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arXiv · 1809.03127

Monitoring data quality for telehealth systems in the presence of missing data

Tahir Mahmood·Philipp Wittenberg·Inez Maria Zwetsloot·Hailiang Wang·Kwok Leung Tsui
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Abstract

Background: All-in-one station-based health monitoring devices are implemented in elder homes in Hong Kong to support the monitoring of vital signs of the elderly. During a pilot study, it was discovered that the systolic blood pressure was incorrectly measured during multiple weeks. A real-time solution was needed to identify future data quality issues as soon as possible. Methods: Control charts are an effective tool for real-time monitoring and signaling issues (changes) in data. In this study, as in other healthcare applications, many observations are missing. Few methods are available for monitoring data with missing observations. A data quality monitoring method is developed to signal issues with the accuracy of the collected data quickly. This method has the ability to deal with missing observations. A Hotelling's T-squared control chart is selected as the basis for our proposed method. Findings: The proposed method is retrospectively validated on a case study with a known measurement error in the systolic blood pressure measurements. The method is able to adequately detect this data quality problem. The proposed method was integrated into a personalized telehealth monitoring system and prospectively implemented in a second case study. It was found that the proposed scheme supports the control of data quality. Conclusions: Data quality is an important issue and control charts are useful for real-time monitoring of data quality. However, these charts must be adjusted to account for missing data that often occur in healthcare context.

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Tahir Mahmood, Philipp Wittenberg, Inez Maria Zwetsloot, Hailiang Wang, Kwok Leung Tsui. 2018-09-10. Monitoring data quality for telehealth systems in the presence of missing data. https://doi.org/10.1016/j.ijmedinf.2019.03.011

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