Association of patient-to-intensivist ratio with hospital mortality in Australia and New Zealand.
Ontology highlight
ABSTRACT: Purpose
The impact of intensivist workload on intensive care unit (ICU) outcomes is incompletely described and assessed across healthcare systems and countries. We sought to examine the association of patient-to-intensivist ratio (PIR) with hospital mortality in Australia/New Zealand (ANZ) ICUs.Methods
We conducted a retrospective study of adult admissions to ANZ ICUs (August 2016-June 2018) using two cohorts: "narrow", based on previously used criteria including restriction to ICUs with a single daytime intensivist; and "broad", refined by individual ICU daytime staffing information. The exposure was average daily PIR and the outcome was hospital mortality. We used summary statistics to describe both cohorts and multilevel multivariable logistic regression models to assess the association of PIR with mortality. In each, PIR was modeled using restricted cubic splines to allow for non-linear associations. The broad cohort model included non-PIR physician and non-physician staffing covariables.Results
The narrow cohort of 27,380 patients across 67 ICUs (predicted mortality: median 1.2% [IQR 0.4-1.4%]; mean 5.9% [sd 13.2%]) had a median PIR of 10.1 (IQR 7-14). The broad cohort of 91,206 patients across 73 ICUs (predicted mortality: 1.9% [0.6-6.5%]; 7.6% [14.9%]) had a median PIR of 7.8 (IQR 5.8-10.2). We found no association of PIR with mortality in either the narrow (PIR 1st spline term odds ratio [95% CI]: 1 [0.94, 1.06], Wald testing of spline terms p = 0.61) or the broad (1.02 [0.97, 1.07], p = 0.4) cohort.Conclusion
We found no association of PIR with hospital mortality across ANZ ICUs. The low cohort predicted mortality may limit external validity.
SUBMITTER: Gershengorn HB
PROVIDER: S-EPMC8638228 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background and objectivesThe burden of infectious disease is high among kidney transplant recipients because of concomitant immunosuppression. In this study the incidence of infectious-related mortality and associated factors were evaluated.Design, setting, participants, & measurementsIn this registry-based retrospective, longitudinal cohort study, recipients of a first kidney transplant in Australia and New Zealand between 1997 and 2015 were included. Cumulative incidence of infectious-related mortality was estimated using competing risk regression (using noninfectious mortality as a competing risk event), and compared with age-matched, populated-based data using standardized incidence ratios.ResultsAmong 12,519 patients, (median age 46 years, 63% men, 15% diabetic, 6% Indigenous ethnicity), 2197 (18%) died, of whom 416 (19%) died from infection. The incidence of infection-related mortality during the study period (1997-2015) was 45.8 (95% confidence interval [95% CI], 41.6 to 50.4) per 10,000 patient-years. The incidence of infection-related mortality reduced from 53.1 (95% CI, 45.0 to 62.5) per 10,000 person-years in 1997-2000 to 43.9 (95% CI, 32.5 to 59.1) per 10,000 person-years in 2011-2015 (P<0.001) Compared with the age-matched general population, kidney transplant recipients had a markedly higher risk of infectious-related death (standardized incidence ratio, 7.8; 95% CI, 7.1 to 8.6). Infectious mortality was associated with older age (≥60 years adjusted subdistribution hazard ratio [SHR], 4.16; 95% CI, 2.15 to 8.05; reference 20-30 years), female sex (SHR, 1.62; 95% CI, 1.19 to 2.29), Indigenous ethnicity (SHR, 2.87; 95% CI, 1.84 to 4.46; reference white), earlier transplant era (2011-2015: SHR, 0.39; 95% CI, 0.20 to 0.76; reference 1997-2000), and use of T cell-depleting therapy (SHR, 2.43; 95% CI, 1.36 to 4.33). Live donor transplantation was associated with lower risk of infection-related mortality (SHR, 0.53; 95% CI, 0.37 to 0.76).ConclusionsInfection-related mortality in kidney transplant recipients is significantly higher than the general population, but has reduced over time. Risk factors include older age, female sex, Indigenous ethnicity, T cell-depleting therapy, and deceased donor transplantation.PodcastThis article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2019_08_27_CJN03200319.mp3.
| S-EPMC6777595 | biostudies-literature
Project description:The ANZDATA Registry includes all patients treated with renal replacement therapy (RRT) throughout Australia and New Zealand. Funding is predominantly from government sources, together with the non-government organization Kidney Health Australia. Registry operations are overseen by an Executive committee, and a Steering Committee with wide representation. Data is collected from renal units throughout Australia and New Zealand on a regular basis, and forwarded to the Registry. Areas covered include demographic details, primary renal disease, type of renal replacement therapy, process measures, and a variety of outcomes. From this data collection a number of themes of work are produced. These include production of Registry reports with an extensive range of national and regional data, a suite of quality assurance reports, key process indicator (KPI) reports, and data sets for a variety of audit and research purposes. The various types of information from the ANZDATA Registry are used in a wide variety of areas, including health services planning, safety and quality programs, and clinical research projects.
