Leveraging the Electronic Health Record to Implement Emergency Department Delirium Screening

Abstract

Objective The aim of this study is to understand how emergency departments (EDs) use health information technology (HIT), and specifically the electronic health record (EHR), to support implementation of delirium screening.

Methods We conducted semi-structured interviews with 23 ED clinician-administrators, representing 20 EDs, about how they used HIT resources to implement delirium screening. Interviews focused on challenges participants experienced when implementing ED delirium screening and EHR-based strategies they used to overcome them. We coded interview transcripts using dimensions from the Singh and Sittig sociotechnical model, which addresses use of HIT in complex adaptive health care systems. Subsequently, we analyzed data for common themes across dimensions of the sociotechnical model.

Results Three themes emerged about how the EHR could be used to address challenges in implementation of delirium screening: (1) staff adherence to screening, (2) communication among ED team members about a positive screen, and (3) linking positive screening to delirium management. Participants described several HIT-based strategies including visual nudges, icons, hard stop alerts, order sets, and automated communications that facilitated implementation of delirium screening. An additional theme emerged about challenges related to the availability of HIT resources.

Conclusion Our findings provide practical HIT-based strategies for health care institutions planning to adopt geriatric screenings. Building delirium screening tools and reminders to perform screening into the EHR may prompt adherence to screening. Automating related workflows, team communication, and management of patients who screen positive for delirium may help save staff members' time. Staff education, engagement, and access to HIT resources may support successful screening implementation.

Keywords

delirium - screening - geriatrics - electronic health record

Background and Significance

Delirium is a syndrome of confusion, inattention, and acute brain failure, which is potentially fatal for older adults and incurs billions of dollars of annual health care costs.[1] Delirium affects about 10% of older adults in the emergency department (ED) setting,[2] [3] but over two-thirds of cases are not detected.[4] [5] [6] [7] Patients with unrecognized delirium—that is, not detected by clinicians but determined to be present on formal assessment by researchers—who are discharged from the ED have a sevenfold increased mortality rate.[8] As older adults' ED utilization continually increases over time,[9] so must the adoption of care processes geared toward their unique clinical needs.[10] National emergency medicine organizations such as the American College of Emergency Physicians, Society for Academic Emergency Medicine, and Emergency Nurses Association have recommended evidence-based ED delirium screening.[10] However, ED environments are characterized by high acuity, crowding, and staff time constraints. Incorporating delirium screenings into routine ED environments is challenging.[11] [12] Optimizing information technology systems to support clinicians in performing geriatric screenings is an important consideration for their successful implementation.[11] [13] [14]

Uptake of evidence-based guidelines for ED delirium screening has been limited.[15] [16] This is in part due to the complexities of implementation, such as determining appropriate time points for screening, which personnel should be involved, and incorporating tools into existing workflow.[13] [17] The Geriatric ED Guidelines, a set of evidence-based recommendations for the emergency care of adults ages 65 and over,[10] recommends ED delirium screening using the Delirium Triage Screen (DTS),[18] which, if positive, is followed by the brief Confusion Assessment Method (bCAM).[19] These tools use both observation of a patient and direct questions to the patient to assess for altered level of consciousness, inattention, and disorganized thinking. This DTS/bCAM-based screening process can involve multiple health care professionals and communication among multiple members of the care team. Additionally, in emergency care settings that do not have dedicated geriatric resources or formal geriatric protocols, emergency clinicians and nurses may be unfamiliar with these delirium screening tools.[3] [20] [21] Given these potential challenges, understanding implementation of ED delirium screening is crucial. However, scholarship on this subject[13] is limited and includes only a description of a protocol development process and a qualitative study describing challenges screening patients with non-English primary languages.[22]

Health information technology (HIT) can be used to facilitate implementation of interventions to improve patient safety.[23] Little is known about how to successfully implement ED delirium screening.[3] One recently described ED delirium screening program highlighted the crucial roles of nursing involvement and documentation in the electronic health record (EHR) in successful implementation.[13] Otherwise, it is unknown how best to integrate delirium screening into the EHR so it fits within the ED workflow and can provide optimal cognitive support to clinicians.

