Sensor-integrated Multidimensional Evaluation of Specialty Development and Quality Development in an Academic Medical Center

analysis-Malmquist, high-quality developmentWe developed and validated a sensor-integrated multidimensional evaluation framework for discipline construction in a large tertiary public hospital using longitudinal data from 2018 to 2023.The framework fuses expert judgment with IoT sensor telemetry and electronic medical record data.Subjective weights were derived using the Analytic Hierarchy Process with strict consistency control (consistency ratio, CR < 0.1), while objective weights were obtained using the Entropy and Criteria Importance through Intercriteria Correlation methods.Final weights were determined through cross-validated convex fusion to balance expert cognition and datadriven variability.Multisource sensing and operational signals, including patient-flow time, bed turnover, real-time location system-based bed occupancy, medical-device uptime, and ward environmental conditions, were standardized and externally benchmarked against organization for economic cooperation and development hospital-activity indicators.Patient experience was incorporated as an outcome anchor using the Hospital Consumer Assessment of Healthcare Providers and Systems survey.Results showed sustained composite improvement, with the largest gains in clinical care, teaching capacity, and mid-level talent development, while progress in research translation and senior-talent pipelines remains limited.Risk-adjusted average length of stay decreases without increased readmissions, bed occupancy converges toward a 75-85% safety corridor, and efficiency dynamics follow an efficiency change-to-technical change relay.In contrast, patient-experience recovery lags behind activity normalization, indicating staffing and ward-process bottlenecks detectable through sensor-informed metrics.Overall, in this work, we reframed the high-quality development as a measurable system property.By integrating calibrated expert judgment, sensor-derived measurements, and international benchmarks within a unified framework, we provide a robust, interpretable, and transferable measurement paradigm for continuous monitoring and sensor-enabled governance in academic medical centers.