| S-EPMC4455186 | biostudies-other
Project description:BackgroundRisk adjusted mortality for intensive care units (ICU) is usually estimated via logistic regression. Random effects (RE) or hierarchical models have been advocated to estimate provider risk-adjusted mortality on the basis that standard estimators increase false outlier classification. The utility of fixed effects (FE) estimators (separate ICU-specific intercepts) has not been fully explored.MethodsUsing a cohort from the Australian and New Zealand Intensive Care Society Adult Patient Database, 2009-2010, the model fit of different logistic estimators (FE, random-intercept and random-coefficient) was characterised: Bayesian Information Criterion (BIC; lower values better), receiver-operator characteristic curve area (AUC) and Hosmer-Lemeshow (H-L) statistic. ICU standardised hospital mortality ratios (SMR) and 95%CI were compared between models. ICU site performance (FE), relative to the grand observation-weighted mean (GO-WM) on odds ratio (OR), risk ratio (RR) and probability scales were assessed using model-based average marginal effects (AME).ResultsThe data set consisted of 145355 patients in 128 ICUs, years 2009 (47.5%) & 2010 (52.5%), with mean(SD) age 60.9(18.8) years, 56% male and ICU and hospital mortalities of 7.0% and 10.9% respectively. The FE model had a BIC = 64058, AUC = 0.90 and an H-L statistic P-value = 0.22. The best-fitting random-intercept model had a BIC = 64457, AUC = 0.90 and H-L statistic P-value = 0.32 and random-coefficient model, BIC = 64556, AUC = 0.90 and H-L statistic P-value = 0.28. Across ICUs and over years no outliers (SMR 95% CI excluding null-value = 1) were identified and no model difference in SMR spread or 95%CI span was demonstrated. Using AME (OR and RR scale), ICU site-specific estimates diverged from the GO-WM, and the effect spread decreased over calendar years. On the probability scale, a majority of ICUs demonstrated calendar year decrease, but in the for-profit sector, this trend was reversed.ConclusionsThe FE estimator had model advantage compared with conventional RE models. Using AME, between and over-year ICU site-effects were easily characterised.
| S-EPMC4100889 | biostudies-literature
Project description:BackgroundA large body of research suggests that hospitals with intensive care units staffed by board-certified intensivists have lower mortality rates than those that do not.ObjectiveTo determine whether hospitals can reduce their mortality by adopting an intensivist staffing model.DesignRetrospective, longitudinal study using 2003-2010 Medicare data and the Leapfrog Group Hospital surveys.Setting and patientsIn total, 2,916,801 Medicare patients at 488 US hospitals.MeasurementsWe studied 30-day and in-hospital mortality among patients with several common medical and surgical conditions. We first compared risk-adjusted mortality rates of 3 groups of hospitals: those that were intensivist staffed throughout this time period, those that were not intensivist staffed, and those that transitioned to intensivist staffing somewhere during the period. We then examined rates of mortality improvement within each of the 3 groups and used difference-in-differences techniques to assess the independent effect of intensivist staffing among the subset of hospitals that transitioned.ResultsHospitals with intensivist staffing at the beginning of our study period had lower mortality rates than those without. However, hospitals that adopted intensivist staffing during the study period did not substantially improve their mortality rates. In our difference-in-differences analysis, there was no significant independent improvement in mortality after transitioning to intensivist staffing either overall [relative risk (RR), 0.96; 95% confidence interval (CI), 0.90-1.02] or in the medical (RR, 0.95; 95% CI, 0.89-1.02) or surgical populations (RR, 0.97; 95% CI, 0.84-1.10).LimitationsRisk adjustment was based on administrative data. Categorization of exposure was by survey response at the hospital level.ConclusionsAdoption of an intensivist staffing model was not associated with improved mortality in Medicare beneficiaries. These findings suggest that the lower mortality rates previously observed at hospitals with intensivist staffing may be attributable to other factors.
