The clinician in the driver's seat: part 2 - intelligent uses of space in a drag/drop user-composable electronic health record

Efficiency, efficacy and subjective user satisfaction of alternative laboratory report formats. An investigation on behalf of the Working Group for Postanalytical Phase (WG-POST), of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

OBJECTIVES

Although laboratory result presentation may lead to information overload and subsequent missed or delayed diagnosis, little has been done in the past to improve this post-analytical issue. We aimed to investigate the efficiency, efficacy and user satisfaction of alternative report formats.

METHODS

We redesigned cumulative (sparkline format) and single reports (improved tabular and z-log format) and tested these on 46 physicians, nurses and medical students in comparison to the classical tabular formats, by asking standardized questions on general items on the reports as well as on suspected diagnosis and follow-up treatment or diagnostics.

RESULTS

Efficacy remained at a very high level both in the new formats as well as in the classical formats. We found no significant difference in any of the groups. Efficiency improved in all groups when using the sparkline cumulative format and marginally when showing the improved tabular format. When asking medical questions, efficiency and efficacy remained similar between report formats and groups. All alternative reports were subjectively more attractive to the majority of participants.

CONCLUSIONS

Showing cumulative reports as a graphical display led to faster detection of general information on the report with the same level of correctness. Considering the familiarity bias of the classical single report formats, the borderline-significant improvement of the alternative tabular format and the non-inferiority of the z-log format, suggests that single reports might benefit from some improvements derived from basic information design.

Presentation and formatting of laboratory results: a narrative review on behalf of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group "postanalytical phase" (WG-POST)

In laboratory medicine, much effort has been put into analytical quality in the past decades, making this medical profession one of the most standardized with the lowest rates of error. However, even the best analytical quality cannot compensate for errors or low quality in the pre or postanalytical phase of the total testing process. Guidelines for data reporting focus solely on defined data elements, which have to be provided alongside the analytical test results. No guidelines on how to format laboratory reports exist. The habit of reporting as much diagnostic data as possible, including supplemental information, may lead to an information overload. Considering the multiple tasks physicians have to do simultaneously, unfiltered data presentation may contribute to patient risk, as important information may be overlooked, or juxtaposition errors may occur. As laboratories should aim to answer clinical questions, rather than providing sole analytical results, optimizing formatting options may help improve the effectiveness and efficiency of medical decision-making. In this narrative review, we focus on the underappreciated topic of laboratory result reporting. We present published literature, focusing on the impact of laboratory result report formatting on medical decisions as well as approaches, potential benefits, and limitations for alternative report formats. We discuss influencing variables such as, for example, the type of patient (e.g. acute versus chronic), the medical specialty of the recipient of the report, the display of reference intervals, the medium or platform on which the laboratory report is presented (printed paper, within electronic health record systems, on handheld devices, etc.), the context in which the report is viewed in, and difficulties in formatting single versus cumulative reports. Evidence on this topic, especially experimental studies, is scarce. When considering the medical impact, it is of utmost importance that laboratories focus not only on the analytical aspects but on the total testing process. The achievement of high analytical quality may be of minor value if essential results get lost in overload or scattering of information by using a non-formatted tabular design. More experimental studies to define guidelines and to standardize effective and efficient reporting are most definitely needed.

We're Lost, But We are Making Good Time: Navigating Complex Pathways in a Patient-Order Management Task

Patient order management (POM) is a mission-critical task for perioperative workflow. Interface complexity within different EHR systems result in poor usability, increasing documentation burden. POM interfaces were compared across two systems prior to (Cerner SurgiNet) and subsequent to an EHR conversion (Epic). Here we employ a navigational complexity framework useful for examining differences in EHR interface systems. The methodological approach includes 1) expert-based methods-specifically, functional analysis, keystroke level model (KLM) and cognitive walkthrough, and 2) quantitative analysis of observed interactive user behaviors. We found differences in relation to navigational complexity with the SurgiNet interface displaying a higher number of unused POM functions, with 12 in total whereas Epic displayed 7 total functions. As reflected in all measures, Epic facilitated a more streamlined task-focused user experience. The approach enabled us to scrutinize the impact of different EHR interfaces on task performance and usability barriers subsequent to system implementation.

Characterizing and Visualizing Display and Task Fragmentation in the Electronic Health Record: Mixed Methods Design

BACKGROUND

The complexity of health care data and workflow presents challenges to the study of usability in electronic health records (EHRs). Display fragmentation refers to the distribution of relevant data across different screens or otherwise far apart, requiring complex navigation for the user's workflow. Task and information fragmentation also contribute to cognitive burden.

OBJECTIVE

This study aims to define and analyze some of the main sources of fragmentation in EHR user interfaces (UIs); discuss relevant theoretical, historical, and practical considerations; and use granular microanalytic methods and visualization techniques to help us understand the nature of fragmentation and opportunities for EHR optimization or redesign.

METHODS

Sunburst visualizations capture the EHR navigation structure, showing levels and sublevels of the navigation tree, allowing calculation of a new measure, the Display Fragmentation Index. Time belt visualizations present the sequences of subtasks and allow calculation of proportion per instance, a measure that quantifies task fragmentation. These measures can be used separately or in conjunction to compare EHRs as well as tasks and subtasks in workflows and identify opportunities for reductions in steps and fragmentation. We present an example use of the methods for comparison of 2 different EHR interfaces (commercial and composable) in which subjects apprehend the same patient case.

