Enhancing hospital efficiency in Germany: Process management and scheduling innovations in patient logistics

Zeiler, J. and Strazovska, L. (2025) Enhancing hospital efficiency in Germany: Process management and scheduling innovations in patient logistics. Медичні перспективи, 30 (4). pp. 223-237. ISSN 2307-0404, online 2786-4804

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Abstract

Efficient patient logistics crucial for optimizing healthcare delivery; however, many German hospitals continue to encounter significant challenges in process management and scheduling. The purpose of this study was to address existing gaps in patient logistics by conducting a systematic observation of workflows in German hospitals and developing a practical framework for optimization. To achieve this, the study set out to: (1) identify specific inefficiencies in emergency department operations, surgical scheduling, and interdepartmental coordination; (2) evaluate the applicability of Lean Management and Six Sigma principles in addressing these inefficiencies; and (3) propose a centralized scheduling model as a structural solution for enhancing coordination and resource allocation across departments. Employing a mixed-methods design, the research involved a six-month observation of workflows in three urban hospitals, focusing on emergency department operations, surgical unit scheduling, and interdepartmental coordination. Additionally, qualitative data were gathered through structured interviews with 25 hospital staff members. Data collection lasted six months, from January to June 2023. The analysis incorporated principles of Lean Management and Six Sigma to assess current inefficiencies and explore potential improvements. The study identified critical issues such as triage delays averaging 45 minutes, persistently high bed occupancy rates (95%), and delays in 25% of scheduled elective surgeries. To address these inefficiencies, a new framework was proposed that combines Lean and Six Sigma methodologies. The implementation of dynamic scheduling algorithms led to a 67% reduction in elective surgery delays, while predictive analytics significantly improved bed allocation efficiency. The research highlights the underexplored potential of digital tools and standardized protocols in streamlining patient logistics. However, the study also revealed key barriers to effective process optimization, including fragmented communication between departments, lack of centralized scheduling systems, staff resistance to workflow changes, and insufficient integration of real-time data. These findings emphasize that technological improvements must be supported by organizational change management and systemic coordination to achieve sustainable enhancements in hospital efficiency. Key recommendations include the adoption of predictive analytics, integration of dynamic scheduling systems, and formalization of interdepartmental communication standards. By offering context-specific insights for German healthcare institutions, this study contributes to the broader discourse on healthcare logistics and provides practical strategies for improving patient flow, reducing costs, and enhancing overall care quality.

Item Type:	Article
Additional Information:	DOI:10.26641/2307-0404.2025.4.348716 https://medpers.dmu.edu.ua/uk/2025-tom-xxx/no-4#pdf-23
Uncontrolled Keywords:	patient logistics, process management, dynamic scheduling, predictive analytics, hospital efficiency, Lean Six Sigma
Subjects:	Health Organization
Divisions:	University periodicals > Medical perspectives
Depositing User:	Аліна Чеботарьова
Date Deposited:	29 Apr 2026 09:03
Last Modified:	29 Apr 2026 09:03
URI:	http://repo.dma.dp.ua/id/eprint/9934

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