BackgroundThe rate of immediate breast reconstruction (IBR) following mastectomy for breast cancer in Australia is low and varies between regions. To date, no previous Australian studies have examined IBR rates between all hospitals within a particular jurisdiction, despite hospitals being an important known contributor to variation in IBR rates in other countries.MethodsWe used cross‐classified random‐effects logistic regression models to examine the inter‐hospital variation in IBR rates by using data on 7961 women who underwent therapeutic mastectomy procedures in New South Wales (NSW) between January 2012 and June 2015. We derived IBR rates by patient‐, residential neighbourhood‐ and hospital‐related factors and investigated the underlying drivers for the variation in IBR.ResultsWe estimated the mean IBR rate across all hospitals performing mastectomy to be 17.1% (95% Bayesian credible interval (CrI) 12.1–23.1%) and observed wide inter‐hospital variation in IBR (variance 4.337, CrI 2.634–6.889). Older women, those born in Asian countries (odds ratio (OR) 0.5, CrI 0.4–0.6), residing in neighbourhoods with lower socioeconomic status (OR 0.7, CrI 0.5–0.8 for the most disadvantaged), and who underwent surgery in public hospitals (OR 0.4, CrI 0.1–1.0) were significantly less likely to have IBR. Women residing in non‐metropolitan areas and attending non‐metropolitan hospitals were significantly less likely to undergo IBR than their metropolitan counterparts attending metropolitan hospitals.ConclusionWide inter‐hospital variation raises concerns about potential inequities in access to IBR services and unmet demand in certain areas of NSW. Explaining the underlying drivers for IBR variation is the first step in identifying policy solutions to redress the issue.

Background 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. Methods We 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. Results Analysis 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. Conclusions Investigations 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. Electronic supplementary material The online version of this article (10.1186/s12913-019-4159-1) contains supplementary material, which is available to authorized users.

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