OBJECTIVE: Home telemonitoring improves clinical outcomes but can generate large amounts of data. Automating data surveillance with clinical decision support could reduce the impact of translating these systems to clinical settings. We utilized time-motion methodology to measure the time spent on activities monitoring subjects in the two groups of a home spirometry telemonitoring randomized controlled trial: the manual nurse review (control) group and the automated review (intervention) group. These results are examined for potential workflow effects that could occur when the intervention translates to a clinical setting. MATERIALS AND METHODS: Time motion is an established industrial engineering technique used to evaluate workflow by measuring the time of predefined, discrete tasks. Data were collected via direct observation of two research nurses by a single observer using the repetitive or snap-back timing method. All observed tasks were coded using a list of work activities defined and validated in an earlier study. Reliability data were collected during a 2-h session with a secondary observer. RESULTS: Reliability of the primary observer was established. During 35 h of data collection, a sample of 938 task observations were recorded and coded using 46 previously defined and 5 newly defined work activities. Between-group comparisons of activity time for subjects in the two study groups showed significantly more time spent on data review activities for the automated review group. Reclassification of the 51 observed activities identified 15 activities that would translate to a clinical setting, of which 5 represent potentially new activities. CONCLUSIONS: Implementing an intervention into a clinical setting could add work activities to the clinical workflow. Time-motion study of research personnel working with new clinical interventions provides a template for evaluating the workflow impact of these interventions prior to translation from a research to a clinical setting.
|Number of pages
|Telemedicine journal and e-health : the official journal of the American Telemedicine Association
|Published - Jun 2010