RESULTS

Screen transitions were substantially reduced for the composable interface (from 43 to 14), whereas clicks (including scrolling) remained similar.

CONCLUSIONS

These methods can aid in our understanding of UI needs under complex conditions and tasks to optimize EHR workflows and redesign.

Methods for Addressing Technology-induced Errors: The Current State

OBJECTIVES

The objectives of this paper are to review and discuss the methods that are being used internationally to report on, mitigate, and eliminate technology-induced errors.

METHODS

The IMIA Working Group for Health Informatics for Patient Safety worked together to review and synthesize some of the main methods and approaches associated with technology- induced error reporting, reduction, and mitigation. The work involved a review of the evidence-based literature as well as guideline publications specific to health informatics.

RESULTS

The paper presents a rich overview of current approaches, issues, and methods associated with: (1) safe HIT design, (2) safe HIT implementation, (3) reporting on technology-induced errors, (4) technology-induced error analysis, and (5) health information technology (HIT) risk management. The work is based on research from around the world.

CONCLUSIONS

Internationally, researchers have been developing methods that can be used to identify, report on, mitigate, and eliminate technology-induced errors. Although there remain issues and challenges associated with the methodologies, they have been shown to improve the quality and safety of HIT. Since the first publications documenting technology-induced errors in healthcare in 2005, we have seen in a short 10 years researchers develop ways of identifying and addressing these types of errors. We have also seen organizations begin to use these approaches. Knowledge has been translated into practice in a short ten years whereas the norm for other research areas is of 20 years.

User-composable Electronic Health Record Improves Efficiency of Clinician Data Viewing for Patient Case Appraisal: A Mixed-Methods Study

Background:

Challenges in the design of electronic health records (EHRs) include designing usable systems that must meet the complex, rapidly changing, and high-stakes information needs of clinicians. The ability to move and assemble elements together on the same page has significant human-computer interaction (HCI) and efficiency advantages, and can mitigate the problems of negotiating multiple fixed screens and the associated cognitive burdens.

Objective:

We compare MedWISE—a novel EHR that supports user-composable displays—with a conventional EHR in terms of the number of repeat views of data elements for patient case appraisal.

Design and Methods:

The study used mixed-methods for examination of clinical data viewing in four patient cases. The study compared use of an experimental user-composable EHR with use of a conventional EHR, for case appraisal. Eleven clinicians used a user-composable EHR in a case appraisal task in the laboratory setting. This was compared with log file analysis of the same patient cases in the conventional EHR. We investigated the number of repeat views of the same clinical information during a session and across these two contexts, and compared them using Fisher’s exact test.

Results:

There was a significant difference (p<.0001) in proportion of cases with repeat data element viewing between the user-composable EHR (14.6 percent) and conventional EHR (72.6 percent).

Discussion and Conclusion:

Users of conventional EHRs repeatedly viewed the same information elements in the same session, as revealed by log files. Our findings are consistent with the hypothesis that conventional systems require that the user view many screens and remember information between screens, causing the user to forget information and to have to access the information a second time. Other mechanisms (such as reduction in navigation over a population of users due to interface sharing, and information selection) may also contribute to increased efficiency in the experimental system. Systems that allow a composable approach that enables the user to gather together on the same screen any desired information elements may confer cognitive support benefits that can increase productive use of systems by reducing fragmented information. By reducing cognitive overload, it can also enhance the user experience.

Development and Preliminary Evaluation of a Prototype of a Learning Electronic Medical Record System

Electronic medical records (EMRs) are capturing increasing amounts of data per patient. For clinicians to efficiently and accurately understand a patient's clinical state, better ways are needed to determine when and how to display EMR data. We built a prototype system that records how physicians view EMR data, which we used to train models that predict which EMR data will be relevant in a given patient. We call this approach a Learning EMR (LEMR). A physician used the prototype to review 59 intensive care unit (ICU) patient cases. We used the data-access patterns from these cases to train logistic regression models that, when evaluated, had AUROC values as high as 0.92 and that averaged 0.73, supporting that the approach is promising. A preliminary usability study identified advantages of the system and a few concerns about implementation. Overall, 3 of 4 ICU physicians were enthusiastic about features of the prototype.

The clinician in the Driver's Seat: part 1 - a drag/drop user-composable electronic health record platform

Creating electronic health records that support the uniquely complex and varied needs of healthcare presents formidable challenges. To address some of these challenges we created a new model for healthcare information systems, embodied in MedWISE,(2) a widget-based highly configurable electronic health record (EHR) platform. Founded on the idea that providing clinician users with greater control of the EHR may result in greater fit to user needs and preferences, MedWISE allows drag/drop user configurations and the sharing of user-created elements such as custom laboratory result panels and user-created interface tabs. After reviewing the current state of EHR configurability, we describe the philosophical, theoretical and practical rationales for our model, and the specific functionality of MedWISE. The alternative approach may have several advantages for human-computer interaction, efficiency, cognition, and fit of EHR tools to different contexts and tasks. We discuss potential issues raised by this approach.