Characterizing the dynamic relationship between indoor PM2.5 and fine-grained healthcare performance: A data-driven
Yuhe Zhou1, Chenchen Tian2, Dehao Zou3
1Air Force Communication NCO Academy, Dalian, China; Institute of Systems Engineering, Dalian University of Technology, Dalian, China.
Abstract:
More than 90% of healthcare working hours are spent indoors. Among indoor pollutants, PM2.5 has been associated with decision-making and behavioral outcomes. Therefore, modeling the relationship between indoor PM2.5 and healthcare performance has vital value for improving the medical environment, enhancing performance management, and raising the quality of healthcare services. However, existing research mainly employs questionnaire surveys or macro-scale annual data for analysis, lacking objective analysis and resulting in an unclear understanding of the long-term, dynamic association. Therefore, this study establishes a real-time monitoring system to collect long-term, continuous, and real-time PM2.5 data and to extract the dynamic features of indoor PM2.5; proposes a fine-grained characterization method for healthcare performance; and adopts a progressive approach from the macro to the micro level to analyze the association. The findings are as follows: Indoor PM2.5 exhibited marked spatio-temporal heterogeneity, with an overall annual mean concentration of 31.29 μg/m3 and clear seasonal, weekly, and intra-day fluctuations related to departmental characteristics and staff activities. Across departments, indoor PM2.5 was generally negatively associated with healthcare performance. At the annual level, the strongest negative association was observed in the outpatient hall (Spearman's ρ = -0.661), whereas lower-exposure departments showed weaker associations. Seasonally, the association was strongest in winter, followed by spring and autumn, and weakest in summer. Robustness analyses further showed that these associations were attenuated when workload-dependent components were removed from the performance metric. These findings provide new empirical evidence on the dynamic relationship between indoor PM2.5 and healthcare performance and support more targeted strategies for indoor environmental management and performance-oriented decision-making in healthcare buildings.
Insights
Indoor fine particulate matter (PM2.5) negatively impacts healthcare performance, with effects varying by season and department. Real-time monitoring reveals dynamic associations crucial for improving healthcare environments.
Area of Science:
- Environmental Health
- Occupational Health
- Healthcare Management
Background:
- Healthcare professionals spend over 90% of working hours indoors.
- Indoor fine particulate matter (PM2.5) is linked to cognitive and behavioral outcomes.
- Existing research on PM2.5 and healthcare performance lacks objective, long-term data.
Purpose of the Study:
- To establish a real-time monitoring system for indoor PM2.5.
- To develop a fine-grained method for characterizing healthcare performance.
- To analyze the dynamic association between indoor PM2.5 and healthcare performance.
Main Methods:
- Continuous, real-time monitoring of indoor PM2.5 concentrations.
- Extraction of dynamic PM2.5 features and spatio-temporal heterogeneity.
- Progressive analysis from macro to micro levels, correlating PM2.5 with performance metrics.
Main Results:
- Indoor PM2.5 showed significant spatio-temporal variations (annual mean 31.29 μg/m³).
- A general negative association between indoor PM2.5 and healthcare performance was observed.
- The association was strongest in winter and in high-traffic areas like outpatient halls.
Conclusions:
- Indoor PM2.5 levels exhibit dynamic fluctuations influenced by building characteristics and human activities.
- Targeted strategies for indoor environmental management can enhance healthcare performance.
- Findings support data-driven decision-making for healthcare building optimization.
