Hospital differences in mortality rates after hip fracture surgery in Denmark
Kristensen, Pia Kjær ; Merlo, Juan LU
; Ghith, Nermin
LU
; Leckie, George
LU
and Johnsen, Søren Paaske
(2019)
In Clinical Epidemiology
11.
p.605-614
- Abstract
Background: Thirty-day mortality after hip fracture is widely used when ranking hospital performance, but the reliability of such hospital ranking is seldom calculated. We aimed to quantify the variation in 30-day mortality across hospitals and to determine the hospital general contextual effect for understanding patient differences in 30-day mortality risk. Methods: Patients aged ≥65 years with an incident hip fracture registered in the Danish Multidisciplinary Fracture Registry between 2007 and 2016 were identified (n=60,004). We estimated unadjusted and patient-mix adjusted risk of 30-day mortality in 32 hospitals. We performed a multilevel analysis of individual heterogeneity and discriminatory accuracy with patients nested within... (More)
Background: Thirty-day mortality after hip fracture is widely used when ranking hospital performance, but the reliability of such hospital ranking is seldom calculated. We aimed to quantify the variation in 30-day mortality across hospitals and to determine the hospital general contextual effect for understanding patient differences in 30-day mortality risk. Methods: Patients aged ≥65 years with an incident hip fracture registered in the Danish Multidisciplinary Fracture Registry between 2007 and 2016 were identified (n=60,004). We estimated unadjusted and patient-mix adjusted risk of 30-day mortality in 32 hospitals. We performed a multilevel analysis of individual heterogeneity and discriminatory accuracy with patients nested within hospitals. We expressed the hospital general contextual effect by the median odds ratio (MOR), the area under the receiver operating characteristics curve and the variance partition coefficient (VPC). Results: The overall 30-day mortality rate was 10%. Patient characteristics including high sociodemographic risk score, underweight, comorbidity, a subtrochanteric fracture, and living at a nursing home were strong predictors of 30-day mortality (area under the curve=0.728). The adjusted differences between hospital averages in 30-day mortality varied from 5% to 9% across the 32 hospitals, which correspond to a MOR of 1.18 (95% CI: 1.12–1.25). However, the hospital general context effect was low, as the VPC was below 1% and adding the hospital level to a single-level model with adjustment for patient-mix increased the area under the receiver operating characteristics curve by only 0.004 units. Conclusions: Only minor hospital differences were found in 30-day mortality after hip fracture. Mortality after hip fracture needs to be lowered in Denmark but possible interventions should be patient oriented and universal rather than focused on specific hospitals.
(Less)
- author
- Kristensen, Pia Kjær
; Merlo, Juan
LU
; Ghith, Nermin
LU
; Leckie, George
LU
and Johnsen, Søren Paaske
- organization
- publishing date
- 2019
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- 30-day mortality, Hip fracture, Hospital variance, Multilevel analysis
- in
- Clinical Epidemiology
- volume
- 11
- pages
- 605 - 614
- publisher
- Dove Medical Press Ltd.
- external identifiers
-
- pmid:31410068
- scopus:85070384840
- ISSN
- 1179-1349
- DOI
- 10.2147/CLEP.S213898
- language
- English
- LU publication?
- yes
- id
- bbaf5714-0021-40aa-8bd2-51893107383d
- date added to LUP
- 2019-08-26 14:01:46
- date last changed
- 2024-06-11 23:08:56
@article{bbaf5714-0021-40aa-8bd2-51893107383d,
abstract = {{<p>Background: Thirty-day mortality after hip fracture is widely used when ranking hospital performance, but the reliability of such hospital ranking is seldom calculated. We aimed to quantify the variation in 30-day mortality across hospitals and to determine the hospital general contextual effect for understanding patient differences in 30-day mortality risk. Methods: Patients aged ≥65 years with an incident hip fracture registered in the Danish Multidisciplinary Fracture Registry between 2007 and 2016 were identified (n=60,004). We estimated unadjusted and patient-mix adjusted risk of 30-day mortality in 32 hospitals. We performed a multilevel analysis of individual heterogeneity and discriminatory accuracy with patients nested within hospitals. We expressed the hospital general contextual effect by the median odds ratio (MOR), the area under the receiver operating characteristics curve and the variance partition coefficient (VPC). Results: The overall 30-day mortality rate was 10%. Patient characteristics including high sociodemographic risk score, underweight, comorbidity, a subtrochanteric fracture, and living at a nursing home were strong predictors of 30-day mortality (area under the curve=0.728). The adjusted differences between hospital averages in 30-day mortality varied from 5% to 9% across the 32 hospitals, which correspond to a MOR of 1.18 (95% CI: 1.12–1.25). However, the hospital general context effect was low, as the VPC was below 1% and adding the hospital level to a single-level model with adjustment for patient-mix increased the area under the receiver operating characteristics curve by only 0.004 units. Conclusions: Only minor hospital differences were found in 30-day mortality after hip fracture. Mortality after hip fracture needs to be lowered in Denmark but possible interventions should be patient oriented and universal rather than focused on specific hospitals.</p>}},
author = {{Kristensen, Pia Kjær and Merlo, Juan and Ghith, Nermin and Leckie, George and Johnsen, Søren Paaske}},
issn = {{1179-1349}},
keywords = {{30-day mortality; Hip fracture; Hospital variance; Multilevel analysis}},
language = {{eng}},
pages = {{605--614}},
publisher = {{Dove Medical Press Ltd.}},
series = {{Clinical Epidemiology}},
title = {{Hospital differences in mortality rates after hip fracture surgery in Denmark}},
url = {{http://dx.doi.org/10.2147/CLEP.S213898}},
doi = {{10.2147/CLEP.S213898}},
volume = {{11}},
year = {{2019}},
}