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The relationship between historical risk-adjusted 30-day mortality and subsequent hip fracture outcomes: Retrospective cohort study.

ABSTRACT: While 30-day risk-adjusted mortality is a performance measure for hip fracture care, it has not been shown to predict long-term outcomes. We assessed whether hospital rankings based on historical 30-day mortality predicted subsequent hip fracture outcomes.Using national Medicare data, we calculated annual hospital performance rankings based on standardized 30-day hip fracture mortality ratios. We used logistic regression to measure the association of patients' survival at 180 days with their hospital's ranking for the year prior to admission. Subgroup analyses assessed whether associations between hospital performance and 180-day outcomes were similar for community-dwelling patients as well as those living in nursing homes prior to fracture.Out of 378,077 patients hospitalized with hip fractures between January 1, 2007 and June 30, 2009, 81,653 (21.6%) died by 180 days. Worse historical hospital performance was associated with a greater adjusted odds of 30 day mortality (odds ratio (OR), fourth vs. first quartile: 1.24, 95% confidence interval (CI): 1.18, 1.29, P<0.001) and 180 day mortality (OR, fourth vs. first quartile: 1.15, 95% CI 1.11, 1.18, P<0.001). Past hospital performance was associated with death or new nursing home placement among community dwellers (OR, fourth vs. first quartile: 1.09, 95% CI 1.05, 1.13, P<0.001), but was not associated with death or new dependence in locomotion among nursing home residents (OR 1.05, 95% CI 0.97, 1.15, P=0.229).Better historical hospital hip fracture mortality predicts modest decreases in mortality at 180 days for subsequent patients, but is inconsistently associated with changes in functional outcomes.Level 3 (Non-randomized controlled cohort study).

SUBMITTER: Neuman MD

PROVIDER: S-EPMC5027070 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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The relationship between historical risk-adjusted 30-day mortality and subsequent hip fracture outcomes: Retrospective cohort study.

Neuman Mark D MD Passarella Molly R MR Werner Rachel M RM

Healthcare (Amsterdam, Netherlands) 20151030 3

<h4>Background</h4>While 30-day risk-adjusted mortality is a performance measure for hip fracture care, it has not been shown to predict long-term outcomes. We assessed whether hospital rankings based on historical 30-day mortality predicted subsequent hip fracture outcomes.<h4>Methods</h4>Using national Medicare data, we calculated annual hospital performance rankings based on standardized 30-day hip fracture mortality ratios. We used logistic regression to measure the association of patients' ...[more]

PMID: 27637826

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Project description:PurposeThe 30-day mortality rate after hip fracture surgery has been considered as an indirect indicator of the quality of care. The aim of this work is to analyse preoperative and postoperative factors potentially related to early 30-day mortality in patients over 65 undergoing hip fracture surgery.MethodsProspective cohort study including all consecutive primary hip fracture patients over 65 admitted to Trauma and Orthopaedics department from January 1, 2018 to December 31, 2019. Bed-ridden, non- surgically treated patients, and high energy trauma or tumoral aetiology fractures were excluded. A total of 943 patients were eligible (attrition rate: 2.1%). Follow-up included 30-days after discharge. We noted the 30-day mortality after hip fracture surgery, analysing 130 potentially related variables including biodemographic, fracture-related, preoperative, and postoperative clinical factors. Qualitative variables were assessed by χ2, and quantitative variables by non-parametric tests. Odds ratio determined by binary logistic regression. We selected preventable candidate variables for multivariate risk assessment by logistic regression.ResultsA total of 923 patients were enrolled (mean age 86.22±6.8, 72.9% women). The 30-day mortality rate was 6.0%. We noted significant increased mortality on men (OR = 2.381[1.371-4.136], p = 0.002), ageing patients (ORyear = 1.073[1.025-1.122], p = 0.002), and longer time to surgery (ORday = 1.183[1.039-1146], p<0.001), on other 20 preoperative clinical variables, like lymphopenia (lymphocyte count <103/μl, OR = 1.842[1.063-3.191], p = 0.029), hypoalbuminemia (≤3.5g/dl, OR = 2.474[1.316-4.643], p = 0.005), and oral anticoagulant intake (OR = 2.499[1.415-4.415], p = 0.002), and on 25 postoperative clinical variables, like arrhythmia (OR = 13.937[6.263-31.017], p<0.001), respiratory insufficiency (OR = 7.002[3.947-12.419], p<0.001), hyperkalaemia (OR = 10.378[3.909-27.555], p<0.001), nutritional supply requirement (OR = 3.576[1.894-6.752], p = 0.021), or early arthroplasty dislocation (OR = 6.557[1.206-35.640], p = 0.029). We developed a predictive model for early mortality after hip fracture surgery based on postoperative factors with 96.0% sensitivity and 60.7% specificity (AUC = 0.863).ConclusionWe revealed that not only preoperative, but also postoperative factors have a great impact after hip fracture surgery. The influence of post-operative factors on 30-day mortality has a logical basis, albeit so far they have not been identified or quantified before. Our results provide an advantageous picture of the 30-day mortality after hip fracture surgery.

