Consequences of discharges from intensive care at night

Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study

BACKGROUND

Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events.

OBJECTIVE

To describe IHCA demographics during three day/time periods-weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)-and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care.

METHODS

We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals.

RESULTS

Risk-adjusted outcomes (OR (95% CI)) were worse (p<0.001) for both weekend daytime (ROSC>20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses.

CONCLUSIONS

IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during weekday daytimes. Organisational or care differences at night and weekends, rather than patient case mix, appear to be responsible.

Quality and performance measures of strain on intensive care capacity: a protocol for a systematic review

BACKGROUND

The matching of critical care service supply with demand is fundamental for the efficient delivery of advanced life support to patients in urgent need. Mismatch in this supply/demand relationship contributes to "intensive care unit (ICU) capacity strain," defined as a time-varying disruption in the ability of an ICU to provide well-timed and high-quality intensive care support to any and all patients who are or may become critically ill. ICU capacity strain leads to suboptimal quality of care and may directly contribute to heightened risk of adverse events, premature discharges, unplanned readmissions, and avoidable death. Unrelenting strain on ICU capacity contributes to inefficient health resource utilization and may negatively impact the satisfaction of patients, their families, and frontline providers. It is unknown how to optimally quantify the instantaneous and temporal "stress" an ICU experiences due to capacity strain.

METHODS

We will perform a systematic review to identify, appraise, and evaluate quality and performance measures of strain on ICU capacity and their association with relevant patient-centered, ICU-level, and health system-level outcomes. Electronic databases (i.e., MEDLINE, EMBASE, CINAHL, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Web of Science, and the Agency of Healthcare Research and Quality (AHRQ) - National Quality Measures Clearinghouse (NQMC)) will be searched for original studies of measures of ICU capacity strain. Selected gray literature sources will be searched. Search themes will focus on intensive care, quality, operations management, and capacity. Analysis will be primarily narrative. Each identified measure will be defined, characterized, and evaluated using the criteria proposed by the US Strategic Framework Board for a National Quality Measurement and Reporting System (i.e., importance, scientific acceptability, usability, feasibility).

DISCUSSION

Our systematic review will comprehensively identify, define, and evaluate quality and performance measures of ICU capacity strain. This is a necessary step towards understanding the impact of capacity strain on quality and performance in intensive care and to develop innovative interventions aimed to improve efficiency, avoid waste, and better anticipate impending capacity shortfalls.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, CRD42015017931.

Is weekend discharge associated with hospital readmission?

BACKGROUND

Although recent evidence suggests worse outcomes for patients admitted to the hospital on a weekend, the impact of weekend discharge is less understood.

METHODS

Utilizing the 2012 California Office of Statewide Health Planning and Development database, the impact of weekend discharge on 30-day hospital readmission rates for patients admitted with acute myocardial infarction (AMI), congestive heart failure (CHF), or pneumonia (PNA) was investigated.

RESULTS

Out of 266,519 patients, 60,097 (22.5%) were discharged on a weekend. Unadjusted 30-day hospital readmission rates were similar between weekend and weekday discharges (AMI: 21.9% vs 21.9%; CHF: 15.4% vs 16.0%; PNA: 12.1% vs 12.4%). Patients discharged on a weekday had a longer length of stay and were more often discharged to a skilled nursing facility. However, in multivariable logistic regression models, weekend discharge was not associated with readmission (AMI: odds ratio [OR] 1.02 [95% CI: 0.98-1.06]; CHF: OR 0.99 [95% CI: 0.94-1.03]; PNA: OR 1.02 (95% CI: 0.98-1.07)).

CONCLUSIONS

Among patients in California with AMI, CHF, and PNA, discharge on a weekend was not associated with an increased hospital readmission rate.

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.

Epidemiology of admissions to 11 stand-alone high-dependency care units in the UK

PURPOSE

High-dependency care units (HDUs) are a focus of research to optimize critical care resource allocation. HDUs provide a level of care between the general ward and the intensive care unit (ICU). However, few data report on the case mix and outcomes of patients in these units.

METHODS

Retrospective observational cohort study of patients admitted to 11 stand-alone HDUs in the UK from 2008 to 2011. We stratified patients by location prior to HDU admission and location on discharge from HDU, and we summarized the case mix, transitions of care, and mortality.

RESULTS

Of 9008 patients admitted to 11 stand-alone HDUs, 56.5% were male and the mean age was 62.7 ± 17.9 years. The majority of patients admitted to HDUs were non-surgical (59.3%), with 22.4 and 20.1% admitted from the ICU and general ward, respectively; 41.3% were admitted from the operating room or recovery suite. The median length of stay in HDU was 1.8 days (IQR 0.9-3.5) and in-HDU mortality was 5.1%. Among HDU survivors (n = 8551), 8.5% were discharged to an ICU, 80.9% to a general ward, and 10.6% to other care areas. For patients admitted to HDU from an ICU, only 5.8% were readmitted to ICU. Hospital mortality for the HDU population was 14.8%; for patients discharged to an ICU, hospital mortality was 43.6%.

CONCLUSIONS

In a sample of 11 stand-alone HDUs in the UK, patients are from many different hospital locations. Hospital mortality for patients requiring HDU care is high, particularly for patients who require transfer to an ICU.

Out-of-hours discharge from intensive care, in-hospital mortality and intensive care readmission rates: a systematic review protocol

BACKGROUND

Most patients are discharged from an intensive care unit with an expectation that they will survive their hospital stay, yet these patients have high subsequent in-hospital mortality. Patients are frequently discharged from an intensive care unit to a lower level of hospital care in the evenings and at night (out-of-hours). By affecting the care that patients receive, out-of-hours discharge may alter post-intensive care in-hospital mortality rates.

METHODS/DESIGN

Two searches will be conducted-the first a general search for all factors associated with post-intensive care in-hospital mortality and a second focused specifically on out-of-hours discharges. Searches will be performed in multiple databases, including Medline, Embase, Web of Knowledge, Cumulative Index of Nursing and Allied Health Literature (CINAHL) and the Cochrane Library. OpenGrey will also be searched, to ensure any unpublished 'grey' data are accessed. Language and date restrictions will not be applied. Assessment for inclusion and data extraction will be undertaken by two independent reviewers. Methodological quality will be assessed using the ACROBAT-NRSI tool. The primary outcome measure will be post-intensive care in-hospital mortality. To provide a clearer picture of this problem, studies reporting readmission to the intensive care unit (ICU) will also be included, even in the absence of report of in-hospital mortality. The primary outcome data will be synthesised and summarised using a random-effects meta-analysis. Where possible, subgroup meta-analyses will assess associated factors such as discharge destination, palliative care discharges and severity of illness scores.

DISCUSSION

To the best of our knowledge, a systematic review of the association of out-of-hours discharge with in-hospital mortality has never been undertaken. Synthesis of the available information is important because out-of-hours discharge remains common and, if associated with post-intensive care unit mortality, is highly amenable to system change.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42014010321.

The timing of discharge from the intensive care unit and subsequent mortality. A prospective, multicenter study

RATIONALE

Previous studies suggested an association between after-hours intensive care unit (ICU) discharge and increased hospital mortality. Their retrospective design and lack of correction for patient factors present at the time of discharge make this association problematic.

OBJECTIVES

To determine factors independently associated with mortality after ICU discharge.

METHODS

This was a prospective, multicenter, binational observational study involving 40 ICUs in Australia and New Zealand. Participants were consecutive adult patients discharged alive from the ICU between September 2009 and February 2010.

MEASUREMENTS AND MAIN RESULTS

We studied 10,211 patients discharged alive from the ICU. Median age was 63 years (interquartile range, 49-74), 6,224 (61%) were male, 5,707 (56%) required mechanical ventilation, and their median Acute Physiology and Chronic Health Evaluation III risk of death was 9% (interquartile range, 3-25%). A total of 8,539 (83.6%) patients were discharged in-hours (06:00-18:00) and 1,672 (16.4%) after-hours (18:00-06:00). Of these, 408 (4.8%) and 124 (7.4%), respectively, subsequently died in hospital (P < 0.001). After risk adjustment for markers of illness severity at time of ICU discharge including limitations of medical therapy (LOMT) orders, the time of discharge was no longer a significant predictor of mortality. The presence of a LOMT order was the strongest predictor of death (odds ratio, 35.4; 95% confidence interval, 27.5-45.6).

CONCLUSIONS

In this large, prospective, multicenter, binational observational study, we found that patient status at ICU discharge, particularly the presence of LOMT orders, was the chief predictor of hospital survival. In contrast to previous studies, the timing of discharge did not have an independent association with mortality.

The impact of the organization of high-dependency care on acute hospital mortality and patient flow for critically ill patients

RATIONALE

Little is known about the utility of provision of high-dependency care (HDC) that is in a geographically separate location from a primary intensive care unit (ICU).

OBJECTIVES

To determine whether the availability of HDC in a geographically separate unit affects patient flow or mortality for critically ill patients.

METHODS

Admissions to ICUs in the United Kingdom, from 2009 to 2011, who received Level 3 intensive care in the first 24 hours after admission and subsequently Level 2 HDC. We compared differences in patient flow and outcomes for patients treated in hospitals providing some HDC in a geographically separate unit (dual HDC) with patients treated in hospitals providing all HDC in the same unit as intensive care (integrated HDC) using multilevel mixed effects models.

MEASUREMENTS AND MAIN RESULTS

In 192 adult general ICUs, 21.4% provided dual HDC. Acute hospital mortality was no different for patients cared for in ICUs with dual HDC versus those with integrated HDC (adjusted odds ratio, 0.94 [0.86-1.03]; P = 0.16). Dual HDC was associated with a decreased likelihood of a delayed discharge from the primary unit. However, total duration of critical care and the likelihood of discharge from the primary unit at night were increased with dual HDC.

CONCLUSIONS

Availability of HDC in a geographically separate unit does not impact acute hospital mortality. The potential benefit of decreasing delays in discharge should be weighed against the increased total duration of critical care and greater likelihood of a transfer out of the primary unit at night.

Findings from the implementation of a validated readmission predictive tool in the discharge workflow of a medical intensive care unit

RATIONALE

Provider decisions about patients to be discharged from the intensive care unit (ICU) are often based on subjective intuition, sometimes leading to premature discharge and early readmission. The Stability and Work Load Index for Transfer (SWIFT) score, as a risk stratification tool, has moderate ability to predict patients at risk of ICU readmission.

OBJECTIVES

To describe findings following the incorporation of the SWIFT score into the discharge workflow of a medical ICU.

METHODS

The study involved 5,293 consecutive patients discharged alive from the medical ICU of an academic medical center. The SWIFT score and associated percentage risk for readmission were incorporated into daily rounds for purpose of discharge decision-making. We measured readmission rates before and after implementation and observed changes in provider discharge decisions for individual patients after SWIFT discussions.

MEASUREMENTS AND MAIN RESULTS

Baseline (n = 1,906) and implementation (n = 1,938) cohorts differed with respect to APACHE III scores (P = 0.03). In the implementation cohort, 26.2% of subjects had SWIFT scores greater than 15 and thus were predicted to have a higher risk of unplanned readmissions. In this high-risk group, 25% had SWIFT discussed in their discharge planning. There was modification of provider discharge decisions in 108 (30%) of cases in which the SWIFT was discussed. SWIFT score values above a prespecified cutoff of 15 were associated with physician tendency to prolong ICU stay or to discharge to a monitored setting (P < 0.001). There was no difference in 24-hour or 7-day readmission rates between the baseline and implementation cohorts (1.9 vs. 2.4%, P = 0.24; 6.5 vs. 7.4%, P = 0.26, respectively) even after adjustment for severity of illness.

CONCLUSIONS

Using the SWIFT score as an adjunct to clinical judgment, physicians modified their discharge decisions in one-third of subjects. Introducing such tools into the discharge workflow may present change management challenges that limit the evaluation of their impact on readmission rates and other relevant ICU outcomes.

A meta-analysis to derive literature-based benchmarks for readmission and hospital mortality after patient discharge from intensive care

Introduction

We sought to derive literature-based summary estimates of readmission to the ICU and hospital mortality among patients discharged alive from the ICU.

Methods

We searched MEDLINE, Embase, CINAHL and the Cochrane Central Register of Controlled Trials from inception to March 2013, as well as the reference lists in the publications of the included studies. We selected cohort studies of ICU discharge prognostic factors that in which readmission to the ICU or hospital mortality among patients discharged alive from the ICU was reported. Two reviewers independently abstracted the number of patients readmitted to the ICU and hospital deaths among patients discharged alive from the ICU. Fixed effects and random effects models were used to estimate the pooled cumulative incidence of ICU readmission and the pooled cumulative incidence of hospital mortality.

Results

The analysis included 58 studies (n = 2,073,170 patients). The majority of studies followed patients until hospital discharge (n = 46 studies) and reported readmission to the ICU (n = 46 studies) or hospital mortality (n = 49 studies). The cumulative incidence of ICU readmission was 4.0 readmissions (95% confidence interval (CI), 3.9 to 4.0) per 100 patient discharges using fixed effects pooling and 6.3 readmissions (95% CI, 5.6 to 6.9) per 100 patient discharges using random effects pooling. The cumulative incidence of hospital mortality was 3.3 deaths (95% CI, 3.3 to 3.3) per 100 patient discharges using fixed effects pooling and 6.8 deaths (95% CI, 6.1 to 7.6) per 100 patient discharges using random effects pooling. There was significant heterogeneity for the pooled estimates, which was partially explained by patient, institution and study methodological characteristics.

Conclusions

Using current literature estimates, for every 100 patients discharged alive from the ICU, between 4 and 6 patients on average will be readmitted to the ICU and between 3 and 7 patients on average will die prior to hospital discharge. These estimates can inform the selection of benchmarks for quality metrics of transitions of patient care between the ICU and the hospital ward.

Factors that correlate with the decision to delay extubation after multilevel prone spine surgery

BACKGROUND

Multilevel spinal decompressions and fusions often require long anesthetic and operative times, which may result in airway edema and prolonged postoperative intubation. Delayed extubation can lead to bronchopulmonary infections and other complications. This study analyzed which factors correlated with the decision to delay extubation after multilevel spine surgery.

METHODS

We reviewed the records of 289 patients who underwent multilevel spine surgery lasting ≥8 hours in the prone position from 2006 to 2012. Variables hypothesized to affect the decision of the anesthesiologist to delay extubation at the end of the surgery were collected. These included preoperative factors (age, sex, ASA class, history of obstructive sleep apnea, BMI, previous spine surgery, current cervical surgery, anterior in addition to posterior spine surgery, emergency surgery) and intraoperative factors (difficult intubation, number of surgical levels, case time, estimated blood loss, fluid and blood administration, attending handoff and resident handoff, and case end time). We also compared the incidence of pulmonary postoperative complications between patients extubated at the end of the case to patients who had a delayed extubation.

RESULTS

A total of 126 patients (44%) were kept intubated after multilevel spine surgery. Multiple linear regression analysis showed factors that correlated with prolonged intubation which included age, ASA class, procedure duration, extent of surgery, total crystalloid volume administered, total blood volume administered, and the case end time. Patients who had a delayed extubation had a 3-fold higher rate of postoperative pneumonia.

CONCLUSIONS

Our study found that age, ASA class, procedure duration, extent of surgery, and total crystalloid and blood volume administered correlate with the decision to delay extubation in multilevel prone spine surgery. It also finds that the time the case ends is an independent variable that correlates with the decision not to extubate at the end of a long multilevel spinal surgery. The incidence of postoperative pneumonia is higher in patients who had a delayed extubation after surgery.

Hospital mortality of adults admitted to Intensive Care Units in hospitals with and without Intermediate Care Units: a multicentre European cohort study

Introduction

The aim of the study was to assess whether adults admitted to hospitals with both Intensive Care Units (ICU) and Intermediate Care Units (IMCU) have lower in-hospital mortality than those admitted to ICUs without an IMCU.

Methods

An observational multinational cohort study performed on patients admitted to participating ICUs during a four-week period. IMCU was defined as any physically and administratively independent unit open 24 hours a day, seven days a week providing a level of care lower than an ICU but higher than a ward. Characteristics of hospitals, ICUs and patients admitted to study ICUs were recorded. The main outcome was all-cause in-hospital mortality until hospital discharge (censored at 90 days).

Results

One hundred and sixty-seven ICUs from 17 European countries enrolled 5,834 patients. Overall, 1,113 (19.1%) patients died in the ICU and 1,397 died in hospital, with a total of 1,397 (23.9%) deaths. The illness severity was higher for patients in ICUs with an IMCU (median Simplified Acute Physiology Score (SAPS) II: 37) than for patients in ICUs without an IMCU (median SAPS II: 29, P <0.001). After adjustment for patient characteristics at admission such as illness severity, and ICU and hospital characteristics, the odds ratio of mortality was 0.63 (95% CI 0.45 to 0.88, P = 0.007) in favour of the presence of IMCU. The protective effect of the IMCU was absent in patients who were admitted for basic observation, for example, after surgery (odds ratio 1.15, 95% CI 0.65 to 2.03, P = 0.630) but was strong in patients admitted to an ICU for other reasons (odds ratio 0.54, 95% CI 0.37 to 0.80, P = 0.002).

Conclusions

The presence of an IMCU in the hospital is associated with significantly reduced adjusted hospital mortality for adults admitted to the ICU. This effect is relevant for the patients requiring full intensive treatment.

Trial registration

Clinicaltrials.gov NCT01422070. Registered 19 August 2011.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-014-0551-8) contains supplementary material, which is available to authorized users.

Surge capacity: analysis of census fluctuations to estimate the number of intensive care unit beds needed

OBJECTIVE

To compare methods of characterizing intensive care unit (ICU) bed use and estimate the number of beds needed.

STUDY SETTING

Three geographic regions in the Canadian province of Manitoba.

STUDY DESIGN

Retrospective analysis of population-based data from April 1, 2000, to March 31, 2007.

METHODS

We compared three methods to estimate ICU bed requirements. Method 1 analyzed yearly patient-days. Methods 2 and 3 analyzed day-to-day fluctuations in patient census; these differed by whether each hospital needed to independently fulfill its own demand or this resource was shared across hospitals.

PRINCIPAL FINDINGS

Three main findings were as follows: (1) estimates based on yearly average usage generally underestimated the number of beds needed compared to analysis of fluctuations in census, especially in the smaller regions where underestimation ranged 25-58 percent; (2) 4-29 percent fewer beds were needed if it was acceptable for demand to exceed supply 18 days/year, versus 4 days/year; and (3) 13-36 percent fewer beds were needed if hospitals within a region could effectively share ICU beds.

CONCLUSIONS

Compared to using yearly averages, analyzing day-to-day fluctuations in patient census gives a more accurate picture of ICU bed use. Failing to provide adequate "surge capacity" can lead to demand that frequently and severely exceeds supply.

Comparing the monitoring of patients transferred from a critical care unit to hospital wards at after-hours with day transfers: an exploratory, prospective cohort study

AIMS

To investigate possible factors related to patient monitoring to explain the higher mortality rates associated with after-hours transfers compared with daytime transfers from critical care units to the wards.

