Between-Hospital and Between-Physician Variation in Outcomes and Costs in High- and Low-Complex Surgery: A Nationwide Multilevel Analysis

Salet, Nèwel; Stangenberger, Vincent A; Bremmer, Rolf H.; Eijkenaar, Frank

doi:10.1016/j.jval.2022.11.006

Cited by 2 publications

(3 citation statements)

References 39 publications

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“…Only two studies1 10 (5%) presented reliability coefficients for hospital-level variation in quality indicator scores. Both studies generally show high hospital-level reliability (>0.85) and low physician-level reliability (<0.70), which in addition to differences in level-specific variation (generally higher for hospital than for physician) is likely to be related to much smaller patient samples at the physician level relative to the hospital level.…”

Section: Resultsmentioning

confidence: 99%

“…The importance of distinguishing between indicator types when assessing variation is further underscored by the results of studies that analysed variation at both the hospital level and physician level 1 10 15 20–24. Specifically, these results indicate higher hospital-level variation for care processes and intermediate outcomes, but higher physician-level variation for final outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…With multilevel modelling, total variation can be decomposed and attributed to defined levels, while also allowing for adjustment for differences in casemix and statistical uncertainty. From this decomposition, a level-specific variance partitioning coefficient (VPC, also known as intraclass correlation coefficient) can be calculated,1 10 reflecting the proportion of total variation that can be attributed to a specific level.…”

Section: Methodsmentioning

confidence: 99%

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Between-hospital variation in indicators of quality of care: a systematic review

van der Linde,

Salet,

van Leeuwen

et al. 2024

BMJ Qual Saf

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BackgroundEfforts to mitigate unwarranted variation in the quality of care require insight into the ‘level’ (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores.MethodsEmbase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type.ResultsIn total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%–9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%–33.5%) and lowest for final clinical outcomes (1.4%, 0.6%–4.2%) and patient-reported outcomes (1.0%, 0.9%–1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores.ConclusionHospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered.PROSPERO registration numberCRD42022315850.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Between-hospital variation in indicators of quality of care: a systematic review

van der Linde,

Salet,

van Leeuwen

et al. 2024

BMJ Qual Saf

Self Cite

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Surgeon- and hospital-level variation in wait times for scheduled non-urgent surgery in Ontario, Canada: A cross-sectional population-based study

de Jager,

Aleman,

Baxter

et al. 2024

PLoS ONE

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Background Canadian health systems fare poorly in providing timely access to elective surgical care, which is crucial for quality, trust, and satisfaction. Methods We conducted a cross-sectional analysis of surgical wait times for adults receiving non-urgent cataract surgery, knee arthroplasty, hip arthroplasty, gallbladder surgery, and non-cancer uterine surgery in Ontario, Canada, between 2013 and 2019. We obtained data from the Wait Times Information System (WTIS) database. Inter- and intra-hospital and surgeon variations in wait time were described graphically with caterpillar plots. We used non-nested 3-level hierarchical random effects models to estimate variation partition coefficients, quantifying the proportion of wait time variance attributable to surgeons and hospitals. Results A total of 942,605 procedures at 107 healthcare facilities, conducted by 1,834 surgeons, were included in the analysis. We observed significant intra- and inter-provider variations in wait times across all five surgical procedures. Inter-facility median wait time varied between six-fold for gallbladder surgery and 15-fold for knee arthroplasty. Inter-surgeon variation was more pronounced, ranging from a 17-fold median wait time difference for cataract surgery to a 216-fold difference for non-cancer uterine surgery. The proportion of variation in wait times attributable to facilities ranged from 6.2% for gallbladder surgery to 23.0% for cataract surgery. In comparison, surgeon-related variation ranged from 16.0% for non-cancer uterine surgery to 28.0% for cataract surgery. Implications There is extreme variability in surgical wait times for five common, high-volume, non-urgent surgical procedures. Strategies to address surgical wait times must address the variation between service providers through better coordination of supply and demand. Approaches such as single-entry models could improve surgical system performance.

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Between-Hospital and Between-Physician Variation in Outcomes and Costs in High- and Low-Complex Surgery: A Nationwide Multilevel Analysis

Cited by 2 publications

References 39 publications

Between-hospital variation in indicators of quality of care: a systematic review

Between-hospital variation in indicators of quality of care: a systematic review

Surgeon- and hospital-level variation in wait times for scheduled non-urgent surgery in Ontario, Canada: A cross-sectional population-based study

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