Interface Design Recommendations to Support

Clinical Task Switching

September 30, 2016

Prepared by:Jason Slagle, PhD

Carrie Reale, MSN, RN-BCShilo Anders, PhD

Russ BeebeDan France, PhD

Matthew Weinger, MDHuman Factors & Information Design group

Center for Research and Innovation in Systems SafetyVanderbilt University Medical Center

Prepared for:Ross Speir

Human Factors EngineeringOffice of Health Informatics

Office of Informatics and Information Governance (10P2)Veterans Health Administration

Guidelines & Potential SolutionsWhile performing new or ongoing clinical tasks that demand substantial amounts of providers’ attention, task switching may be disruptive and require reorientation of attention. When switching from one task to another, the cognitive readjustment between tasks, referred to as a “switch cost,” results in slower responses that are more error-prone (Monsell, 2003). It is more difficult and takes twice as long to be reoriented to (resume) more complex tasks compared to routine tasks (Czerwinski, Horvitz & Wilhite, 2004). Task disruptions can have undesirable psychological effects (including more negative mood) and increase required cognitive effort (Zijlstra, et al., 1999). According to the “cognitive fatigue model,” cognitive disruptions increase cognitive demands and are an unexpected and uncontrollable source of mental stress, fatigue and information overload that can cause slips, memory lapses, and/or errors (Collins et al., 2006; Collins et al., 2007; Zheng et al., 2010). Additional effort is required to ignore distractions and remain attendant to the current task and goals (Cohen, 1978; Cohen, 1980). Task disruptions may be important contributors to medical adverse events (Page, 2004; Ely et al., 1995; Hicks et al., 2004; Pape et al., 2005; Potter et al., 2005; Santell et al., 2003; Desselle, 2005; Beso, Franklin & Barber, 2005; Stratton et al., 2004; Wakefield et al., 1998; Walters, 1992; Davis, 1990).

The outpatient care setting is a highly dynamic and complex healthcare domain with many interruptions, workflow process and task inefficiencies which may impact productivity, flow, error rates, and patient satisfaction (Louthan, 2006, Buitrago et al., 1992). Moreover, in primary care, which was the healthcare domain of focus for this project, there are multiple forms of task switching when clinicians interact with electronic health records (EHR). Scenarios where users are required to switch tasks are the result of various system factors. The tasks performed during this process may be highly fragmented (Mamykina et al., 2012). This is particularly true when the clinician is working in an EHR with suboptimal design that does not provide an integrated view of information (Parker & Coiera, 2000). Fragmentation of the documentation process often leads to increased mental workload (secondary to cognitive switching and recall issues among other factors), reduced efficiency, and increased error rates. Properly designed and implemented EHR can promote quality of care (Zahabi, Kaber, & Swangnetr, 2015). Some task switching scenarios can be minimized or even avoided by improved user interface (UI) design (Card & Henderson, 1986). While some interruptions and task switches are inevitable, a properly designed EHR can minimize these disruptions and reduce the negative effects of having to switch tasks. Overall, this can improve quality of care as well as provider experience.

This document summarizes the findings of our project that aimed to: (1) identify task switching scenarios and corresponding UI design recommendations and potential solutions for, at minimum, the primary care setting; and (2) develop usability test objectives and measures for scenarios involving task switching. We conducted a review of the literature by searching a variety of databases (Pubmed, CINAHL, PsycINFO, Web of Science,

ScienceDirect, Wiley Online Library, and Engineering Village) with variations of the following search terms: task switch, interruption, distract, distraction, task fragmentation, toggling, multi-tasking, primary care, task performance and analysis, non-interruptive, Medical Order Entry Systems, electronic medical record, and patient record. The database searches yielded a total of 1,014 articles, of which 52 articles were retained. In addition, 6 articles, which were cited in some of these articles, were also retained as well as 22 articles that were obtained through team members (e.g., previously obtained references, recently observed presentations, reviewer feedback, etc.). All of the scenarios are based on identified issues with CPRS (the VA’s current EHR) or commercial EHRs, based on the literature. The majority of the literature lacked specific recommendations to help resolve workflow disruptions and issues related to task switching in EHR tasks and usage. Therefore, some of the proposed guidelines and potential solutions are ideas generated from the team based on discussions and experiences. Furthermore, the recommendations and potential solutions must be evaluated in context, prior to implementation, when addressing a specific design problem or functional component of the EHR, as there are additional factors that may impact how the concepts are applied in the real world (e.g., VA practice guidelines and policies, or trade-offs between efficiency and safety). The recommendations and potential solutions, which are to be considered as supplemental to previously established guidelines (e.g., NIST, ONC, etc.), are not specific to or aimed towards the current (or imminent) state of the VA’s EHR (i.e., CPRS or eHMP) or any other specific commercial EHR since aspects of their functionality and UIs could always change. Also, note that the accompanying diagrams are intended as illustrative examples only, and not as design guidelines regarding content, layout, styling or interaction characteristics.

