Optimization of hospital stay through length-of-stay-oriented case management: an empirical study
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Background and objectives
An important component of efficient and high-quality treatment of patients under DRG conditions is the control of patients’ length of stay in hospitals. Medical processes need to be structured in such a way that unnecessary extensions of the length of stay are avoided, thus achieving an economically and qualitatively optimal result. The study presented here examines the question of whether the introduction of length-of-stay-oriented case management can optimize the duration of patients' hospital stays.
In total, 168 inpatient cases and their matched control cases from the cardiology and urology stations of a maximum care hospital are examined in this study.
The result of the t-test for the difference of means indicates that the average length of stay of the intervention cases (5.79 days) was significantly shorter than the average length of stay of the control cases (7.34 days). With respect to the re-admission rate, a statistically significant dependence could not be determined.
Discussion and conclusion
The operationalization of case management in daily clinical routines was tested by a comprehensive survey. Length-of-stay-oriented case management provides transparency of the entire treatment process and integrates procedures to an optimal extent. However, the doctor's sovereignty over therapy is not affected by the introduction of length-of-stay-oriented case management. Hence, the form of case management presented here serves as a new and innovative control and monitoring system for hospitals, as it makes institutions that implement such a system more competitive through the improvement of economical aspects as well as through the introduction of higher process efficiency.
- Optimization of hospital stay through length-of-stay-oriented case management: an empirical study
Journal of Public Health
Volume 17, Issue 6 , pp 395-400
- Cover Date
- Print ISSN
- Online ISSN
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- Case management
- Length of stay
- Process optimization
- Author Affiliations
- 1. Institute for Social Medicine, Epidemiology, and Health Economics, Charité University Medical Center Berlin, Charité, CCM D- 10098, Berlin, Germany
- 2. Helmholtz Zentrum München, Institute of Health Economics and Health Care Management, Munich, Germany
- 3. Department of Finance, University of Maastricht, Maastricht, The Netherlands