Abstract

BackgroundWhether patients receive low-value hospital care (care that is not expected to provide a net benefit) may be influenced by unmeasured factors at the hospital they attend or the hospital’s Local Health District (LHD), or the patients’ areas of residence. Multilevel modelling presents a method to examine the effects of these different levels simultaneously and assess their relative importance to the outcome. Knowing which of these levels has the greatest contextual effects can help target further investigation or initiatives to reduce low-value care.MethodsWe conducted multilevel logistic regression modelling for nine low-value hospital procedures. We fit a series of six models for each procedure. The baseline model included only episode-level variables with no multilevel structure. We then added each level (hospital, LHD, Statistical Local Area [SLA] of residence) separately and used the change in the c statistic from the baseline model as a measure of the contribution of the level to the outcome. We then examined the variance partition coefficients (VPCs) and median odds ratios for a model including all three levels. Finally, we added level-specific covariates to examine if they were associated with the outcome.ResultsAnalysis of the c statistics showed that hospital was more important than LHD or SLA in explaining whether patients receive low-value care. The greatest increases were 0.16 for endoscopy for dyspepsia, 0.13 for colonoscopy for constipation, and 0.14 for sentinel lymph node biopsy for early melanoma. SLA gave a small increase in c compared with the baseline model, but no increase over the model with hospital. The VPCs indicated that hospital accounted for most of the variation not explained by the episode-level variables, reaching 36.8% (95% CI, 31.9–39.0) for knee arthroscopy. ERCP (8.5%; 95% CI, 3.9–14.7) and EVAR (7.8%; 95% CI, 2.9–15.8) had the lowest residual variation at the hospital level. The variables at the hospital, LHD and SLA levels that were available for this study generally showed no significant effect.ConclusionsInvestigations into the causes of low-value care and initiatives to reduce low-value care might best be targeted at the hospital level, as the high variation at this level suggests the greatest potential to reduce low-value care.

Highlights

  • Whether patients receive low-value hospital care may be influenced by unmeasured factors at the hospital they attend or the hospital’s Local Health District (LHD), or the patients’ areas of residence

  • In New South Wales (NSW, the most populous state of Australia), hospitals belong to Local Health Districts (LHDs), which govern funding and can make policy for all hospitals in the LHD

  • Variation between hospitals may reflect the treatment preferences of surgeons who operate in the different hospitals, whereas variation between areas of residence may reflect the decisions of general practitioners (GPs) and their referral pathways

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Summary

Introduction

Whether patients receive low-value hospital care (care that is not expected to provide a net benefit) may be influenced by unmeasured factors at the hospital they attend or the hospital’s Local Health District (LHD), or the patients’ areas of residence. Multilevel modelling presents a method to examine the effects of these different levels simultaneously and assess their relative importance to the outcome Knowing which of these levels has the greatest contextual effects can help target further investigation or initiatives to reduce low-value care. Understanding the relative importance of hospital, LHD, and area of residence will be useful for guiding programs to reduce low-value care. This information might provide indirect information about possible pathways that lead to low-value care. Variation between hospitals may reflect the treatment preferences of surgeons who operate in the different hospitals, whereas variation between areas of residence may reflect the decisions of general practitioners (GPs) and their referral pathways (in Australia GPs are ‘gate-keepers’ who must refer patients to specialists, including surgeons)

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