BACKGROUND

International research suggests that patients transferred from critical care units after-hours have a higher mortality rate than transfers during daytime, although the reasons remain unknown.

DESIGN

A prospective exploratory study.

METHODS

Twenty-nine patients transferred from a UK critical care unit to a ward within the same hospital after-hours for 10 weeks beginning April 2009 were compared with 29 transfers during daytime hours matched on potentially confounding characteristics. UK Critical Care Unit transfer guidelines have remained unchanged since data collection. Outcomes were as follows: (i) frequency of nursing observations; (ii) time periods from transfer to first medical review; (iii) time period from transfer to first clinical observations; (iv) frequency of transfer to an inappropriate ward; (v) delayed transfers from Critical Care Unit to ward.

RESULTS

Using Wilcoxon's Rank test (two tail) to compare paired data from the matched groups, observations were recorded significantly less frequently within the first 12 hours for after-hours transfers. Time from transfer to first clinical observations was significantly longer for after-hour transfer patients. The delay from when the patient was ready for ward care and actual transfer was also longer for the after-hours transfer group.

CONCLUSIONS

Surveillance differences, including time to the first set of observations and frequency of observations in the first 12 hours, are potential factors that may explain the differential mortality associated with after-hours transfers.

Organizing safe transitions from intensive care

Background. Organizing and performing patient transfers in the continuum of care is part of the work of nurses and other staff of a multiprofessional healthcare team. An understanding of discharge practices is needed in order to ultimate patients' transfers from high technological intensive care units (ICU) to general wards. Aim. To describe, as experienced by intensive care and general ward staff, what strategies could be used when organizing patient's care before, during, and after transfer from intensive care. Method. Interviews of 15 participants were conducted, audio-taped, transcribed verbatim, and analyzed using qualitative content analysis. Results. The results showed that the categories secure, encourage, and collaborate are strategies used in the three phases of the ICU transitional care process. The main category; a safe, interactive rehabilitation process, illustrated how all strategies were characterized by an intention to create and maintain safety during the process. A three-way interaction was described: between staff and patient/families, between team members and involved units, and between patient/family and environment. Discussion/Conclusions. The findings highlight that ICU transitional care implies critical care rehabilitation. Discharge procedures need to be safe and structured and involve collaboration, encouraging support, optimal timing, early mobilization, and a multidiscipline approach.

Intensive care in a general hospital: demographics, utilization and outcomes

INTRODUCTION

Intensive care units (ICU) in Irish academic centres are known to fare as well as their international counterparts. Our aim in this study was to characterise the role and outcomes of an ICU in a smaller Irish hospital and to compare these to international best practice.

METHODS

We reviewed admissions of patients to the ICU of St. Luke's Hospital, Kilkenny. Patient demographics, indications for admission, and outcomes were all recorded and analysed. Sequential organ failure assessment (SOFA) scores were calculated.

RESULTS

Forty-three patients were included in our study, 33 (76.7 %) of which were emergency admissions. Median length of stay was 2 days. The observed mortality rate in our cohort was 20.9 %. The median SOFA score in patients admitted was 7. Higher median SOFA scores on admission were predictive of mortality. The ICU occupancy rate during the duration of our study was 98 %, with only 15 (35.7 %) of admissions to ICU occurring within core working hours.

CONCLUSION

Critical care can be provided safely and in line with current best practice in smaller Irish hospitals. There is a cohort of patients for whom care may be best provided in a tertiary centre, how best to provide for these patients will likely be achieved by early identification (e.g. with SOFA score). Bed capacity issues remain problematic.

Access to urban acute care services in high- vs. middle-income countries: an analysis of seven cities

Purpose

Cities are expanding rapidly in middle-income countries, but their supply of acute care services is unknown. We measured acute care services supply in seven cities of diverse economic background.

Methods

In a cross-sectional study, we compared cities from two high-income (Boston, USA and Paris, France), three upper-middle-income (Bogota, Colombia; Recife, Brazil; and Liaocheng, China), and two lower-middle-income (Chennai, India and Kumasi, Ghana) countries. We collected standardized data on hospital beds, intensive care unit beds, and ambulances. Where possible, information was collected from local authorities. We expressed results per population (from United Nations) and per acute illness deaths (from Global Burden of Disease project).

Results

Supply of hospital beds where intravenous fluids could be delivered varied fourfold from 72.4/100,000 population in Kumasi to 241.5/100,000 in Boston. Intensive care unit (ICU) bed supply varied more than 45-fold from 0.4/100,000 population in Kumasi to 18.8/100,000 in Boston. Ambulance supply varied more than 70-fold. The variation widened when supply was estimated relative to disease burden (e.g., ICU beds varied more than 65-fold from 0.06/100 deaths due to acute illnesses in Kumasi to 4.11/100 in Bogota; ambulance services varied more than 100-fold). Hospital bed per disease burden was associated with gross domestic product (GDP) (R² = 0.88, p = 0.01), but ICU supply was not (R² = 0.33, p = 0.18). No city provided all requested data, and only two had ICU data.

Conclusions

Urban acute care services vary substantially across economic regions, only partially due to differences in GDP. Cities were poor sources of information, which may hinder their future planning.

The effects of discharge to an intermediate care unit after a critical illness: a 5-year cohort study

PURPOSE

The impact of the intermediate care unit (IMCU) on post-intensive care unit (ICU) outcomes is controversial.

MATERIALS AND METHODS

We analyzed admissions from January 2003 to December 2008 from a mixed ICU in a teaching hospital in Brazil with a high patient-to-nurse ratio (3.5:1 on the ICU, 11:1 on the IMCU, 20-25:1 on the ward). A retrospective propensity-matched analysis was performed with data from 690 patients who were discharged after at least 3 days of ICU stay.

RESULTS

Of the 690 patients, 160 (23%) were discharged to the IMCU. A total of 399 propensity-matched patients were compared: 298 were discharged to the ward and 101 were discharged to the IMCU. Ninety-day mortality rate was similar between the IMCU and ward patients (22% vs 18%, respectively, P = .37), as was the unplanned ICU readmission rate (P = .63). In a multivariate logistic regression, discharge to the IMCU had no effect on the 90-day mortality rate (P = .27).

CONCLUSIONS

In a resource-limited setting with a high patient-to-nurse ratio, discharge to IMCU had no impact on 90-day mortality rate and on unplanned readmission rate. The impact of discharge to the IMCU on the outcome for critically ill patients should be evaluated in further studies.