Objectives

Our objective was to use qualitative methods to understand how early adopters of ED delirium screening use the EHR to support its implementation. Generating such information can provide practical strategies for health care institutions planning to adopt geriatric screenings in the ED to improve patient care outcomes.

Methods

We performed a qualitative study with a convenience sample of clinician-administrators and clinician-leaders of geriatric care processes in EDs that had adopted delirium screening and had incorporated it into their EHR. We report methods using the Consolidated Criteria for Reporting Qualitative Research (COREQ).[24]

Study Design

Between December 2021 and June 2022, we conducted semi-structured interviews focusing on challenges participants experienced when implementing ED delirium screening and strategies they used to overcome them. As part of this investigation, we asked participants about their experiences with HIT resources, such as EHR support teams and infrastructure, to implement their delirium screening protocols. The interview guide for the study was developed based on literature review and the authors' prior experiences with implementation of geriatric processes and policies in EDs.[15] We modified and refined wording of questions based on two pilot interviews, each with one participant within the research team, to finalize the interview guide ([Supplementary Appendix], available in the online version).

Recruitment and Study Sample

To recruit participants, we sent email invitations to list-servs of national geriatric emergency medicine organizations (Geriatric ED Collaborative, the Academy for Geriatric Emergency Medicine) and a multidisciplinary network focused on delirium research (the Network for Investigation of Delirium: Unifying Scientists). We recruited ED clinician-administrators due to their unique insights into the conceptualization, design, and implementation of the ED delirium screening process at their institution. ED administrators included nurses, physicians, advanced practice providers (APPs), and allied health professionals, all of whom practiced clinically in the ED. Given their active clinical practice, all interviewees were also end-users of their delirium screening protocols, but this research focused on participants with operational roles and knowledge. From the set of initial respondents, we used chain referral sampling to identify and recruit additional participants from sites that had adopted ED delirium screening. Chain referral sampling is a respondent-driven network sampling technique used to reach a hard-to-find population of individuals with a rare trait of interest[25]—here, the adoption of ED delirium screening. Twenty-six ED administrators and leaders of geriatric care processes volunteered to participate. Of these, 23 completed interviews, and 3 lacked mutual availability with the interviewer.

Data Collection

A research assistant (I. S.) with prior interviewing experience performed semi-structured interviews. The research assistant was not a clinician and did not have prior relationships with study participants. Interviews were supervised by a qualitative methods expert with a PhD in Anthropology (A. N. C.). We used an online audio-visual platform to obtain informed consent and perform interviews. Seventeen one-on-one interviews were performed and an additional three interviews were conducted with two interviewees each representing their respective institution. Participants received no financial compensation. Excluding informed consent procedures, interviews lasted 15 to 50 minutes. Audio recordings of interviews were professionally transcribed and reviewed for accuracy by the research team.

Data Analysis

Our analytic approach was based in phenomenology, which aims to understand participants' experiences related to a specific context or phenomenon—here, ED delirium screening. For responses to questions about the use of information technology, we first used a deductive approach, in which a priori codes are applied to categorize interviewee responses. Codes were derived from the Singh and Sittig sociotechnical model, which addresses use of HIT in complex adaptive health care systems.[26] Dimensions are described in [Table 1], which paraphrases definitions of the model and served as the study codebook.

