ICU capacity strain and the quality and allocation of critical care

Geographic access to high capability severe acute respiratory failure centers in the United States

OBJECTIVE

Optimal care of adults with severe acute respiratory failure requires specific resources and expertise. We sought to measure geographic access to these centers in the United States.

DESIGN

Cross-sectional analysis of geographic access to high capability severe acute respiratory failure centers in the United States. We defined high capability centers using two criteria: (1) provision of adult extracorporeal membrane oxygenation (ECMO), based on either 2008-2013 Extracorporeal Life Support Organization reporting or provision of ECMO to 2010 Medicare beneficiaries; or (2) high annual hospital mechanical ventilation volume, based 2010 Medicare claims.

SETTING

Nonfederal acute care hospitals in the United States.

MEASUREMENTS AND MAIN RESULTS

We defined geographic access as the percentage of the state, region and national population with either direct or hospital-transferred access within one or two hours by air or ground transport. Of 4,822 acute care hospitals, 148 hospitals met our ECMO criteria and 447 hospitals met our mechanical ventilation criteria. Geographic access varied substantially across states and regions in the United States, depending on center criteria. Without interhospital transfer, an estimated 58.5% of the national adult population had geographic access to hospitals performing ECMO and 79.0% had geographic access to hospitals performing a high annual volume of mechanical ventilation. With interhospital transfer and under ideal circumstances, an estimated 96.4% of the national adult population had geographic access to hospitals performing ECMO and 98.6% had geographic access to hospitals performing a high annual volume of mechanical ventilation. However, this degree of geographic access required substantial interhospital transfer of patients, including up to two hours by air.

CONCLUSIONS

Geographic access to high capability severe acute respiratory failure centers varies widely across states and regions in the United States. Adequate referral center access in the case of disasters and pandemics will depend highly on local and regional care coordination across political boundaries.

ICU occupancy and mechanical ventilator use in the United States

OBJECTIVES

Detailed data on occupancy and use of mechanical ventilators in U. S. ICU over time and across unit types are lacking. We sought to describe the hourly bed occupancy and use of ventilators in U.S. ICUs to improve future planning of both the routine and disaster provision of intensive care.

DESIGN

Retrospective cohort study. We calculated mean hourly bed occupancy in each ICU and hourly bed occupancy for patients on mechanical ventilators. We assessed trends in overall occupancy over the 3 years. We also assessed occupancy and mechanical ventilation rates across different types and sizes of ICUs.

SETTING

Ninety-seven U.S. ICUs participating in Project IMPACT from 2005 to 2007.

PATIENTS

A total of 226,942 consecutive admissions to ICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Over the 3 years studied, total ICU occupancy ranged from 57.4% to 82.1% and the number of beds filled with mechanically ventilated patients ranged from 20.7% to 38.9%. There was no change in occupancy across years and no increase in occupancy during influenza seasons. Mean hourly occupancy across ICUs was 68.2% ± 21.3% (SD) and was substantially higher in ICUs with fewer beds (mean, 75.8% ± 16.5% for 5-14 beds vs 60.9% ± 22.1% for 20+ beds, p = 0.001) and in academic hospitals (78.7% ± 15.9% vs 65.3% ± 21.3% for community not-for-profit hospitals, p < 0.001). More than half of ICUs (53.6%) had 4+ beds available more than half the time. The mean percentage of ICU patients receiving mechanical ventilation in any given hour was 39.5% (± 15.2%), and a mean of 29.0% (± 15.9%) of ICU beds were filled with a patient on a ventilator.

CONCLUSIONS

Occupancy of U.S. ICUs was stable over time, but there is uneven distribution across different types and sizes of units. Only three of 10 beds were filled at any time with mechanically ventilated patients, suggesting substantial surge capacity throughout the system to care for acutely critically ill patients.

Mortality among patients admitted to strained intensive care units

RATIONALE

The aging population may strain intensive care unit (ICU) capacity and adversely affect patient outcomes. Existing fluctuations in demand for ICU care offer an opportunity to explore such relationships.

OBJECTIVES

To determine whether transient increases in ICU strain influence patient mortality, and to identify characteristics of ICUs that are resilient to surges in capacity strain.

METHODS

Retrospective cohort study of 264,401 patients admitted to 155 U.S. ICUs from 2001 to 2008. We used logistic regression to examine relationships of measures of ICU strain (census, average acuity, and proportion of new admissions) near the time of ICU admission with mortality.

MEASUREMENTS AND MAIN RESULTS

A total of 36,465 (14%) patients died in the hospital. ICU census on the day of a patient's admission was associated with increased mortality (odds ratio [OR], 1.02 per standardized unit increase; 95% confidence interval [CI]: 1.00, 1.03). This effect was greater among ICUs employing closed (OR, 1.07; 95% CI: 1.02, 1.12) versus open (OR, 1.01; 95% CI: 0.99, 1.03) physician staffing models (interaction P value = 0.02). The relationship between census and mortality was stronger when the census was composed of higher acuity patients (interaction P value < 0.01). Averaging strain over the first 3 days of patients' ICU stays yielded similar results except that the proportion of new admissions was now also associated with mortality (OR, 1.04 for each 10% increase; 95% CI: 1.02, 1.06).

CONCLUSIONS

Several sources of ICU strain are associated with small but potentially important increases in patient mortality, particularly in ICUs employing closed staffing models. Although closed ICUs may promote favorable outcomes under static conditions, they are susceptible to being overwhelmed by patient influxes.

Outcomes among patients discharged from busy intensive care units

BACKGROUND

Strains on the capacities of intensive care units (ICUs) may influence the quality of ICU-to-floor transitions.

OBJECTIVE

To determine how 3 metrics of ICU capacity strain (ICU census, new admissions, and average acuity) measured on days of patient discharges influence ICU length of stay (LOS) and post-ICU discharge outcomes.

DESIGN

Retrospective cohort study from 2001 to 2008.

SETTING

155 ICUs in the United States.

PATIENTS

200 730 adults discharged from ICUs to hospital floors.

MEASUREMENTS

Associations between ICU capacity strain metrics and discharged patient ICU LOS, 72-hour ICU readmissions, subsequent in-hospital death, post-ICU discharge LOS, and hospital discharge destination.

RESULTS

Increases in the 3 strain variables on the days of ICU discharge were associated with shorter preceding ICU LOS (all P < 0.001) and increased odds of ICU readmissions (all P < 0.050). Going from the 5th to 95th percentiles of strain was associated with a 6.3-hour reduction in ICU LOS (95% CI, 5.3 to 7.3 hours) and a 1.0% increase in the odds of ICU readmission (CI, 0.6% to 1.5%). No strain variable was associated with increased odds of subsequent death, reduced odds of being discharged home from the hospital, or longer total hospital LOS.

LIMITATION

Long-term outcomes could not be measured.

CONCLUSION

When ICUs are strained, triage decisions seem to be affected such that patients are discharged from the ICU more quickly and, perhaps consequentially, have slightly greater odds of being readmitted to the ICU. However, short-term patient outcomes are unaffected. These results suggest that bed availability pressures may encourage physicians to discharge patients from the ICU more efficiently and that ICU readmissions are unlikely to be causally related to patient outcomes.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality; National Heart, Lung, and Blood Institute; and Society of Critical Care Medicine.

An empirical derivation of the optimal time interval for defining ICU readmissions

BACKGROUND

Intensive care unit (ICU) readmission rates are commonly viewed as indicators of ICU quality. However, definitions of ICU readmissions vary, and it is unknown which, if any, readmissions are associated with ICU quality.

OBJECTIVE

Empirically derive the optimal interval between ICU discharge and readmission for purposes of considering ICU readmission as an ICU quality indicator.

RESEARCH DESIGN

Retrospective cohort study.

SUBJECTS

A total of 214,692 patients discharged from 157 US ICUs participating in the Project IMPACT database, 2001-2008.

MEASURES

We graphically examined how patient characteristics and ICU discharge circumstances (eg, ICU census) were related to the odds of ICU readmissions as the allowable interval between ICU discharge and readmission was lengthened. We defined the optimal interval by identifying inflection points where these relationships changed significantly and permanently.

RESULTS

A total of 2242 patients (1.0%) were readmitted to the ICU within 24 hours; 9062 (4.2%) within 7 days. Patient characteristics exhibited stronger associations with readmissions after intervals >48-60 hours. By contrast, ICU discharge circumstances and ICU interventions (eg, mechanical ventilation) exhibited weaker relationships as intervals lengthened, with inflection points at 30-48 hours. Because of the predominance of afternoon readmissions regardless of time of discharge, using intervals defined by full calendar days rather than fixed numbers of hours produced more valid results.

DISCUSSION

It remains uncertain whether ICU readmission is a valid quality indicator. However, having established 2 full calendar days (not 48 h) after ICU discharge as the optimal interval for measuring ICU readmissions, this study will facilitate future research designed to determine its validity.

Unscheduled readmissions to the PICU: epidemiology, risk factors, and variation among centers

OBJECTIVES

To determine the rate of, and potential risk factors for, unscheduled PICU readmission and assess for variability among PICUs within the United States.

DESIGN AND DATA SOURCE

This retrospective cohort study used 2005-2008 data from 73 PICUs in the Virtual PICU Systems database.

METHODS AND MEASUREMENTS

Early (within 48 hr of PICU discharge) and late (later than 48 hr) unscheduled readmission rates were calculated. Hierarchical logistic regression, with a random intercept for site, was used to identify factors independently associated with early readmission. Significant random effects identified sites with an outlying risk of readmission, adjusting for patient and admission characteristics.

MAIN RESULTS

For 117,923 children meeting inclusion criteria, the unscheduled readmission rate was 3.7% with 38% (1.4%) occurring early. Half of early readmissions had the same primary diagnosis as the first admission. Patients with late readmissions had a higher mortality (6.6% vs 3.3%, p < 0.001) and longer median total PICU length of stay (11 d vs 6 d, p < 0.0001) than those with early readmission. Patient characteristics strongly associated with increased risk of early readmission included the following: age < 6 months, acute respiratory and renal disease, and several underlying chronic conditions such as liver disease, bone marrow transplant, airway stenosis, and abnormal antidiuretic hormone balances. An initial PICU admission that was unscheduled, originated from the general floor, or with a discharge time between 4 PM and 8 AM was associated with higher risk of readmission. A quarter of sites were identified as potential high (16%) or low (8%) outliers.

CONCLUSIONS

The rate of unscheduled PICU readmission was low but associated with worse outcomes. Patient and admission/discharge characteristics associated with increased risk of readmissions could be used to target high-risk populations or modifiable factors to improve outcome. Variation of risk among centers suggests room for improvement.

Unplanned pediatric intensive care unit readmissions: a single-center experience

PURPOSE

The purpose of the study was to compare patients readmitted to the pediatric intensive care unit (PICU) unexpectedly within 48 hours (early), more than 48 hours from transfer (late), or not readmitted during the same hospitalization.

MATERIALS AND METHODS

A retrospective study (2007-2009) was performed at a tertiary care pediatric academic hospital. Readmitted at-risk patients were grouped by timing of readmission, and a sample of nonreadmitted patients was randomly selected. Early readmissions were compared to late readmissions and to nonreadmissions.

RESULTS

Of 3805 eligible patients, 3.9% had an unplanned PICU readmission with almost half occurring within 48 hours. Median times to readmission were 21.5 hours (early) and 7 days (late). Compared with late readmissions, early readmissions were more often admitted from and transferred to a surgical service, transferred on a weekend, and readmitted with the same primary diagnosis. Compared with nonreadmitted patients, independent risk factors for early readmission were admission source and respiratory support at PICU transfer. Readmitted patients had longer total PICU and hospital lengths of stay than nonreadmitted patients. Late readmissions had a higher mortality than early readmissions.

CONCLUSIONS

Patients requiring an unplanned PICU readmission had worse outcomes than those without a readmission. Future studies should focus on identifying modifiable risk factors for targeted interventions.

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.

Homeward bound: an analysis of patients discharged home from an oncologic intensive care unit

PURPOSE

The objectives of our study were to evaluate the characteristics and outcomes of patients discharged home directly from an oncologic intensive care unit (ICU) and their 30-day hospital readmission patterns.

MATERIALS AND METHODS

We retrospectively reviewed ICU discharges over 3 years (2008-2010) and identified patients who were discharged directly home. Demographic, clinical, ICU discharge, and 30-day hospital readmission and mortality rates were analyzed.

RESULTS

Ninety-five patients (3.6%) were discharged home directly from the ICU (average annual rate of 3.9%). ICU diagnoses primarily included respiratory insufficiency, sepsis, cardiac syndromes, and gastrointestinal bleeding. Home discharge occurred most commonly between Thursday and Saturday. Five (5.3%) patients, including 2 hospice patients, died within 30 days of ICU home discharge. Thirty (31.6%) patients were readmitted within 30 days of discharge. The unplanned 30-day readmission rate was 23.2% (22/95) with a median time to hospital readmission of 13 (8-18) days. Most (64%) of the unplanned readmissions were related to the initial ICU admission.

CONCLUSIONS

Home discharge of ICU patients at our institution is infrequent but consistent. Almost one third of these patients were readmitted to the hospital within 30 days. Enhancements to the ICU home discharge process may be required to ensure optimal post-ICU care.

The epidemiology of intensive care unit readmissions in the United States

RATIONALE

The incidence of intensive care unit (ICU) readmissions across the United States is unknown.

OBJECTIVES

To determine incidence of ICU readmissions in United States hospitals, and describe the distribution of time between ICU discharges and readmissions.

METHODS

This retrospective cohort study used 196,202 patients in 156 medical and surgical ICUs in 106 community and academic hospitals participating in Project IMPACT from April 1, 2001, to December 31, 2007. We used mixed-effects logistic regression, adjusting for patient and hospital characteristics, to describe how ICU readmission rates differed across patient types, ICU models, and hospital types.

MEASUREMENTS AND MAIN RESULTS

Measurements consisted of 48- and 120-hour ICU readmission rates and time to readmission. A total of 3,905 patients (2%) were readmitted to the ICU within 48 hours, and 7,171 (3.7%) within 120 hours. In adjusted analysis, there was no difference in ICU readmissions across patient types or ICU models. Among medical patients, those in academic hospitals had higher odds of 48- and 120-hour readmission than patients in community hospitals without residents (1.51 [95% confidence interval, 1.12-2.02] and 1.63 [95% confidence interval, 1.24-2.16]). Median time to ICU readmission was 3.07 days (interquartile range, 1.27-6.58). Closed ICUs had the longest times to readmission (3.55 d [interquartile range, 1.42-7.50]).

CONCLUSIONS

Approximately 2% and 4% of ICU patients discharged to the ward are readmitted within 48 and 120 hours, within a median time of 3 days. Medical patients in academic hospitals are more likely to be readmitted than patients in community hospitals without residents. ICU readmission rates could be useful for policy makers and investigations into their causes and consequences.