Mortality among patients admitted to strained intensive care units

The Volume-Outcome Relationship in Critical Care: A Systematic Review and Meta-analysis

OBJECTIVE

The purpose of this study was to systematically review the research on volume and outcome relationships in critical care.

METHODS

From January 1, 2001, to April 30, 2014, MEDLINE and EMBASE were searched for studies assessing the relationship between admission volume and clinical outcomes in critical illness. Bibliographies were reviewed to identify other articles of interest, and experts were contacted about missing or unpublished studies. Of 127 studies reviewed, 46 met inclusion criteria, covering seven clinical conditions. Two investigators independently reviewed each article using a standardized form to abstract information on key study characteristics and results.

RESULTS

Overall, 29 of the studies (63%) reported a statistically significant association between higher admission volume and improved outcomes. The magnitude of the association (mortality OR between the lowest vs highest stratum of volume centers), as well as the thresholds used to characterize high volume, varied across clinical conditions. Critically ill patients with cardiovascular (n = 7, OR = 1.49 [1.11-2.00]), respiratory (n = 12, OR = 1.20 [1.04-1.38]), severe sepsis (n = 4, OR = 1.17 [1.03-1.33]), hepato-GI (n = 3, OR = 1.30 [1.08-1.78]), neurologic (n = 3, OR = 1.38 [1.22-1.57]), and postoperative admission diagnoses (n = 3, OR = 2.95 [1.05-8.30]) were more likely to benefit from admission to higher-volume centers compared with lower-volume centers. Studies that controlled for ICU or hospital organizational factors were less likely to find a significant volume-outcome relationship than studies that did not control for these factors.

CONCLUSIONS

Critically ill patients generally benefit from care in high-volume centers, with more substantial benefits in selected high-risk conditions. This relationship may in part be mediated by specific ICU and hospital organizational factors.

Association Between Nighttime Discharge from the Intensive Care Unit and Hospital Mortality: A Multi-Center Retrospective Cohort Study

Background

We aimed to determine the impact of nighttime discharge from the intensive care unit (ICU) to the ward on hospital mortality and readmission rates in consecutive critically ill patients admitted to five Canadian ICUs. We hypothesized that hospital mortality and readmission rates would be higher for patients discharged after hours compared with discharge during the day.

Methods

A multi-center retrospective cohort study was carried out at five hospitals in Edmonton, Canada, between July 2002 and December 2009. Nighttime discharge was defined as discharge from the ICU occurring between 07:00 pm and 07:59 am. Logistic regression analysis was used to explore the associations between nighttime discharge and outcomes.

Results

Of 19,622 patients discharged alive from the ICU, 3,505 (17.9 %) discharges occurred during nighttime. Nighttime discharge occurred more commonly among medical than surgical patients (19.9 % vs. 13.8 %, P < 0.001) and among those with more comorbid conditions, compared with daytime discharged patients. Crude hospital mortality (11.8 % versus 8.8 %, P < 0.001) was greater for nighttime discharged as compared to daytime discharged patients. In a multivariable analysis, after adjustment for comorbidities, diagnosis and source of admission, nighttime discharge remains associated with higher mortality (odds ratio [OR] 1.29; 95 % CI, 1.14 to 1.46, P < 0.001). This finding was robust in two sensitivity analyses examining discharges occurring between 00:00 am and 04:59 am (OR 1.28; 1.12–1.47; P < 0.001) and for those who died within 48 h of ICU discharge without readmission (OR 1.24; 1.07–1.42, P = 0.002). There was no difference in ICU readmission for nighttime compared with daytime discharges (7.4 % vs. 6.9 %, p = 0.26). However, rates were higher for nighttime discharges in community compared with tertiary hospitals (7.7 % vs. 5.7 %, P = 0.023).

Conclusions

In a large integrated health region, 1 in 5 ICU patients are discharged at nighttime, a factor with increasing occurrence during our study and shown to be independently associated with higher hospital mortality.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-015-1044-4) contains supplementary material, which is available to authorized users.

