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

Abstract

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.

Patient safety issues from information overload in electronic medical records: A systematic review

“…Efficiently extracting clinically relevant information from the EHR can be a difficult task for physicians. 15,16,20,21 This increased cognitive load placed on physicians makes them more prone to clinical errors, which puts patient safety at risk. 15 In addition, the stresses of information overload contribute to physician frustration and burnout, which can also lead to an increase in medical errors.…”

“…One such solution is a customizable EHR to ensure that important data is easier to find. 15,20 Studies that tested this type of software showed significant reductions in error rates and improvements in efficiency. Pickering et al 31 introduced a novel user interface called AWARE (Ambient Warning and Response Evaluation) for use in the intensive care unit.…”

“…A conclusion offered by these authors was that the poor usability of conventional EHR's decreases physician comprehension, requiring data to be revisited multiple times until it is fully understood. 20 However, simply allowing for user composability does not guarantee increased efficiency as illustrated by Ratwani et al 21 The usability and safety of Cerner and Epic were assessed by having 4 different groups of 12-15 physicians at different institutions (two groups using Epic, two groups using Cerner) complete basic tasks such as ordering imaging, labs, and medication for fictitious patients.…”

User-Centered Clinical Display Design Issues for Inpatient Providers

“…Second, switching between screens to assemble the picture increases the demand on memory and, when memory fails, it causes users to repeatedly look back to previous screens to remind themselves what they have already seen. [31][32][33] Third, forcing the user to decide what to look at next in sequence increases the cognitive burden of assembling the picture. 34,35 This burden is particularly heavy for less-experienced trainees.…”

<p>Clinical Documentation to Predict Factors Associated with Urinary Incontinence Following Prostatectomy for Prostate Cancer</p>

“…8 Previous studies have shown that detail regarding a patient's experience of UI is often documented in free-text, unstructured EHR elements such as clinician notes, which can be parsed with data mining methods such as natural language processing (NLP) to extract the incidence of the outcome. 9 As structured data (e.g., billing codes) analysis alone may not sufficiently capture outcomes like UI that are not routinely coded, data mining methods may improve the robustness of research on these patient-centered outcomes (PCOs) and on larger patient populations, which could yield more generalizable findings. 10 Previously, we have described an NLP approach for identifying UI following prostatectomy that showed high concordance with patient-reported outcomes captured using EPIC-26.…”