Patient volume affects outcome in critically ill patients

Case volume and specialization in critically ill emergency patients: a nationwide cohort study in Japanese ICUs

BACKGROUND

Previous studies have explored the association between the number of cases and patient outcomes for critical illnesses such as sepsis and trauma, as well as various surgeries, with the expectation that a higher number of cases would have a more favorable effect on patient outcomes. The aim of this study was to elucidate the association among intensive care unit (ICU) case volume, specialization, and patient outcomes in critically ill emergency patients and to determine how ICU case volumes and specializations impact the outcomes of these patients in Japanese ICUs.

METHODS

Utilizing data from the Japanese Intensive Care PAtient Database (JIPAD) from April 2015 to March 2021, this retrospective cohort study was conducted in 80 ICUs across Japan and included 72,214 emergency patients aged ≥ 16 years. The primary outcome measure was in-hospital mortality, and the secondary outcomes encompassed ICU mortality, 28-day mortality, ventilator-free days, and the lengths of ICU and hospital stays. Bayesian hierarchical generalized linear mixed models were used to adjust for patient- and ICU-level variables.

RESULTS

This study revealed a significant association between a higher ICU case volume and decreased in-hospital mortality. In particular, ICUs with a higher percentage (> 75%) of emergency patients showed more pronounced effects, with the odds ratios for in-hospital mortality in the higher case volume quartiles (Q2, Q3, and Q4) being 0.92 (95% credible interval [CI]: 0.88-0.96), 0.70 (95% CI: 0.67-0.73), and 0.78 (95% CI: 0.73-0.83), respectively, compared with the lowest quartile (Q1). Similar trends were observed for various secondary outcomes.

CONCLUSIONS

Higher ICU case volumes were significantly associated with lower in-hospital mortality rates in Japanese ICUs predominantly treating critically ill emergency patients. These findings emphasize the importance of ICU specialization and highlight the potential benefits of centralized care for critically ill emergency patients. These findings are potential insights for improving health care policy in Japan and may be valuable in emergency care settings in other countries with similar healthcare systems, after careful consideration of contextual differences.

A scoping review of registry captured indicators for evaluating quality of critical care in ICU

BACKGROUND

Excess morbidity and mortality following critical illness is increasingly attributed to potentially avoidable complications occurring as a result of complex ICU management (Berenholtz et al., J Crit Care 17:1-2, 2002; De Vos et al., J Crit Care 22:267-74, 2007; Zimmerman J Crit Care 1:12-5, 2002). Routine measurement of quality indicators (QIs) through an Electronic Health Record (EHR) or registries are increasingly used to benchmark care and evaluate improvement interventions. However, existing indicators of quality for intensive care are derived almost exclusively from relatively narrow subsets of ICU patients from high-income healthcare systems. The aim of this scoping review is to systematically review the literature on QIs for evaluating critical care, identify QIs, map their definitions, evidence base, and describe the variances in measurement, and both the reported advantages and challenges of implementation.

METHOD

We searched MEDLINE, EMBASE, CINAHL, and the Cochrane libraries from the earliest available date through to January 2019. To increase the sensitivity of the search, grey literature and reference lists were reviewed. Minimum inclusion criteria were a description of one or more QIs designed to evaluate care for patients in ICU captured through a registry platform or EHR adapted for quality of care surveillance.

RESULTS

The search identified 4780 citations. Review of abstracts led to retrieval of 276 full-text articles, of which 123 articles were accepted. Fifty-one unique QIs in ICU were classified using the three components of health care quality proposed by the High Quality Health Systems (HQSS) framework. Adverse events including hospital acquired infections (13.7%), hospital processes (54.9%), and outcomes (31.4%) were the most common QIs identified. Patient reported outcome QIs accounted for less than 6%. Barriers to the implementation of QIs were described in 35.7% of articles and divided into operational barriers (51%) and acceptability barriers (49%).

CONCLUSIONS

Despite the complexity and risk associated with ICU care, there are only a small number of operational indicators used. Future selection of QIs would benefit from a stakeholder-driven approach, whereby the values of patients and communities and the priorities for actionable improvement as perceived by healthcare providers are prioritized and include greater focus on measuring discriminable processes of care.