Optimal timing of transfer out of the intensive care unit

BACKGROUND

Little other than subjective judgment is available to help clinicians determine when a patient should be transferred out of the intensive care unit.

OBJECTIVE

To assess whether remaining in the intensive care unit longer than judged to be medically necessary is associated with increased 30-day mortality.

METHODS

This prospective, observational cohort study was performed in a 13-bed, closed-model, adult medical intensive care unit of a county-owned, university-affiliated hospital that often has difficulty transferring patients to general care areas because of a lack of available beds. Analysis included all 2401 survivors of intensive care from the study period. Delay in discharge from the intensive care unit was defined as time elapsed between the request for transfer and the actual transfer. Logistic regression was used to assess the association of discharge delay with 30-day mortality, adjusting for demographics, comorbid conditions, type and severity of acute illness, care limitations in the unit, and other potential confounding variables. Nonlinear relationships with continuous variables were modeled with restricted cubic splines.

RESULTS

Overall, 30-day mortality was 10.1%. Mean discharge delay was 9.6 (SD, 11.7) hours; 9.9% had a discharge delay exceeding 24 hours. The relationship of 30-day mortality to discharge delay was statistically significant and U-shaped, with the nadir at 20 hours.

CONCLUSIONS

These data indicate an optimal time window for patients to leave the intensive care unit, with increased mortality not only if they leave earlier but also if they leave later than this optimal timing.

Intensive care unit bounce back in trauma patients: an analysis of unplanned returns to the intensive care unit

BACKGROUND

Discharging patients from the intensive care unit (ICU) often requires complex decision making to balance patient needs with available resources. Unplanned return to the ICU ("bounce back" [BB]) has been associated with increased resource use and worse outcomes, but few data on trauma patients are available. The goal of this study was to review ICU BB and define ICU discharge variables that may be predictive of BB.

METHODS

Adults admitted to ICU and discharged alive to a ward from November 04, 2012, to September 9, 2012 (interval with no changes in coverage), were selected from our trauma registry. Patients with unplanned return to ICU (BB cases) were matched 1:2 with controls on age, Injury Severity Score (ISS), and duration of post-ICU stay. Data were collected by chart review then analyzed with univariate and conditional multivariate techniques.

RESULTS

Of 8,835 hospital admissions, 1,971 (22.3%) were discharged alive from ICU to a ward. Eighty-eight patients (4.5%) met our criteria for BB (male, 75%; mean [SD] age, 52.9 [21.9] years; mean [SD] ISS, 23.1 [10.2]). Most (71.6%) occurred within 72 hours. Mortality for BB cases was high (19.3%). Regression analysis showed that male sex (odds ratio, 2.9; p = 0.01), Glasgow Coma Scale [GCS] score of less than 9 (odds ratio, 22.3; p < 0.01), discharge during day shift (odds ratio, 6.9; p < 0.0001), and presence of one (odds ratio, 3.5; p = 0.03), two (odds ratio, 3.8; p = 0.03), or three or more comorbidities (odds ratio, 8.4; p < 0.001) were predictive of BB.

CONCLUSION

In this study, BB rate was 4.8%, and associated mortality was 19.3%. At the time of ICU discharge, male sex, a GCS score of less than 9, higher FIO2, discharge on day shift, and presence of one or more comorbidities were the strongest predictors of BB. A multi-institutional study is needed to validate and extend these results.

LEVEL OF EVIDENCE

Epidemiologic/prognostic study, level IV.

A strategy to enhance the safety and efficiency of handovers of ICU patients: study protocol of the pICUp study

Background

To use intensive care unit (ICU) facilities efficiently and ensure high quality of care, an optimal patient flow is necessary. Discharging patients relieves the pressure on ICU beds but the risk of premature discharge must be managed carefully. Suboptimal patient discharge may result in ICU readmissions and in patients’ death.

The aim of this study is to obtain insight into the safety and efficiency of current ICU discharge practices and into barriers and facilitators to the implementation of effective ICU discharge interventions, and to develop an implementation strategy tailored to the barriers and facilitators identified.

Methods/design

This study exists of five phases. Phase A: analysis of routinely registered data on variation in ICU readmissions and hospital mortality after ICU discharge of all ICUs participating in the Dutch National Intensive Care Evaluation registry (n = 83). Phase B: systematic review of effective interventions aiming to improve the efficiency and safety of the ICU discharge process. Phase C: assessing the intervention adherence with a questionnaire survey among all Dutch ICUs (n = 90). Phase D: assessing barriers and facilitators to the implementation of effective ICU discharge interventions with a questionnaire survey among all Dutch intensivists (n = 700). The questionnaire will be based on barriers and facilitators identified by focus groups (n = 4) and individual interviews with professionals of ICUs and general wards and adult discharged ICU patients (n = 25 to 30). Phase E: systematic development of an implementation strategy based on the sampled data in phase A to D, and effective implementation strategies from the literature using the intervention mapping method.

Discussion

Using theory and empirical data, an implementation strategy will be developed to improve the safety and efficiency of the ICU discharge process. The developed strategy will be evaluated in a subsequent study. The knowledge obtained in this study should be used for further implementation of ICU discharge interventions, and can be used for implementation of handover interventions in other healthcare transition settings.

Nutritional rehabilitation after ICU - does it happen: a qualitative interview and observational study

AIMS AND OBJECTIVES

To compare and contrast current nutritional rehabilitation practices against recommendations from National Institute for Health and Excellence guideline Rehabilitation after critical illness (NICE) (2009, http://www.nice.org.uk/cg83).

BACKGROUND

Recovery from critical illness has gained increasing prominence over the last decade but there is remarkably little research relating to nutritional rehabilitation.

DESIGN

The study is a qualitative study based on patient interviews and observations of ward practice.

METHODS

Seventeen patients were recruited into the study at discharge from the intensive care unit (ICU) of a large teaching hospital in central Scotland in 2011. Semi-structured interviews were conducted on transfer to the ward and weekly thereafter. Fourteen of these patients were followed up at three months post-ICU discharge, and a semi-structured interview was carried out. Observations of ward practice were carried out twice weekly for the duration of the ward stay.

RESULTS

Current nutritional practice for post-intensive care patients did not reflect the recommendations from the NICE guideline. A number of organisational issues were identified as influencing nutritional care. These issues were categorised as ward culture, service-centred delivery of care and disjointed discharge planning. Their influence on nutritional care was compounded by the complex problems associated with critical illness.