| S-EPMC4718837 | biostudies-literature
Project description:ObjectivesTo determine whether there was variation in nurse staffing across hospitals in Queensland prior to implementation of nurse-to-patient ratio legislation targeting medical-surgical wards, and if so, the extent to which nurse staffing variation was associated with poor outcomes for patients and nurses.DesignAnalysis of cross-sectional data derived from nurse surveys linked with admitted patient outcomes data.SettingPublic hospitals in Queensland.Participants4372 medical-surgical nurses and 146 456 patients in 68 public hospitals.Main outcome measures30-day mortality, quality and safety indicators, nurse outcomes including emotional exhaustion and job dissatisfaction.ResultsMedical-surgical nurse-to-patient ratios before implementation of ratio legislation varied significantly across hospitals (mean 5.52 patients per nurse; SD=2.03). After accounting for patient characteristics and hospital size, each additional patient per nurse was associated with 12% higher odds of 30-day mortality (OR=1.12; 95% CI 1.01 to 1.26). Each additional patient per nurse was associated with poorer outcomes for nurses including 15% higher odds of emotional exhaustion (OR=1.15; 95% CI 1.07 to 1.23) and 14% higher odds of job dissatisfaction (OR=1.14; 95% CI 1.02 to 1.28), as well as higher odds of concerns about quality of care (OR=1.12; 95% CI 1.01 to 1.25) and patient safety (OR=1.32; 95% CI 1.11 to 1.57).ConclusionsBefore ratios were implemented, nurse staffing varied considerably across Queensland hospital medical-surgical wards and higher nurse workloads were associated with patient mortality, low quality of care, nurse emotional exhaustion and job dissatisfaction. The considerable variation across hospitals and the link with outcomes suggests that taking action to improve staffing levels was prudent.
| S-EPMC7476482 | biostudies-literature
Project description:Wide variations in blood glucose excursions in critically ill patients may influence adverse outcomes such as hospital mortality. However, whether blood glucose variability is independently associated with mortality or merely captures the excess risk attributable to hyperglycemic and hypoglycemic episodes is not established. We investigated whether blood glucose variability independently predicted hospital mortality in nonhyperglycemic critical care patients. Design:Retrospective, registry data analyses of outcomes. Setting:Large, binational registry (Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Adult Patient Database repository) of 176 ICUs across Australia and New Zealand. Patients:We used 10-year data on nonhyperglycemic patients registered in the Australia and New Zealand Intensive Care Society Centre for Outcome and Resource Evaluation Adult Patient Database repository (n = 290,966). Interventions:None. Measurements and Main Results:Glucose variability was captured using glucose width defined as the difference between highest and lowest blood glucose concentration within first 24 hours of ICU admission. We used hierarchical, mixed effects logistic regression models that accounted for ICU variation and several fixed-effects covariates. Glucose width was specifically and independently associated with hospital mortality. The association of blood glucose variability with mortality remained significant (odds ratio for highest vs lowest quartile of glucose, 1.43; 95% CI, 1.32-1.55; p < 0.001) even after adjusting for the baseline risk of mortality, midpoint blood glucose level, occurrence of hypoglycemia and inter-ICU variation. Mixed effects modeling showed that there was a statistically significant variation in this association across ICUs. Conclusions:Our study demonstrates that glucose variability is independently associated with hospital mortality in critically ill adult patients. Inclusion of correction for glucose variability in glycemic control protocols needs to be investigated in future studies.
| S-EPMC7063954 | biostudies-literature
Project description:BackgroundComparing the mortality profiles of dialysis centres is important to ensure that high standards of care are maintained. We compare the performance of dialysis centres in Australia and New Zealand in their treatment of haemodialysis patients, accounting for the competing risks of kidney transplantation and transfer to peritoneal dialysis.MethodsObservational cohort study. We included data from all adult patients (5574 patients) commencing haemodialysis at home or in a facility between 2008 and 2010 across 62 dialysis centres, from the Australia and New Zealand Dialysis and Transplant Registry. Standardised mortality ratios were calculated by estimating mortality probabilities from a pooled random effects logistic regression model, accounting for the competing risk of transplantation using an inverse probability weighting approach. Models were adjusted for patient comorbidities, sex, height, weight, late referral to a nephrologist, age, race, primary kidney disease, smoking status, and serum creatinine (?mol/l).ResultsTwo dialysis centres were found to have relatively higher levels of risk-adjusted mortality lying outside the prediction intervals for "usual" performance. Risk adjusted mortality rates were not associated with centres' compliance with guidelines for vascular access and biochemical and haematological targets.ConclusionsWe demonstrate that standardised mortality ratios are useful to identify facilities that have statistically outlying mortality risk. Our criterion for determining whether a centre has better or worse performance than expected is statistical, and thus analyses such as ours can serve only as a screening tool, and are only one aspect of assessment of "quality" of performance.