A. Patient Identification

Scenario 1: A provider reviews lab results and places follow up orders for multiple patients on his to do list (Mamykina et al., 2012). While confirming dosing recommendations through an online reference database for a new medication to be ordered for patient A, he is interrupted by a phone call regarding patient B. He opens patient B’s chart to address the phone call request. He then resumes the original secondary task of medication research, but fails to notice the chart currently open is now for patient B, not patient A. The provider accidentally orders a medication for the wrong patient when resuming the original primary task.

Problem: Frequent interruptions; distractions; opening and editing multiple patient charts simultaneously; ease of toggling between patient records.

Outcomes: Wrong patient errors; near misses; patient harm.

Recommendation 1: “Information required to accurately identify the patient is clearly displayed on all computer screens, wristbands, and printouts” (ONC, 2014).

Potential Solution: All EHR screens incorporate the following information to support correct patient identification: Last name, first name, date of birth, age, gender, medical record number, in-patient location (or home address or ZIP code), recent photograph (recommended), responsible physician (optional). Appropriate exceptions and alternative identifiers should be considered for cases where this information could create other risks (e.g., victims of domestic violence) (ONC, 2014; Wiklund et al., 2015).

Figure 1: Patient information is displayed similarly in multiple places.

Recommendation 2: Limit the number of open and editable patient charts that can be displayed on the same computer at the same time (ONC, 2014). [Note: For web-based EHR, when users create additional windows or tabs, users should be required to login again and all subsequent logins should be in a “Read Only” mode, with this mode being clearly noted and distinguishable.]

Potential Solution: “The EHR limits the number of patient records that can be displayed on the same computer at the same time to one, unless all subsequent patient records are opened as ‘Read Only’ and are clearly differentiated to the user” (ONC, 2014).

Figure 2: Only one patient’s chart is editable at a time.

Recommendation 3: The EHR supports verification of patient identity, specifically that the intended patient record is open and active when performing a potentially high risk task, at key points in the care delivery process (e.g., vital sign recording, order entry, medication administration, and check out) (ONC, 2014; Wilcox, Chen & Hripcsak, 2011; Adelman et al., 2012).

Potential Solution: “Before opening a specific patient record or signing an order, the user is shown a picture, or the name, gender, and age of the patient” (ONC, 2014). When there is the possibility of patient identity

confusion or known risk to patient safety, a confirmation screen may be used (Adelman et al., 2012). At a minimum, these patient identifiers are displayed in close proximity to the ordering fields within the order confirmation screen. [Note: This recommendation involves a clear trade off between efficiency and safety. In a randomized controlled trial, Adelman et al. (2012) found “an ID-verify alert (single-click confirmation of patient identity) reduced wrong-patient electronic orders by 16%” but added an average of 0.5 seconds to the task time.]

Figure 3: Patient confirmation dialog.

Potential Solution: Clinicians are asked to reaffirm patient identity by entering the patient’s initials before signing an order (e.g., high risk medications) (ONC, 2014; Adelman et al., 2012). [Note: This recommendation involves a clear trade off between efficiency and safety. In a randomized controlled trial, Adelman et al. (2012) found “an active ID-reentry function (requiring active reentry of identifiers [initials, gender and age]) achieved a 41% reduction” in wrong-patient electronic orders but added an average of 6.6 seconds to the task time. Of the actual wrong patient order errors analyzed, the ordering providers identified 80.6% as interruption errors.]

Figure 4: Patient confirmation via active entry of patient’s initials.

Potential Solution: After a specified period of inactivity, the user is shown a picture, name, gender, and age of the patient to verify identity before resuming data entry in the EHR.

