Proposing a Model for Designing Smart Health-Oriented Products and Services for the Elderly Based on Cognitive Factors

Purpose: This study aimed to design and validate a cognitive-based smart health-oriented product–service system (PSS) model tailored for elderly care in social security organizations. Methods and Materials: A qualitative exploratory approach was employed to identify and structure the key dimensions, components, and indicators of the proposed model. Data were collected through semi-structured interviews with 12 experts, including managers, health technology specialists, university faculty, and policymakers in the field of elderly care. Thematic analysis was applied to the transcribed interview data using a two-level coding process—textual and conceptual. The final model was synthesized through iterative categorization and expert consensus validation, comprising both functional system elements and a quality evaluation framework. Findings: The results identified four core dimensions of the smart PSS: (1) business model, (2) software (cloud) platform, (3) cognitive–biological factors, and (4) physical platform. Each dimension consists of multiple components (totaling 16) and operational parameters (61 indicators). Additionally, a multidimensional quality assessment framework was developed with four evaluation constructs: outcome quality, interaction quality, system quality, and stakeholder satisfaction. The model emphasizes user-centricity, real-time personalization, integration of digital infrastructure, and AI-driven monitoring. Elderly users were positioned as co-creators of value, with service adaptation based on continuous feedback and emotional-cognitive profiling. The model integrates both physical and cyber infrastructure to support comprehensive care delivery. Conclusion: The proposed smart health-oriented PSS model offers a comprehensive, adaptable, and intelligent framework for improving elderly care services in social security contexts.