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Original Investigation |

Use of Intensive Care Units for Patients With Low Severity of Illness FREE

Gary E. Rosenthal, MD; Carl A. Sirio, MD; Laura B. Shepardson, MS; Dwain L. Harper, DO; Armando J. Rotondi, PhD; Gregory S. Cooper, MD
[+] Author Affiliations

From the Divisions of General Internal Medicine (Dr Rosenthal) and Gastroenterology (Dr Cooper) and the Program in Health Care Research (Drs Rosenthal and Cooper and Ms Shepardson), Cleveland Veterans Affairs Medical Center and University Hospitals of Cleveland, the Department of Medicine, Case Western Reserve University School of Medicine (Drs Rosenthal and Cooper), and Quality Information Management Corporation, Cleveland Health Quality Choice Coalition (Dr Harper), Cleveland, Ohio; and the Health Evaluation Systems Delivery Team, Departments of Anesthesiology and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pa (Drs Sirio and Rotondi).


Arch Intern Med. 1998;158(10):1144-1151. doi:10.1001/archinte.158.10.1144.
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Objective  To determine variations among hospitals in use of intensive care units (ICUs) for patients with low severity of illness.

Design  Retrospective cohort study.

Setting  Twenty-eight hospitals with 44 ICUs in a large metropolitan region.

Patients  Consecutive eligible patients (N=104487) admitted to medical, surgical, neurological, or mixed medical-surgical ICUs from March 1, 1991, to March 31, 1995.

Outcome Measures  The predicted risk of in-hospital death for each patient was assessed using a validated method that is based on age, ICU admission source, diagnosis, severe comorbid conditions, and abnormalities in 17 physiologic variables. Admissions were classified as low severity if the patient's predicted risk of death was less than 1%. In a subset of 12929 consecutive patients, use of 19 specific interventions typically delivered in ICUs was examined.

Results  Twenty thousand four hundred fifty-one admissions (19.6%) were categorized as low severity, including 23.6% of postoperative and 16.9% of nonoperative admissions. Alcohol and other drug overdoses accounted for 40.2% of nonoperative low-severity admissions; laminectomy and carotid endarterectomy accounted for 52.3% of postoperative low-severity admissions. Mortality among patients with low-severity illness was 0.3%, and only 28.6% received an ICU-specific intervention during the first ICU day. Although mean ICU length of stay was shorter (P<.001) in low-severity admissions (2.2 vs 4.7 days in nonoperative and 2.4 vs 4.2 days in postoperative admissions), low-severity admissions accounted for 11.1% of total ICU bed days. Rates of low-severity admissions varied (P<.001) across hospitals, ranging from 5% to 27% for nonoperative and 9% to 68% for postoperative admissions.

Conclusions  A large proportion of patients admitted to the ICU have a low probability of death and do not receive ICU-specific interventions. Rates of low-severity admissions varied among hospitals. The development and implementation of protocols to target ICU care to patients most likely to benefit may decrease the number of low-severity ICU admissions and improve the cost-effectiveness of ICU care.

Figures in this Article

NUMEROUS studies performed during the last 2 decades suggest that a substantial proportion of medical care is inappropriate or of questionable value.16 These results, combined with the increasing penetration of managed care and desire by payers to decrease costs, have spawned aggressive efforts to manage use more effectively through review programs and case management. An important focus of most efforts has been the use of high-cost clinical services, such as coronary artery revascularization,7,8 and high-cost delivery settings, such as hospitals.9

Within hospitals, a major source of expenditures is the intensive care unit (ICU).10,11 The ICU typically provides levels of care and clinical services (eg, mechanical ventilation and hemodynamic monitoring) that are unavailable in other patient care areas. Although the delineation of care that can be provided inside and outside the ICU is clear in most hospitals, it is unclear what types of patients are most likely to benefit from ICU care. Indeed, few validated clinical criteria for ICU admission exist.12 In the absence of such information, it is reasonable to expect variation in the use of ICUs. However, few empirical data exist.13,14

We examined variations in severity of illness of patients admitted to ICUs in a single metropolitan region. For each patient, a standard set of clinical information was collected that enabled us to quantify the risk of in-hospital death. Although we were unable to directly examine the appropriateness of each ICU admission, we were able to identify patients with low severity of illness (ie, patients in whom the likelihood of death was <1%) and in whom the benefit of ICU admission may have been minimal. Our primary objective was to determine the degree to which rates of low-severity admissions varied across hospitals. In addition, we sought to identify diagnoses that accounted for substantial proportions of low-severity admissions.

