Monitoring data quality for telehealth systems in the presence of missing data
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Quality issue: 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. Initial assessment: Control charts are an effective tool for real-time monitoring and signaling issues (changes) in data. In this study, as in other health care applications, many observations are missing. Few methods are available for monitoring data with missing observations. Choice of solution: 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 Hotellings T-squared control chart is selected as the basis for our proposed method. Implementation: The proposed method is retrospectively validated on a case study with the known measurement error in the systolic blood pressure measurements. The method is able to adequately detect this data quality problem. Evaluation: The proposed method was integrated in 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. Lessons learned: 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 a health care context.
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