CONCLUSIONS

The NICE guideline provides few nutrition-specific recommendations for rehabilitation; however, current practice does not reflect the nutritional recommendations that are detailed in the rehabilitation care pathway.

RELEVANCE TO CLINICAL PRACTICE

Nutritional care of post-ICU patients is problematic and strategies to overcome these issues need to be addressed in order to improve nutritional intake.

The epidemiology of septic shock in French intensive care units: the prospective multicenter cohort EPISS study

INTRODUCTION

To provide up-to-date information on the prognostic factors associated with 28-day mortality in a cohort of septic shock patients in intensive care units (ICUs).

METHODS

Prospective, multicenter, observational cohort study in ICUs from 14 French general (non-academic) and university teaching hospitals. All consecutive patients with septic shock admitted between November 2009 and March 2011 were eligible for inclusion. We prospectively recorded data regarding patient characteristics, infection, severity of illness, life support therapy, and discharge.

RESULTS

Among 10,941 patients admitted to participating ICUs between October 2009 and September 2011, 1,495 (13.7%) patients presented inclusion criteria for septic shock and were included. Invasive mechanical ventilation was needed in 83.9% (n=1248), inotropes in 27.7% (n=412), continuous renal replacement therapy in 32.5% (n=484), and hemodialysis in 19.6% (n=291). Mortality at 28 days was 42% (n=625). Variables associated with time to mortality, right-censored at day 28: age (for each additional 10 years) (hazard ratio (HR)=1.29; 95% confidence interval (CI): 1.20-1.38), immunosuppression (HR=1.63; 95%CI: 1.37-1.96), Knaus class C/D score versus class A/B score (HR=1.36; 95%CI:1.14-1.62) and Sepsis-related Organ Failure Assessment (SOFA) score (HR=1.24 for each additional point; 95%CI: 1.21-1.27). Patients with septic shock and renal/urinary tract infection had a significantly longer time to mortality (HR=0.56; 95%CI: 0.42-0.75).

CONCLUSION

Our observational data of consecutive patients from real-life practice confirm that septic shock is common and carries high mortality in general ICU populations. Our results are in contrast with the clinical trial setting, and could be useful for healthcare planning and clinical study design.

The association between ICU readmission rate and patient outcomes

OBJECTIVE

To examine the association between ICU readmission rates and case-mix-adjusted outcomes.

DESIGN

Retrospective cohort study of ICU admissions from 2002 to 2010.

SETTING

One hundred five ICUs at 46 United States hospitals.

PATIENTS

Of 369,129 admissions, 263,082 were first admissions that were alive at ICU discharge and candidates for readmission.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The median unit readmission rate was 5.9% (intraquartile range 5.1%-7.0%). Across all admissions, hospital mortality for patients with and without readmission was 21.3% vs. 3.6%, mean ICU stay 4.9 days vs. 3.4 days, and hospital stay 13.3 days vs. 4.5 days, respectively. We stratified ICUs according to their readmission rate: high (>7%), moderate (5%-7%), and low (<5%) rates. Observed and case-mix-adjusted hospital mortality, ICU and hospital lengths of stay were examined by readmission rate strata. Observed outcomes were much worse in the high readmission rate units. But after adjusting for patient and institutional differences, there was no association between level of unit readmission rate and case-mix-adjusted mortality. The difference between observed and predicted mortality was -0.4%, 0.4%, and -1.1%, for the high, medium, and low readmission rate strata, respectively. Additionally, the difference between observed and expected ICU length of stay was approximately zero for the three strata.

CONCLUSIONS

Patients readmitted to ICUs have increased hospital mortality and lengths of stay. After case-mix adjustment, there were no significant differences in standardized mortality or case-mix-adjusted lengths of stay between units with high readmission rates compared to units with moderate or low rates. The use of readmission as a quality measure should only be implemented if patient case-mix is taken into account.

National survey focusing on the crucial information needs of intensive care charge nurses and intensivists: same goal, different demands

Background

Although information technology adequately supports clinical care in many intensive care units (ICUs), it provides much poorer support for the managerial information needed to coordinate multi-professional care. To gain a general view of the most crucial multi-professional information needs of ICU shift leaders a national survey was conducted, focusing on the information needs of charge nurses and intensivists.

Methods

Based on our previous observation study an online survey was developed, containing 122 information need statements related to the decision-making of ICU shift leaders. Information need statements were divided into six dimensions: patient admission, organisation and management of work, allocation of staff and material resources, special treatments, and patient discharge. This survey involved all ICU shift leaders (n = 738) who worked in any of the 17 highest level ICUs for adults in university hospitals in Finland during the autumn of 2009. Both charge nurses’ and intensivists’ crucial information needs for care coordination were evaluated.

Results

Two hundred and fifty-seven (50%) charge nurses and 96 (43%) intensivists responded to the survey. The consistency of the survey was found to be good (Cronbach’s α scores between .87–.97, with a total explanatory power of 64.53%). Altogether, 57 crucial information needs for care coordination were found; 22 of which were shared between shift leaders. The most crucial of these information needs were related to organisation and management, patient admission, and allocation of staff resources. The associations between working experience, or shift leader acting frequencies, and crucial information needs were not statistically significant. However, a statistically significant difference was found between the number of ICU beds and the ICU experience of charge nurses with information needs, under the dimension of organisation and management of work. The information needs of charge nurses and intensivists differed. Charge nurses’ information needs related to care coordination, were more varied, and concerned issues at a unit level, whereas intensivists focused on direct patient care.

Conclusions

The reliability and validity of our survey was found to be good. Our study findings show that care coordination at an ICU is a collaborative process among ICU shift leaders with multiprofessional information needs related to organisation and management, patient admission, and allocation of staff resources. Study findings can be used to identify the most crucial information needs of ICU shift leaders when new information technology is developed to support managerial decision-making during care coordination.

International comparisons of intensive care: informing outcomes and improving standards

PURPOSE OF REVIEW

Interest in international comparisons of critical illness is growing, but the utility of these studies is questionable. This review examines the challenges of international comparisons and highlights areas in which international data provide information relevant to clinical practice and resource allocation.

RECENT FINDINGS

International comparisons of ICU resources demonstrate that definitions of critical illness and ICU beds vary due to differences in ability to provide organ support and variable staffing. Despite these limitations, recent international data provide key information to understand the pros and cons of different availability of ICU beds on patient flow and outcomes, and also highlight the need to ensure long-term follow-up due to heterogeneity in discharge practices for critically ill patients. With increasing emphasis on curbing costs of healthcare, systems that deliver lower cost care provide data on alternative options, such as regionalization, flexible allocation of beds, and bed rationing.