A descriptive survey on the use of resuscitative endovascular balloon occlusion of the aorta (REBOA) for pelvic fractures at US level I trauma centers

Background

Resuscitative endovascular balloon occlusion of the aorta (REBOA) is not widely adopted for pelvic fracture management. Western Trauma Association recommends REBOA for hemodynamically unstable pelvic fractures, whereas Eastern Association for the Surgery of Trauma and Advanced Trauma Life Support do not.

Method

Utilizing a prospective cross-sectional survey, all 158 trauma medical directors at American College of Surgeons-verified Level I trauma centers were emailed survey invitations. The study aimed to determine the rate of REBOA use, REBOA indicators, and the treatment sequence of REBOA for hemodynamically unstable pelvic fractures.

Results

Of those invited, 25% (40/158) participated and 90% (36/40) completed the survey. Nearly half of trauma centers [42% (15/36)] use REBOA for pelvic fracture management. All participants included hemodynamic instability as an indicator for REBOA placement in pelvic fractures. In addition to hemodynamic instability, 29% (4/14) stated REBOA is used for patients who are ineligible for angioembolization, 14% (2/14) use REBOA when interventional radiology is unavailable, 7% (1/14) use REBOA for patients with a negative FAST. Fifty percent (7/14) responded that hemodynamically unstable pelvic fractures exclusively indicates REBOA placement. Hemodynamic instability for pelvic fractures was most commonly defined as systolic blood pressure of < 90 [56% (20/36)]. At centers using REBOA, REBOA was the first line of treatment for hemodynamically unstable pelvic fractures 40% (6/15) of the time.

Conclusions

There is little consensus on REBOA use for pelvic fractures at US Level I Trauma Centers, except that hemodynamically unstable pelvic fractures consistently indicated REBOA use.

Effect of Institutional Case Volume on In-Hospital and Long-Term Mortality in Critically Ill Patients Requiring Mechanical Ventilation for 48 Hours or More

BACKGROUND

The purpose of this study was to evaluate whether institutional case volume affects clinical outcomes in patients receiving mechanical ventilation for 48 hours or more.

METHODS

We conducted a nationwide retrospective cohort study using the database of Korean National Healthcare Insurance Service. Between January 2007 and December 2016, 158,712 adult patients were included at 55 centers in Korea. Centers were categorized according to the average annual number of patients: > 500, 500 to 300, and < 300.

RESULTS

In-hospital mortality rates in the high-, medium-, and low-volume centers were 32.6%, 35.1%, and 39.2%, respectively. After adjustment, in-hospital mortality was significantly higher in low-volume centers (adjusted odds ratio [OR], 1.332; 95% confidence interval [CI], 1.296-1.368; P < 0.001) and medium-volume centers (adjusted OR, 1.125; 95% CI, 1.098-1.153; P < 0.001) compared to high-volume centers. Long-term survival for up to 8 years was better in high-volume centers.

CONCLUSION

Centers with higher case volume (> 500 patients/year) showed lower in-hospital mortality and long-term mortality, compared to centers with lower case volume (< 300 patients/year) in patients who required mechanical ventilation for 48 hours or more.

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

Background

In 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.

Methods

A 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.

Results

In 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.

Conclusions

Patients 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.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-017-1812-0) contains supplementary material, which is available to authorized users.

The effect of nurse-to-patient ratios on nurse-sensitive patient outcomes in acute specialist units: a systematic review and meta-analysis

Background:

Nurses are pivotal in the provision of high quality care in acute hospitals. However, the optimal dosing of the number of nurses caring for patients remains elusive. In light of this, an updated review of the evidence on the effect of nurse staffing levels on patient outcomes is required.

Aim:

To undertake a systematic review and meta-analysis examining the association between nurse staffing levels and nurse-sensitive patient outcomes in acute specialist units.

Methods:

Nine electronic databases were searched for English articles published between 2006 and 2017. The primary outcomes were nurse-sensitive patient outcomes.

