BackgroundIntensive care clinicians use several sources of data in order to inform decision-making. We set out to evaluate a new interactive data integration platform called T3™ made available for pediatric intensive care. Three primary functions are supported: tracking of physiologic signals, displaying trajectory, and triggering decisions, by highlighting data or estimating risk of patient instability. We designed a human factors study to identify interface usability issues, to measure ease of use, and to describe interface features that may enable or hinder clinical tasks.MethodsTwenty-two participants, consisting of bedside intensive care physicians, nurses, and respiratory therapists, tested the T3™ interface in a simulation laboratory setting. Twenty tasks were performed with a true-to-setting, fully functional, prototype, populated with physiological and therapeutic intervention patient data. Primary data visualization was time series and secondary visualizations were: 1) shading out-of-target values, 2) mini-trends with exaggerated maxima and minima (sparklines), and 3) bar graph of a 16-parameter indicator. Task completion was video recorded and assessed using a use error rating scale. Usability issues were classified in the context of task and type of clinician. A severity rating scale was used to rate potential clinical impact of usability issues.ResultsTime series supported tracking a single parameter but partially supported determining patient trajectory using multiple parameters. Visual pattern overload was observed with multiple parameter data streams. Automated data processing using shading and sparklines was often ignored but the 16-parameter data reduction algorithm, displayed as a persistent bar graph, was visually intuitive. However, by selecting or automatically processing data, triggering aids distorted the raw data that clinicians use regularly. Consequently, clinicians could not rely on new data representations because they did not know how they were established or derived.ConclusionsUsability issues, observed through contextual use, provided directions for tangible design improvements of data integration software that may lessen use errors and promote safe use. Data-driven decision making can benefit from iterative interface redesign involving clinician-users in simulated environments. This study is a first step in understanding how software can support clinicians’ decision making with integrated continuous monitoring data. Importantly, testing of similar platforms by all the different disciplines who may become clinician users is a fundamental step necessary to understand the impact on clinical outcomes of decision aids.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-017-0520-7) contains supplementary material, which is available to authorized users.

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To identify unique latent safety threats spanning routine pediatric critical care activities and categorize them according to their underlying work system factors (i.e., "environment, organization, person, task, tools/technology") and associated clinician behavior (i.e., "legal": expected compliance with or "illegal-normal": deviation from and "illegal-illegal": disregard for standard policies and protocols). DESIGN:A prospective observational study with contextual inquiry of clinical activities over a 5-month period. SETTING: Two PICUs (i.e., medical-surgical ICU and cardiac ICU) in an urban free-standing quaternary children's hospital. SUBJECTS:Attending physicians and trainees, nurse practitioners, registered nurses, respiratory therapists, dieticians, pharmacists, and patient services assistants were observed. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS:Conducted 188 hours of observations to prospectively identify unique latent safety threats. Qualitative observational notes were analyzed by human factors experts using a modified framework analysis methodology to summarize latent safety threats and categorize them based on associated clinical activity, predominant work system factor, and clinician behavior. Two hundred twenty-six unique latent safety threats were observed. The latent safety threats were categorized into 13 clinical activities and attributed to work system factors as follows: "organization" (n = 83; 37%), "task" (n = 52; 23%), "tools/technology" (n = 40; 18%), "person" (n = 32; 14%), and "environment" (n = 19; 8%). Twenty-three percent of latent safety threats were identified when staff complied with policies and protocols (i.e., "legal" behavior) and 77% when staff deviated from policies and protocols (i.e., "illegal-normal" behavior). There was no "illegal-illegal" behavior observed. CONCLUSIONS:Latent safety threats span various pediatric critical care activities and are attributable to many underlying work system factors. Latent safety threats are present both when staff comply with and deviate from policies and protocols, suggesting that simply reinforcing compliance with existing policies and protocols, the common default intervention imposed by healthcare organizations, will be insufficient to mitigate safety threats. Rather, interventions must be designed to address the underlying work system threats. This human factors informed framework analysis of observational data is a useful approach to identifying and understanding latent safety threats and can be used in other clinical work systems.

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IntroductionThe effective exchange of clinical information is essential to high-quality patient care, especially in the critical care unit (CCU) where communication failures can have profoundly negative impacts on critically ill patients with limited physiological capacity to tolerate errors. A comprehensive systematic characterisation of information exchange within a CCU is needed to inform the development and implementation of effective, contextually appropriate interventions. The objective of this study is to characterise when, where and how healthcare providers exchange clinical information in the Department of Critical Care Medicine at The Hospital for Sick Children and explore the factors that currently facilitate or counter established best rounding practices therein.Methods and analysisA convergent parallel mixed-methods study design will be used to collect, analyse and interpret quantitative and qualitative data. Naturalistic observations of rounds and relevant peripheral information exchange activities will be conducted to collect time-stamped event data on workflow and communication patterns (time–motion data) and field notes. To complement observational data, the subjective perspectives of healthcare providers and patient families will be gathered through surveys and interviews. Departmental metrics will be collected to further contextualise the environment. Time–motion data will be analysed quantitatively; patterns in field note, survey and interview results will be examined based on themes identified deductively from literature and/or inductively based on the data collected (thematic analysis). The proactive triangulation of these systemic, procedural and contextual data will inform the design and implementation of efficacious interventions in future work.Ethics and disseminationInstitutional research ethics approval has been acquired (REB #1000059173). Results will be published in peer-reviewed journals and presented at relevant conferences. Findings will be presented to stakeholders including interdisciplinary staff, departmental management and leadership and families to highlight the strengths and weaknesses of the exchange of clinical information in its current state and develop user-centred recommendations for improvement.