected following renal function testing and important because associated with increased mortality and morbidity, especially in people with diabetes and proteinuria. OBJECTIVES To investigate who has their renal function tested and any association with age, sex, ethnicity and diabetes. METHOD A cross-sectional survey in a primary care research network in south-west London (n = 220 721). The following data were extracted from routine data: age, gender, ethnicity, latest serum creatinine, diagnosis of diabetes and recording of proteinuria. We used logistic regression to explore any association in testing for CKD. RESULTS People (82.1%) with diabetes had renal function and proteinuria tested; the proportion was much smaller (<0.5%) in those without. Women were more likely to have a creatinine test than men (28% versus 24%, P < 0.05), but this association was modified by age, ethnicity and presence of diabetes. People >75 years and with diabetes were most likely to have been tested. Black [adjusted odds ratio (AOR) 2.1, 95% confidence interval (CI) 2.0-2.2] and south Asian (AOR 1.65, 95% CI 1.56-1.75) patients were more likely to be tested than whites. Those where ethnicity was not stated were the only group not tested more than whites. CONCLUSIONS Quality improvement initiatives and equity audits, which include CKD should take account of disparities in renal function testing.

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

BACKGROUND 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. OBJECTIVE To observe how the evidence base for assessing and managing cardiovascular risk is implemented in practice. METHOD We compared the different risk calculators promoted for calculating cardiovascular risk in primary care using four test cases. We looked to see how these calculators were implemented in primary care EPR systems. We explored through a workshop which risk factors GPs thought were important and felt motivated to address as part of clinical care. RESULTS The risk calculators reviewed use different sets of risk factors and the levels of risk calculated for the same test patient profiles vary by up to 100%. The risk factor calculators embedded within UK computer systems all include the Framingham equation though there is variation in interface, default values and patient groups included. GPs showed consensus around the importance of managing smoking, blood pressure, obesity (body mass index), diabetes and cholesterol but also stressed the importance of providing personalized care and exercising professional judgement. CONCLUSIONS There appears to be an evidence-base lost in translation. Different guidelines calculate risk differently, and even when the same guideline is used, variation in implementation leads to further variation. Education and development of improved risk calculators should enable the most appropriate calculator to be used for an individual patient; accreditation of implementation could be achieved through the use of a standard set of test cases.

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 applications 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.

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.