Toward a better understanding of task demands, workload, and performance during physician-computer interactions

OBJECTIVE: To assess the relationship between (1) task demands and workload, (2) task demands and performance, and (3) workload and performance, all during physician-computer interactions in a simulated environment. METHODS: Two experiments were performed in 2 different electronic medical record (EMR) environments: WebCIS (n = 12) and Epic (n = 17). Each participant was instructed to complete a set of prespecified tasks on 3 routine clinical EMR-based scenarios: urinary tract infection (UTI), pneumonia (PN), and heart failure (HF). Task demands were quantified using behavioral responses (click and time analysis). At the end of each scenario, subjective workload was measured using the NASA-Task-Load Index (NASA-TLX). Physiological workload was measured using pupillary dilation and electroencephalography (EEG) data collected throughout the scenarios. Performance was quantified based on the maximum severity of omission errors. RESULTS: Data analysis indicated that the PN and HF scenarios were significantly more demanding than the UTI scenario for participants using WebCIS (P < .01), and that the PN scenario was significantly more demanding than the UTI and HF scenarios for participants using Epic (P < .01). In both experiments, the regression analysis indicated a significant relationship only between task demands and performance (P < .01). DISCUSSION: Results suggest that task demands as experienced by participants are related to participants' performance. Future work may support the notion that task demands could be used as a quality metric that is likely representative of performance, and perhaps patient outcomes. CONCLUSION: The present study is a reasonable next step in a systematic assessment of how task demands and workload are related to performance in EMR-evolving environments

Use of mobile device technology to continuously collect patient-reported symptoms during radiation therapy for head and neck cancer: A prospective feasibility study

AbstractPurposeAccurate assessment of toxicity allows for timely delivery of supportive measures during radiation therapy for head and neck cancer. The current paradigm requires weekly evaluation of patients by a provider. The purpose of this study is to evaluate the feasibility of monitoring patient reported symptoms via mobile devices.Methods and materialsWe developed a mobile application for patients to report symptoms in 5 domains using validated questions. Patients were asked to report symptoms using a mobile device once daily during treatment or more often as needed. Clinicians reviewed patient-reported symptoms during weekly symptom management visits and patients completed surveys regarding perceptions of the utility of the mobile application. The primary outcome measure was patient compliance with mobile device reporting. Compliance is defined as number of days with a symptom report divided by number of days on study.ResultsThere were 921 symptom reports collected from 22 patients during treatment. Median reporting compliance was 71% (interquartile range, 45%-80%). Median number of reports submitted per patient was 34 (interquartile range, 21-53). Median number of reports submitted by patients per week was similar throughout radiation therapy and there was significant reporting during nonclinic hours. Patients reported high satisfaction with the use of mobile devices to report symptoms.ConclusionsA substantial percentage of patients used mobile devices to continuously report symptoms throughout a course of radiation therapy for head and neck cancer. Future studies should evaluate the impact of mobile device symptom reporting on improving patient outcomes

Deformable M-Reps for 3D Medical Image Segmentation

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models, which define objects at coarse scale by a hierarchy of figures – each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure