Medication reconciliation is an important and complex task for which careful user interface design has the potential to help reduce errors and improve quality of care. In this paper we focus on the hospital discharge scenario and first describe a novel interface called Twinlist. Twinlist illustrates the novel use of spatial layout combined with multi-step animation, to help medical providers see what is different and what is similar between the lists (e.g., intake list and hospital list), and rapidly choose the drugs they want to include in the reconciled list. We then describe a series of variant designs and discuss their comparative advantages and disadvantages. Finally we report on a pilot study that suggests that animation might help users learn new spatial layouts such as the one used in Twinlist.

1School of Biomedical Informatics, The University of Texas Health Science Center at Houston, TX; 2National Center for Cognitive Informatics and Decision Making in Healthcare, Houston, TX; 3 The University of Texas MD Anderson Cancer Center. Houston, TX, 77030, USA. 4 FIT Lab — Interaction Laboratory, Swansea University, Swansea, Wales, UK. Eliz A. Markowitz1,2 MS, MS, Todd R. Johnson 1,2 PhD, Elmer V. Bernstam 1,2 MD, MSE, Jorge R. Herskovic 2,3 MD, PhD, Harold Thimbleby 4 PhD A Systematic Yet Flexible Systems Analysis Framework

Mirroring successes in other industries, efforts to improve health care quality have led to an increased push to develop and adopt systems that enforce or encourage consistent procedures based on best practices and evidence-based medicine. Although such systems can lead to more efficient and safer care, health care is filled with complexity, variations, and exceptions that are not easily captured by idealized processes. Information systems that are too rigid to support such deviations can lead to decreases in quality, along with caregiver resistance and creative workarounds, that together lower the adoption rate and decrease the positive effects of technology [1-5]. Similar problems in other industries have led to the concept of Systematic Yet Flexible (SYF) systems, in which the system supports and encourages a systematic approach, while simultaneously allowing for considerable flexibility [6]. Building upon the general design goals for SYF systems, we designed a framework, called SYFSA (Systematic Yet Flexible System Analysis) for analyzing and designing SYF systems by considering the trade-off between systematicity and flexibility. SYFSA is based on analyzing a task using three related problem spaces: the idealized space, which represents the best practice. the natural space, which captures the possible path actions that may be taken in the real world, and the system space, which specifies how the task is to be done in the the system being (re)designed. According to this framework, the most effective system is one that maximizes the chance of idealized performance, as specified by the task space, while also allowing flexible behavior to cope with the inevitable variations in healthcare tasks. We can use SYFSA to predict performance by comparing the systematicity and flexibility of the task and the system. The long-term goal of this work is to guide the design of systems that allow graceful degradation from ideal performance on standard cases to more flexible performance for coping with variations. Our unifying hypothesis is that SYSFA will allow us to predict user performance. We will test this hypothesis with the following specific aims: Specific Aim 1: Evaluate the flexibility-compatibility hypothesis. We hypothesize that user performance will improve when the flexibility of the system interface matches the flexibility of the task. We will vary task flexibility and interface flexibility in a 2 × BLOCKIN BLOCKIN 2 (task flexibility × system flexibility) design and measure user error rates, task completion rates, and task completion times. Specific Aim 2: Evaluate the prediction that …

Medication errors can result from administration inaccuracies at any point of care and are a major cause for concern. To develop a successful Medication Reconciliation (MR) tool, we believe it necessary to build a Work Domain Ontology (WDO) for the MR process. A WDO defines the explicit, abstract, implementation-independent description of the task by separating the task from work context, application technology, and cognitive architecture. We developed a prototype based upon the WDO and designed to adhere to standard principles of interface design. The prototype was compared to Legacy Health System's and Pre-Admission Medication List Builder MR tools via a Keystroke-Level Model analysis for three MR tasks. The analysis found the prototype requires the fewest mental operations, completes tasks in the fewest steps, and completes tasks in the least amount of time. Accordingly, we believe that developing a MR tool, based upon the WDO and user interface guidelines, improves user efficiency and reduces cognitive load.

In the midst of pressing demands for viable Electronic Health Record (EHR) technology, Medsphere OpenVista offers a Graphical User Interface (GUI) system that strives to provide such technology across a variety of healthcare organizations and settings. While the overall structure and function of OpenVista may improve overall performance, in terms of cost reduction, clinical performance, and patient care outcomes, there is still much room for improvement in OpenVista's user interface. Via the application of user interface design methods and techniques, recommendations for the overall improvement of the OpenVista Patient Summary screen were made and a low-fidelity prototype was created. The goal of the new patient summary screen was to create a user environment that will optimize user performance via reduction of time spent acquiring data, improving the ease of data acquisition, and clarity of data. The two patient summary screens were compared via a KLM analysis and the low-fidelity prototype screen was found to increase ease of use and efficiency. Specifically, OpenVista required, on average, 60% more mental operations and 31% more time per task than the prototype. Consequently, while EHRs are quite valuable, poor design can lead to extensive usability issues amongst both novice and expert users. While OpenVista is quite prevalent amongst many hospitals utilizing EHRs, there is still much room for improvement.

Medication reconciliation is a National Patient Safety Goal (NPSG) from The Joint Commission (TJC) that entails reviewing all medications a patient takes after a health care transition. Medication reconciliation is a resource-intensive, error-prone task, and the resources to accomplish it may not be routinely available. Computer-based methods have the potential to overcome these barriers. We designed and explored a rule-based medication reconciliation algorithm to accomplish this task across different healthcare transitions. We tested our algorithm on a random sample of 94 transitions from the Clinical Data Warehouse at the University of Texas Health Science Center at Houston. We found that the algorithm reconciled, on average, 23.4% of the potentially reconcilable medications. Our study did not have sufficient statistical power to establish whether the kind of transition affects reconcilability. We conclude that automated reconciliation is possible and will help accomplish the NPSG.