Results:

Of 3429 unique articles identified, 35 met the inclusion criteria. All were cross-sectional and the majority utilised large administrative databases. Higher staffing levels were associated with reduced mortality, medication errors, ulcers, restraint use, infections, pneumonia, higher aspirin use and a greater number of patients receiving percutaneous coronary intervention within 90 minutes. A meta-analysis involving 175,755 patients, from six studies, admitted to the intensive care unit and/or cardiac/cardiothoracic units showed that a higher nurse staffing level decreased the risk of inhospital mortality by 14% (0.86, 95% confidence interval 0.79–0.94). However, the meta-analysis also showed high heterogeneity (I2=86%).

Conclusion:

Nurse-to-patient ratios influence many patient outcomes, most markedly inhospital mortality. More studies need to be conducted on the association of nurse-to-patient ratios with nurse-sensitive patient outcomes to offset the paucity and weaknesses of research in this area. This would provide further evidence for recommendations of optimal nurse-to-patient ratios in acute specialist units.

Quality Indicators but Not Admission Volumes of Neonatal Intensive Care Units Are Effective in Reducing Mortality Rates of Preterm Infants

AIM

To investigate how two different strategies to form larger neonatal intensive care units (NICU) impact neonatal mortality rates.

METHODS

Cross-sectional study modeling admission volumes and mortality rates of 177,086 VLBW infants aggregated into 862 NICUs. Cumulative 3-year data was abstracted from Vermont Oxford Network. The model simulated a reduction in number of NICUs by stepwise exclusion using either admission volume (VOL) or quality (QUAL) cut-offs. After randomly redirecting infants of excluded to remaining NICUs resulting system mortality rates were calculated with and without adjusting for effects of experience levels (EL) using published data to reflect effects of different team-to-patient exposure.

RESULTS

The quality-based strategy is more effective in reducing mortality; while VOL alone was not able to reduce system mortality, QUAL already achieved a 5% improvement after reducing 8% of NICUs and redirecting 6% of infants. Including "EL", a 5% improvement of mortality was achieved by reducing 77% (VOL) vs. 7% (QUAL) of NICUs and redirecting 54% (VOL) vs. 5% (QUAL) of VLBW infants, respectively.

CONCLUSION

While a critical number of admissions is needed to maintain skills this study emphasizes the importance of including quality parameters to restructure neonatal care. The findings can be generalized to other medical fields.

Relationship between Annualized Case Volume and Mortality in Sepsis

Background

The relationship between annualized case volume and mortality in patients with sepsis is not fully understood. The authors performed a dose–response meta-analysis to assess the effect of annualized case volume on mortality among patients with sepsis in the intensive care unit, emergency department, or hospital, hypothesizing that higher annualized case volume may lead to lower mortality.

Methods

The authors searched PubMed and Embase through July 2015 to identify observational studies that examined the relationship between annualized case volume and mortality in sepsis. The predefined outcome was mortality. Odds ratios with 95% CIs were pooled using a random-effects model.

Results

Ten studies involving 3,495,921 participants and 834,009 deaths were included. The pooled estimate suggested that annualized case volume was inversely associated with mortality (odds ratio, 0.76; 95% CI, 0.65 to 0.89; P = 0.001), with high heterogeneity (I2 = 96.6%). The relationship was consistent in most subgroup analyses and robust in sensitivity analysis. Dose–response analysis identified a nonlinear relationship between annualized case volume and mortality (P for nonlinearity less than 0.001).

Conclusions

This meta-analysis confirmed the study hypothesis and provided strong evidence for an inverse and a nonlinear dose–response relationship between annualized case volume and mortality in patients with sepsis. Variations in cutoff values of category for annualized case volume across studies may mainly result in the overall heterogeneity. Future studies should uncover the mechanism of volume–mortality relationship and standardize the cutoff values of category for annualized case volume in patients with sepsis.

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.

Modeling hospital infrastructure by optimizing quality, accessibility and efficiency via a mixed integer programming model

Background

The majority of curative health care is organized in hospitals. As in most other countries, the current 94 hospital locations in the Netherlands offer almost all treatments, ranging from rather basic to very complex care. Recent studies show that concentration of care can lead to substantial quality improvements for complex conditions and that dispersion of care for chronic conditions may increase quality of care. In previous studies on allocation of hospital infrastructure, the allocation is usually only based on accessibility and/or efficiency of hospital care. In this paper, we explore the possibilities to include a quality function in the objective function, to give global directions to how the ‘optimal’ hospital infrastructure would be in the Dutch context.

