Letter to the editor of Heliyon: Development of minimum data set and dashboard for monitoring adverse events in radiology departments. Heliyon. 2024;10(9): e30054

Abstract

We read the paper entitled Development of Minimum Data Set and Dashboard for Monitoring Adverse Events in Radiology Departments [1Karami M. Hafizi N. Nickfarjam A.-M. Refahi S. Development of minimum data set and dashboard for monitoring adverse events in radiology departments.Heliyon. 2024; 10e30054https://doi.org/10.1016/j.heliyon.2024.e30054Abstract Full Text Full Text PDF Scopus (1) Google Scholar] in April 2024 (issue 9) with great interest. Karami et al., targeted to develop a dashboard for monitoring adverse events in radiology departments based on the importance of patient safety monitoring in medical imaging departments. This is indeed a crucial aspect of quality of care. However, some points need to be addressed: The article could not well distinguish between the concepts “indicator” and “data”; “dashboard” and “stand-alone charts” and also a " dashboard” and “information system". In Table 1, items were introduced as indicators. However, they were the titles of minimum data elements groups, not indicators. They were the required data groups are used to calculate and measure indicators to monitor the patient's safety status. So, Table 1 is not clear if it is considered data or an indicator. It is the most important step in designing the dashboard after the step of determining the indicators, the mapping between the indicators with their required data elements, and even, the mapping between critical and sensitive tasks that have the potential to achieve the desired goals (which was there to achieve the highest safety for the patient during service delivery), with key performance indicators (KPIs) [2Azadmanjir Z. Torabi M. Safdari R. Bayat M. Golmahi F. A map for clinical laboratories management indicators in the intelligent dashboard.Acta Inf. Med. 2015 Aug; 23: 210-214https://doi.org/10.5455/aim.2015.23.210-214.PMC4584098Crossref PubMed Google Scholar]. These associations should be transparent, and induced in the designed dashboard to the indicators can be layered from PIs to KPIs. Only in this way can the dashboard intelligently reflect two phenomena: First, the negative or positive correlation of different indicators relative to each other. Second, the affectability of each indicator from how to do each task in the para-clinical/clinical care delivery department during the service delivery process. The ability to drill down in the lower layers or levels to view and zoom in more detail to understand the cause, by the user, is a capability that requires specifying these relationships. Dashboards are, in essence, tools by which the audience/manager can assess the situation, fact-based make decisions, and identify the source of failures [3Nagy P.G. Warnock M.J. Daly M. Toland C. Meenan C.D. Mezrich R.S. Informatics in radiology: automated Web-based graphical dashboard for radiology operational business intelligence.Radiographics. 2009; 29: 1897-1906Crossref PubMed Scopus (56) Google Scholar]. This is why dashboards are different from stand-alone charts. On one screen from the dashboard, the audience should see the entire status of indicators or at least a related set of indicators. The phrase “at a glance” exists in multiple definitions on the dashboard [4Evans D.L. Developing dashboards: performance at a glance.ACSM's Health & Fit. J. 2009; 13: 27-30Crossref Scopus (2) Google Scholar, 5Nadj M. Maedche A. Schieder C. The effect of interactive analytical dashboard features on situation awareness and task performance.Decis. Support Syst. 2020 Aug; 135113322https://doi.org/10.1016/j.dss.2020.113322.PMC7234950Crossref PubMed Google Scholar, 6Christen O.M. Mösching Y. Müller P. Denecke K. Nüssli S. Dashboard visualization of information for emergency medical services.Stud. Health Technol. Inf. 2020; 275 (2020/11//): 27-31https://doi.org/10.3233/shti200688Crossref PubMed Google Scholar, 7Few S. Information Dashboard Design: the Effective Visual Communication of Data. O'Reilly Media, CA2006Google Scholar, 8Bach B. Freeman E. Abdul-Rahman A. Turkay C. Khan S. Fan Y. et al.Dashboard design patterns.IEEE Trans. Visual. Comput. Graph. 