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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

Relative hospital performance for AMIplus between 1995 and 2010
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Fig5: Relative hospital performance for AMIplus between 1995 and 2010

Mentions: Figures 5 and 6 illustrate the extent to which hospital rankings reflect significant differences between hospitals in terms of LOS. A diagnosis with high correlation in hospital performance over time (AMIplus), and one with low correlation (PNEU) are shown (the order of the hospitals on the y-axis is the same in all years). Fig. 6 shows that good and bad performers can be distinguished for AMIplus in 1995, even though some confidence intervals overlap. Several hospitals with average performance in 1995 had become good or bad performers in 2010. For PNEU the confidence intervals are much wider and hospitals can be distinguished to a lesser extent.Fig. 5


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)

Relative hospital performance for AMIplus between 1995 and 2010
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig5: Relative hospital performance for AMIplus between 1995 and 2010
Mentions: Figures 5 and 6 illustrate the extent to which hospital rankings reflect significant differences between hospitals in terms of LOS. A diagnosis with high correlation in hospital performance over time (AMIplus), and one with low correlation (PNEU) are shown (the order of the hospitals on the y-axis is the same in all years). Fig. 6 shows that good and bad performers can be distinguished for AMIplus in 1995, even though some confidence intervals overlap. Several hospitals with average performance in 1995 had become good or bad performers in 2010. For PNEU the confidence intervals are much wider and hospitals can be distinguished to a lesser extent.Fig. 5

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