Keywords data warehousing - documentation - efficiency - electronic health records - workflow
Background and Significance
Background and Significance
Children undergoing radiation therapy require sedation or general anesthesia to enable
them to lie still during their treatments.[1 ] Radiation sessions are scheduled on a daily or near-daily basis for treatment courses
that typically extend over several weeks. At our institution, the optimal anesthetic
medication doses and infusion rates for each patient are often determined early in
their treatment courses. Patients with head and neck lesions receive a customized
mask to replicate the same position over multiple treatments, and the profile of the
airway device that is used during general anesthesia forms part of the mask shape.[2 ] Prior work on a prototype of the dashboard by our group found an association between
changes in the type of airway device and an unscheduled proton therapy simulation
session to allow fitting of a new customized mask. This was accompanied by a change
in treatment from proton therapy to conventional radiation therapy during planning
of proton therapy with the new mask shape.[3 ] Thus, the anesthesia team strives to maintain consistency with each patient's anesthetic,
and on the morning of a treatment day, the anesthesia, nursing, and radiation oncology
teams meet to discuss each patient's recent anesthetics and the anesthesia plan for
the day.
Unfortunately, viewing each prior anesthetic record in our electronic health record
(EHR) requires excessive scrolling and multiple clicks, thereby hindering quick, efficient
review of weeks or months of anesthesia records. Thus, we convened a focus group of
anesthesiologists, nurse anesthetists, and radiation oncology nurses to discuss the
relevant elements of the anesthesia record. These were determined to be the medications,
the airway device, and the recovery time and quality. To provide a broader view of
the patient's clinical radiation course, we also included the days between treatments
and the type of procedure. We then built a visual analytics tool to display this key
data from multiple anesthesia encounters in a single screen. The resulting dashboard
was created in accordance with the design heuristic principles of match between system
and the real world and aesthetic and minimal design.[4 ]
[5 ] Specifically, we used visually distinct colors for the different sections of the
dashboard and used icons rather than text where possible. Data elements in the dashboard
are placed in locations similar to the existing anesthesia record system, and data
are displayed in a left to right chronological orientation. The visual analytics interface
enables focused review of multiple prior anesthetics and allows the anesthesia team
to visualize patterns between the anesthetic management and the time and quality of
recovery in a patient receiving multiple similar anesthetics within a short time period.
Initial assessment of the usability of the dashboard was based on prior usability
studies that quantified the number of clicks required to complete common EHR orders[6 ] and involved quantifying user input device interactions while using the dashboard
versus the EHR. We counted the number of mouse button clicks needed to obtain the
same information from the dashboard and prior anesthetic records. To account for usage
differences between the prior anesthetic records review and the visual analytics dashboard,
we counted the number of mouse scroll clicks needed to review the multiple pages of
prior anesthesia records and the number of mouse hovers on the dashboard view to see
all doses of one medication type.
Objectives
Our goal was to develop and implement a visual analytics interface that simultaneously
displays key data from multiple anesthesia encounters in a single screen to facilitate
review of prior anesthetics and to visualize patterns between anesthetic management
and patient recovery characteristics.
Methods
Clinical documentation is conducted in the EHR (Epic Systems, Verona, Wisconsin, United
States). The clinical data that is backed up to a clinical data warehouse every 24 hours
is available for reporting applications ([Fig. 1 ]). A visual analytics interface (Qlikview, QlikTech, Radnor, Pennsylvania, United
States) was built to aggregate data from all anesthesia encounters in pediatric radiation
oncology at the Children's Hospital of Philadelphia. Patients were included if they
received general anesthesia in the radiation oncology suite at the Children's Hospital
of Philadelphia. Anesthetic records from other units in the hospital were not included.
Fig. 1 The production electronic health record (EHR) is backed up to the reporting EHR server
with a 24-hour delay. Once documentation is in the EHR server, it is available to
the clinical data warehouse (CDW). Data in the CDW is then exported to the visual
analytics dashboard daily in the early morning.
The display includes the patient schedule, medications administered, airway device
used, radiation procedure completed, recovery room time, and agitation scale using
the Watcha score.[7 ] The dashboard application was embedded in the EHR's anesthesia module and made accessible
to clinicians in the pediatric radiation therapy suite. The application was set to
update at 6:00 a.m. daily.