Figure 5: Patient confirmation following period of inactivity.

Potential Solution: The EHR alerts users when a medication is ordered without an appropriate active problem on the patient’s problem list (Galanter et al., 2013).

Figure 6: Alert regarding potential wrong medication order.

B. Incomplete or Disrupted Tasks

Scenario 2: A provider is interrupted by a phone call (or other external distraction such as a page, e-mail, conversation with another clinician or patient). This interruption draws her away from her current task in the EHR. She then cannot remember what she was doing in that patient’s chart.

Problem: Work disruptions.

Outcomes: Uncompleted tasks or work.

Recommendation 4: Provide users the ability to re-visit and flag a field or section and make temporary comments to help users remember what they were doing, or meant to do, when interrupted.

Potential Solution: By right-clicking, hot keys or menus, clinicians can flag a section and make temporary annotations, which support recall when users go back to the section and resume the task that was interrupted.

Figure 7: Adding a “note to self” and accessing it at a later time.

Potential Solution: Provide navigation buttons (i.e., back and forward buttons) in the EHR sections to re-visit areas where users were previously documenting or reviewing.

Recommendation 5: Provide an aggregate list of recent EHR related activity to help users review where they have been over a specified period of time. This should include an easy way to identify and access the last dozen patients’ charts opened by the provider, and the last document accessed in each one.

Potential Solution: A sortable (e.g., by date/time, field, patient, due date, etc.) log of items or recent EHR activities would help users see where they were previously working before switching to another task(s). When applicable, the log would also indicate if the item is incomplete.

Figure 8: An automatically generated log of a user’s activity within the EHR.

Scenario 3: A provider is documenting between patient visits, trying to finish the note for the patient she just saw (Park, Lee & Chen, 2012). She suddenly remembers something else more pressing she must do before the next patient’s visit. She does not want to forget what or where she was in the current EHR task so she can come back to it sometime later that day.

Problem: Work disruptions.

Outcomes: Uncompleted tasks or work.

Recommendation 6: Provide users with the ability to record their plans to accomplish interrupted or necessary tasks in the near

future, for both individual patients and populations of patients (e.g., screen my panel for current pneumovax).

Potential Solution: Provide a dedicated area for personal “To-do lists” or “Next steps” lists, which are not part of the permanent patient record.

Figure 9: A user’s to-do list.

C. Patient Visits (Patient Engagement, Privacy Concerns, Entry Reminders)

Scenario 4: During patient encounters, the provider is switching between paying attention to the patient and documenting in the EHR (e.g., History and physical, symptoms, problem list and reason for visit) (Alkureishi et al., 2016; Asan, Ye & Acharya, 2013; Asan et al., 2015; Aydin & Forsythe, 1997; Booth, Robinson & Kohannejad, 2004; Delbanco, 2002; Delbanco et al., 2012; Elli, 2012; Farber et al., 2015; Gibson et al., 2005; Jing et al., 2016; Koong et al., 2015; Pandit & Boland, 2013; Pearce et al., 2012; Realini, Kalet & Sparling, 1995; Saleem et al., 2014; Shachak et al., 2009; Street Jr, et al., 2014; Zhang et al., 2016).

Problem: Inability to include the patient in or engage the patient during EHR usage.

Outcomes: Back or side of body facing patient; providers are distracted by EHR-related tasks (e.g., documentation tasks); breaks or interruptions in conversation; delays and prolonged encounters that contribute to increased workload; decreased patient satisfaction or trust in the provider (Alkureishi et al., 2016; Asan, Ye & Acharya, 2013).

Recommendation 7: The EHR should include a simplified “patient encounter mode,” which includes visual tools (Plaisant et al., 1996) that help clinicians increase patient engagement during encounters. This mode would support shared use of the EHR as an educational and communication tool, while minimizing distractions related to EHR usage, increasing eye contact during patient encounters, and possibly involving the patient in at least part of the documentation process (Asan, Ye & Acharya, 2013; Asan et al., 2015).

Potential Solution: The “patient encounter mode” UI promotes provider and patient collaboration in shared information gathering and review tasks (e.g., creating shared goals and an individualized care plan, reviewing test results across time, etc.) by presenting simplified input fields and information displays, with the ability to exclude sensitive information (Eikey et al., 2015).