Modeling for critically ill patients: An introduction for beginners

Models are mathematical tools used to describe real-world features. Therapeutic interventions in the field of critical care medicine may easily be translated into such models. Indeed, numerous variables influencing drug pharmacokinetics and pharmacodynamics are systematically documented in the intensive care unit over time. Organ failure, fluid shifts, other drug administration, and renal replacement therapy may cause changes in physiological values, such as body weight and composition, temperature, serum protein levels, arterial pH, and renal or hepatic function. Trials assessing the efficacy and safety of novel drugs usually exclude critically ill patients, and guidelines regarding drug dosage rarely apply to such patients. Modeling in the critically ill may allow physicians to inform decisions related to therapeutic interventions, particularly relating to infectious diseases. However, few clinicians are familiar with these methods. Here, we present a current overview of population pharmacokinetic and pharmacodynamic models applicable in critically ill patients aimed at nonspecialists and then emphazize recent potential of modeling for optimizing treatments and care in the intensive care unit.

Intensive care unit capacity strain and adherence to prophylaxis guidelines

PURPOSE

The purpose of the study is to examine the relationship between different measures of capacity strain and adherence to prophylaxis guidelines in the intensive care unit (ICU).

MATERIALS AND METHODS

We conducted a retrospective cohort study within the Project IMPACT database. We used multivariable logistic regression to examine relationships between ICU capacity strain and appropriate usage of venous thromboembolism prophylaxis (VTEP) and stress ulcer prophylaxis (SUP).

RESULTS

Of 776,905 patient-days eligible for VTEP, appropriate therapy was provided on 68%. Strain as measured by proportion of new admissions (odds ratio [OR], 0.91; 95% confidence interval [CI], 0.90-0.91) and census (OR, 0.97; 95% CI, 0.97-0.98) was associated with decreased odds of receiving VTEP. With increasing strain as measured by new admissions, the degradation of VTEP utilization was more severe in ICUs with closed (OR, 0.85; 95% CI, 0.83-0.88) than open (OR, 0.91; 95% CI, 0.91-0.92) staffing models (interaction P<.001). Of 185425 patient-days eligible for SUP, 48% received appropriate therapy. Administration of SUP was not significantly influenced by any measure of strain.

CONCLUSIONS

Rising capacity strain in the ICU reduces the odds that patients will receive appropriate VTEP but not SUP. The variability among different types of ICUs in the extent to which strain degraded VTEP use suggests opportunities for systems improvement.

Prevalência de incidentes relacionados à medicação em unidade de terapia intensiva

Objetivo Estimar a prevalência de incidentes relacionados à medicação em uma Unidade de Terapia Intensiva. Métodos Estudo transversal que incluiu 116 registros de internações hospitalares no período de 12 meses. O instrumento de pesquisa foi elaborado com base nas variáveis de estudo e validado por dois experts. A prevalência foi calculada considerando o número de internações expostas como numerador e o total de internações investigadas como denominador, calculando intervalo de confiança de 95%. Para a verificação de associação significativa entre as variáveis, utilizou-se o Teste Exato de Fisher, assumindo nível de significância máximo de 5% (p<0,05). Resultados Verificou-se que 113 internações foram expostas a pelo menos um tipo de incidente, totalizando 2.869 ocorrências, sendo 1.437 circunstâncias notificáveis, 1.418 incidentes sem dano, nove potenciais eventos adversos e cinco eventos adversos. Os incidentes aconteceram durante a fase da prescrição (45,4%) e a ausência de conduta dos profissionais de saúde frente aos incidentes foi identificada em 99% dos registros. Conclusão Estimou-se prevalência de 97,4% incidentes relacionados à medicação.

Integrating palliative care in the ICU

PURPOSE OF REVIEW

Although providing palliative care in the ICU has become a priority, the success of different methods to integrate palliative care into the ICU has varied. This review examines the current evidence supporting the different models of palliative care delivery and highlights areas for future study.