Usability testing of the dashboard was conducted and compared with the standard EHR
interface. The number of clicks and mouse scroll clicks to go through the multiple
screens of a single anesthesia record on our existing EHR were counted by a nurse
anesthetist and reviewed by a senior attending anesthesiologist (J.A.G.). The same
process was repeated using the patient visual analytics dashboard. Click and scroll
click counts for each method were then calculated using the number of patients on
the actual schedule and the number of prior anesthetic records for each of these patients
on a randomly selected clinical day. The number of mouse hovers required to review
the dosage of one medication per prior anesthetic record was assessed for the dashboard
view.
Results
The Qlikview application runs on the hospital server and is available as a hyperlink
within the EHR. The dashboard displays a list of the patients scheduled to receive
anesthesia for radiation therapy on the left side of the screen ([Fig. 2 ]). The dashboard display is activated by clicking on each patient. The patient-level
view displays each anesthesia encounter as a vertical line with the date at the bottom
of the screen; serial anesthetics are shown sequentially from left to right. Each
vertical line was divided into four sections with icon legends: medications, airways,
procedures, and recovery score and time.
Fig. 2 The dashboard is divided into four sections with icon legends: medications, airways,
procedures, and recovery score and time. Each anesthetic is represented by a vertical
line chronologically from left to right, with the date of each encounter at the bottom
of the screen (exact dates removed here). The Medications section includes those commonly
used for this type of general anesthetic, with separate icons for sevoflurane, propofol,
dexmedetomidine, glycopyrrolate, ondansetron, and vecuronium. Dosage is shown if the
mouse cursor is hovered over an icon, as shown by the cursor. The Airway section shows
icons for endotracheal tubes (ETTs) or laryngeal mask airways (LMAs) as well as a
number corresponding to the size of the device. The Procedures section shows common
procedure types performed in pediatric radiation therapy, including computed tomography
(CT) simulation (CT-SIM), conventional radiation therapy (XRT), and proton radiation
therapy (PROTON). Above the Procedures section, the number of days between treatments
is listed to assist with identifying gaps in treatment. The Recovery Score shows the
maximum recovery score based on the Watcha scale (1–calm, asleep, 2–calm, can be consoled,
3–crying, cannot be consoled, 4–thrashing and inconsolable). The Recovery Time in
minutes is listed above the line representing the Recovery Scale.
Medication
The medication icons display the dose administered for each agent (e.g., propofol
bolus, propofol infusion rate, ondansetron) when the mouse cursor hovers over the
respective medication icon.
Airway
The airway section shows icons for endotracheal tube (ETT) or laryngeal mask airway
(LMA) and a number to denote the size of the device (e.g., a green circle with 1.5
represents a size 1.5 LMA).
Procedure
The procedures section shows the procedure completed during each anesthesia encounter,
including computed tomography simulation (CT-SIM), conventional radiation therapy
(XRT), and proton radiation therapy (PROTON). Of note, if a patient receives general
anesthesia but does not complete a treatment procedure (i.e., proton therapy cancelled),
then the procedure icon is blank. The “days between” field represents the number of
days between the current and previous anesthetic; this field is useful in identifying
gaps in treatment. For example, the patient displayed in [Fig. 2 ] underwent one course of radiation therapy that ended in 2017, and then began another
course of radiation therapy 352 days later. Most radiation therapy patients undergo
a series of multiple treatments over a span of weeks to months.
Recovery
The recovery section includes “Time to Phase 2” representing the duration of the initial
postanesthesia recovery phase in minutes. The delirium scale shows the patient's maximum
recovery score based on the Watcha scale (1–calm, asleep, 2–calm, can be consoled,
3–crying, cannot be consoled, 4–thrashing and inconsolable).[7 ] A summary view enables users to identify recovery patterns and changes across multiple
anesthetics more easily than the onerous native EHR interface. For example, in the
dashboard, the medications given and their dosages for each anesthetic are displayed
along with the corresponding recovery time and score. In the native EHR interface,
viewing the same information would involve accessing each anesthetic record individually.
Usability testing found that the patient dashboard required three clicks to open to
the screen showing the summary view of all of the prior anesthetics for a patient
([Table 1 ]). Each prior anesthetic also required approximately one mouse hover per medication
icon to review the relevant intravenous anesthetic dosage given. In contrast, the
existing EHR required three clicks to access the anesthesia section of the chart,
followed by additional clicks and mouse scroll clicks to view the approximately 14.5
screens that comprise each prior anesthetic record. Reviewing each additional prior
anesthetic record required 3 clicks and 109 mouse scroll clicks. There were 5 patients
on the schedule, each with several prior anesthetic records, ranging from 17 to 32.
