Clinical trial NCT05937646: Improving Providers' Decision-Making and Reducing Information Overload Using Information Visualization in EHRs
Official title: Improving Providers' Decision-Making and Reducing Information Overload Using Information Visualization in EHRs
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Electronic Health Records
Usability
Information Seeking Behavior
Critical Care
Keywords: Visualization
Lead sponsor: University of North Carolina, Chapel Hill
Sponsor class: OTHER
Collaborators: name: Mayo Clinic
name: University of Pittsburgh Medical Center
name: MedStar Health
name: National Library of Medicine (NLM)
First posted: 2023-07-10
Enrollment: 113
Sex: ALL
Minimum age (years): 18
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Intervention model description: Participants will be randomly assigned to a control or an intervention and then conduct a crossover stage. For example, a participant who is in the control group (EHR) will review two patient cases in the EHR. Then, the participant will review two other patient cases in AWARE (intervention), i.e., the crossover stage. Similarly, a participant who is in the intervention group (AWARE) will review two patient cases in AWARE. Then, the participant will review two other patient cases in the EHR (control), i.e., the crossover stage.
Primary purpose: DIAGNOSTIC

Brief summary: This study aims to test the efficacy of an information visualization dashboard on decision-making using a randomized controlled trial with crossover.

This study aims to test the efficacy of using an information visualization dashboard on ICU providers' decision-making, efficiency, and performance compared to their institutional EHR through a randomized control trial with crossover.

Detailed description: Electronic Health Records (EHRs) are a major source of data for ICU clinicians. Synthesizing complex, electronic patient data is key to effective care delivery. EHRs contain both a record of past medical data and present continuous flows of new clinical data from various sources such as physiological inputs, laboratory results, imaging studies, and clinician notes. This complex, continuous stream of patient data can contribute to information overload, which can create barriers to the key cognitive tasks of data identification, extraction, and interpretation. Intensive Care Unit (ICU) providers must quickly synthesize data from more than 200 variables during critical care rounds, with critically ill patients generating a median of 1348 individual data points per day. Information overload has been identified as a key factor in the misinterpretation of data, leading to medical errors such as misdiagnoses. Improving our understanding of information overload-and investigations into new efforts to minimize it-can improve clinician workflow and productivity as well as patient safety. The objective of this study is to explore the impact of current data representation in the EHR on ICU clinicians' cognitive workload, performance, and satisfaction. The research design uses a mixed methods approach, including eye-tracking assessment and surveys, to assess the efficacy of current EHR interfaces for ICU clinicians in live and simulated environments.

The investigators will randomize consented participants into two groups: the control (EHR) group and the intervention (AWARE) group. During the Randomized Controlled Trial (RCT) crossover, providers in each group will review the same patient records and will perform the same tasks, and complete the same survey instruments. Providers in the control groups will review two patient cases in their institution EHR (Epic or Cerner) first and then, two new cases in AWARE, and providers in the intervention group will review two patient cases in AWARE and then two new cases in the EHR. Cases will be randomized to eliminate order bias and selection bias.

For the cases in the EHR, participants will navigate through the EHR as per their usual routine in the ICU, with no added training sessions before the study. For the cases in AWARE, participants will receive a short training presentation by the study team, explaining the functionality and design of AWARE. Also, a day before each session, the RA will send an email to the provider with a short demonstration video of AWARE to become familiar with the tool.

The study will be conducted in simulation or Biobehavioral labs at each site. The PI, or research assistant, will explain the study procedure and obtain consent; participants will be asked to use Tobii Pro Fusion during the session, participants will not need to wear anything, the eye-tracker will be mounted to the monitor. During the session, participants will review 2 patient cases in their institutional EHR and two in AWARE. After the participant completes the patient record review, the research assistant (RA) will ask the participant a series of decision-based Q\&A activities requiring verbal responses or task completion in the EHR or AWARE. The provider may use the EHR or AWARE to complete the Q\&A activity. Cases will be in random order for each participant to avoid selection or order bias. After usability testing, the investigators will ask the participant to fill out the NASA-TLX survey and the System Usability Scale (SUS). The NASA-TLX measures the perceived workload of using the EHR, and the SUS measures the level of satisfaction as a result of using the EHR. All sessions will be recorded.

Eligibility criteria: Inclusion Criteria:

ICU physicians and advanced practice providers (APPs),

* active full time ICU service,
* use an institutional EHR (Epic or Cerner) to deliver care, and
* reads and speaks English;

Residents

* prior ICU rotation experience,
* use an institutional EHR (Epic or Cerner) to deliver care, and
* reads and speaks English;

Combined Exclusion Criteria:

* Non-ICU Physicians or APPs,
* residents with no prior ICU experience

Primary outcomes:
measure: Time to Task Completion
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: Percent of Successfully Completed EHR Tasks
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: Time to Case Completion
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: Number of Clicks Per Case
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: Degree of Pupil Constriction
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: System Usability Scale Survey Score
timeFrame: Immediately following each intervention, within approximately 4-5 minutes
Secondary outcomes:
measure: Perceived Workload Score
timeFrame: Immediately following each intervention, within approximately 1-2 minutes
measure: Number of Eye Fixations on Screen
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: Number of Screens Per Case
timeFrame: Duration of Single Usability Session, up to 25 minutes
measure: Stress Score
timeFrame: Baseline
measure: Sleepiness Score
timeFrame: Baseline
Other outcomes:
Locations:
city: Chapel Hill
country: United States
facility: University of North Carolina at Chapel Hill
state: North Carolina
Study officials:
affiliation: University of North Carolina, Chapel Hill
name: Saif Khairat, PhD
role: PRINCIPAL_INVESTIGATOR
References: