3.2 Constraints and Assumptions

Constraints

Using AI and algorithms for patient monitoring raises ethical concerns about bias, transparency, and potential discrimination. Transparency in data collection, analysis, and decision-making is crucial.
Informed consent and patient privacy need to be carefully addressed to ensure ethical data utilization.

Currently, the focus might be on StayHealthy devices, but future integration with diverse medical devices with varying data formats and communication protocols might pose challenges.
Standardizing data formats and ensuring seamless interoperability can be complex and require collaboration across the healthcare industry.

The accuracy of alerts and analysis heavily relies on the quality of data received from devices. Ensuring data integrity throughout the system is crucial.
Factors like device calibration, data transmission errors, and missing data need to be addressed for reliable outcomes.

Healthcare professionals need proper training and ongoing support to effectively utilize and interpret information provided by MonitorMe.
Alert fatigue and potential overreliance on the system can be risks, requiring clear guidelines and responsible use practices.

Protecting sensitive patient data from cyberattacks and unauthorized access is paramount. Robust security measures, encryption, and access control are essential.
Regularly updating security protocols and monitoring system vulnerabilities are ongoing requirements.

AI algorithms might not be perfect, and potential biases or limitations need to be considered to avoid erroneous interpretations or missed critical events.
Continuous innovation and adaptation of the system with evolving technologies and evolving patient needs are important.

The initial architecture in this repository must be completed by midnight US Eastern Time, 22nd February 2024.

Reliable network connectivity: Continuous and stable internet connection is crucial for data transmission and system operation.
Standardized medical devices: MonitorMe might assume compatibility with standardized data formats and protocols used by most medical devices.
Adequate computing resources: The system needs sufficient computational power and storage to handle real-time processing and data storage for all patients and devices.
Availability of skilled IT personnel: Maintaining and operating the system efficiently requires skilled IT staff.

Healthcare professionals are familiar with the system: User training and ongoing support might be needed to ensure proper utilization and interpretation of information.
Patients understand and consent to data collection: Clear communication and informed consent are crucial for data privacy and ethical considerations.
Alerts are promptly addressed: The system relies on healthcare professionals to respond to and investigate alerts in a timely manner.

Market demand for remote patient monitoring: The system's success depends on the demand for this type of technology in the healthcare market.
Financial viability: Implementation and ongoing maintenance costs need to be balanced against the potential revenue and cost savings achieved through MonitorMe.
Regulatory compliance: While MonitorMe doesn't have to comply with HIPAA, the team made an assumption to consider amd list out other regulations like SOC2, HiTrust, Section 508 for designing MonitorMe.

Data quality and integrity: The accuracy of analysis and alerts depends on the quality of data received from devices.
Cybersecurity threats: Measures need to be in place to mitigate potential security breaches and data leaks.
Ethical considerations: The use of AI and data analysis in healthcare raises ethical questions that need to be addressed.
The IT Staff at the hospital will serve as the first line of support for Level-0 troubleshooting and monitoring of MonitorMe as a self-serve system. StayHealthy, Inc. tech support will get involved in L1 and L2 escalations.
Implied security concerns and considered as part of the system. Ex: IAM, Password Policies, etc.