HOSPITALS

We conducted this study in 38 ICUs in 28 hospitals in northeast Ohio. All hospitals were participants in Cleveland Health Quality Choice, a regional program to examine hospital performance.15 Nineteen of these ICUs were mixed medical-surgical units; 8 were medical; 8 were surgical; and 3 were neurological and/or neurosurgical. Thirteen additional ICUs that specialized in coronary care (n=11) or cardiovascular surgery (n=2) were excluded from the study, per Cleveland Health Quality Choice protocols. Eight of the 28 hospitals had more than 1 ICU included in the analysis. The mean number of beds (excluding "stepdown" beds) of study ICUs was 16 (range, 4-42). Five hospitals that were members of the Council of Teaching Hospitals of the Association of American Medical Colleges were classified as major teaching hospitals, and 6 additional hospitals with 1 or more allopathic (n=4) or osteopathic (n=2) residency training programs were classified as minor teaching hospitals.10

PATIENTS

The eligible sample included 136491 consecutive patients ages 16 years or older admitted to study ICUs from March 1, 1991, to March 31, 1995. The following patients were ineligible for the study: (1) patients with burn injuries, because they were preferentially admitted to a single hospital; (2) patients admitted to the ICU solely for hemodialysis, because many hospitals had dedicated dialysis units and would not admit such patients to ICUs; (3) patients boarded in the ICU for less than 4 hours following a surgical procedure; and (4) patients who died within the first hour after ICU admission or within the first 4 hours after admission to the ICU in cardiopulmonary arrest, because outcomes in such patients may be less attributable to quality of care. Of the eligible sample, 24072 patients with diagnoses that would be managed in coronary care or cardiovascular surgery units (acute myocardial infarction or chest pain, n=10468; unstable angina, n=7468; cardiac arrhythmias, n=4047; and coronary artery bypass, cardiac valve, or heart transplant surgery, n=2089) were excluded from analysis because admissions to such units were ineligible. These patients may also be admitted to ICUs for cardiac monitoring, independent of acute physiologic abnormalities. In addition, 7316 patients who were readmitted to an ICU during a single episode of hospitalization and 616 patients (0.5% of eligible sample) with missing severity of illness or admission diagnosis information were also excluded, resulting in a final study sample of 104487.

DATA

Data were abstracted from patients' ICU medical records on standard forms and included age, sex, admission source, dates of ICU and hospital admission and discharge, vital status at ICU and hospital discharge, comorbid conditions, ICU admission diagnosis, and the most abnormal value during the first 24 hours of ICU admission for 17 specific physiologic variables (ie, temperature; heart rate; respiratory rate; blood pressure; hematocrit; white blood cell count; serum levels of sodium, albumin, bilirubin, glucose, blood urea nitrogen, and creatinine; urine output; arterial oxygen and carbon dioxide tensions; arterial pH; and abbreviated Glasgow Coma Score). Physiologic variables with missing data were assumed to be within the normal range.16 However, a minimum of 9 physiologic measurements were required for inclusion in the analysis. Source of ICU admission was classified into the following 8 mutually exclusive categories: operating room, recovery room, emergency department, hospital ward, another ICU, another acute care hospital (hospital ward or ICU), home or subacute or chronic care facility, and non-ICU holding area (eg, observation bed). Primary diagnoses prompting admission to the ICU were classified into 76 categories, based on a previously developed taxonomy16; 31 of the diagnoses were considered postoperative (ie, the patient was admitted to the ICU after undergoing a surgical procedure during the index hospitalization [postoperative admission]), and 45 were considered nonoperative (ie, nonoperative admission).

In addition, for 12929 consecutive patients admitted from January 1 through June 31, 1994, information was collected on the use of 19 interventions during the first day of care that are typically delivered in ICUs and for which patients are often admitted to ICUs. The 3 general types of interventions consisted of mechanical ventilation or tracheal intubation, invasive monitoring or treatment procedures (ie, intra-arterial or pulmonary artery pressure monitoring, cardiac pacing, electrical cardioversion, left-ventricular assist devices, pericardiocentesis, urgent hemodialysis, tamponade of gastric or esophageal varices, and ventriculostomy), and pharmacologic and other therapies (ie, arterial drug infusion; intravenous infusion of vasoactive drugs, antiarrhythmic and thrombolytic agents, anticonvulsants, or mannitol hexanitrate; rapid blood transfusions or intravenous fluid replacement; barbiturate anesthesia; and intravenous treatment of acid-base abnormalities).