| S-EPMC6311072 | biostudies-literature
Project description:IntroductionThough peritonitis is associated with increased mortality in patients receiving peritoneal dialysis (PD), its association with cardiovascular mortality remains uncertain.MethodsThe study participants included adult patients (≥18 years old) commencing PD in Australia (from October 2003 to December 2019) using the Australia and New Zealand Dialysis and Transplant (ANZDATA) registry. Association between peritonitis and cardiovascular mortality was evaluated using Cox proportional hazards analysis and competing risks analysis. Associations between peritonitis rates between different eras and cardiovascular mortality were also compared using Jointpoint regression model to determine the time point when a significant change in peritonitis trend occurred to define the era for cardiovascular mortality. Subgroup analysis dividing the groups into 0, 1 and ≥2 episodes of peritonitis and sensitivity analysis censoring at 90 days post-transfer to hemodialysis (HD) were performed.ResultsThe study included 9699 incident PD patients. The overall peritonitis rate was 0.37 episodes per patient-year and declined by 4.7% (95% confidence interval [CI] 3.6-5.8%) during the study period. Peritonitis was associated with increased cardiovascular mortality risk (subdistribution hazard ratio [SHR] 1.53, 95% CI 1.39-1.69, P < 0.001) with increasing peritonitis episodes associated with higher risk (1 episode of peritonitis SHR 1.41, 95%CI 1.24-1.61; ≥2 episodes of peritonitis SHR 1.69, 95% CI 1.47-1.93, P < 0.001). Patients who commenced PD between 2012 and 2019 had a lower risk of cardiovascular mortality (SHR 0.60, 95% CI 0.50-0.72, P < 0.001), compared to patients who commenced between 2003 and 2011. Results were consistent in the sensitivity analysis.ConclusionPeritonitis is independently associated with an increased risk of cardiovascular mortality, and the association is episode-dependent. Prevention and adequate treatment of PD peritonitis may improve cardiovascular outcomes among patients receiving PD.
| S-EPMC9751840 | biostudies-literature
Project description:BackgroundPatients with burn injuries are considered to have an increased risk of venous thromboembolism (VTE). While untreated VTEs can be fatal, no studies have examined chemoprophylaxis effectiveness. This study aimed to quantify the variation in prevalence of VTE prophylaxis use in patients in Australian and New Zealand burns units and whether prophylaxis use is associated with in-hospital outcomes following burn injury.MethodsAdmission data for adult burns patients (aged ≥16 years) admitted between 1 July 2016 and 31 December 2018 were extracted from the Burns Registry of Australia and New Zealand. Mixed effects logistic regression modelling investigated whether VTE prophylaxis use was associated with the primary outcome of in-hospital mortality.ResultsThere were 5066 admissions over the study period. Of these patients, 81% (n = 3799) with a valid response to the VTE prophylaxis data field received some form of VTE prophylaxis. Use of VTE prophylaxis ranged from 48.6% to 94.8% of patients between units. In-hospital death was recorded in <1% of patients (n = 33). After adjusting for confounders, receiving VTE prophylaxis was associated with a decrease in the adjusted odds of in-hospital mortality (adjusted odds ratio = 0.21; 95% CI, 0.07-0.63; p = 0.006).ConclusionsVariation in the use of VTE prophylaxis was observed between the units, and prophylaxis use was associated with a decrease in the odds of mortality. These findings provide an opportunity to engage with units to further explore differences in prophylaxis use and develop future best practice guidelines.
| S-EPMC7901708 | biostudies-literature
Project description:BACKGROUND: The hospital standardized mortality ratio (HSMR) is developed to evaluate and improve hospital quality. Different methods can be used to standardize the hospital mortality ratio. Our aim was to assess the validity and applicability of directly and indirectly standardized hospital mortality ratios. METHODS: Retrospective scenario analysis using routinely collected hospital data to compare deaths predicted by the indirectly standardized case-mix adjustment method with observed deaths. Discharges from Dutch hospitals in the period 2003-2009 were used to estimate the underlying prediction models. We analysed variation in indirectly standardized hospital mortality ratios (HSMRs) when changing the case-mix distributions using different scenarios. Sixty-one Dutch hospitals were included in our scenario analysis. RESULTS: A numerical example showed that when interaction between hospital and case-mix is present and case-mix differs between hospitals, indirectly standardized HSMRs vary between hospitals providing the same quality of care. In empirical data analysis, the differences between directly and indirectly standardized HSMRs for individual hospitals were limited. CONCLUSION: Direct standardization is not affected by the presence of interaction between hospital and case-mix and is therefore theoretically preferable over indirect standardization. Since direct standardization is practically impossible when multiple predictors are included in the case-mix adjustment model, indirect standardization is the only available method to compute the HSMR. Before interpreting such indirectly standardized HSMRs the case-mix distributions of individual hospitals and the presence of interactions between hospital and case-mix should be assessed.
| S-EPMC3621877 | biostudies-literature