SUMMARY

Differences in provision of critical care can be leveraged to inform decisions on allocation of ICU beds, improve interpretation of clinical outcomes, and assess ways to decrease costs of care. International definitions of key components of critical care are needed to facilitate research and ensure rigorous comparisons.

Emergency nurse as hospital clinical team coordinator--shining a light into the night

BACKGROUND

The Clinical Team Coordinator (CTC) is a senior experienced nurse from the Emergency Department (ED) that provides an after-hours clinical supervision and liaison service for the entire hospital. The role guides and supports nursing and junior medical staff regarding clinical and hospital procedures, protocols and individual patient problems and assists with clinical issues on the wards such as patient assessment and management.

METHOD

Following a qualitative evaluation of the CTC role in 2009, the scope of activity and impact on clinical services after hours was established through shift data collation and analysis during the calendar year 2011.

RESULTS

In 2011, the CTC was directly involved with 18,165 occasions of care across the evening and night shift periods, with only one third of these calls requiring Resident Medical Officer (RMO) attention. The CTC role reviews patients, provides support and advice, facilitates impromptu education and learning, as well as assists nursing and medical staff with difficult and complex clinical tasks.

CONCLUSION

Senior clinical nursing support from the CTC has been well received from nursing and medical staff and the role is now a permanently established in the hospital.

Use of national clinical databases for informing and for evaluating health care policies

Policy-makers and analysts could make use of national clinical databases either to inform or to evaluate meso-level (organisation and delivery of health care) and macro-level (national) policies. Reviewing the use of 15 of the best established databases in England, we identify and describe four published examples of each use. These show that policy-makers can either make use of the data itself or of research based on the database. For evaluating policies, the major advantages are the huge sample sizes available, the generalisability of the data, its immediate availability and historic information. The principal methodological challenges involve the need for risk adjustment and time-series analysis. Given their usefulness in the policy arena, there are several reasons why national clinical databases have not been used more, some due to a lack of 'push' by their custodians and some to the lack of 'pull' by policy-makers. Greater exploitation of these valuable resources would be facilitated by policy-makers' and custodians' increased awareness, minimisation of legal restrictions on data use, improvements in the quality of databases and a library of examples of applications to policy.

The risks and rewards of expanding ICU capacity

ICU capacity strain is associated with increased morbidity and lost hospital revenue, leading many hospitals to increase the number of ICU beds. However, this approach can lead to inefficiency and waste. A recent report in Critical Care highlights a different approach: creating new service lines for low-risk patients. In this case, the authors started a post-anesthesia care unit with an intensivist-led care team, resulting in lower hospital costs with no changes in ICU mortality. Although this type of change carries some risks, and will not work for every hospital, it is an example of the creative solutions hospitals must sometimes undertake to maintain the supply of critical care in response to a rising demand.

Is there a Starling curve for intensive care?

Large differences exist in the provision of ICU beds worldwide, with a complicated mix of risks and benefits to the population of having either too few or too many beds. Having too few beds can result in delayed admission of patients to the ICU or no admission at all, with either scenario potentially increasing mortality. Potential societal benefits of having few beds include lower costs for health care and less futile intensive care at the end of life. With added ICU beds for a population, mortality benefit should accrue, but there is still the question of whether the addition of beds always means that more lives will be saved or whether there is a point at which no additional mortality benefit is gained. With an abundance of ICU beds may come the possibility of increasing harm in the forms of unnecessary costs, poor quality of deaths (ie, excessively intensive), and iatrogenic complications. The possibility of harm may be likened to the concept of falling off a Starling curve, which is traditionally used to describe worsening heart function when overfilling occurs. This commentary examines the possible implications of having too few or too many ICU beds and proposes the concept of a family of Starling curves as a way to conceptualize the balance of societal benefits and harms associated with different availability of ICU beds for a population.

A clinical nurse specialist intervention to facilitate safe transfer from ICU

PURPOSE/OBJECTIVES

The purpose of this article was to describe an innovative quality initiative implemented by the clinical nurses specialist in medicine to facilitate the transition process between the intensive care unit and the medical wards.

BACKGROUND/RATIONALE

Safely transferring patients with complex health conditions from an area of high technology and increased monitoring, like the intensive care unit, to an area with lower nurse-to-patient ratio is an intricate process. The care of these patients, once transferred, also requires varying levels of expertise. As indicated in the nursing literature, this type of transition is often associated with high stress levels for the patient and family, as well as for the healthcare providers. To maximize patient safety and ensure optimal care for this patient population, well-defined mechanisms must be put in place.

DESCRIPTION OF THE PROJECT/INNOVATION

The introduction of a formal assessment, consultation, and follow-up process conducted by a clinical nurse specialist (CNS).

OUTCOMES

On average, 150 patients are assessed each year by the CNS. Among these patients, 15% are considered at high risk for complications upon transfer to the unit. INTERPRETATION/CONCLUSION/IMPLICATIONS: A systematic evaluation of patients by the CNS, before their transfer from the ICU to a medical unit, has been proven beneficial in ensuring a comprehensive patient care plan. Patients and families have verbalized that this intervention is helpful. Staff members have indicated that this safety initiative is useful in planning patient transfers. The next step would be to formally measure patient, family, and staff satisfaction with this initiative.

Intensive care unit readmissions in U.S. hospitals: patient characteristics, risk factors, and outcomes

OBJECTIVE

To examine which patient characteristics increase the risk for intensive care unit readmission and assess the association of readmission with case-mix adjusted mortality and resource use.

DESIGN

: Retrospective cohort study.

SETTING

Ninety-seven intensive and cardiac care units at 35 hospitals in the United States.

PATIENTS

A total of 229,375 initial intensive care unit admissions during 2001 through 2009 who met inclusion criteria.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

For patients who were discharged alive and candidates for readmission, we compared the characteristics of those with and without a readmission. A multivariable logistic regression analysis was used to identify potential patient-level characteristics that increase the risk for subsequent readmission. We also evaluated case-mix adjusted outcomes by comparing observed and predicted values of mortality and length of stay for patients with and without intensive care unit readmission. Among 229,375 first admissions that met inclusion criteria, 13,980 (6.1%) were eventually readmitted. Risk factors associated with the highest multivariate odds ratio for unit readmission included location before intensive care unit admission, age, comorbid conditions, diagnosis, intensive care unit length of stay, physiologic abnormalities at intensive care discharge, and discharge to a step-down unit. After adjustment for risk factors, patients who were readmitted had a four-fold greater probability of hospital mortality and a 2.5-fold increase in hospital stay compared to patients without readmission.