Review of all prior anesthetic records using the traditional EHR would require 235
clicks and 12,535 mouse scroll clicks to see 1,677.5 screens of data.
Table 1
Prior to starting the click counting, the computer was on, Epic was logged on under
the anesthesia profile, and was showing the “My Cases” status board
Patient
Number of anesthetic records
EHR
Visual dashboard
Number of clicks to open all prior records
Number of screen pages in prior records
Number of mouse scroll clicks
Number of clicks to review prior records
Number of screen pages
Number of mouse hovers
1
23
47
333.5
2,507
3
1
23
2
17
35
246.5
1,853
3
1
17
3
17
35
246.5
1,853
3
1
17
4
32
65
464
3,488
3
1
32
5
26
53
377
2,834
3
1
26
Total
115
235
1667.5
12,535
15
5
115
Abbreviation: EHR, electronic health record.
Note: All clicks were counted from the ‘my cases’ status board in Epic.
The summary view of multiple anesthetics can also facilitate the identification of
documentation errors in the medical record. For example, in the case displayed in
[Fig. 2 ], both ETTs and LMAs were documented, but the ETT size of 2.0 corresponds to the
correct size 2 LMA for this patient. A 2.0 ETT would be far too small for this patient.
A documentation error involving the wrong dose of ondansetron documented in the record
(12 mg instead of 1.2 mg) was also revealed by the dashboard format. Inconsistencies
in medication dosing are more easily seen on the dashboard view.
The utility of this visual analytics tool is not limited to the anesthesia team. The
radiation therapy team can use the visual dashboard to review the plan for each patient.
The radiation therapy multidisciplinary team at our institution has a daily morning
meeting to discuss the plan for each patient. The dashboard serves as a visual tool
to improve situational awareness of the anesthetic plan and potential issues for the
entire radiation oncology team.
Discussion
We successfully designed and implemented a visual analytics tool that automatically
refreshes each morning with an updated, graphical display of multiple prior anesthetics
that allows the anesthesia team to optimize the care of radiation therapy patients
and visualize patterns in anesthetic management and patient recovery. The dashboard
facilitates discussion during the radiation oncology suite's multidisciplinary daily
morning meeting.
The dashboard provides a high-level summary of all radiation therapy anesthesia records
for children receiving recurrent treatments. In this clinical setting, it is desirable
to replicate an optimal anesthetic approach each day or to adjust the anesthetic based
on observed patterns. Inconsistencies in medication dosing and recovery time from
day to day are more readily reviewed in the dashboard format. Patients who undergo
radiation treatments have minimal time between anesthetics, which allowed us to select
key elements of the anesthetic record for review in a single screen visual analytics
format. We then incorporated this tool into our daily pediatric radiation oncology
meetings and used it to assist with formulating the anesthetic plan for each patient.
The overview of key anesthetic elements also highlighted airway documentation errors
and prompted us to redesign our airway documentation interface in the EHR.
The dashboard's unanticipated utility in identifying documentation errors has provided
significant benefits. For example, the airway documentation error mentioned in the
“Results” ultimately led to the redesign of the EHR user interface for airway device
documentation for better workflow integration and to reduce user data entry errors.
