Summary

To compare hospitals’ hip fracture patient mortality in a quality of care registry, correction for patient characteristics is needed. This study evaluates in 39,374 patients which characteristics are associated with 30 and 90-day mortality, and showed how using these characteristics in a case mix-model changes hospital comparisons within the Netherlands.

Purpose

Mortality rates after hip fracture surgery are considerable and may be influenced by patient characteristics. This study aims to evaluate hospital variation regarding patient demographics and disease burden, to develop a case-mix adjustment model to analyse differences in hip fracture patients’ mortality to calculate case-mix adjusted hospital-specific mortality rates.

Methods

Data were derived from 64 hospitals participating in the Dutch Hip Fracture Audit (DHFA). Adult hip fracture patients registered in 2017–2019 were included. Variation of case-mix factors between hospitals was analysed, and the association between case-mix factors and mortality at 30 and 90 days was determined through regression models.

Results

There were 39,374 patients included. Significant variation in case-mix factors amongst hospitals was found for age ≥ 80 (range 25.8–72.1% p < 0.001), male gender (12.0–52.9% p < 0.001), nursing home residents (42.0–57.9% p < 0.001), pre-fracture mobility aid use (9.9–86.7% p < 0,001), daily living dependency (27.5–96.5% p < 0,001), ASA-class ≥ 3 (25.8–83.3% p < 0.001), dementia (3.6–28.6% p < 0.001), osteoporosis (0.0–57.1% p < 0.001), risk of malnutrition (0.0–29.2% p < 0.001) and fracture types (all p < 0.001). All factors were associated with 30- and 90-day mortality. Eight hospitals showed higher and six showed lower 30-day mortality than expected based on their case-mix. Six hospitals showed higher and seven lower 90-day mortality than expected. The specific outlier hospitals changed when correcting for case-mix factors.

Conclusions

Dutch hospitals show significant case-mix variation regarding hip fracture patients. Case-mix adjustment is a prerequisite when comparing hospitals’ 30-day and 90-day hip fracture patients’ mortality. Adjusted mortality may serve as a starting point for improving hip fracture care.

中文翻译：

---

开发用于比较髋部骨折护理医院绩效的数据驱动病例组合调整模型

概括

为了在护理质量登记处比较医院的髋部骨折患者死亡率，需要对患者特征进行校正。这项研究评估了 39,374 名患者的哪些特征与 30 天和 90 天的死亡率相关，并展示了在病例混合模型中使用这些特征如何改变荷兰境内的医院比较。

目的

髋部骨折手术后的死亡率相当高，并且可能受患者特征的影响。本研究旨在评估医院在患者人口统计和疾病负担方面的差异，开发病例组合调整模型来分析髋部骨折患者死亡率的差异，以计算病例组合调整后的医院特定死亡率。

方法

数据来自参与荷兰髋部骨折审计 (DHFA) 的 64 家医院。纳入了 2017-2019 年登记的成人髋部骨折患者。分析了医院间病例组合因素的变化，并通过回归模型确定了病例组合因素与 30 天和 90 天死亡率之间的关联。

结果

共包括 39,374 名患者。发现年龄≥80 岁（范围 25.8–72.1% p  < 0.001）、男性（12.0–52.9% p  < 0.001）、疗养院居民（42.0–57.9% p  < 0.001）的医院病例组合因素存在显着差异、骨折前助行器的使用 (9.9–86.7% p  < 0,001)、日常生活依赖性 (27.5–96.5% p  < 0,001)、ASA 级 ≥ 3 (25.8–83.3% p  < 0.001)、痴呆 (3.6–28.6 % p  < 0.001)、骨质疏松症 (0.0–57.1% p  < 0.001)、营养不良风险 (0.0–29.2% p  < 0.001) 和骨折类型（所有p < 0.001)。所有因素都与 30 天和 90 天死亡率相关。根据病例组合，八家医院的 30 天死亡率高于预期，六家医院的死亡率低于预期。六家医院的 90 天死亡率高于预期，七家低于预期。在校正病例组合因素时，具体的离群医院发生了变化。

结论

荷兰医院在髋部骨折患者方面表现出显着的病例组合差异。在比较医院的 30 天和 90 天髋部骨折患者死亡率时，病例组合调整是先决条件。调整后的死亡率可以作为改善髋部骨折护理的起点。