CONCLUSIONS

Intensive care readmission is associated with patient factors that reflect a greater severity and complexity of illness, resulting in a higher risk for hospital mortality and a longer hospital stay. To improve patient safety, physicians should consider these risk factors when making intensive care discharge decisions. Because intensive care unit readmission correlates with more complex and severe illness, readmission rates require case-mix adjustment before they can be properly interpreted as quality measures.

Redesigning the ICU nursing discharge process: a quality improvement study

PURPOSE

To evaluate the impact of a redesigned intensive care unit (ICU) nursing discharge process on ICU discharge delay, hospital mortality, and ICU readmission within 72 hours.

METHODS

A quality improvement study using a time series design and statistical process control analysis was conducted in one Australian general ICU. The primary outcome measure was hours of discharge delay per patient discharged alive per month, measured for 15 months prior to, and for 12 months after the redesigned process was implemented. The redesign process included appointing a change agent to facilitate process improvement, developing a patient handover sheet, requesting ward staff to nominate an estimated transfer time, and designing a daily ICU discharge alert sheet that included an expected date of discharge.

RESULTS

A total of 1,787 ICU discharges were included in this study, 1,001 in the 15 months before and 786 in the 12 months after the implementation of the new discharge processes. There was no difference in in-hospital mortality after discharge from ICU or ICU readmission within 72 hours during the study period. However, process improvement was demonstrated by a reduction in the average patient discharge delay time of 3.2 hours (from 4.6 hour baseline to 1.0 hours post-intervention).

CONCLUSIONS

Involving both ward and ICU staff in the redesign process may have contributed to a shared situational awareness of the problems, which led to more timely and effective ICU discharge processes. The use of a change agent, whose ongoing role involved follow-up of patients discharged from ICU, may have helped to embed the new process into practice.

Mortality associated with timing of admission to and discharge from ICU: a retrospective cohort study

Background

Although the association between mortality and admission to intensive care units (ICU) in the "after hours" (weekends and nights) has been the topic of extensive investigation, the timing of discharge from ICU and outcome has been less well investigated. The objective of this study was to assess effect of timing of admission to and discharge from ICUs and subsequent risk for death.

Methods

Adults (≥18 years) admitted to French ICUs participating in Outcomerea between January 2006 and November 2010 were included.

Results

Among the 7,380 patients included, 61% (4,481) were male, the median age was 62 (IQR, 49-75) years, and the median SAPS II score was 40 (IQR, 28-56). Admissions to ICU occurred during weekends (Saturday and Sunday) in 1,708 (23%) cases, during the night (18:00-07:59) in 3,855 (52%), and on nights and/or weekends in 4,659 (63%) cases. Among 5,992 survivors to ICU discharge, 903 (15%) were discharged on weekends, 659 (11%) at night, and 1,434 (24%) on nights and/or weekends. After controlling for a number of co-variates using logistic regression analysis, admission during the after hours was not associated with an increased risk for death. However, patients discharged from ICU on nights were at higher adjusted risk (odds ratio, 1.54; 95% confidence interval, 1.12-2.11) for death.

Conclusions

In this study, ICU discharge at night but not admission was associated with a significant increased risk for death. Further studies are needed to examine whether minimizing night time discharges from ICU may improve outcome.

A prospective observational study of physician handoff for intensive-care-unit-to-ward patient transfers

BACKGROUND

Poor physician handoff can be a major contributor to suboptimal care and medical errors occurring in the hospital. Physician handoffs for intensive care unit (ICU)-to-ward patient transfer may face more communication hurdles. However, few studies have focused on physician handoffs in patient transfers from the ICU to the inpatient ward.

METHODS

We performed a hospitalized patient-based observational study in an urban, university-affiliated tertiary care center to assess physician handoff practices for ICU-to-ward patient transfer. One hundred twelve adult patients were enrolled. The stakeholders (sending physicians, receiving physicians, and patients/families) were interviewed to evaluate the quality of communication during these transfers. Data collected included the presence and effectiveness of communication, continuity of care, and overall satisfaction.

RESULTS

During the initial stage of patient transfers, 15.6% of the consulted receiving physicians verbally communicated with sending physicians; 26% of receiving physicians received verbal communication from sending physicians when patient transfers occurred. Poor communication during patient transfer resulted in 13 medical errors and 2 patients being transiently "lost" to medical care. Overall, the levels of satisfaction with communication (scored on a 10-point scale) for sending physicians, receiving physicians, and patients were 7.9±1.1, 8.1±1.0, and 7.9±1.7, respectively.

CONCLUSION

The overall levels of satisfaction with communication during ICU-to-ward patient transfer were reasonably high among the stakeholders. However, clear opportunities to improve the quality of physician communication exist in several areas, with potential benefits to quality of care and patient safety.

Expert nurses and the division of labour in hospitals

This article analyses nursing expertise with a particular focus at the level of clinical and organizational practice. Through an examination of a specialist team of hospital nurses, and drawing on the concept of a community of practice, the article provides a critique of discussions of nursing expertise which can be overly normative, individualistic or divorced from practice. The theoretical background to our analysis is the division of labour in health care; the case study on which this analysis is based is a particular health policy: the introduction of critical care outreach services. The empirical portions of the article are based on a qualitative study of eight such services in England. In the first part of the analysis we elaborate on three ways in which 'expertise' can be deployed in practice: teaching and training; consultancy and advice; and practical clinical action. Each of these is shown to be related to the development of a community of practice. In the second part of the analysis we examine in more detail the impact of outreach nurses on the division of labour in health care and on traditional occupational hierarchies. A general implication of our findings is that expertise has fundamentally social characteristics which need to be acknowledged in academic and policy discourse.

Off-peak nurse staffing: critical-care nurses speak

The off-peak work environment is important to understand because the risk for mortality increases for patients at night and on the weekend in hospitals. Because critical-care nurses are on duty in hospitals 24 hours a day, 7 days a week, they are excellent sources of information regarding what happens on a unit during off-peak times. Inadequate nurse staffing on off-peak shifts was described as a major problem by the nurses we interviewed. The study reported here contributes the type of information needed to better understand the organization of nursing units and nurse staffing on outcomes.