Exploring variation in low-value care: a multilevel modelling study

Abstract

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.

Variation of colorectal, breast and prostate cancer screening activity in Switzerland: Influence of insurance, policy and guidelines

“…This could underestimate the utilization of less expensive screening procedures (PSA and FOBT testing), whereas mammography and colonoscopy are not likely to be paid out of pocket. Finally, we could not analyze the influence of screening service provider, which could be a significant driver of regional variation [44].…”

Estimating misclassification error in a binary performance indicator: case study of low value care in Australian hospitals

“…The individual level data can be aggregated to any relevant unit, such as a geographical area or hospital, and different denominators can be used to address different questions 27. The indicators can be analysed to examine trends or variation28 and to address questions such as complications associated with low-value care, as we have reported 26. They could also be used for continual monitoring with statistical process control charts.…”

Hospital characteristics associated with low-value care in public hospitals in New South Wales, Australia

“…In New South Wales, Australia’s most populous state, there is considerable interhospital variation in the prevalence of low-value care [ 10 ]. In a previous analysis, we used multilevel models to assess the contribution of Local Health District (LHD) and hospital of treatment and patient’s area of residence to the variation in low-value care prevalence [ 13 ]. LHDs are administrative regions that make funding and policy decisions for all hospitals in the region.…”

“…Hence, differences in policy could explain differences in low-value care prevalence. However, we found the LHD contributed little to the total variation [ 13 ]. We also found the patient’s area of residence explained little of the variation; most variation is at the hospital level [ 13 ].…”

“…However, we found the LHD contributed little to the total variation [ 13 ]. We also found the patient’s area of residence explained little of the variation; most variation is at the hospital level [ 13 ]. Therefore, for this analysis we narrow the focus to further examine variation between hospitals.…”