National Survey on Implementation Patterns and Functional Needs for Hospital-Wide Glycemic Management Systems in the Chinese Mainland: Mixed Methods Study

Background Diabetes mellitus is a major global public health burden, and achieving optimal glycemic control remains challenging. Multidisciplinary, hospital-wide glycemic management systems (HGMS) have emerged as a promising strategy. In the Chinese mainland, the adoption of HGMS has accelerated; yet, substantial variations remain in system functionality, regional coverage, and management effectiveness across hospitals, underscoring the need for a national survey. Objective This study aimed to survey the implementation patterns and functional needs for HGMS in the Chinese mainland. Methods A mixed methods design was used, integrating a cross-sectional quantitative survey and qualitative interviews. From April 2024 to December 2024, health care professionals across 31 provincial-level administrative regions in the Chinese mainland were recruited. Data were collected using standardized questionnaires and purposive semistructured interviews to evaluate the adoption, functional demands, and satisfaction with HGMS. Quantitative data were analyzed using SPSS (version 27.0; IBM Corp). Differences in mean ratings across HGMS functions were evaluated using the Friedman test, with post hoc pairwise comparisons performed via the Wilcoxon signed-rank test and Bonferroni correction. Qualitative data underwent thematic analysis following Braun and Clarke’s framework, supported by NVivo (version 12; QSR International). Results A total of 988 health care professionals from 265 hospitals participated. HGMS implementation across hospitals in the Chinese mainland exhibited pronounced heterogeneity: 12.45% remained at level 0 (handwritten glucose records), 47.92% at level 1 (manual data entry), and 21.51% at level 2 (department-level data sharing). Levels 3, 4, and 5 accounted for 13.21%, 3.40%, and 1.51%, respectively, revealing significant regional disparities. Functional demand analysis indicated consensus on the importance of basic HGMS functions, including real-time hypo- or hyperglycemia alerts (68.42%), Computerized Physician Order Entry–Electronic Medical Record interoperability (68.02%), and automatic glucose data transmission (67.51%). Among advanced functions, standardized education and training (64.47%), clinical decision support (61.54%), and tele-endocrinology consultation (61.13%) were also valued. Satisfaction was highest for automatic glucose data transmission (81.63%), while clinical decision support received the lowest satisfaction (45.51%). The Friedman test indicated significant differences in perceived importance and satisfaction across the 7 functions (χ²6=89.895, 286.680, respectively; P<.001). Post hoc analyses with Bonferroni adjustment revealed that participants ranked the relative importance and satisfaction of functions in distinct orders, with automated glucose data transmission consistently rated highest for both. Qualitative analysis revealed persistent barriers in nonspecialist wards, including insufficient information integration and collaboration, absence of risk stratification and misaligned management, and insufficient knowledge and education need. Conclusions HGMS implementation in the Chinese mainland is generally transitioning from digitized glucose recording toward intelligent glycemic management across hospitals. Future efforts should focus on establishing virtual wards for integrated care, developing dynamic glucose monitoring-guided management pathways, creating patient-centered collaborative platforms, and incorporating AI-enhanced clinical decision support to overcome existing barriers.