Figure 10: Patient encounter mode simplifies the UI.

Recommendation 8: The EHR should include a “patient encounter mode” that enables multiple types of data entry to minimize time spent on activities that divert attention from the patient encounter, direct communication, and eye contact.

Potential Solution: A “patient encounter mode” allows for data to be entered via a variety of methods, other than typed text, such as voice (i.e., dictation), and handwriting (i.e., note-taking on paper or on touch screen via a stylus) recognition (Asan et al., 2015; Dela Cruz et al., 2014).

Recommendation 9: Allow providers to flag an entry to be filled in later (e.g., when alone with the patient to avoid discussing potentially embarrassing information in front of family members; after patient visit if involves information that does not pertain directly to the patient encounter).

Potential Solution: Clicking an icon within a data entry section highlights the empty or incomplete fields with a unique color that is easily recognizable for quickly locating the information on subsequent return.

Figure 11: Items in sections can be highlighted for locating quickly at some later time.

Potential Solution: Integrate patient information (e.g., insurance and other billing information based on payment guidelines), which is previously entered by patients and staff (e.g., from clinic forms, patient portals, other EHR sections or recent records), into the note in advance of the patient appointment to allow a provider to review and accept it (i.e. through templates designed by the practice or institution). This will allow documentation during and between patient encounters to be limited to pertinent medical information (Feufel, Robinson & Shalin, 2011).

Scenario 5: In the middle of a conversation with the patient, the provider feels the need to populate missing data (i.e., empty fields prominently displayed on the computer screen in front of her) before she forgets to do so later (Feufel, Robinson & Shalin, 2011; . The provider interrupts the flow of the current conversation with the patient to ask the patient for the data in a particular field.

Problem: Inability to include the patient in or engage the patient during EHR usage.

Outcomes: Prolonged pauses or awkward breaks in patient conversations; forgetting train of thought in the topic of conversation before the interruption; delays and prolonged encounters that contribute to increased workload; decreased patient satisfaction or trust in the provider.

Recommendation 10: Aggregate missing data fields to help providers remember to enter the data at their earliest convenience and to streamline the subsequent data entry process.

Potential Solution: Missing data fields are aggregated on a separate form to be filled out after or at the end of the patient encounter.

Figure 12: Incomplete form fields are aggregated for efficient completion at some later time.

D. Alerts

Scenario 6: A provider is taking a patient's history and physical, and obtaining information about the chief complaint. While talking with the patient and

attempting to document the key data elements, multiple alerts and reminders interrupt him.

Problem: Avoidable disruptions; poor UI design.

Outcomes: Prolonged pauses or awkward breaks in patient conversations; forgetting train of thought in the topic of conversation before the interruption; delays and prolonged encounters that contribute to increased workload; alert fatigue or the majority of alerts are overridden (Gaikwad et al., 2007; Horsky et al., 2013; Koplan et al., 2012; Lo et al., 2007; Lo et al., 2009; McDonald et al., 2011; Phansalkar, Desai et al., 2013; Phansalkar, van der Sijs et al., 2013; Rayo et al., 2015; Wipfli & Lovis, 2010).

Recommendation 11: Avoid alerts and reminders that are modals, with the exception of safety critical alerts, which force providers to stop what they are doing and tend to that alert or reminder before they can do anything else.

Potential Solution: Provide non-critical alerts in a constantly visible but unobtrusive zone so that other active workspaces are not obstructed from view until they are resolved. The alerts could be formatted in a way that draws attention to or minimizes the potential of them being forgotten (Rayo et al., 2015) (e.g., color-coded borders).

Figure 13: Display of most alerts occurs in one consistent, prominent location.

Recommendation 12: Allow for alerts and reminders to be aggregated, sorted, searched, managed, and acknowledged.

Potential Solution: Provide an aggregated alert function which is sortable and searchable (e.g., by name, patient ID, date, type, and priority level) and can be referred to at the end of or after a patient visit.

Figure 14: Alerts can be viewed as a sortable, independently actionable table.

Potential Solution: If information is already in the system (e.g., NLP or clinical decision support tools), the EHR automatically populates appropriate fields related to the reminders and alerts and, if possible, sends the questions to the patient for completion in advance of the appointment (e.g., patient portal messages or email with a link to the patient portal) to minimize data gathering time for the clinician.

