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Go to Editorial ManagerThe introduction of Artificial Intelligence (AI) in medical care is becoming an acknowledged challenge in the framework of engineering systems, in which the level of computational readiness, the integration of the infrastructure, the level of user competence, and the limitations of the ethical aspect play a role. The paper analyzes the most important engineering predictors of a readiness to use AI in Indian hospitals, which are assessed using correlation and multiple linear regression frameworks._x000D_ There was a structured survey on 120 healthcare workers and 20 deep interviews with experts to evaluate system-level perceptions and institutional preparedness. The results of regression showed that the model is well fitted (R 2 = 0.61, p < 0.001) with Perceived Usefulness (= 0.43), Infrastructure Availability (= 0.38) and AI Training Exposure ( = 0.26) identified as significant and positive predictors of AI adoption readiness. The Ethical Concern Scores (β = -0.32) had a significant negative impact, highlighting the importance of governance as an important constraint of the system._x000D_ These findings were reinforced by qualitative thematic analysis, which identified interoperability challenges, lack of computational training, data governance oversights, and infrastructure vulnerability as significant engineering limitations. The respondents positively indicated the conditional acceptance of AI on the basis of the explainable model transparency, as well as the system of institutional AI training._x000D_ The research adds a new regression-tested engineering preparedness pathway to AI implementation in Low- and Middle-Income Country (LMIC) hospital setting, suggesting system interface, capacity formation, and ethical algorithm control as the main keystones on the sustainable AI implementation in Indian healthcare.
Primary healthcare institutions are highly important socio-technical systems, where infrastructure, digital technologies, and service delivery processes collaborate to establish service resilience and performance. Digital systems and sustainable infrastructure may not be integrated as well in a limited environment with resources, which may lead to reduced system robustness and efficiency. This paper is a systematic digital systems and infrastructure evaluation of the process of providing primary healthcare in Paschim Bardhaman District, India, through an engineering-based, multi-criteria analysis framework._x000D_ Cross-sectional engineering analysis was carried out on 25 Primary Health Centers (PHCs) chosen based on the rural and semi-urban settings. They have developed a composite system performance index by incorporating five domains of engineering, namely infrastructure robustness, operational workflow efficiency, outcome performance, digital systems readiness (ICT), and environmental sustainability systems. Information was gathered based on formal auditing of facilities, check of readiness of ICT equipment and software, field observation of operations and review of documents. Domain-specific scores were also summed up to create a Composite Quality and Resilience Index (CQRI). Statistical analyses were made to provide measures of description, correlation analysis and comparative testing between rural and semi-urban facilities._x000D_ Findings showed that there was moderate system performance (mean CQRI = 1.21 ± 0.24) and there was high inter-facility difference. The positive correlation of infrastructure robustness and the efficiency of operational workflow were found to be strong with composite system performance (r = 0.67 and r = 0.74, respectively). The readiness to digital systems, and environmental sustainability scored relatively low, which points out to the underutilization of ICT infrastructure, lack of telemedicine adoption, and the integration of renewable energy sources. The composite performance of semi-urban PHCs was much better than that of rural facilities (p < 0.05), which highlights the importance of infrastructure accessibility and digital connectivity to system resilience._x000D_ The results show that integration of digital systems and infrastructure design that is sustainable are important engineering determinants of resilient primary healthcare delivery. The suggested composite assessment framework can be used as a scalable engineering-based tool to estimate and optimize the performance of low-resource healthcare infrastructure in supporting the resilience of the system and its long-term sustainability and efficiency in delivering the services.