Table 1 Singh and Sittig sociotechnical model for use of health information technology in healthcare systems*

Sociotechnical domain	Description
Hardware and software	Equipment and software that supports clinical applications
Human–computer interface	Aspects of computer that users see, touch, hear while interacting with it
Workflow and communication	Processes involved in effectively carrying out patient care tasks
People	All individuals who interact with the system in some way, including developers and end users
Measurement and monitoring	Measuring and evaluating consequences of implementing health information technology–supported intervention
Clinical content	Data and images comprising the “language” of clinical applications
Internal organizational policies, procedures, and culture	Internal organization's structures and environment that impact all dimensions of sociotechnical model
External rules and regulations	External forces that facilitate or constrain design, development, implementation, and use of health information technology

Source: Adapted with permission from Sittig and Singh.[26]

We used the qualitative data analysis program SaturateApp (www.saturateapp.com). Two researchers coded each transcript independently (B. T. and E. B.). Subsequently, a third researcher with qualitative expertise (A. N. C.) led consensus discussions to resolve discrepancies in coding. The eight dimensions of the sociotechnical model are overlapping and interdependent.[26] As such, we then used an inductive approach, in which themes are identified based on repeated patterns among interviewee experiences, to identify common themes across codes about how the EHR could be used to address challenges in implementation. We held consensus discussions involving group review of each piece of coded data to identify themes. No new themes emerged after 15 interviews, indicating thematic and data saturation and an adequate sample size to capture participants' range of experiences.

Results

Twenty-three administrators participated in interviews, representing 20 EDs that performed ED delirium screening in the United States and Canada. ED administrators included physicians, nurses, APPs, and an allied health professional. Participants served as champions of geriatric initiatives in their departments. All EDs were teaching institutions and the majority were accredited as geriatric EDs by the American College of Emergency Physicians.[27] Most of the EDs represented used a two-step ED delirium screening process consisting of an initial screen performed by a triage or bedside nurse, which, if positive, required a clinician to perform a second screen. Almost all sites (n = 19, 95%) used the Confusion Assessment Method (CAM) or a modified version of the CAM as their screening tool. Sample characteristics are further described in [Table 2].

Table 2 Interviewee roles and represented emergency departments' characteristics

Characteristic	N (%)
Interviewee's professional role
Emergency physician	14 (70)
Emergency nurse	5 (25)
Emergency medicine advanced practice clinician	3 (15)
Emergency medicine allied health professional	1 (5)
Country of practice
United States	18 (90)
Canada	2 (10)
Teaching institution	20 (100)
Geographic setting
Urban	14 (70)
Suburban	4 (20)
Rural	2 (10)
ED geriatric accreditation status
Accredited	14 (70)
Nonaccredited	6 (30)

Abbreviation: ED, emergency department.

Note: The first row details identities of N = 23 interviewees who represent 20 EDs. All subsequent rows detail attributes of N = 20 EDs.

Four main themes emerged. Three were related to how the EHR could be used to address challenges in implementation of delirium screening: (1) staff adherence to screening, (2) communication among ED team members about a positive screen, and (3) linking positive screening to delirium management. The fourth theme that emerged was about challenges related to the availability of information technology resources. [Table 3] provides quotations illustrating each theme, organized by dimension of the Singh and Sittig sociotechnical model used for data analysis. [Table 4] presents challenges and HIT-based strategies participants identified and carried out in their implementation experiences, organized by six dimensions of the Singh and Sittig sociotechnical model. These strategies are additionally described in the following text.

Table 3 Illustrative quotes about sociotechnical considerations in ED delirium screening among early adopters