Project description:Importance:Although wait times for hip fracture surgery have been linked to mortality and are being used as quality-of-care indicators worldwide, controversy exists about the duration of the wait that leads to complications. Objective:To use population-based wait-time data to identify the optimal time window in which to conduct hip fracture surgery before the risk of complications increases. Design, Setting, and Participants:Population-based, retrospective cohort study of adults undergoing hip fracture surgery between April 1, 2009, and March 31, 2014, at 72 hospitals in Ontario, Canada. Risk-adjusted restricted cubic splines modeled the probability of each complication according to wait time. The inflection point (in hours) when complications began to increase was used to define early and delayed surgery. To evaluate the robustness of this definition, outcomes among propensity-score matched early and delayed surgical patients were compared using percent absolute risk differences (RDs, with 95% CIs). Exposure:Time elapsed from hospital arrival to surgery (in hours). Main Outcomes and Measures:Mortality within 30 days. Secondary outcomes included a composite of mortality or other medical complications (myocardial infarction, deep vein thrombosis, pulmonary embolism, and pneumonia). Results:Among 42 230 patients with hip fracture (mean [SD] age, 80.1 years [10.7], 70.5% women) who met study entry criteria, overall mortality at 30 days was 7.0%. The risk of complications increased when wait times were greater than 24 hours, irrespective of the complication considered. Compared with 13 731 propensity-score matched patients who received surgery earlier, 13 731 patients who received surgery after 24 hours had a significantly higher risk of 30-day mortality (898 [6.5%] vs 790 [5.8%]; % absolute RD, 0.79; 95% CI, 0.23-1.35) and the composite outcome (1680 [12.2%]) vs 1383 [10.1%]; % absolute RD, 2.16; 95% CI, 1.43-2.89). Conclusions and Relevance:Among adults undergoing hip fracture surgery, increased wait time was associated with a greater risk of 30-day mortality and other complications. A wait time of 24 hours may represent a threshold defining higher risk.

Project description:BackgroundRecent publications indicate increased mortality in patients admitted to hospital at the weekend, but these findings may be subject to inadequate adjustment for case-mix and the complexities of resource provision. Hip fractures generally occur in a frail comorbid population with a consistent diagnosis precipitating admission as an emergency. We therefore aimed to examine the association between the day of the week of milestones in the care pathway and 30-day mortality in this population.MethodsUsing data from a prospective national database of hip fractures, we investigated the association between day of the week of admission, surgery, inpatient stay, and discharge (care pathway milestones) and 30-day mortality using generalised linear models. Data was collected between January 1, 2011, and December 31, 2014, on 241,446 patients. An incremental case-mix adjustment strategy was performed using patient characteristics, non-surgical interventions, surgical interventions and discharge characteristics.ResultsThe day of admission was not associated with 30-day mortality. Sunday surgery (OR, 1.094; 95% CI, 1.043-1.148; P < 0.0001) and a delay to surgery of more than 24-hours (OR, 1.094; 95% CI, 1.059, 1.130; P < 0.0001) were both associated with a 9.4% increase in 30-day mortality. Discharge from the hospital on a Sunday (OR, 1.515; 95% CI, 1.224, 1.844; P < 0.0001) or out-of-hours discharge (OR, 1.174; 95% CI, 1.081, 1.276; P < 0.0001) were associated with a 51.5% and 17.4% increase in 30-day mortality, respectively. Mortality during the inpatient stay was 5.6% lower (IRR, 0.944; 95% CI, 0.909, 0.980; P = 0.003) at the weekend compared to weekdays.ConclusionsThere is limited evidence of a generalised weekend effect in patients admitted to hospital for hip fracture. Optimising resource utilisation is an essential element of planning and delivering healthcare services. Interventions that lead to surgery within 24-hours of admission are justified. Factors such as Sunday operations, discharge and out-of-hours discharge require further investigation.

