Table 1.

Interview themes, challenges raised, and implications for the system and data collection design.

Theme	Challenges for the User	System and Data Collection Design Implications
Stigma and anonymity	Patient: Requires anonymity, privacy and discretion to share data due to the stigma surrounding HSV	Patient motivation and needs must be considered
		Data must remain private and ideally anonymous
	Researcher: The quality of data is negatively affected by the ability and willingness to provide data and participate in studies	Details must be provided as to the use of the data to maximise data quality
		Education must be provided to raise awareness of HSV
Selection bias problems	Researcher: Patients with HSV are diverse in their socio-demographic backgrounds but also in the manifestation of HSV, not limited to those who have frequent recurrences, complications, pain, or psychological ramifications	Selection bias must be overcome
		The registry must be easily accessible by a wide body of populations
		Age-related accessibility must be considered throughout development, e.g., the choice of a technology platform for data collection
Understanding treatment and outcome gaps	Patient: many unaware of support or treatments after diagnosis and are not registered in the healthcare system	Data must be obtained on the unseen, to identify gaps and enable machine learning and unsupervised pattern recognition
	Researcher: Relevant and reliable data must be accessible in a suitable format that will help to inform and support research. There are gaps in current HSV treatment, management, or outcomes	A data solution should take into consideration the current gaps which might be affected by improved data collection
Risk factors and transmission	Patient: unsure how to alter their lifestyle to help minimise or mitigate recurrences	Consider associated lifestyle factors and ways to collect this data
	Researcher: Lifestyle factors play an important role in the spread and management of HSV	Enable enrichment and integration with multiple data sources (e.g., mobile applications)
Individualised vs. population-level	Researchers: The data needs to be integrated and enriched	Interoperability and importance of standardised data dissemination must be considered
		Link and enrich with EHR data
		Adhere to widely accepted data formats