Singh and Sittig sociotechnical dimension	Quotation
Hardware and software	Theme: Adherence to screening “We don't have a computer in every patient room. The screens weren't intuitive to the nurses. And so it was just this extra sort of step where you would have to grab this thing to find out what the questions were to kind of get it implemented.” -Participant J Theme: Adherence to screening “We were doing [screening] first on paper for the first couple of years, which is extremely burdensome and hard to do, and try to really remain compliant with. But once we got them to the electronic health record and kind of started forcing people to do it, it became a little more automated. So yeah, I'd say our compliance rate is pretty good now.” -Participant K
Clinical content	Theme: Compliance “[The physician] has a dot phrase that pulls all that information [responses to each component of screening] into their note along with marking if the patient is truly delirious or not.” -Participant G Theme: Linking screening to management “[The delirium order set] walks through any medications that you may need to order. It also walks through things to keep the patients safe … making sure they're toileting, removing any unnecessary tethers, providing food and drink, mobilizing the patient if you're able to.” -Participant P
Human–computer interface	Theme: Adherence to screening “We also made it a hard stop so they [nurses] can't complete their notes without doing the screen as well.” -Participant V Theme: Communication and situational awareness “So we're looking at putting icons within our electronic system that notify anybody that this person screened positive.” -Participant F Theme: Linking screening to management “So once the patient screen is positive, the nonpharmacologic interventions will pop up.” -Participant A
Workflow and communication	Themes: Communication and situational awareness “Again, I think the biggest challenge is just continuing to remind the nurses to notify the physician when they do screen. And I think that line of communication isn't happening as well as it probably should. And there's not a great mechanism to do it within the EHR.” -Participant X Themes: Adherence to screening, resources “Make sure you have all of your people in all the areas on your side right from the start…working with IT closely. Because if you can get [delirium screening] within the nurses' already current workflow…and not added as an extra, they'll have a better chance of sustainability.” -Participant B
People	Theme: Resources “I had an assigned information technology analyst. Our ED quality improvement officer helped with data pulling and building a dashboard.” -Participant G
Measurement and monitoring	Theme: Resources “We've got a pretty extensive tracking system. We've got dashboards that are really easy to review.” -Participant T Theme: Resources “We have a report that comes monthly from informatics that shows us each patient that received a geriatric nurse assessment. And so right now we have a dashboard that's in progress that we're working on.” -Participant E
Internal organizational policies, procedures, and culture	Theme: Resources, linking screening to management “We pulled the delirium triage screen and brief Confusion Assessment Method [delirium screening tools] from [the] inpatient [setting]. It was already implemented in the EMR inpatient. And so we chose those two specific screening tools to keep it consistent with our hospitalists, and it was easy to then pull into the ED interface.” -Participant A
External rules and regulations	Theme: Resources, linking screening to management “In [my state], the governor has put a mandate out there for all health care systems to focus on recognizing and acting on delirium, dementia, [and] geriatric cognitive needs.” -Participant F Theme: Resources “I think that being accredited as a level one geriatric emergency department kind of brings additional weight behind these sorts of decisions...We used the geriatric ED guidelines [for our delirium screening protocol].” -Participant H

Table 4 Sociotechnical interventions to overcome challenges in delirium screening in early adopter emergency departments

Singh and Sittig sociotechnical dimension	Challenge	Sociotechnical intervention
Hardware and software	Components of screening are hard to remember and document in real time	Make available portable workstations that can be used at bedside to facilitate screening Build dot phrase that displays screening components
Human–computer interface	Nurses and clinicians forget to perform and document screening	Click through menu in nurse documentation as reminder to screen and record results in real time Visual nudge (stop sign icon) or pop-up reminder to screen patients 65+ when entering chart Nurse or clinician unable to complete note or exit chart until screening performed/documented Create icon that displays on track board and department map flagging patients who screen positive
Workflow and communication	Nurse needs to communicate positive screen to clinician but does not work in same area Care teams not aware of which patients have screened positive	Positive screen result appears on first page of patient's chart that a clinician navigates to Use secure chat/messaging system within electronic medical record Create hard stop alert to physician about positive screen if patient is being discharged
People	Availability of information technology analysts and specialists	Engage information technology specialists early in initiative development
Measurement and monitoring	Organization has no process to monitor/measure follow-up actions after positive screens	Create automated dashboard that provides information on how clinicians are performing on screening and follow-up actions taken
Clinical content	Difficult to remember options for delirium management if patient screens positive	Develop order sets, file share access, link to management protocol such as ADEPT

Screening Adherence

The theme of staff adherence to screening procedures emerged across the sociotechnical domains of hardware and software, the human–computer interface, workflow and communication, and clinical content. Interviewees noted that frontline nurses and clinicians did not always remember to perform or document screening despite an initial announcement of availability and ongoing reinforcement for its use in the months after it was in place. Furthermore, delirium screening is not routinely taught in professional training programs for emergency nurses, APPs, or physicians. As such, interviewees reported that frontline staff were unfamiliar with screening tools, some of which involve multiple questions on a template to test patient cognition and attention.

