Decision Making Tasks in Time-Critical Medical Settings

ABSTRACT We examine decision-making tasks and information sources during fast-paced, high-risk medical events, such as trauma resuscitation. Interviews with surgical team leaders and ED physicians reveal several environmental aspects that make decision making difficult, including diagnostic tradeoffs, missing and unreliable information, and managing multiple patients simultaneously. We discuss the implications of these findings for the design of wall displays to support decision making in timecritical medical settings

An ontology co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Can acquisition of expertise be supported by technology?

Professional trainees in the workplace are increasingly required to demonstrate specific standards of competence. Yet, empirical evidence of how professionals acquire competence in practice is lacking. The danger, then, is that efforts to support learning processes may be misguided. We hypothesised that a systemic view of how expertise is acquired would support more timely and appropriate development of technology to support workplace learning. The aims of this study were to provide an empirically based understanding of workplace learning and explore how learning could be facilitated through suitable application of technology. We have used the medical specialist trainee as an exemplar of how professionals acquire expertise within a complex working environment. We describe our methodological approach, based on the amalgam of systems analysis and qualitative research methods. We present the development of a framework for analysis and early findings from qualitative data analysis. Based on our findings so far, we present a tentative schema representing how technology can support learning with suggestions for the types of technology that could be used

Tensions and paradoxes in electronic patient record research: a systematic literature review using the meta-narrative method

Background: The extensive and rapidly expanding research literature on electronic patient records (EPRs) presents challenges to systematic reviewers. This literature is heterogeneous and at times conflicting, not least because it covers multiple research traditions with different underlying philosophical assumptions and methodological approaches. Aim: To map, interpret and critique the range of concepts, theories, methods and empirical findings on EPRs, with a particular emphasis on the implementation and use of EPR systems. Method: Using the meta-narrative method of systematic review, and applying search strategies that took us beyond the Medline-indexed literature, we identified over 500 full-text sources. We used ‘conflicting’ findings to address higher-order questions about how the EPR and its implementation were differently conceptualised and studied by different communities of researchers. Main findings: Our final synthesis included 24 previous systematic reviews and 94 additional primary studies, most of the latter from outside the biomedical literature. A number of tensions were evident, particularly in relation to: [1] the EPR (‘container’ or ‘itinerary’); [2] the EPR user (‘information-processer’ or ‘member of socio-technical network’); [3] organizational context (‘the setting within which the EPR is implemented’ or ‘the EPR-in-use’); [4] clinical work (‘decision-making’ or ‘situated practice’); [5] the process of change (‘the logic of determinism’ or ‘the logic of opposition’); [6] implementation success (‘objectively defined’ or ‘socially negotiated’); and [7] complexity and scale (‘the bigger the better’ or ‘small is beautiful’). Findings suggest that integration of EPRs will always require human work to re-contextualize knowledge for different uses; that whilst secondary work (audit, research, billing) may be made more efficient by the EPR, primary clinical work may be made less efficient; that paper, far from being technologically obsolete, currently offers greater ecological flexibility than most forms of electronic record; and that smaller systems may sometimes be more efficient and effective than larger ones. Conclusions: The tensions and paradoxes revealed in this study extend and challenge previous reviews and suggest that the evidence base for some EPR programs is more limited than is often assumed. We offer this paper as a preliminary contribution to a much-needed debate on this evidence and its implications, and suggest avenues for new research

A conceptual framework and protocol for defining clinical decision support objectives applicable to medical specialties.

BackgroundThe U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis.DesignWe developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as "CDS opportunities," might impact each performance gap and the extent to which each CDS opportunity is compatible with specialists' clinical workflows. The protocol was tested by expert panels representing four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics