Evidence map›Paper›PMID 31410068›Full record

ArticleClinical epidemiology2019

Hospital differences in mortality rates after hip fracture surgery in Denmark.

Pia Kjær Kristensen, Juan Merlo, Nermin Ghith, George Leckie, Søren Paaske Johnsen

Abstract read
In one paragraph

Article in Clinical epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pia Kjær KristensenDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus N DK-8200, Denmark.
Juan MerloResearch Unit of Social Epidemiology, CRC, Faculty of Medicine, Lund University, Malmö SE-20502, Sweden.
Nermin GhithResearch Unit of Social Epidemiology, CRC, Faculty of Medicine, Lund University, Malmö SE-20502, Sweden.
George LeckieCentre for Multilevel Modelling, School of Education, University of Bristol, Bristol BS8 1JA, UK.
Søren Paaske JohnsenDepartment of Clinical Medicine, Aalborg University, Aalborg DK-9000, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThirty-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.

methodsPatients 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).

resultsThe 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.

conclusionsOnly 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.

Indexed as

30-day mortalityhip fracturehospital variancemultilevel analysis

Identifiers

PMID31410068
PMCPMC6643065

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.