Participants used their EHR to support screening procedures in several ways. First, they built step-by-step instructions and fields for documentation into nursing flowsheets. They also created dot phrases, or abbreviations that summon predefined text and clickable responses to questions into clinician notes. This meant that frontline staff did not have to look up or recall from memory the questions used in each screening tool. Having computers or portable workstations at bedside allowed both nurses' screening and documentation to be completed in real time. Second, interviewees created visual nudges such as stop sign icons to remind nurses and clinicians to perform screening before exiting the chart. Third, participants developed hard-stop mechanisms to disallow nurses or clinicians from exiting the chart of a screening-eligible patient until completing screening. Some interviewees reported that compliance with screening ranged from 20 to 50% without these EHR supports and increased to above 80% after their introduction.

Communication and Situational Awareness

The theme of communication and situational awareness emerged across the sociotechnical domains of the human–computer interface and workflow and communication. Interviewees described challenges related to follow-up actions to a positive screen. In most sites, nurses performed delirium screening and were responsible for informing physicians or APPs of a positive screening result. Communicating a positive screen helps guide both subsequent delirium management and may impact decision-making around ED disposition (admission vs discharge). However, communicating a positive screen was difficult when nurses and clinicians did not work in the same area—for example, if a triage nurse at the front of the ED could not leave their station to communicate with a clinician working in a pod at the back of the ED. Furthermore, not all sites had phones or pagers to facilitate communication when face-to-face conversations were not possible.

Participants identified several ways that the EHR supported communication and facilitated next steps in delirium management. First, some were able to build their EHR such that documentation of a positive screen triggered an automated alert to the clinician responsible for the patient's care. In some sites, this alert popped up if a clinician attempted to discharge a patient who screened positive, creating a hard stop to help avoid any potential harm from premature discharge. Second, some interviewees created a visual icon, such as a brain, to display next to a patient's name or room number on the EHR track board or department map depicting the patient census. Such a display increased situational awareness of the care team and among ED leadership about the patient's unique vulnerability and needs. Interviewees reported that these methods of flagging screen-positive patients helped nurses, clinicians, and individuals in charge of assessing and optimizing ED throughput (flow managers) to take actions to promote patient orientation and comfort, such as moving screen-positive patients from hallways into rooms or into rooms closer to nurses' stations, where they could be monitored more closely.

Linking Screening to Management

Themes related to linking screening to management appeared in the sociotechnical domains of clinical content, internal organizational policies, and external rules and regulations. Participants described that the frontline staff in their EDs wanted to be able to take action to help their patients with a positive delirium screen. Nurses and clinicians had variable familiarity with delirium management, which includes measures to orient patients and normalize function, such as providing clocks, turning off lights at nighttime, minimizing interruptions to sleep, and helping them to ambulate and toilet during each shift. Some participants made delirium management order sets, agitation protocols, or checklists of bedside interventions available through the EHR. Storing this clinical content in the EHR provided reminders without relying on individual providers' recall and helped standardize the response to patients who screened positive for delirium. In some EDs, administrators modified their EHR such that documentation of a positive screen triggered automated specialist consults. These included consults to a pharmacist, who could perform a medication reconciliation and identify medications that may have precipitated delirium or could worsen the patient's mental status, and to a geriatrics team, which could perform a global assessment of and help co-manage the patient. Automating this process took the task of reaching out to these consultants out of the hands of otherwise busy frontline clinicians.

