Development of a customised data management system for a COVID-19-adapted colorectal cancer pathway

Article activity feed

1. Version published to 10.1136/bmjhci-2020-100307

   Jul 1, 2021
2. 

   ScreenIT

   Mar 1, 2021

   SciScore for 10.1101/2020.10.05.20206920: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   Although spreadsheets such as Microsoft Excel® or Google Sheets are some of the commonly used tabular data management tools in clinical practice and research, they are known to be inefficient for handling large volumes of data [4].	Microsoft Excel® suggested: (Microsoft Excel, RRID:SCR_016137)

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   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Data cleaning to ensure all …

   SciScore for 10.1101/2020.10.05.20206920: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   Although spreadsheets such as Microsoft Excel® or Google Sheets are some of the commonly used tabular data management tools in clinical practice and research, they are known to be inefficient for handling large volumes of data [4].	Microsoft Excel® suggested: (Microsoft Excel, RRID:SCR_016137)

   ---

   Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

   ---

   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Data cleaning to ensure all correct codes were applied required time and effort but this was expected due to the makeshift nature of the system and the inherent limitations of a spreadsheet being able to function as a bona fide database. From a governance perspective, this data validation process was heavily dependent on personnel. However, periodic discussion within the team and monitoring of the pathway helped to ensure accuracy and flow of the patients. Presentation of real-time data and feedback from other clinicians was useful to develop the pathway and make necessary adjustments to data definition and validation. The flexibility and user-friendliness of the spreadsheet allowed staff to familiarise themselves with the system in a relatively short period of time without much training. The system was easily adaptable as the pathway evolved with the rapid changes within the healthcare system. Although dealing with a pandemic is a situation unique to most, managing large volumes of data using a spreadsheet is quite common both in clinical practice as well as research. The described concept is applicable to any data management system construction requiring speed and flexibility in a resource limited situation.

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   Results from TrialIdentifier: No clinical trial numbers were referenced.

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   Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   Results from rtransparent:

   • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
   • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
   • No protocol registration statement was detected.

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   Read the original source
3. 

   Version published to 10.1101/2020.10.05.20206920v1 on medRxiv

   Oct 6, 2020