Methods

To create optimal societal value we have used a mathematical mixed integer programming (MIP) model that balances quality, efficiency and accessibility of care for 30 ICD-9 diagnosis groups. Typical aspects that are taken into account are the volume-outcome relationship, the maximum accepted travel times for diagnosis groups that may need emergency treatment and the minimum use of facilities.

Results

The optimal number of hospital locations per diagnosis group varies from 12-14 locations for diagnosis groups which have a strong volume-outcome relationship, such as neoplasms, to 150 locations for chronic diagnosis groups such as diabetes and chronic obstructive pulmonary disease (COPD).

Conclusions

In conclusion, our study shows a new approach for allocating hospital infrastructure over a country or certain region that includes quality of care in relation to volume per provider that can be used in various countries or regions. In addition, our model shows that within the Dutch context chronic care may be too concentrated and complex and/or acute care may be too dispersed. Our approach can relatively easily be adopted towards other countries or regions and is very suitable to perform a ‘what-if’ analysis.

Characterizing performance profiles of ICUs

PURPOSE OF REVIEW

Benchmarking of the ICU was till last year based on the assumption that performance was independent of the severity of illness of the admitted patients. In the past years, this assumption has been challenged several times, but only last year a concrete method to evaluate the performance of individual ICUs through the calculation and visualization of risk profiles was proposed and experimentally tested in a cohort of 102 561 patients consecutively admitted to 77 ICUs in Austria, belonging to the Austrian Center of Documentation and Quality Assurance in Intensive Care Medicine.

RECENT FINDINGS

The demonstration, although using the New Simplified Acute Physiology Score (SAPS II), is independent of the specific general outcome prediction model used. The method allows the computation of individual risk profiles for all ICUs in the data set under analysis and both 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.

SUMMARY

The new method, the Risk Profile Management method, makes it possible to evaluate individual ICUs on the basis of the specific risk for patients to die compared with a reference sample over the whole spectrum of hospital mortality. This way, even ICUs operating with different levels of mean severity of illness of the admitted patients 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.

Impact of nosocomial infections on clinical outcome and resource consumption in critically ill patients

OBJECTIVE

Nosocomial infections still present a major problem in intensive care units (ICUs), accounting for prolonged ICU and hospital stays and worsened outcomes. There exist differences in the literature regarding the impact of nosocomial infections on attributable mortality and resource consumption. The aim of this study was to observe these effects in a large cohort of critically ill patients.

PATIENTS AND SETTINGS

Thirty-four Austrian ICUs participated in the study by documenting all nosocomial infections from 1 June to 30 November 2003 according to the Hospital in Europe Link for Infection Control through Surveillance (HELICS) protocol.

MEASUREMENTS AND RESULTS

Of 2,392 patients with a length-of-stay (LOS) >2 days, 683 (28.6%) developed at least one nosocomial infection. The most common infection was pneumonia (n = 456), followed by central venous catheter (CVC) infections (n = 101). Risk-adjusted mortality rates (standardized mortality ratios) were significantly increased for infected patients [0.91 (0.83-0.99) vs. 0.68 (0.61-0.74)]. Significant attributable risk-adjusted mortality was found for patients with pneumonia, combined infections (both 32%) and CVC-related infections (26%). LOS in the ICU increased significantly for all infections.

CONCLUSIONS

We conclude that significant attributable mortality for several nosocomial infections exists in a large cohort of critically ill patients, with the highest impact occurring in those with microbiologically diagnosed pneumonia and combined infections. All infections were associated with an increased resource consumption. Effective infection control measures could improve both clinical outcome and proper and effective use of ICU resources.

Characterizing the risk profiles of intensive care units

OBJECTIVE

To develop a new method to evaluate the performance of individual ICUs through the calculation and visualisation of risk profiles.

METHODS

The 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 RESULTS

We 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.

CONCLUSIONS

Our 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.