Scenario 7: While documenting between patient visits, the provider received an alert about an abnormal CT scan on one patient suggesting a possible new lung mass. However, she was interrupted about another patient, and when she opened the other patient’s chart, the first alert disappeared. Unfortunately, she cannot remember on which of her many patients was the alert and now cannot retrieve it. To find the patient with the potentially serious new finding, she requests a report of all radiology alerts in last 48 hours. She jots a paper note to herself to watch for the report knowing that she may have to manually review dozens of charts (Ruark et al., 2016).

Problem: Avoidable disruptions; poor UI design.

Outcomes: Delays in patient treatment; forgetting train of thought before the interruption; delayed patient encounters that contribute to increased workload; relying on paper rather than using EHR (Mamykina et al., 2012; Mc Quaid et al., 2010; Niazkhani et al., 2011; Park, Lee & Chen, 2012).

Recommendation 13: Allow users to ask to be reminded later when an alert displays, and to specify at what stage of their workflow to redisplay the alert.

Potential Solution: After selecting the “remind me later” option in the alert, allow users to specify at what stage of their workflow to redisplay the alert (e.g., date and time, days or hours hence, or next time they are doing a specific function, such as writing orders, opening that patient’s chart, logging in, etc.).

Figure 15: Users can opt to redisplay alerts at a set time.

SCENARIO 8: A provider is bombarded with alerts and reminders, during and between patient encounters, which may not have clinical value and may be quite distracting (Gaikwad et al., 2007; Horsky et al., 2013; Koplan et al., 2012; Lo et al., 2007; Lo et al., 2009; McDonald et al., 2011; Phansalkar, Desai et al., 2013; Phansalkar, van der Sijs et al., 2013; Rayo et al., 2015; Wipfli & Lovis, 2010). He reflexively overrides almost all of them.

Problem: Avoidable disruptions; poor UI design.

Outcomes: Prolonged pauses or awkward breaks in patient conversations; forgetting train of thought after the interruption; delays or prolonged tasks and encounters that contribute to increased workload.

Recommendation 14: Provide a feedback mechanism that allows clinicians to indicate if an alert or reminder was not useful, inappropriate, or uninformative.

Potential Solution: Provide a checkbox for alerts, when appropriate, that allows clinicians to indicate they feel the content is inappropriate or not useful and, if so, provide the reason. This information will help identify patterns, via data analytics, that identify alerts to be considered for elimination.

Figure 16: Users can provide feedback about alerts.

E. Orders

Scenario 9: The provider is unable to complete the consult template questions without reviewing her visit note. In addition, she is not able to pause or save her work. Therefore, she must exit the consult template, find and review her

visit note, copy information to paper, and then restart the consult template (Ruark et al., 2016).

Problem: Poor functionality and UI design.

Outcomes: Inefficiencies and prolonged tasks; potential for incorrect entries or orders due to rushing; delays in subsequent tasks and workflow.

Recommendation 15: When a user exits a section, any data entered should be automatically saved or stored to a draft mode, as appropriate; if in a draft mode, the user should be given the option to confirm or cancel the autosaving. The user should also have the option to manually save data. The state of data saving should be indicated.

Potential Solution: Each section should have a save button (as well as autosave to draft mode functionality when appropriate) and a separate “confirm” button when exiting that section.

F. Searching

Scenario 10: A provider ends up spending considerable amounts of time before, during and after patient visits switching back and forth from writing in his note on a particular patient to searching the EHR for pertinent patient information (e.g., other notes and specific information from prior visits, related labs and tests, current medications, consults, etc.). It is often difficult to find specific information, particularly data elements embedded in narrative documents (Benda et al., 2016; Billman & Bier, 2007; Chao, 2016; Han & Lopp, 2013; Hsu et al., 2012; Mamykina et al., 2012; Press et al., 2015; Varpio et al., 2015). The Problem and Medication Lists are frequently out-of-date and inaccurate (Schnipper, 2008; Zhou et al., 2012).

Problem: Inability to have automated searching capabilities from multiple data sources.

Outcomes: Increased workload due to inefficiently spending substantial amounts of time searching and switching between note writing and information search and retrieval tasks; incomplete tasks or work; dissatisfaction with EHR; burnout.

