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Alert Reduction and Telemonitoring Process Optimization for Improving Efficiency in Remote Patient Monitoring

Job van Steenkiste1,2,3, Niki Lupgens2, Martijn Kool4

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Summary

Optimizing telemonitoring programs for hypertension can significantly reduce alert burden by adjusting alert thresholds. This framework enhances efficiency and allows healthcare professionals to focus on high-risk patients.

Keywords:
alertalertsalgorithmalgorithmsanalyticscare deliverydatadata processinghigh blood pressurehypertensionhypertension monitoringmedical informaticsmodelmodelspatient monitoringremote monitoringremote patient monitoringtelemonitoringworkflowworkflows

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Area of Science:

  • Health Informatics
  • Digital Health
  • Cardiovascular Medicine

Background:

  • Telemonitoring enhances healthcare efficiency through risk stratification and reduced physical care needs.
  • However, telemonitoring implementation and alert processing demand significant time investment.
  • A structured approach for telemonitoring process optimization is currently lacking.

Purpose of the Study:

  • To propose a framework for optimizing efficient care delivery in telemonitoring programs.
  • The framework is based on alert data analysis and scenario analysis of a hypertension telemonitoring program.
  • A narrative literature review on improving telemonitoring efficiency was also conducted.

Main Methods:

  • Analysis of 1-year alert processing data from a hypertension telemonitoring program (June 2022-May 2023).
  • Scenario analysis of blood pressure alert thresholds to assess impact on alert burden.
  • Comprehensive literature search for studies on telemonitoring alert or workflow optimization.

Main Results:

  • 174 users and 30,184 measurements were analyzed, triggering 17,293 alerts.
  • Manual alert processing by e-nurses averaged 21 alerts per user.
  • Adjusting alert thresholds could reduce alert numbers by ~50%, saving significant e-nurse time.

Conclusions:

  • A 4-step framework was developed to optimize telemonitoring efficiency.
  • Key steps include accurate measurements, algorithm/alert optimization, user-centric focus, and process improvement.
  • This framework offers a foundational approach to enhance modern telemonitoring programs.