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Illustrative inpatient blood glucose datasets for QcDM project

Citation

Chen, Ying et al. (2022), Illustrative inpatient blood glucose datasets for QcDM project, Dryad, Dataset, https://doi.org/10.5061/dryad.bzkh1898d

Abstract

Glucometrics is a set of measures designed to assess whether the blood glucose of patients with diabetes mellitus are effectively managed, and is useful in regular surveillance for adverse events such as hypoglycaemia and hyperglycaemia. To evaluate the quality of glycemic control using glucometrics, routinely collected blood glucose data needs to be consolidated, processed, and analysed in different units of analysis (i.e., patient-sample, patient-day, and patient-stay). Such procedure is challenging without dedicated manpower with specific professional skills. 

We developed an open-source tool with a user-friendly graphical interface, named the Quality care for Diabetes Mellitus (QcDM) Project (available at: https://github.com/nyilin/QcDM_Project), to facilitate the monitoring of the quality of inpatient glycemic control. To illustrate the usage of the tool, we provide two datasets: test_format1.csv to generate glucometrics for monitoring glucose readings in an inpatient setting, and test1.csv to compare the glucometrics generated between different software programs.

Usage Notes

The simulated dataset, test_format1.csv, contains blood glucose data with 5594 rows for 100 unique hospital stays in July 2020, randomly assigned into 4 ward locations. It has 4 columns:

- ADMISSION.ID: integer-valued admission identifier for each unique hospital stay.

- RESULT: blood glucose readings measured in mmol/L. To illustrate how the software program developed in the QcDM Project handles non-numerical values, three entries had non-numerical values.

- RESULT.DATE: date-time stamp of glucose readings, in the format of "mm/dd/yyyy hh:mm". 

- LOCATION: ward location of hospital stays where each unique hospital stay is assigned to one of the following labels: A, B, C, and D.

This simulated dataset and the R script used to generate the dataset is available from the GitHub repository of the QcDM Project: https://github.com/nyilin/QcDM_Project/blob/main/data/Test1.

 

The anonymized dataset, test1.csv, is the test data from the Yale Glucometrics, with 2456 rows for 72 unique hospital stays in March and April. It has 3 columns without column headings:

- Column 1: integer-valued admission identifier for each unique hospital stay.

- Column 2: date stamp of glucose readings, in the format of "dd/mm/yyyy". The year of the anonymized date is further masked as 0000 and users are advised to replace it with a year of their choosing (e.g., 2005) before applying the QcDM tool.

- Column 3: blood glucose readings measured in mg/dL.

This dataset with the year of the anonymized date further masked as 0000 is also available from the GitHub repository of the QcDM Project: https://github.com/nyilin/QcDM_Project/blob/main/Supplementary_data/test1.csv.

Funding

National University Health System, Award: Summit Research Program (Metabolic Program)