Informatics in Medicine Unlocked (Jan 2024)

The design of a quality improvement dashboard for monitoring spinal cord and column injuries

  • Zahra Azadmanjir,
  • Mohsen Sadeghi-Naini,
  • Mohammad Dashtkoohi,
  • Maziar Moradi-Lakeh,
  • Jalil Arabkheradmand,
  • James S. Harrop,
  • Vafa Rahimi-Movaghar

Journal volume & issue
Vol. 47
p. 101489

Abstract

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Background: Interactive dashboards are a powerful tool for dynamic visualization and monitoring of patient performance and serve as a useful to for optimal decision-making. The National Spinal Column and Cord Injury Registry of Iran (NSCIR-IR) was designed to efficiently display and broadcast important patient care data. This has been achieved through an electronic dashboard display (graph and visual displays), rather than traditional static paper reports (text). Objectives: The objective of this study was to design and develop an electronic visual dashboard as a display system to monitor the quality of care in the NSCIR-IR collaborating centers. Methods: The indicators chosen were 20 pre-hospital and in-hospital quality of care (QoC) assessment tool indicators. A structured query was created from the NSCIR-IR system database to create the dashboard database. The Microsoft Power BI software was used. After data cleaning, filtering of erroneous records, and modeling, visual displays were designed and evaluated. Results: The dashboard reported on quality of care (QoC) for 2,745 patients registered in NSCIR-IR. 17% of registered cases had at least one data error in the quality of care indicators. These errors were automatically filtered by the system. The two most prominent weaknesses in (QoC indicators were delay in patient transfer by EMS (Mean and SD were 9.54 ± 13.8 h) and timing of surgical spinal cord decompression (114.5 ± 45.3 h). Conclusions: Electronic dashboards provide efficient and concise data summaries “at a glance”. However, their value and accuracy are dependent on the entered data quality. Identifying data source errors and correcting them continuously led to improved quality of data.

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