Data visualization through visual analytical platforms incorporates concepts from
human factors engineering and cognitive psychology. Information visualization can
decrease information overload[8 ]
[9 ] and has been shown to improve recall of important clinical information.[10 ] High-dimensional data can support clinical decision making.[8 ] Visual analytics dashboards have been used to allow real-time tracking of information
in health care, including creation of a hospital-specific antibiogram,[11 ] to monitor for adverse drug events,[12 ] and to track departmental performance metrics.[13 ]
Visual analytics tools have been used across various health care settings to decrease
information overload. The Glucolyzer is a visual analytics tool that utilizes patient-generated
data to help dieticians see links between dietary intake and subsequent blood glucose
in patients with type 2 diabetes. Dieticians using the Glucolyzer tool as compared
with a standard diet log book reported decreased information overload. Interestingly,
this visual analytics overview of multiple blood glucose and diet parings illuminated
recurring patterns such that these dieticians were able to make more complex connections
between dietary intake and subsequent blood glucose.[14 ] In this case, subtracting superfluous information allowed clinicians to draw connections
between relevant data. Dashboards have also been used to provide clinicians caring
for patients with diabetes with decision support based on longitudinal predictive
modeling. Clinicians who used such a dashboard had decreased visit times and increased
screening rates for complications of diabetes.[15 ] Implementation of a dashboard in the surgical intensive care unit increased compliance
with a ventilator-associated pneumonia (VAP) prevention care bundle and decreased
rates of VAP.[16 ] The VAP compliance dashboard is similar to many other dashboards in that it employs
a red-yellow-green traffic light motif as a visual short cut to convey areas of concern.[17 ]
Prior information visualization work in the anesthesia environment has centered around
decreasing information overload and increasing situational awareness of the multiple
streams of physiologic and patient data that are available to anesthesiologists in
the operating room.[10 ]
[18 ]
[19 ]
[20 ]
[21 ] Few applications of visual analytics to anesthesia data to facilitate preoperative
processes have been described in the literature. Visual analytics has been used to
explore perioperative blood transfusion patterns to guide preoperative blood ordering
practices.[22 ] A visual analytics approach has been used to analyze nonanesthesiologists' utilization
of preoperative assessments.[23 ] Our dashboard is a novel application of visual analytics that complements these
earlier applications and gives clinicians a second, potentially more efficient, option
to review prior anesthetic data in the preoperative period.
The dashboard's unanticipated utility in identifying documentation errors has provided
significant benefits. For example, the airway documentation error mentioned in the
“Results” ultimately led to the redesign of the EHR user interface for airway device
documentation for better workflow integration and to reduce user data entry errors.
Conclusion
The primary goal of this project was to provide information on prior anesthetics to
allow clinicians to tailor their anesthetic plan based on a more complete understanding
of prior anesthetic experiences for each patient. The patient visual dashboard drastically
decreased the number of clicks and mouse scroll clicks needed to review prior anesthetic
records. In the future, we will continue to further assess and refine this prototype
based on feedback from anesthesiologists and other members of the pediatric radiation
oncology team and to develop similar visual analytics dashboards to summarize multiple
anesthesia records for other patient populations.
Clinical Relevance Statement
Clinical Relevance Statement
The visual analytics dashboard describes an innovative solution to the clinical problem
of inefficient patient records review in EHR systems in which patient data are spread
over multiple screens and records review is a click-intensive process. We created
a single screen view of key components of serial anesthetics for patients undergoing
daily or near-daily anesthesia to allow efficient records review and comparison of
recovery trends. This type of summary dashboard can be utilized for multiple clinical
areas in which patients are undergoing serial anesthetics.
Multiple Choice Questions
Multiple Choice Questions
The pediatric radiation therapy anesthesia visual analytics dashboard can be used
to identify which of the following?
Whether recovery scores fall within accepted optimal standards as shown by red-yellow-green
denotations.
Predict which patients would benefit from additional antiemetic medication.
See qualitative trends between individual medication doses and recovery quality and
duration.
Identify patients at risk of cancer relapse.
Correct Answer: The correct answer is option c. The dashboard provides a distilled view of an individual
patient's prior anesthetic records. As such, it can be used to see trends between
medication doses and recovery times as well as the quality of recovery. Standards
and benchmarking for optimal anesthetic recovery from pediatric radiation therapy
have not yet been created (a). Although the dashboard would show which patients have
received multiple antiemetic medications in the past, it does not provide the granularity
of data to show postanesthetic nausea and vomiting. However, a prolonged recovery
and/or the medication history might prompt the anesthesiologist to inquire about this
issue (b). The dashboard provides anesthetic information; while it would show gaps
in treatment or changes in treatment type from proton to conventional radiation therapy,
it would not assist with predicting response to radiation treatment (d).
Why is proton radiation therapy preferred in pediatric head and neck malignancies?
Despite wider margins of healthy tissue damage, the effectiveness is higher.
Patient positioning can be less precise, and therefore treatment gaps are uncommon.
The cost is lower and it is widely available at several centers.
The proton beam does not have an exit path and nearby tissue receives less radiation.
Correct Answer: The correct answer is option d. Proton therapy is preferred in pediatric patients
because it is more precisely targeted to the tumor. The beam does not go past the
tumor; therefore, it does not damage the healthy tissue that is located beyond the
tumor (d, a). This targeting comes at the cost of requiring careful replication of
patient position, and changes in patient position can cause gaps in treatment (b).
Although proton therapy is offered by an increasing number of centers, it is still
less accessible than conventional radiation therapy (c).
