Hospital variation in the risk of infection after hip fracture surgery: a population-based cohort study including 29,598 patients from 2012–2017

Vesterager, Jeppe Damgren; Kristensen, Pia Kjær; Petersen, Inge; Pedersen, Alma B

doi:10.1080/17453674.2020.1863688

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…Studies (Bai et al, 2020; Barcelo et al, 2021) have shown that pulmonary infection is an independent risk factor for death after hip fracture in the elderly. Studies (Stahl et al, 2021; Vesterager et al, 2021) have found that 14% of elderly hip fracture patients with postoperative lung infections die within 30 days, while the mortality rate of patients with non-pulmonary infections within 30 days is only 1.7%. At the same time, the risk of death for patients with pulmonary infection after hip fracture is 7.36 times higher than that of patients without pulmonary infection after surgery (The HIP ATTACK Investigators, 2020).…”

Section: Discussionmentioning

confidence: 99%

Risk Factors Associated With Postoperative Pulmonary Infection in Elderly Patients With Hip Fracture: A Longitudinal Study

Chen

Shi

et al. 2022

Clin Nurs Res

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Background: This study aimed to conduct a longitudinal study to explore the influencing factors of pulmonary infection in elderly patients with hip fracture after surgery, to provide evidence and reference for the early identification and nursing care of patients at high risk of postoperative pulmonary infection. Methods: A secondary analysis was conducted of electronic medical record data from elderly patients with hip fractures treated in a tertiary hospital from January 1, 2020 to June 30, 2021. Results: A total of 526 patients were included. Age ≥70 years (odd ratio [ OR] 2.042, 95% confidence interval [CI] [1.516–4.022]), history of smoking ( OR 2.755, 95% CI [2.009–3.175]), time from fracture to operation ≥5 days ( OR 3.117, 95% CI [1.925–3.911]), American Society of Anesthesiologists grade ≥II ( OR 1.254, 95% CI [1.053–1.921]), chronic obstructive pulmonary disease ( OR 2.832, 95% CI [1.775–3.808]), hypoproteinemia ( OR 1.395, 95% CI [1.022–1.841]), red blood cell distribution width >15% ( OR 3.142, 95% CI [2.104–4.172]), intensive care unit stay ( OR 2.174, 95% CI [1.083–3.718]) and duration of mechanical ventilation ≥180 minutes ( OR 3.117, 95% CI [2.199–4.807]) were the independent risk factors (all p < .05). Conclusions: Early nursing care should be taken for patients with risk factors to reduce the pulmonary infection.

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Section: Discussionmentioning

confidence: 99%

Risk Factors Associated With Postoperative Pulmonary Infection in Elderly Patients With Hip Fracture: A Longitudinal Study

Chen

Shi

et al. 2022

Clin Nurs Res

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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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Prediction Ability of Charlson, Elixhauser, and Rx-Risk Comorbidity Indices for Mortality in Patients with Hip Fracture. A Danish Population-Based Cohort Study from 2014 – 2018

Vesterager¹,

Madsen²,

Hjelholt³

et al. 2022

CLEP

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Objective Comorbidity has an important role in risk prediction and risk adjustment modelling in observational studies. However, it is unknown which comorbidity index is most accurate to predict mortality in hip fracture patients. We aimed to evaluate the prediction ability, including discrimination and calibration of Charlson comorbidity index (CCI), Elixhauser comorbidity index (ECI) and Rx-risk index for 30 day- and 1 year mortality in a population-based cohort of hip fracture surgery patients. Methods Using the Danish Multidisciplinary Hip Fracture Registry in the period 2014–2018, 31,443 patients were included. CCI and ECI were based on discharge diagnoses, while Rx-Risk index was based on pharmacy dispensings. We used logistic regression to assess discrimination of the different indices, individually and in combinations, by calculating c-statistics and the contrast in c-statistic to a base model including only age and gender with 95% confidence intervals (CI). Results The study cohort were primarily female (69%) and older than 85 years (42%). The 30-day mortality was 10.1% and the 1-year mortality was 26.6%. Age and gender alone had a good discrimination ability for 30-day and 1-year mortality (c-statistic=0.70, CI: 0.69–0.71 and c-statistic=0.68, CI: 0.67 −0.69, respectively). By adding indices individually to the base model, Rx-risk index had the best 30-day and 1-year mortality discrimination ability (c-statistic=0.73, CI: 0.72–0.74 and 0.71 CI: 0.71–0.72, respectively). By adding combination of indices to the base model, a combination of CCI and the Rx-risk index had a 30-day and 1-year mortality discrimination ability of c-statistic=0.74, CI: 0.73–0.75 and c-statistic=0.73, CI: 0.73–0.74, respectively. Calibration of indices was similar. Conclusion The highest discrimination ability was achieved by combining CCI and Rx-risk index in addition to age and gender. However, age and gender alone had a fair mortality discrimination ability.

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Hospital variation in the risk of infection after hip fracture surgery: a population-based cohort study including 29,598 patients from 2012–2017

Cited by 3 publications

References 27 publications

Risk Factors Associated With Postoperative Pulmonary Infection in Elderly Patients With Hip Fracture: A Longitudinal Study

Risk Factors Associated With Postoperative Pulmonary Infection in Elderly Patients With Hip Fracture: A Longitudinal Study

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

Prediction Ability of Charlson, Elixhauser, and Rx-Risk Comorbidity Indices for Mortality in Patients with Hip Fracture. A Danish Population-Based Cohort Study from 2014 – 2018

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