RECENT FINDINGS

The need for palliative care for ICU patients is substantial. A large percentage of patients meet criteria for palliative care consultation and there is frequent use of intensive care and other nonbeneficial care at the end of life. Overall, the consultative model of palliative care appears to have more of an impact on patient care. However, given the current workforce shortage of palliative care providers, a sustainable model of delivering palliative care requires both an effective integrative model, in which palliative care is delivered by ICU clinicians, and appropriate use of the consultative model, in which palliative care consultation is reserved for patients at highest risk of having unmet or long-term palliative care needs.

SUMMARY

Developing a mixed model of palliative care delivery is necessary to meet the palliative care needs of critically ill patients. Efforts focused on improving integrative models and appropriately targeting the use of palliative care consultants are needed.

Nighttime intensivist staffing, mortality, and limits on life support: a retrospective cohort study

BACKGROUND

Evidence regarding nighttime physician staffing of ICUs is suboptimal. We aimed to determine how nighttime physician staffing models influence patient outcomes.

METHODS

We performed a multicenter retrospective cohort study in a multicenter registry of US ICUs. The exposure variable was the ICU's nighttime physician staffing model. The primary outcome was hospital mortality. Secondary outcomes included new limitations on life support, ICU length of stay, hospital length of stay, and duration of mechanical ventilation. Daytime physician staffing was studied as a potential effect modifier.

RESULTS

The study included 270,742 patients in 143 ICUs. Compared with nighttime staffing with an attending intensivist, nighttime staffing without an attending intensivist was not associated with hospital mortality (OR, 1.03; 95% CI, 0.92-1.15; P = .65). This relationship was not modified by daytime physician staffing (interaction P = .19). When nighttime staffing was subcategorized, neither attending nonintensivist nor physician trainee staffing was associated with hospital mortality compared with attending intensivist staffing. However, nighttime staffing without any physician was associated with reduced odds of hospital mortality (OR, 0.79; 95% CI, 0.68-0.91; P = .002) and new limitations on life support (OR, 0.83; 95% CI, 0.75-0.93; P = .001). Nighttime staffing was not associated with ICU or hospital length of stay. Nighttime staffing with an attending nonintensivist was associated with a slightly longer duration of mechanical ventilation (hazard ratio, 1.05; 95% CI, 1.02-1.09; P < .001).

CONCLUSIONS

We found little evidence that nighttime physician staffing models affect patient outcomes. ICUs without physicians at night may exhibit reduced hospital mortality that is possibly attributable to differences in end-of-life care practices.

Assessing the utility of ICU readmissions as a quality metric: an analysis of changes mediated by residency work-hour reforms

BACKGROUND

ICU readmissions are associated with increased mortality and costs; however, it is unclear whether these outcomes are caused by readmissions or by residual confounding by illness severity. An assessment of temporal changes in ICU readmission in response to a specific policy change could help disentangle these possibilities. We sought to determine whether ICU readmission rates changed after 2003 Accreditation Council for Graduate Medical Education Resident Duty Hours reform ("reform") and whether there were temporally corresponding changes in other ICU outcomes.

METHODS

We used a difference-in-differences approach using Project IMPACT (Improved Methods of Patient Information Access of Core Clinical Tasks). Piecewise regression models estimated changes in outcomes immediately before and after reform in 274,491 critically ill medical and surgical patients in 151 community and academic US ICUs. Outcome measures included ICU readmission, ICU mortality, and in-hospital post-ICU-discharge mortality.

RESULTS

In ICUs with residents, ICU readmissions increased before reform (OR, 1.5; 95% CI, 1.22-1.84; P < .01), and decreased after (OR, 0.85; 95% CI, 0.73-0.98; P = .03). This abrupt decline in ICU readmissions after reform differed significantly from an increase in readmissions observed in ICUs without residents at this time (difference-in-differences P < .01). No comparable changes in mortality were observed between ICUs with vs without residents.

