Key result
Analytics-based remote monitoring systems reduced false negative rates by 61.4% and overall readmission costs by 61.5% compared to conventional threshold-based systems.
Why the study?
Does an analytics-based Remote Monitoring System improve prediction accuracy and reduce readmission costs compared to conventional RMS in heart failure patients?
Observational (n=486)
Does an analytics-based Remote Monitoring System improve prediction accuracy and reduce readmission costs compared to conventional RMS in heart failure patients?
Machine learning-based analytics for remote patient monitoring can significantly improve prediction accuracy and reduce readmission costs in heart failure patients compared to simple thresholding.
Answers are grounded in this paper and cite their sources.
May support analytics-based HF monitoring to cut costs; leaves open randomized confirmation before practice change.
While significant effort has been made on designing Remote Monitoring Systems (RMS), limited research has been conducted on the potential cost savings that these systems offer in terms of reduction in readmission costs, as well as the costs associated with human resources involved in the intervention process. This paper is particularly interested in exploring potential cost savings that an analytics engine can provide in presence of intelligent back-end data processing and machine learning algorithms against conventional RMS that operate based on simple thresholding approaches. Using physiological data collected from 486 heart failure patients through a clinical study in collaboration with the UCLA School of Medicine, we conduct a retrospective data analysis to estimate prediction accuracy as well as associated costs of the two remote monitoring approaches. Our results show that analytics-based RMS can reduce false negative rates by 61.4% while maintaining a false positive performance close to that of conventional RMS. Furthermore, the proposed analytics engine achieves 61.5% reduction in the overall readmission costs.
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Lee et al. (2013) conducted an observational in Heart failure (n=486). Analytics-based Remote Monitoring Systems (RMS) vs. Conventional RMS (simple thresholding) was evaluated on False negative rates and overall readmission costs. Analytics-based remote monitoring systems reduced false negative rates by 61.4% and overall readmission costs by 61.5% compared to conventional threshold-based systems.
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