  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.
