Using a Clinical Data Warehouse to Calculate and Present Key Metrics for the Radiology Department: Implementation and Performance Evaluation.

data warehouse eHealth electronic health records hospital data medical records radiology statistics and numerical data

Journal

JMIR medical informatics
ISSN: 2291-9694
Titre abrégé: JMIR Med Inform
Pays: Canada
ID NLM: 101645109

Informations de publication

Date de publication:
22 May 2023
Historique:
received: 09 08 2022
accepted: 03 05 2023
revised: 08 02 2023
medline: 22 5 2023
pubmed: 22 5 2023
entrez: 22 5 2023
Statut: epublish

Résumé

Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals. This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI). Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics. The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations. A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing.

Sections du résumé

BACKGROUND BACKGROUND
Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals.
OBJECTIVE OBJECTIVE
This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI).
METHODS METHODS
Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics.
RESULTS RESULTS
The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations.
CONCLUSIONS CONCLUSIONS
A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing.

Identifiants

pubmed: 37213191
pii: v11i1e41808
doi: 10.2196/41808
pmc: PMC10242501
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e41808

Informations de copyright

©Leon Liman, Bernd May, Georg Fette, Jonathan Krebs, Frank Puppe. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 22.05.2023.

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Auteurs

Leon Liman (L)

Chair of Computer Science VI, Würzburg University, Würzburg, Germany.

Bernd May (B)

Management und Beratung in der Medizin (MBM) Medical-Unternehmensberatung GmbH, Mainz, Germany.

Georg Fette (G)

Service Centre Medical Informatics, University Hospital of Würzburg, Würzburg, Germany.

Jonathan Krebs (J)

Chair of Computer Science VI, Würzburg University, Würzburg, Germany.

Frank Puppe (F)

Chair of Computer Science VI, Würzburg University, Würzburg, Germany.

Classifications MeSH