Project description:BackgroundThe purpose of this study was to assess the validity of patient administrative data (PAS) for calculating 30-day mortality after hip fracture as a quality indicator, by a retrospective study of medical records.MethodsWe used PAS data from all Norwegian hospitals (2005-2009), merged with vital status from the National Registry, to calculate 30-day case-mix adjusted mortality for each hospital (n = 51). We used stratified sampling to establish a representative sample of both hospitals and cases. The hospitals were stratified according to high, low and medium mortality of which 4, 3, and 5 hospitals were sampled, respectively. Within hospitals, cases were sampled stratified according to year of admission, age, length of stay, and vital 30-day status (alive/dead). The final study sample included 1043 cases from 11 hospitals. Clinical information was abstracted from the medical records. Diagnostic and clinical information from the medical records and PAS were used to define definite and probable hip fracture. We used logistic regression analysis in order to estimate systematic between-hospital variation in unmeasured confounding. Finally, to study the consequences of unmeasured confounding for identifying mortality outlier hospitals, a sensitivity analysis was performed.ResultsThe estimated overall positive predictive value was 95.9% for definite and 99.7% for definite or probable hip fracture, with no statistically significant differences between hospitals. The standard deviation of the additional, systematic hospital bias in mortality estimates was 0.044 on the logistic scale. The effect of unmeasured confounding on outlier detection was small to moderate, noticeable only for large hospital volumes.ConclusionsThis study showed that PAS data are adequate for identifying cases of hip fracture, and the effect of unmeasured case mix variation was small. In conclusion, PAS data are adequate for calculating 30-day mortality after hip-fracture as a quality indicator in Norway.

Project description:BackgroundTraffic incidents are still a major contributor to hospital admissions and trauma-related mortality. The aim of this nationwide study was to examine risk-adjusted traffic injury mortality to determine whether hospital type was an independent survival factor.MethodsData on all patients admitted to Swedish hospitals with traffic-related injuries, based on International Classification of Diseases codes, between 2001 and 2011 were extracted from the Swedish inpatient and cause of death registries. Using the binary outcome measure of death or survival, data were analysed using logistic regression, adjusting for age, sex, comorbidity, severity of injury and hospital type. The severity of injury was established using the International Classification of Diseases Injury Severity Score (ICISS).ResultsThe final study population consisted of 152,693 hospital admissions. Young individuals (0-25 years of age) were overrepresented, accounting for 41% of traffic-related injuries. Men were overrepresented in all age categories. Fatalities at university hospitals had the lowest mean (SD) ICISS 0.68 (0.19). Regional and county hospitals had mean ICISS 0.75 (0.15) and 0.77 (0.15), respectively, for fatal traffic incidents. The crude overall mortality in the study population was 1193, with a mean ICISS 0.72 (0.17). Fatalities at university hospitals had the lowest mean ICISS 0.68 (0.19). Regional and county hospitals had mean ICISS 0.75 (0.15) and 0.77 (0.15), respectively, for fatal traffic incidents.When regional and county hospitals were merged into one group and its risk-adjusted mortality compared with university hospitals, no significant difference was found. A comparison between hospital groups with the most severely injured patients (ICISS ≤0.85) also did not show a significant difference (odds ratio, 1.13; 95% confidence interval, 0.97-1.32).ConclusionsThis study shows that, in Sweden, the type of hospital does not influence risk adjusted traffic related mortality, where the most severely injured patients are transported to the university hospitals and centralization of treatment is common.

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The relationship between historical risk-adjusted 30-day mortality and subsequent hip fracture outcomes: Retrospective cohort study.

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The relationship between historical risk-adjusted 30-day mortality and subsequent hip fracture outcomes: Retrospective cohort study.

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