The use of large data systems or databases has always played a major role in clinical research. These datasets have been based in individual institutions as well as national, international, and professional society registries. Although valuable resources, these databases all have limitations including: biased patient selection, variable institutional involvement and failure to update database components over time. Potentially, the single greatest drawback to many national datasets is the fact that they were not designed to specifically address clinical research projects. This has motivated certain clinical groups to develop "made for purpose" datasets. An example of this type of dataset was developed in 2015 by the Esophageal Complications Consensus Group (ECCG) who produced a standardized online platform including pre-established definitions and quality parameters for assessing perioperative outcomes associated with esophageal resection. This online clinical database (Esodata.org) is a unique resource, designed with a secure and standardized web-based interface and consensus-based data fields and analysis. In 2017, utilizing data from Esodata.org, the ECCG published the first benchmark for perioperative outcomes and complications associated with esophagectomy. This was achieved by the collaboration of 24 high-volume centers, gathering targeted data on 2,704 esophageal resections between 2015 and 2016. The number of high-volume member institutions has now increased to 40 international participants from 19 individual countries, which has created the opportunity to exponentially increase numbers within the dataset but, also, increase the international relevance of the clinical research. The Esodata database now provides a reliable vehicle for monitoring longitudinal, technical and clinical benchmarks, in a period of rapid technical and process changes associated with esophageal resection.

Current approaches to clinical research with respect to esophageal resection: Are online clinical datasets the future?

Puccetti F.;
2020-01-01

Abstract

The use of large data systems or databases has always played a major role in clinical research. These datasets have been based in individual institutions as well as national, international, and professional society registries. Although valuable resources, these databases all have limitations including: biased patient selection, variable institutional involvement and failure to update database components over time. Potentially, the single greatest drawback to many national datasets is the fact that they were not designed to specifically address clinical research projects. This has motivated certain clinical groups to develop "made for purpose" datasets. An example of this type of dataset was developed in 2015 by the Esophageal Complications Consensus Group (ECCG) who produced a standardized online platform including pre-established definitions and quality parameters for assessing perioperative outcomes associated with esophageal resection. This online clinical database (Esodata.org) is a unique resource, designed with a secure and standardized web-based interface and consensus-based data fields and analysis. In 2017, utilizing data from Esodata.org, the ECCG published the first benchmark for perioperative outcomes and complications associated with esophagectomy. This was achieved by the collaboration of 24 high-volume centers, gathering targeted data on 2,704 esophageal resections between 2015 and 2016. The number of high-volume member institutions has now increased to 40 international participants from 19 individual countries, which has created the opportunity to exponentially increase numbers within the dataset but, also, increase the international relevance of the clinical research. The Esodata database now provides a reliable vehicle for monitoring longitudinal, technical and clinical benchmarks, in a period of rapid technical and process changes associated with esophageal resection.
2020
Database management systems
Esophagectomy
Hospital high-volume
Outcome assessment health care
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/127117
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