Recommendation 16: Provide the ability to perform queries to retrieve information from multiple EHR data sources. The information from the patient record that matches the query should be displayed in an adjacent or simultaneously visible zone. Values related to such queries (e.g., lab values) should be presented in visually aggregated forms (e.g., tables, charts, etc.). Minimize the effort (e.g., keystrokes and mouse clicks) and time required to generate such data queries (Wilcox et al., 2010).

Potential Solution: By selecting text with the cursor and right-clicking or pressing on a hot key, the EHR's data sources (e.g., multiple documents, notes or records for a particular patient) are searched for the selected text (Wilcox et al., 2010).

Figure 17: Search results are aggregated.

Recommendation 17: Allow for data that is displayed in other data sources to be inserted into a patient's note with minimal effort (e.g., keystrokes and mouse clicks) and time spent.

Potential Solution: By right-clicking or pressing on a hot key, a selected item (e.g., a lab value of interest) is copied and entered directly into the patient's note that is currently being written (Wilcox et al., 2010).

Figure 18: Appending content to a note is streamlined.

Recommendation 18: Key text, which matches a user-generated query, should be formatted to be visibly distinguishable from other displayed text (Wilcox et al., 2010).

Potential Solution: Key words that match the search term(s) for user-generated queries are highlighted.

Figure 19: Search terms are highlighted.

Scenario 11: A provider must manually search to find more recent results for her patient than the tests that she had ordered at the patient’s last visit. In the interim, that patient had been to the ER and then referred to several specialists.

Problem: Inability to have automated updating capabilities from multiple data sources.

Outcomes: Increased workload due to inefficiently spending substantial amounts of time searching and switching between note writing and information search and retrieval tasks; incomplete tasks or work; dissatisfaction with EHR; burnout.

Recommendation 19: Allow providers to request that a specific item (e.g., values from lab tests) related to a particular organ system or function to be automatically updated in a note still in progress for a specified time period or frequency (Wilcox et al., 2010). The request should be able to be easily cancelled. The provider should receive a non-interruptive notification if an automatic update occurs, that allows the provider to access that patient’s note. The updated information should be visually distinct (Wilcox et al., 2010).

Potential Solution: By right-clicking the selected item or pressing on a hot key, each type of test is marked, through high level terms (e.g., all labs, tests, and orders related to liver function with a query for the search term “liver” or “hepatic”), and set to automatically update the value of the selected items at a specified time period or frequency (Wilcox et al., 2010).

Figure 20: Lab or test values can be automatically updated.

Recommendation 20: Allow for all values (i.e., initial value and subsequent values since request) of the queried item to be aggregated and displayed.

Potential Solution: Provide summaries of initial and updated values of a queried item to be aggregated and displayed in an interactive table or chart (Wilcox et al., 2010).

Figure 21: Lab or test histories are easily accessed and acted on.

Scenario 12: A provider cannot place orders or modify the care plan because he is waiting on lab results for that patient (Saleem et al., 2014).

Problem: Delays in treatment; inability to have automated alerting capabilities from multiple data sources; potential to forget contingency plan due to lack of support for prospective memory.

Outcomes: Increased workload due to inefficiently spending substantial amounts of time searching and switching between note writing and information search and retrieval tasks; incomplete tasks or work; dissatisfaction with EHR; burnout

Recommendation 21: Allow other members of the patient’s care team to request notification when the value(s) for a selected item (e.g., values from the selected lab test) falls outside a certain range (Wilcox, 2010; Alkasab, 2010; Feufel, Robinson & Shalin, 2011; Park, Lee & Chen, 2012; Weidemann, 2012).

Potential Solution: Allow a clinician to set an automatically-generated alert for a flagged item if it becomes lesser than, equal to or greater than

a specified value. The user can specify whether the notification should be sent to that user or other clinicians on the patient’s care team.

Figure 22: Alerts can be set to display when test results fall outside pre-set ranges.

G. Training/Tutorials

Scenario 13: A provider is documenting at the end of the day. He is exploring the EHR and trying to figure out how to find and order a specific test. After many minutes of searching and trying things, he gives up in futility. He ends up getting lost in the EHR and forgetting his primary task and intended future tasks.

Problem: Lack of easily accessible and usable educational materials.

Outcomes: Wasted time; increased workload due to running out of time; incomplete tasks or work; dissatisfaction with EHR; burnout.