2022; 29: 342-352PubMed Google Scholar]. Although a good division has been defined for the classification of performance indicators centered on patient safety (pre-procedure, intra-procedure, and post-procedure), the final expectation was that the dashboard displays the status of the indicators of each group or all groups on one page. In Figure 3 of the article, it can be seen that their designed system displays each single indicator on one page and is independent from the others. Karami et al. were forced to design a data collection system due to the lack of a data source regarding the adverse events in the imaging department, to design a dashboard that can monitor these events. But in the end, they did not provide any image of the resulting dashboard and showed the screens of the data entry system as the dashboard. Dashboards are inherently independent of information systems and data source systems. However, it is better to integrate with them or embed them to facilitate the conversion of row data into visualized information. Because if connected to data source systems, real-time monitoring becomes possible. The data quality of the source system is crucial and determines how accurate and reliable the visualized information is. Because the managers are supposed to make decisions based on them, or evaluate the performance of the personnel, or even criticize them. Data cleaning in the Extract, Transform, and Load (ETL) phase is essential to design a trustworthy dashboard. Even if there are prevention, control, and correction mechanisms for data errors in the data source system, it should not be assumed that we can build a reliable dashboard without data cleaning mechanisms. In one of our studies to design a dashboard based on the data of the National Spinal Cord Injury Registry in Iran, despite all the existing mechanisms in the registry system to maintain the highest data quality [9Derakhshan P. Azadmanjir Z. Naghdi K. Habibi Arejan R. Safdarian M. Zarei M.R. et al.The impact of data quality assurance and control solutions on the completeness, accuracy, and consistency of data in a national spinal cord injury registry of Iran (NSCIR-IR).Spinal Cord Ser Cases. 2021 Jun 10; 7: 51https://doi.org/10.1038/s41394-020-00358-2Crossref PubMed Scopus (3) Google Scholar], commands, and capabilities were embedded in the dashboard system that automatically display indicators only based on error-free records [10Azadmanjir Z. Sadeghi-Naini M. Dashtkoohi M. Moradi-Lakeh M. Arabkheradmand J. Harrop J.S. et al.The design of a quality improvement dashboard for monitoring spinal cord and column injuries.Inform. Med. Unlocked. 2024; 47 (2024/01/01/)101489https://doi.org/10.1016/j.imu.2024.101489Crossref Scopus (1) Google Scholar]. Now, the work that the data is entered directly by the user into the dashboard system can increase the concerns about trusting the dashboard. Because it is often not pleasant for personnel and units to report their mistakes or poor performance. It would have been better if the data was obtained from the heart and the context of the current activities. Karami and Hafizi in another paper reported the details of the defined patient safety indicators in the imaging department [11Karami M. Hafizi N. Enhancing patient safety using medical imaging informatics.Radiol. Manag. 2017 Mar; 39: 27-35PubMed Google Scholar]. However, the process of determining and selecting the indicators leads to the production of the indicators profile. The profile of each indicator or metric describes all the characteristics of that indicator including the description and purpose, formula (If applicable including numerator and denominator), the unit of measurement (For example, percentage, number, amount, hour), data required to measure the numerator and denominator, acceptable reliable sources for collecting that data, frequency of calculation and reporting (24/7 or weekly, monthly, yearly), effective indicators and influential indicators, charts suitable for visual display of the indicator. Appendix 1 of the present paper [1Karami M. Hafizi N. Nickfarjam A.-M. Refahi S. Development of minimum data set and dashboard for monitoring adverse events in radiology departments.Heliyon. 2024; 10e30054https://doi.org/10.1016/j.heliyon.2024.e30054Abstract Full Text Full Text PDF Scopus (1) Google Scholar], provides a part of the profile of those indicators. Based on that indicator profile and formula, the data required to calculate and monitor indicators and design the dashboard will be determined. It is debatable that a separate survey (semi-structured interviews and Delphi) was conducted to determine the required data. Zahra Azadmanjir: Conceptualization, Project administration, Writing – original draft, Writing – review & editing. Vafa Rahimi-Movaghar: Supervision, Writing – review & editing. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This work was supported by Sina Trauma and Surgery Research Center (STSRC), Tehran University of Medical Sciences, Tehran, Iran (Grant number 41444-38-01- 98).

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