Resources

The theme of resources emerged across the sociotechnical domains of measurement and monitoring, people, internal policies, and external rules and regulations. Overall, interviewees reported that implementing an ED delirium screening protocol took several months and involved educating staff, training them in using the screening tools, building information technology infrastructure to support the protocol, and monitoring use of the protocol through EHR-based dashboards. Integrating ED delirium screening into the EHR usually necessitated formally requesting HIT support from the institutional HIT office and/or ED leadership, arranging multiple meetings with HIT liaisons and developers, and refining features iteratively after initial implementation. Interviewees had variable levels of HIT support. HIT resources were not always immediately available; some interviewees reported long queues for services. One ED began delirium screening with paper checklists and found screening easier to perform after eventual integration into the EHR. Institutions with broader systems-level or departmental leadership support for the delirium screening initiative were able to prioritize their requests. In some hospital systems where inpatient wards were already using a particular delirium screening tool, the EHR could be adapted more quickly to include that tool for use in the ED context.

Discussion

Our findings provide insights into how EHRs may support implementation of ED delirium screening and suggest implications for other complex health care interventions. As our participants noted, adherence to screening can be promoted through EHR-based reminders and alerts, which has also been observed in studies of EHR-supported screening for a variety of conditions including fall risk in EDs[28] and infectious diseases in outpatient care.[29] [30] Importantly, our participants also described how the EHR can also be used to couple positive screening to delirium management protocols. Primary care clinics have similarly coupled behavioral health screening with EHR alerts with clinical recommendations to promote referrals for clinical interventions.[31] However, HIT resources, which are crucial for successful implementation of screening, may be limited.

Our study also demonstrates how the EHR can be used to automate workflows, communication, and management of patients who screen positive for delirium, as detailed in [Table 4]. Clinical content stored in the EHR in the form of flowsheets and dot phrases can also facilitate adherence by supporting providers to recall information related to delirium screening. Another reported strategy, a hard stop preventing clinicians from exiting a chart until screening is completed, may enforce compliance. However, as observed elsewhere, this strategy could have unintended consequences if end-users become fatigued and document inaccurate information or forgo a necessary order to move past a hard stop.[32] [33] This issue is particularly important in the ED, which faces unique time pressures compared with other practice settings. Discussions with end-users that take into account local practice factors (e.g., patient volume, workflows) can inform when and how to best deploy hard stops for ED delirium. For example, in a high-volume site, creating a hard stop for triage clinicians could dramatically slow the triage process. On the other hand, creating a hard stop to alert a clinician about a positive initial screen for a patient being discharged could prompt further evaluation that changes decision-making about patient disposition.

Staff time constraint is a barrier to ED delirium screening recognized in numerous studies.[3] [11] [16] [34] Several strategies outlined in [Table 4] demonstrate how HIT may address this barrier. Automating care processes, such as using the EHR to communicate positive screens to another ED care team member or specialist through alerts or electronic consult notifications, can improve efficiency and reliability. Furthermore, automation may improve uptake of evidence-based practices—e.g., a positive delirium screen trigger can result in opening of an order set with evidence-based recommendations for management, such as those in the ED delirium tool ADEPT (Assess, Diagnose, Evaluate, Prevent, Treat).[35] The value of automation has similarly been demonstrated in ED sepsis management, in which a positive screen can trigger alerts for clinicians and order sets for management, expediting care.[36] However, to minimize unintended effects of automation, some verbal communication may still be needed to ensure timely and reliable follow-up of the abnormal sceens.[32] Overall, assessing the usability and acceptability of iterations of EHR-based screening platforms for delirium represents a logical and important next step in research.

Notably, HIT alone does not directly address other known barriers to adoption of ED delirium screening among frontline staff, such as limited knowledge of delirium and deprioritization of delirium compared with other acute conditions.[3] [12] [16] [17] [20] [21] As other studies demonstrate, EHR-based tools must be coupled with ongoing training for staff about the importance of screening, feedback about screening performance, and support to ensure adherence to recommendations.[29] [30]

A final important point emphasized by our participants was that HIT support represents a valuable resource, and one that is not readily available in all institutions. In many institutions, integration of delirium screening into the EHR was a months-long process requiring serial and site-specific rounds of refinement. This finding echoes literature demonstrating that implementation of EHR-supported health care initiatives often involves customization[37] as well as testing usability with and obtaining feedback from end-users.[38] [39] Health care institutions anticipating implementation of other complex initiatives involving multiple steps and care team members must consider the availability of and sustained need for HIT resources.