Recommendation 22: Provide avenues for high quality training and documentation skills acquisition for all EHR functions, tasks, items, and topics (Farber et al., 2015; Feufel, Robinson & Shalin, 2011; Saleem et al., 2014).

Potential Solution: Provide educational tutorials in various formats (e.g., videos, text and screenshots) that are easily discoverable within the relevant EHR context, accessible in menus, indexed for searches within an allocated section, and accessible by category headers (e.g., via hyperlinks, right clicking, etc.).

Figure 23: Various help materials are readily available throughout the EHR.

Usability Objectives & Measures

OBJECTIVESOverall usability objectives are to assess the effectiveness, efficiency, and user satisfaction of design solutions implemented to address task switching problems and mitigate the risk for negative outcomes identified in the recommendations and potential solutions. The following examples of usability objectives may be incorporated into broader usability evaluation strategies for specific EHR functionality when task switching has been identified as a frequent or high risk factor.

Usability objectives related to task switching might examine how well the system supports users’:

Completion of primary and secondary tasks that require interaction with multiple screens or modules in the EHR

Ability to pause or save work in progress when a task cannot be completed at that point in time

Prospective memory for interrupted or incomplete tasks Completion of tasks that require searching for additional information

within the EHR (or related systems) Ability to identify or navigate back to recently viewed information within

the EHR Management of interruptive alerts and reminders Entry and extraction of information from the EHR during a face-to-face

patient visit

MEASURESFormative Evaluations:

Effectivenesso Appropriateness of potential task switching design solutions in

context (i.e., within specific clinical functionality, overall workflows, environment of use, etc.)

o Fit of potential design solutions to users’ existing task switching mental models and coping strategies

o Confusion about or misinterpretation of interface elements designed to support task switching

Efficiencyo Relative trade-offs of potential task switching design solutions (e.g.,

efficiency vs. safety when implementing additional patient verification steps)

o Deviations from optimal or expected task pathways when users encounter a task switching activity

Satisfactiono Subjective user impressions of a design solution’s perceived

support for task switching activities

Summative Evaluation:

Effectivenesso Completion rates (successes and failures)

Overall scenario objective Primary or initial tasks Secondary tasks

o Errors Number of errors related to task switching Type of task switching errors (e.g., ordering, such as wrong

or inappropriate medication ordered, ordered for wrong patient or site; ignoring or oversight, such as ignored or inappropriately overrode alerts)

Safety-related errors (e.g., incomplete patient information entered due to an interruption)

General use errors (e.g., clicking on the wrong navigational link when attempting to return to the primary task)

Severity of errors, especially safety critical errors (i.e., severity of impact rating)

Task switching factors and behaviors that contribute to errors Timing of errors in relation to task switching behaviors (i.e.,

did the error occur after the primary task was interrupted, when the primary task was resumed, etc.)

Efficiency (Magrabi et al., 2010; Magrabi et al., 2011; Zheng et al., 2010)o Number of tasks completed in a defined time periodo Task Times

Amount of time to complete the primary task Without secondary task/interruption With secondary task/interruption

Amount of time until primary or initial task was switched or interrupted

Amount of time to resume task when switching to or interrupted by secondary or other tasks (i.e., resumption lag)

Amount of time to complete secondary tasks, switched tasks and interruptions

Number of secondary tasks, switched tasks and interruptions Time between secondary tasks, switched tasks and

interruptions o Steps to complete tasks

Number of actions taken to complete primary objectives and tasks, (e.g., mouse-clicks, right clicks, hot-key usages, searches)

Number of actions taken to complete secondary tasks Deviations from optimal or expected task switching pathways Instances where a task had to be restarted or redundant work

completed due to task switchingo Interruption handling

Number of times switched or interrupted from primary or initial task

Number of broken primary tasks not completed (i.e., broken

tasks) Type and amount of similarity of secondary tasks and

interruptions to primary or interrupted task Source of interruption (e.g., self-initiated but different task or

page; external, such as an alert; environmental, such as other clinicians, patient, phone, pager, EMR navigation or usage confusion resulting in delays in task completion, technical or computer malfunction)

Satisfactiono Subjective user’s impressions of system’s support for cognitive

workload during task switching, interruption handling, prospective memory, and task resumption

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