Alert Reduction and Telemonitoring Process Optimization for Improving Efficiency in Remote Patient Monitoring Programs: Framework Development Study

• Published in: JMIR medical informatics Vol. 13; p. e66066
• Main Authors: van Steenkiste, Job, Lupgens, Niki, Kool, Martijn, Dohmen, Daan, Verberk-Jonkers, Iris
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 13.06.2025
• Subjects: Algorithms; Automation; Blood pressure; Clinical Communication, Electronic Consultation and Telehealth; E-Health / Health Services Research and New Models of Care; Efficiency; Electronic Health Records; Feedback; Hospitals; Humans; Hypertension; Hypertension - diagnosis; Hypertension Prevention and Treatment; Literature reviews; Medical ethics; Monitoring, Physiologic - methods; Nurses; Optimization; Original Paper; Patients; Quality Improvement; Remote Patient Monitoring; Review boards; Smartphones; Telehealth and Telemonitoring; Telemedicine; Values; Netherlands; remote patient monitoring; algorithms; models; data; workflow; data processing; workflows; care delivery; patient monitoring; alerts; analytics; medical informatics; telemonitoring; alert; high blood pressure; hypertension monitoring; model; remote monitoring; hypertension; algorithm
• ISSN: 2291-9694; 2291-9694
• DOI: 10.2196/66066

Telemonitoring can enhance the efficiency of health care delivery by enabling risk stratification, thereby allowing health care professionals to focus on high-risk patients. Additionally, it reduces the need for physical care. In contrast, telemonitoring programs require a significant time investment for implementation and alert processing. A structured method for telemonitoring process optimization is lacking. We propose a framework for optimizing efficient care delivery in telemonitoring programs based on alert data analysis and scenario analysis of a telemonitoring program for hypertension combined with a narrative literature review on methods to improve efficient telemonitoring care delivery. We extracted 1-year alert processing data from the telemonitoring platform and electronic health records (June 2022-May 2023) from all users participating in the hypertension telemonitoring program in the outpatient clinic of the Department of Internal Medicine of the Maasstad Hospital. We analyzed the alert burden and alert processing data. Additionally, a scenario analysis with different threshold values was conducted for existing blood pressure alerts to assess the impact of threshold adjustments on the overall alert burden and processing. We searched for English language academic research papers and conference abstracts reporting clinical alert or workflow optimization in telemonitoring programs on May 24, 2024 in Embase, Medline, Cochrane, Web of Science, and Google Scholar. In total, 174 users were included and analyzed. On average, each user was active in the telemonitoring program for 207 days and a total of 30,184 measurements were performed. These triggered a total of 17,293 simple, complex, and inactive or overdue alerts: 13,647 were processed automatically by the telemonitoring platform, and 3646 were processed manually by e-nurses from the telemonitoring center, equivalent to 21 manually processed alerts per user. Additional analysis of the manually processed alerts revealed that 25 (15%) users triggered more than 50% of these specific alerts. Furthermore, scenario analysis of the alert thresholds revealed that a single increase of 5 and 10 mmHg for the diastolic and systolic blood pressure alerts would reduce the number of alerts by about 50%, resulting in a total reduced time investment for the e-nurse of 5973 minutes over 1 year. Literature search yielded 251 articles, of which 7 studies reported methods to improve efficiency in telemonitoring programs, including the introduction of complex alerts and clinical algorithms to triage alerts, scenario analysis with alert threshold adjustments, and a qualitative analysis to create an alert triage algorithm. Based on the data analysis and literature review, a 4-step framework was developed to optimize the efficiency of telemonitoring programs. The 4 steps include ensuring accurate measurements, telemonitoring algorithm and alert optimization, focusing on individual users' and user groups' needs, and improving telemonitoring process efficiency. This framework can be an important first step to improve the efficiency of 21st-century telemonitoring programs.