Barbara Metnitz

Errors in administration of parenteral drugs in intensive care units: multinational prospective study

Objective To assess on a multinational level the frequency, characteristics, contributing factors, and preventive measures of administration errors in parenteral medication in intensive care units. Design Observational, prospective, 24 hour cross sectional study with self reporting by staff. Setting 113 intensive care units in 27 countries. Participants 1328 adults in intensive care. Main outcome measures Number of errors; impact of errors; distribution of error characteristics; distribution of contributing and preventive factors. Results 861 errors affecting 441 patients were reported: 74.5 (95% confidence interval 69.5 to 79.4) events per 100 patient days. Three quarters of the errors were classified as errors of omission. Twelve patients (0.9% of the study population) experienced permanent harm or died because of medication errors at the administration stage. In a multiple logistic regression with patients as the unit of analysis, odds ratios for the occurrence of at least one parenteral medication error were raised for number of organ failures (odds ratio per increase of one organ failure: 1.19, 95% confidence interval 1.05 to 1.34); use of any intravenous medication (yes v no: 2.73, 1.39 to 5.36); number of parenteral administrations (per increase of one parenteral administration: 1.06, 1.04 to 1.08); typical interventions in patients in intensive care (yes v no: 1.50, 1.14 to 1.96); larger intensive care unit (per increase of one bed: 1.01, 1.00 to 1.02); number of patients per nurse (per increase of one patient: 1.30, 1.03 to 1.64); and occupancy rate (per 10% increase: 1.03, 1.00 to 1.05). Odds ratios for the occurrence of parenteral medication errors were decreased for presence of basic monitoring (yes v no: 0.19, 0.07 to 0.49); an existing critical incident reporting system (yes v no: 0.69, 0.53 to 0.90); an established routine of checks at nurses’ shift change (yes v no: 0.68, 0.52 to 0.90); and an increased ratio of patient turnover to the size of the unit (per increase of one patient: 0.73, 0.57 to 0.93). Conclusions Parenteral medication errors at the administration stage are common and a serious safety problem in intensive care units. With the increasing complexity of care in critically ill patients, organisational factors such as error reporting systems and routine checks can reduce the risk for such errors.

Preoperative anaemia is associated with poor clinical outcome in non-cardiac surgery patients

BACKGROUND Retrospective studies suggest that preoperative anaemia is associated with poor outcomes after surgery. The objective of this study was to describe mortality rates and patterns of intensive care resource use for patients with anaemia undergoing non-cardiac and non-neurological in-patient surgery. METHODS We performed a secondary analysis of a large prospective study describing perioperative care and survival in 28 European nations. Patients at least 16 yr old undergoing in-patient surgery during a 7 day period were included in the study. Data were collected for in-hospital mortality, duration of hospital stay, admission to intensive care, and intensive care resource use. Multivariable logistic regression analysis was performed to understand the effects of preoperative haemoglobin (Hb) levels on in-hospital mortality. RESULTS We included 39 309 patients in the analysis. Preoperative anaemia had a high prevalence in both men and women (31.1% and 26.5%, respectively). Multivariate analysis showed that patients with severe [odds ratio 2.82 (95% confidence interval 2.06-3.85)] or moderate [1.99 (1.67-2.37)] anaemia had higher in-hospital mortality than those with normal preoperative Hb concentrations. Furthermore, hospital length of stay (P<0.001) and postoperative admission to intensive care (P<0.001) were greater in patients with anaemia than in those with normal Hb concentrations. CONCLUSIONS Anaemia is common among non-cardiac and non-neurological surgical patients, and is associated with poor clinical outcome and increased healthcare resource use. CLINICAL TRIAL REGISTRATION NCT01203605 (ClinicalTrials.gov).

Patient volume affects outcome in critically ill patients.

