University of Portsmouth
Obinwa Ozonze
Electronic Health Record Systems (EHR) play an integral role in healthcare practice, enabling health organisations to collect, access and manage data more consistently. There is also a great deal of interest in using EHR data to improve decision-making and accelerate medical interventions. However, like all information systems, they are prone to data quality problems such as incomplete records, values outside normal ranges and implausible relationships. These problems are expected to become more prevalent as more organisations adopt electronic health record systems, aggregate, share and explore health data. The investigators believe current efforts to improve health data quality can be made more effective if backed by appropriate technology in the form of a readily accessible intelligent tool. Building on this, the investigators developed an Artificial Intelligence (AI) tool for automating data quality assessment of health data. In this study, the investigators evaluate the AI tool using a real-world dataset.
Data Quality
The main aim of this study is to assess the reliability and utility of an AI tool in identifying data quality dimensions of interest for secondary use of health data, including completeness, conformance and plausibility. In assessing this tool, this study will retrospectively analyse data captured during routine clinical care and identify records containing listed data quality dimensions. This study will also assess the consistency of the AI tool in generating and executing data quality checks.}}
| Study Type : | Observational |
| Estimated Enrollment : | 60000 participants |
| Official Title : | Collection of Electronic Health Records (EHR) for Validation of Artificial Intelligence Based Tool for Data Quality Assessment |
| Actual Study Start Date : | February 2022 |
| Estimated Primary Completion Date : | April 2022 |
| Estimated Study Completion Date : | April 2022 |
Information not available for Arms and Intervention/treatment
| Ages Eligible for Study: | |
| Sexes Eligible for Study: | All |
| Accepts Healthy Volunteers: | Accepts Healthy Volunteers |
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