JMIR Publications

ABSTRACT

Background:

Modern hospitals face inefficiencies due to siloed departmental layouts, prolonging physician travel time during interdepartmental consultations. This delays patient care and increases resource strain. Data-driven analysis of consultation patterns and characteristics is critical to optimize workflows and spatial design.

Objective:

To analyze the distribution characteristics of interdepartmental consultation data among inpatients and emergency patients at Peking Union Medical College Hospital (PUMCH), explore the patterns and characteristics of cross-departmental collaboration, and provide evidence for optimizing medical workflow design and improving medical efficiency.

Methods:

Based on 102,858 valid records of interdepartmental consultations recorded in the Hospital Information System (HIS) at PUMCH in 2024, consultation records from 42 clinical departments were included. Key analyses focused on consultation request/receipt volume, per capita consultation intensity, high-frequency department association pairs (annual consultation volume≥300), and disease-oriented collaboration patterns. Statistical analyses employed heatmap analysis and descriptive statistics.

Results:

The Emergency Department emerged as the core hub for consultation requests with the highest volume of n=19,698 (19.15%), while the Internal Medicine Consultation Service bore the largest receipt volume at n=10,428 (10.14%). The Critical Care Medicine Department exhibited the highest per capita request intensity at 21.64, significantly exceeding the hospital-wide average (0.32). The top 5% of high-frequency department association pairs (65 pairs, annual consultation volume≥ 300) demonstrated Pareto distribution characteristics, accounting for 42% of the hospital's total consultation volume. Among these, the strongest collaborations were observed between the Emergency Department and the Internal Medicine Consultation Service (n=3,094), Dermatology (n=2,840), and Gastroenterology (n=1,753). Disease-oriented collaboration patterns were prominent in high-frequency pairs such as Endocrinology-Ophthalmology (diabetic eye disease, n=1,287) and General Surgery-Clinical Nutrition (perioperative nutritional support, n=1,032).

Conclusions:

Interdepartmental consultations exhibit significant clustering effects and concentrated collaboration. Disease-oriented partnerships suggest proximity-based layouts and integrated medical centers could optimize efficiency and patient-centered care. The study findings provide evidence for transitioning from siloed specialties to integrated healthcare delivery models. Optimizing spatial reorganization, patient flow redesign, and resource allocation will facilitate such integrated models.