## 6 Discussion, Implications, and Future Work
\begin{table}
\begin{tabular}{c c} \hline \hline
**Participant \#** & **Comment(s)** \\ \hline P1 & “This will be a useful tool to monitor clients.” \\ \hline P2 & \begin{tabular}{c} “The application was easy to navigate, informative. The latter question on above survey was marked as equivocal for following reasons—1. The HR, calories and distance are perhaps patients self monitored targets, when used for HR anomalies, currently if a condition is suspected, it is monitored for 24 h and a treatment plan formulated. However, this would be helpful on long-term monitoring. 2. Secondly, most helpful monitoring and parameters of clinical relevance are BP and blood sugar, I would hope future developments will allow this.” \\ \hline P3 & “Can this be used for all smart-watches-if this is not the case the application would not be too useful.” \\ \hline P4 & “possibly more suitable for hospital based [sic] physiotherapy rehab services or gym based [sic] training. other features [sic] to add could be total time spend exercising, etc. or time spent sitting inactive” \\ \hline P5 & “Power meter data while running and cycling” \\ \hline P6 & \begin{tabular}{c} “The ability to personalize anomaly/abnormality detection. What I want to be notified of” \\ \end{tabular} \\ \hline P7 & \
\begin{tabular}{c} “Heart rate variability metric added, an interactive component with the client may be a built-in chat, a client input function where they can add data such as body weight, mood, and energy levels or leave comments regarding the daily activity that could assist in the review processand explain any abnormalities” \\ \end{tabular} \\ \hline P8 &
\begin{tabular}{c} “I think the challenge of implementation will be streamlining the process of monitoring patients’ health. If a specific client has multiple health conditions and various methods of recording data, having to refer to multiple online platforms or documentation could be a challenge. I feel the current design is useful, but further development to create a “one-stop shop” would be the next step. Patients with heart conditions or diabetes could input their daily blood pressure/blood glucose levels. This does span outside the scope of smartwatch data but may improve the usefulness of the online platform for healthcare professionals.” \\ \end{tabular}
\end{table} 
Table 3: Participant’s comments in the evaluation phase. condition). Responses to the open-ended question highlighted the areas of improvement for future iterations. Features like total exercise time, inactive minutes, and heart rate variability can be included in the machine learning model to detect anomalies in heart rate and other physiological parameters. The prototype can be extended by testing its compatibility with data from other smartwatches and creating a deployment framework for implementation in real-world settings. For example, the Apple Watch's electrocardiogram (ECG) feature can be used to detect cardiac arrhythmias or atrial fibrillation [41]. By addressing HCPs' needs with the prototype, a practical contribution of this study is to provide them with an instrument that detects anomalies and visualizes smartwatch data to improve patient care delivery and reduce their workloads. This study contributes to IS research by combining the concepts of co-design and DSR through the development of a system artefact and the evaluation thereof. The study also theoretically advances the diffusion of innovation theory by operationalizing the design for diffusion notion [19]. The prototype optimizes technology interaction with human oversight by involving HCP (human element) during the co-design and anomaly detection [42]. The study aimed to support HCP in clinical decision-making and not replace them. There are growing efforts to combine health data from multiple sources to give HCP a unified and comprehensive view of clients'/patients' health. Our prototype solution, using user-generated data from smartwatches, is one instance to demonstrate a possible integration of smartwatch data for preventive health monitoring.