ZusammenfassungKONTEXT: Ein positiver Zusammenhang zwischen Patientenvolumen und Outcome wurde bereits für eine ganze Reihe von klinischen Prozeduren demonstriert, für die Intensivmedizin gibt es allerdings nur sehr spärliche Daten. ZIEL: Den Zusammenhang zwischen Patientenvolumen und Outcome in einer großen Kohorte kritisch kranker Patienten zu untersuchen. DESIGN: Prospektive, multizentrische Kohortenstudie. SETTING: 40 österreichische Intensivstationen (IBS). PATIENTEN: 83.259 von Jänner 1998 bis Dezember 2005 konsekutiv aufgenommene Patienten. MESSUNGEN UND ERGEBNISSE: Die Strukturqualität der IBS wurde mittels Fragebogen evaluiert und mit dem prospektiv erfassten Patientendaten gematcht. Aus diesen Daten wurden mehrere Volumen-Indizes berechnet: Patienten-Turnover, Belagsdichte, Arbeitsbelastung des Pflegepersonals und die diagnostische Variabilität. RESULTATE: Die Univariate Analyse zeigte, dass etliche Volums-Indizes mit dem Outcome der Patienten assoziiert waren: mehr Patienten pro Jahr pro Intensivbett und mehr Patienten welche in der gleichen Diagnosekategorie aufgenommen wurden, senkten significant das Risiko im Spital zu versterben. In Kontrast dazu führten weniger Pflegepersonal pro Patient als auch mehr Aufnahmsdiagnosen zu einer Erhöhung des Risikos. Die Multivariate Analyse bestätigte diese Resultate. Die Beziehung zwischen der Anzahl an Patienten welche in der gleichen Diagnosekategorie behandelt wurden und der Mortalität zeigte keine lineare, sondern eine U-förmige Beziehung, mit steigender Mortalität an beiden Enden. SCHLUSS: Unsere Resultate deuten sehr deutlich auf eine Beziehung zwischen Patientenvolumen und Outcome hin. Neben der Anzahl der Patienten spielt dabei auch die diagnostische Variabilität eine Rolle. Der Zusammenhang zwischen Patientenvolumen und Outcome scheint jedoch komplex zu sein und wird offensichtlich auch von anderen Variablen wie dem Arbeitsaufwand mit beeinflusst.SummaryCONTEXT: A positive relationship between patient volume and outcome has been demonstrated for a variety of clinical conditions and procedures, but the evidence is sparse for critically ill patients. OBJECTIVE: To evaluate the relationship between patient volume and outcome in a large cohort of critically ill patients. DESIGN: Prospective multicenter cohort study, January 1998 through December 2005. SETTING: 40 intensive care units in Austria. PATIENTS: A total of 83,259 consecutively admitted patients. MAIN OUTCOME MEASURES: Structural quality of participating ICUs was evaluated using a questionnaire and merged with the prospectively collected data. Volume related indices were then calculated, representing patient turnover, occupancy rate, nursing workload and diagnostic variability. RESULTS: Univariate analysis revealed that several volume variables were associated with outcome: more patients treated per year per bed in the intensive care unit and more patients treated in the same diagnostic category reduced the risk of dying in the hospital (odds ratios, 0.967 and 0.991 for each additional 10 patients treated, respectively). In contrast, an increase in the patient-to-nurse ratio and an increase in the number of diagnostic categories were associated with increased mortality rates. Multivariate analysis confirmed these results. The relationship between the number of patients treated in the same diagnostic category and their outcomes showed not a linear but a U shape, with increasing mortality rates below and above a certain patient volume. CONCLUSIONS: Our results provide evidence for a relationship between patient volume and outcome in critically ill patients. Besides the total number of patients, diagnostic variability plays an important role. The relationship between volume and outcome seems, however, to be complex and to be influenced by other variables, such as workload of nursing staff.

Modeling in-hospital patient survival during the first 28 days after intensive care unit admission: a prognostic model for clinical trials in general critically ill patients.

OBJECTIVE The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS None. MEASUREMENTS AND RESULTS The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

Characterizing the risk profiles of intensive care units

ObjectiveTo develop a new method to evaluate the performance of individual ICUs through the calculation and visualisation of risk profiles.MethodsThe study included 102,561 patients consecutively admitted to 77 ICUs in Austria. We customized the function which predicts hospital mortality (using SAPS II) for each ICU. We then compared the risks of hospital mortality resulting from this function with the risks which would be obtained using the original function. The derived risk ratio was then plotted together with point-wise confidence intervals in order to visualise the individual risk profile of each ICU over the whole spectrum of expected hospital mortality.Main measurements and resultsWe calculated risk profiles for all ICUs in the ASDI data set according to the proposed method. We show examples how the clinical performance of ICUs may depend on the severity of illness of their patients. Both the distribution of the Hosmer–Lemeshow goodness-of-fit test statistics and the histogram of the corresponding P values demonstrated a good fit of the individual risk models.ConclusionsOur risk profile model makes it possible to evaluate ICUs on the basis of the specific risk for patients to die compared to a reference sample over the whole spectrum of hospital mortality. Thus, ICUs at different levels of severity of illness can be directly compared, giving a clear advantage over the use of the conventional single point estimate of the overall observed-to-expected mortality ratio.

Weekends affect mortality risk and chance of discharge in critically ill patients: a retrospective study in the Austrian registry for intensive care

BackgroundIn this study, we primarily investigated whether ICU admission or ICU stay at weekends (Saturday and Sunday) is associated with a different risk of ICU mortality or chance of ICU discharge than ICU admission or ICU stay on weekdays (Monday to Friday). Secondarily, we analysed whether weekend ICU admission or ICU stay influences risk of hospital mortality or chance of hospital discharge.MethodsA retrospective study was performed for all adult patients admitted to 119 ICUs participating in the benchmarking project of the Austrian Centre for Documentation and Quality Assurance in Intensive Care (ASDI) between 2012 and 2015. Readmissions to the ICU during the same hospital stay were excluded.ResultsIn a multivariable competing risk analysis, a strong weekend effect was observed. Patients admitted to ICUs on Saturday or Sunday had a higher mortality risk after adjustment for severity of illness by Simplified Acute Physiology Score (SAPS) 3, year, month of the year, type of admission, ICU, and weekday of death or discharge. Hazard ratios (95% confidence interval) for death in the ICU following admission on a Saturday or Sunday compared with Wednesday were 1.15 (1.08–1.23) and 1.11 (1.03–1.18), respectively. Lower hazard ratios were observed for dying on a Saturday (0.93 (0.87–1.00)) or Sunday (0.85 (0.80–0.91)) compared with Wednesday. This is probably related to the reduced chance of being discharged from the ICU at the weekend (0.63 (0.62–064) for Saturday and 0.56 (0.55–0.57) for Sunday). Similar results were found for hospital mortality and hospital discharge following ICU admission.ConclusionsPatients admitted to ICUs at weekends are at increased risk of death in both the ICU and the hospital even after rigorous adjustment for severity of illness. Conversely, death in the ICU and discharge from the ICU are significantly less likely at weekends.