Abstract
Background: Doctor Buddy (DB) is a novel Remote Patient Monitoring (RPM) and mHealth application deployed in SGH@Home – a hospital at home program in Singapore General Hospital (SGH).
It comprises:
1.Digital forms for patient registration and health data reporting;
2.Clinician dashboard for RPM; and
3.Multi-lingual, interactive bot on Telegram and WhatsApp Messenger for
a.Patient communication and education; and
b.Provider alerts for abnormal readings.
Providers can select clinical parameters and monitoring regimes based on the clinical care pathways, and send personalized instructions and teleconsultation Zoom links from the clinician dashboard. Patients receive automatic push messages on Telegram or WhatsApp with links to disease-specific forms to report their health data. A color-coded dashboard allows prompt identification of patients with abnormal readings.
In addition, we sought feedback from patients and staff to co-design and refine our RPM solution.
Methods: We collected patient feedback and implementation data using the RE-AIM framework from October 2021 to May 2023. The data collection measure(s) for each selected framework dimension are described in Table 1.
RE-AIM DimensionMeasures
Reach: Percentage of SGH@Home patients on DB
Effectiveness: Bed-days saved as a result of patients using DB, Man-days saved and Healthcare expenditure savings
Adoption: Percentage of staff using DB
Implementation: Qualitative feedback from patients and staff on DB
Maintenance: Average percentage of SGH@Home patients enrolled in DB
Findings: As part of the co-design process, we included WhatsApp messenger to improve the reach. To support patients who have difficulties entering vital signs data, we subscribed to application programming interface (APIs) to connect a larger number of blood pressure monitors and pulse oximeters. As an enabler of RPM, DB increases the confidence of SGH and its patients in hospital at home care. 38.5% of SGH@Home patients were enrolled between October 2021 and May 2023, saving 3215 bed days and over $3.21M in healthcare expenditure. DB eliminates the laborious need to call patients to obtain data, allowing SGH@Home to save over 201 man-days. 100% of the clinical team uses DB in their care provision. The team appreciates DB’s ease of implementation as the care model expands its scope and scale. Patients gave positive feedback on their RPM experience. The average monthly DB enrolment in SGH@Home is at 33%.
Conclusion: The effectiveness of DB is supported by a robust co-design process. We have disseminated the effectiveness of DB to hospitals in our network, successfully implemented it in another tertiary hospital (Sengkang General Hospital) and adapted it for SGH Hospital-to-Home program for Chronic Disease management.