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Table5

Odds ratio of 30 day all-cause mortality, according to time of admission

Patient characteristics: type of fracture, fracture positioning, type of operation, age, sex, body-mass index, Charlson comorbidity index, marital status, housing, domicile region, native country, level of income and year of admission. Hospital characteristics: hospital region, type of unit and unit volume.

Adjusted for clustering by unit.

Adjusted for clustering by unit and patient characteristics.

Adjusted for clustering by unit, patient characteristics and hospital characteristics.

Adjusted for clustering by unit, patient characteristics and delay >48 h.

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Table5

Odds ratio of 30 day all-cause mortality, according to time of admission

Patient characteristics: type of fracture, fracture positioning, type of operation, age, sex, body-mass index, Charlson comorbidity index, marital status, housing, domicile region, native country, level of income and year of admission. Hospital characteristics: hospital region, type of unit and unit volume.

Adjusted for clustering by unit.

Adjusted for clustering by unit and patient characteristics.

Adjusted for clustering by unit, patient characteristics and hospital characteristics.

Adjusted for clustering by unit, patient characteristics and delay >48 h.

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We found that patients admitted with hip fractures during on-hours and off-hours were comparable. Furthermore, the admission time had no influence on compliance with performance measures for hip fracture care. However, the risk of surgical delay was lower for patients admitted off-hours compared with patients admitted on-hours. Additional analyses showed that this effect was driven by observations for patients admitted on weekdays during evening and night shifts; indeed the risk of delay was higher for patients admitted during weekends. We found no influence of the time of admission on the 30-day mortality risk in the primary pooled analyses, but additional analyses did reveal an increased mortality risk related to weekend admission.

The strengths included the study size, the nationwide design, the detailed prospective data collection, the complete follow-up and the extensive control for confounding. Only patients without contraindications for the specific performance measure were included in the analyses of the quality of care. This approach reduced the risk of confounding, e.g. by disease severity or by indication, and have also been used in similar studies in other patient groups [ 33 ]. Detailed registration of the exact time of admission enabled the definition of off-hours to reflect the work flow in every day clinical practice.

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