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. 2022 Sep;23(9):e13610.
doi: 10.1002/acm2.13610. Epub 2022 Aug 3.

Real-time analysis and display of quantitative measures to track and improve clinical workflow

Affiliations

Real-time analysis and display of quantitative measures to track and improve clinical workflow

Reshma Munbodh et al. J Appl Clin Med Phys. 2022 Sep.

Abstract

Purpose: Radiotherapy treatment planning is a complex process with multiple, dependent steps involving an interdisciplinary patient care team. Effective communication and real-time tracking of resources and care path activities are key for clinical efficiency and patient safety.

Materials and methods: We designed and implemented a secure, interactive web-based dashboard for patient care path, clinical workflow, and resource utilization management. The dashboard enables visualization of resource utilization and tracks progress in a patient's care path from the time of acquisition of the planning CT to the time of treatment in real-time. It integrates with the departmental electronic medical records (EMR) system without the creation and maintenance of a separate database or duplication of work by clinical staff. Performance measures of workflow were calculated.

Results: The dashboard implements a standardized clinical workflow and dynamically consolidates real-time information queried from multiple tables in the EMR database over the following views: (1) CT Sims summarizes patient appointment information on the CT simulator and patient load; (2) Linac Sims summarizes patient appointment times, setup history, and notes, and patient load; (3) Task Status lists the clinical tasks associated with a treatment plan, their due date, status and ownership, and patient appointment details; (4) Documents provides the status of all documents in the patients' charts; and (5) Diagnoses and Interventions summarizes prescription information, imaging instructions and whether the plan was approved for treatment. Real-time assessment and quantification of progress and delays in a patient's treatment start were achieved.

Conclusions: This study indicates it is feasible to develop and implement a dashboard, tailored to the needs of an interdisciplinary team, which derives and integrates information from the EMR database for real-time analysis and display of resource utilization and clinical workflow in radiation oncology. The framework developed facilitates informed, data-driven decisions on clinical workflow management as we seek to optimize clinical efficiency and patient safety.

Keywords: dashboard; database; electronic medical records; quality assurance; radiation therapy.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
System architecture. The three main components of the dashboard are the web clients, a server, and a SQL database. The server translates queries from the web client into SQL code, which is used to query the database. The results from the SQL queries are processed by the server before being displayed on the dashboard of the web client. All communication is encrypted
FIGURE 2
FIGURE 2
IMRT treatment planning timeline. The Gantt chart displays the care path activities that need to be completed during the creation of an IMRT treatment plan and the timeline associated with each of the activities
FIGURE 3
FIGURE 3
CT simulations. The dashboard consists of five tabs (CT sims, Linac sims, Tasks, Documents, and D&I shown at the top of the panel) unified by a set of filters comprising the date, appointment location, appointment type, and physician. The CT simulations tab displays details of patient appointments on the CT scanner as per the selected set of filters. The graph displays patient load in a period of ± 2 weeks from the selected date
FIGURE 4
FIGURE 4
New treatment simulations. The Linac Sims tab provides details of new treatment simulation appointments on the linear accelerators. Contextual information regarding the patient's CT simulation and any previous or future treatment simulation appointments is also provided. The graph provides a longitudinal assessment of patient load distribution on the different linear accelerators for a period of ± 2 weeks surrounding the selected date. The pie chart provides details about the total load on the different linear accelerators over a period of a month centered around the chosen date
FIGURE 5
FIGURE 5
Tasks. The tab displays the status and due dates of the QCLs associated with the creation of a patient's treatment plan for all patients whose treatment is due to start on the selected date. The due dates are color coded with black indicating a pending but on time task, green indicates on time completion, brown indicates late completion, and red indicates an overdue task. Early or late completion is also indicated by means of the appropriate number of days in brackets next to the due date. Overall plan completion status for every patient is indicated by means of a labeled progress bar
FIGURE 6
FIGURE 6
Documents. The Documents tab lists the approval date (shown here as “Approved” for deidentification purposes) of all documents in a patient's treatment chart for patients with a CT simulation or treatment simulation on the selected date. If the documents have not been approved, their status is listed. Unapproved, pending documents are highlighted in red. All documents require approval prior to the start of treatment
FIGURE 7
FIGURE 7
CT simulation case load. The results of an interrupted time series analysis of the effect of COVID‐19 on the weekly number of CT simulations are shown in black. The number of COVID‐19 hospital admissions in the state is shown in dark red
FIGURE 8
FIGURE 8
Weekly variance in the day‐to‐day CT simulation case load. The results of an interrupted time series analysis of the effect of COVID‐19 on the weekly variance in the daily number of CT simulations are shown in black. The number of COVID‐19 hospital admissions in the state is shown in dark red

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