This study has potential limitations. We focused only on the perspectives of ED clinician-administrators, rather than end-users with no ED operations roles. While the administrators in this sample were also practicing clinicians who engaged with the EHR in patient care, nonadministrator clinician end-users of the EHR may have different experiences and suggestions for improvement, which represents an important area for future investigation. Additionally, most of our participants were physicians or advanced practice clinicians, whereas ED nurses tend to have the largest role in performing screenings. This interview-based study does not provide details about what happens in daily practice; observation-based research could generate insights into ground-level implementation practices. We also did not conduct formal usability testing, which may be valuable in further process improvement. Our interviewees represented EDs that were all teaching institutions; availability of HIT resources in these hospitals may not be representative of that in nonteaching settings. The majority of EDs represented in our sample are geriatric accredited and as such have dedicated resources and staff to the ED care of older adults. Geriatric accreditation likely impacts an ED's ability to prioritize and implement delirium screening and integrate it into the EHR. Our sample size was limited, but the number of sites that have implemented ED delirium screening is limited; furthermore, we achieved thematic saturation, indicating an adequate sample size to understand common considerations in EHR-based ED delirium screening implementation.

Conclusion

Delirium screening of geriatric patients is challenging to implement in emergency care. For health care institutions planning to adopt geriatric screenings, our findings provide practical HIT-based strategies to promote screening adherence, automate workflows and communication, and link positive screening to delirium management protocols. However, the availability of HIT resources in different institutional contexts must be considered when adopting ED delirium screening.

Clinical Relevance Statement

It is challenging but important to identify delirium in geriatric patients in the ED. Implementation of ED delirium screening, a process that can involve multiple steps and care team members, is complex. We describe several ways that the EHR can facilitate ED delirium screening by promoting adherence, integrating screening into existing workflows, and automating communication and next steps after a positive screen. These findings are broadly relevant to clinical settings adopting processes to identify patients at risk of specific conditions and adverse outcomes.

Multiple-Choice Questions

1. How can the EHR facilitate a care team's situational awareness of a positive ED delirium screening result?

   • Provide guided checklist on how to perform delirium screening in nursing flowsheets.

   • Use order set for delirium management.

   • Lock clinicians into chart until screening is performed.

   • Display a visual icon connoting positive screen on patient track board.

   Correct answer: The correct answer is option d. Technicians, nurses, advanced practice providers, and physicians may work in different physical locations of the ED, which can present a barrier to immediate communication about screening results. However, all have access to a patient track board through the EHR. Displaying an icon such as a brain next to a patient's name on the track board to signal a positive delirium screen can help staff understand which patients may benefit from delirium interventions such as having caregivers at bedside or being prioritized for a room rather than a hallway bed.

2. HIT can help address which of the following challenges ED staff face when implementing delirium screening?

   • Competing demands from high-acuity patients.

   • Choosing a screening tool.

   • Remembering components of screening tool.

   • Identifying physical space to perform screening.

   Correct answer: The correct answer is option c. ED staff may be unfamiliar with delirium screening tools, some of which contain multiple steps and questions. Building screening component checklists into standard evaluation forms or dot phrases that summon predefined delirium screening questions into an encounter note can help with recall and encouraging staff to perform all steps and questions systematically.

Conflict of Interest

None declared.

Acknowledgments

We thank Dr. Thithi Wongtangman for assistance with study preparation.

Protection of Human and Animal Subjects

This research was approved by the Baylor College of Medicine Institutional Review Board, Houston, TX (H-50838) and deemed exempt by the Partners Healthcare Institutional Review Board, Boston, Massachusetts, United States (identifier: 2021P001558).

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Publication History

Received: 05 February 2023

Accepted: 06 April 2023

Accepted Manuscript online:
13 April 2023

Article published online:
21 June 2023