CONCLUSIONS

The changes in ICU readmission rates after reform, without corresponding changes in mortality, suggest that ICU readmissions are not causally related to other untoward patient outcomes. Instead, ICU readmission rates likely reflect operational aspects of care that are not patient-centered, making them less useful indicators of ICU quality.

Objective factors associated with physicians' and nurses' perceptions of intensive care unit capacity strain

RATIONALE

Time-varying demand for critical care may strain the capacities of intensive care units (ICUs) to provide optimal care. Intensivists and ICU nurses may be the best judges of the strain on their ICU. Yet, it is not clear what ICU and hospital factors contribute to this perceived sense of strain among ICU providers.

OBJECTIVES

To identify measureable ICU and hospital factors associated with perceived strain by intensivists and ICU nurses.

METHODS

During a 6-month prospective cohort study, we surveyed nurses and physicians responsible for bed management regarding the ability of a 24-bed medical ICU (MICU) to provide optimal critical care. We simultaneously assessed time-varying ICU-level factors, including patient census, number of admissions, average patient acuity, number of interhospital transfer requests, and censuses of other hospital units. To identify factors associated with strain, we used an algorithm for covariate selection in regression models that selects variables that contribute sufficiently to model prediction to justify their inclusion.

MEASUREMENTS AND MAIN RESULTS

Of 254 surveys, 226 (89%) were completed by 18 charge nurses and 17 physicians. On a scale of 1 to 10 (where a higher score indicated more strain), the median perceived strain score among nurses was 6 (interquartile range, 3-7) and among physicians was 5 (interquartile range, 3-7), with moderate correlation within days (interclass correlation coefficient, 0.45; 95% confidence interval: 0.30, 0.60). Average patient acuity, MICU census, number of MICU admissions, and general ward census were included in the most efficient model of strain perceived by nurses. Only MICU census was strongly associated with strain perceived by physicians.

CONCLUSIONS

A model containing commonly available metrics of ICU census, average patient acuity, and the proportion of new admissions has validity as a model of ICU nurses' perceived ICU capacity strain. However, only ICU census was associated with increased perceived capacity strain by physicians, highlighting the need for involvement of multiple stakeholder groups to improve our understanding of ICU capacity strain.

Estimates of the need for palliative care consultation across united states intensive care units using a trigger-based model

RATIONALE

Use of triggers for palliative care consultation has been advocated in intensive care units (ICUs) to ensure appropriate specialist involvement for patients at high risk of unmet palliative care needs. The volume of patients meeting these triggers, and thus the potential workload for providers, is unknown.

OBJECTIVES

To estimate the prevalence of ICU admissions who met criteria for palliative care consultation using different sets of triggers.

METHODS

Retrospective cohort study of ICU admissions from Project IMPACT for 2001-2008. We assessed the prevalence of ICU admissions meeting one or more primary palliative care triggers, and prevalence meeting any of multiple sets of triggers.

MEASUREMENTS AND MAIN RESULTS

Overall, 53,124 (13.8%) ICU admissions met one or more primary triggers for palliative care consultation. Variation in prevalence was minimal across different types of units (mean 13.3% in medical ICUs to 15.8% in trauma/burn ICUs; P = 0.41) and individual units (mean 13.8%, median 13.0%, interquartile range, 10.2-16.5%). A comprehensive model combining multiple sets of triggers identified a total of 75,923 (19.7%) ICU admissions requiring palliative care consultation; of them, 85.4% were captured by five triggers: (1) ICU admission after hospital stay greater than or equal to 10 days, (2) multisystem organ failure greater than or equal to three systems, (3) stage IV malignancy, (4) status post cardiac arrest, and (5) intracerebral hemorrhage requiring mechanical ventilation.

CONCLUSIONS

Approximately one in seven ICU admissions met triggers for palliative care consultation using a single set of triggers, with an upper estimate of one in five patients using multiple sets of triggers; these estimates were consistent across different types of ICUs and individual units. These results may inform staffing requirements for providers to ensure delivery of specialized palliative care to ICU patients nationally.