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Has variation in length of stay in acute hospitals decreased? Analysing trends in the variation in LOS between and within Dutch hospitals.

van de Vijsel AR, Heijink R, Schipper M - BMC Health Serv Res (2015)

Bottom Line: For none of the diagnoses, relative variance decreased on the log scale, suggesting room for further LOS reduction.We found within-hospital variance to be many times greater than between-hospital variance.The results suggest room for efficiency improvement implying lower costs per patient treated.

View Article: PubMed Central - PubMed

Affiliation: National Institute for Public Health and the Environment, Richard Heijink, P.O. Box 1, 3720, BA, Bilthoven, The Netherlands. aart.vandevijsel@xs4all.nl.

ABSTRACT

Background: We aimed to get better insight into the development of the variation in length of stay (LOS) between and within hospitals over time, in order to assess the room for efficiency improvement in hospital care.

Methods: Using Dutch national individual patient-level hospital admission data, we studied LOS for patients in nine groups of diagnoses and procedures between 1995 and 2010. We fitted linear mixed effects models to the log-transformed LOS to disentangle within and between hospital variation and to evaluate trends, adjusted for case-mix.

Results: We found substantial differences between diagnoses and procedures in LOS variation and development over time, supporting our disease-specific approach. For none of the diagnoses, relative variance decreased on the log scale, suggesting room for further LOS reduction. Except for two procedures in the same specialty, LOS of individual hospitals did not correlate between diagnoses/procedures, indicating the absence of a hospital wide policy. We found within-hospital variance to be many times greater than between-hospital variance. This resulted in overlapping confidence intervals across most hospitals for individual hospitals' performances in terms of LOS.

Conclusions: The results suggest room for efficiency improvement implying lower costs per patient treated. It further implies a possibility to raise the number of patients treated using the same capacity or to downsize the capacity. Furthermore, policymakers and health care purchasers should take into account statistical uncertainty when benchmarking LOS between hospitals and identifying inefficient hospitals.

No MeSH data available.


Related in: MedlinePlus

Percentage of variance of LOS explained by case-mix per diagnosis/procedure, between 1995 and 2010
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Fig3: Percentage of variance of LOS explained by case-mix per diagnosis/procedure, between 1995 and 2010

Mentions: The regression results (not shown here) demonstrated that age and the Charlson index had a significant impact on LOS across all diseases and years. The impact of gender and reason for admission was significant in all years for five out of nine diagnoses/procedures. The role of the other case-mix variables (neighbourhood SES, ethnicity and the percentage day-admissions (hospital level) was much more diffuse across diseases and years. In total, the case-mix variables explained between 0 and 10 % of the LOS variance for six diagnoses (Fig. 3). For AMIplus, this percentage was higher (10–20 %) between 2004 and 2010, while the role of case-mix variables was larger particularly for PNEU (20–25 %) and CHOL (30–40 %). Regarding CHOL, this higher percentage was caused by the variable type of treatment (open versus laparoscopic).Fig. 3


Has variation in length of stay in acute hospitals decreased? Analysing trends in the variation in LOS between and within Dutch hospitals.

van de Vijsel AR, Heijink R, Schipper M - BMC Health Serv Res (2015)

Percentage of variance of LOS explained by case-mix per diagnosis/procedure, between 1995 and 2010
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4590267&req=5

Fig3: Percentage of variance of LOS explained by case-mix per diagnosis/procedure, between 1995 and 2010
Mentions: The regression results (not shown here) demonstrated that age and the Charlson index had a significant impact on LOS across all diseases and years. The impact of gender and reason for admission was significant in all years for five out of nine diagnoses/procedures. The role of the other case-mix variables (neighbourhood SES, ethnicity and the percentage day-admissions (hospital level) was much more diffuse across diseases and years. In total, the case-mix variables explained between 0 and 10 % of the LOS variance for six diagnoses (Fig. 3). For AMIplus, this percentage was higher (10–20 %) between 2004 and 2010, while the role of case-mix variables was larger particularly for PNEU (20–25 %) and CHOL (30–40 %). Regarding CHOL, this higher percentage was caused by the variable type of treatment (open versus laparoscopic).Fig. 3

Bottom Line: For none of the diagnoses, relative variance decreased on the log scale, suggesting room for further LOS reduction.We found within-hospital variance to be many times greater than between-hospital variance.The results suggest room for efficiency improvement implying lower costs per patient treated.

View Article: PubMed Central - PubMed

Affiliation: National Institute for Public Health and the Environment, Richard Heijink, P.O. Box 1, 3720, BA, Bilthoven, The Netherlands. aart.vandevijsel@xs4all.nl.

ABSTRACT

Background: We aimed to get better insight into the development of the variation in length of stay (LOS) between and within hospitals over time, in order to assess the room for efficiency improvement in hospital care.

Methods: Using Dutch national individual patient-level hospital admission data, we studied LOS for patients in nine groups of diagnoses and procedures between 1995 and 2010. We fitted linear mixed effects models to the log-transformed LOS to disentangle within and between hospital variation and to evaluate trends, adjusted for case-mix.

Results: We found substantial differences between diagnoses and procedures in LOS variation and development over time, supporting our disease-specific approach. For none of the diagnoses, relative variance decreased on the log scale, suggesting room for further LOS reduction. Except for two procedures in the same specialty, LOS of individual hospitals did not correlate between diagnoses/procedures, indicating the absence of a hospital wide policy. We found within-hospital variance to be many times greater than between-hospital variance. This resulted in overlapping confidence intervals across most hospitals for individual hospitals' performances in terms of LOS.

Conclusions: The results suggest room for efficiency improvement implying lower costs per patient treated. It further implies a possibility to raise the number of patients treated using the same capacity or to downsize the capacity. Furthermore, policymakers and health care purchasers should take into account statistical uncertainty when benchmarking LOS between hospitals and identifying inefficient hospitals.

No MeSH data available.


Related in: MedlinePlus