SEVERITY OF ILLNESS

Measurement of admission severity of illness was based on the Acute Physiology and Chronic Health Evaluation (APACHE) III method.16 For each patient, an APACHE III Acute Physiology Score was determined on the basis of age, presence of 7 severe comorbid conditions (acquired immunodeficiency syndrome, hematologic malignant neoplasms, metastatic cancer, use of immunosuppressive agents, hepatic failure, lymphoma, and cirrhosis), and abnormalities in the 17 physiologic variables. Scores have a possible range of 0 to 299 and were determined using previously validated weights for each variable.16

A predicted risk of in-hospital death was then determined using a multivariable logistic regression model that included the APACHE III Acute Physiology Score, ICU admission source (expressed as 7 indicator variables), and ICU admission diagnosis (expressed as 75 indicator variables). To improve model fit (ie, calibration), APACHE III Acute Physiology Scores were represented in the model as a continuous variable and as 2 additional indicator variables for scores that were less than 20 or greater than 150. Other representations of this score (ie, logarithmic or exponential transformation) were tested but did not improve model discrimination or calibration. Discrimination of the final logistic regression model, as assessed by a receiver operating characteristic curve area of 0.901, was nearly identical to the discrimination initially reported for the APACHE III method.16

Several explicit steps were taken to ensure data quality.15 First, guidelines for abstraction of each variable were developed to be consistent with previous applications of the APACHE III method.17 Second, data abstractors were required to attend initial training sessions and semi-annual training updates that addressed frequently identified issues and questions. Third, electronic edits were performed to identify variables with out-of-range values or patients with discrepant data (eg, patients with a diagnosis of shock and normal vital signs). Such records were then reviewed by a registered nurse, who requested that hospitals resubmit data when indicated. Finally, a random sample of 20 to 30 patient records from each hospital were independently reabstracted semiannually. Comparisons of originally abstracted and reabstracted data revealed no evidence of systematic misclassification.15

ANALYSIS

Patients in whom the predicted risk of death was 1% or lower were classified as having low severity of illness. Differences between these and other patients were examined using the χ2 test or the Wilcoxon signed rank test. Variability in rates of low-severity admissions across individual hospitals was examined by comparing rates in individual hospitals to the rate in all patients using a 1-sample test of proportions; a criterion of P<.001 was used to indicate statistical significance because of the large number of observations per hospital and the multiple number of hospital comparisons. Separate analyses were conducted in postoperative and nonoperative admissions. In addition, the correlation between the rate of low-severity admissions in each hospital and the standardized mortality ratio (SMR) was determined. The SMR is a widely used measure of hospital performance18,19 that is equal to the number of actual deaths divided by the number of deaths predicted by the risk-adjustment model. Standardized mortality ratios of greater than 1.0 denote higher than expected mortality (ie, worse performance), whereas SMRs of less than 1.0 denote lower than expected mortality (ie, better performance). Finally, in patients with ICU treatment data, the use of specific interventions in low-severity and other admissions was compared using the χ2 statistic. Unless otherwise indicated, data are given as mean±SD.

The mean age of the 104487 study patients was 61.9±18.1 years, and 52.0% were male. Of the study patients, 42.1% of patients were admitted to the ICU from the operating room or recovery room; 37.1%, from the emergency department; and 11.7%, from another hospital ward. The remaining patients were admitted from another ICU or another acute care hospital or were direct admissions. The mean APACHE III Acute Physiology Score was 48.6±28.2, and the mean hospital and ICU stays were 12.6±13.2 and 4.1±5.2 days, respectively. Observed mortality was 11.8%. Of the 12360 patients who died, 55.4% died in the ICU during initial ICU admissions.

Among nonoperative admissions (n=62771), the 10 most common ICU admission diagnoses included congestive heart failure (13.0%), alcohol and other drug overdoses (7.5%), hemorrhagic peptic ulcer disease (6.3%), nonhemorrhagic stroke (4.7%), bacterial or viral pneumonia (4.4%), chronic obstructive lung disease (4.4%), head trauma (4.0%), nonurinary tract sepsis (3.8%), seizure (3.0%), and postcardiac arrest (2.7%). Among postoperative admissions (n=41716), the 10 most common diagnoses included carotid endarterectomy (11.9%), peripheral vascular disease with bypass (9.5%), vertebral laminectomy (7.7%), gastrointestinal tract neoplasm without obstruction or perforation (6.8%), peripheral vascular disease without bypass (6.1%), lung neoplasm (5.2%), gastrointestinal tract obstruction (4.8%), craniotomy for neoplasm (4.0%), multiple-site trauma excluding head (3.9%), and elective abdominal aneurysm repair (3.8%).

The mean predicted risk of in-hospital death in all patients was 11.9% and was nearly identical to the observed rate of death. Distributions of predicted risks of death for nonoperative and postoperative admissions are shown in Figure 1. Patients with low-severity illness accounted for 19.6% of all admissions, including 23.6% of postoperative and 16.9% of nonoperative admissions. Rates of low-severity admissions declined somewhat during the 4 years in which data were collected (21.2%, 19.6%, 18.9%, and 18.8% in years 1 to 4, respectively; P<.001).

Place holder to copy figure label and caption
Figure 1.

Distribution of predicted risks of in-hospital death in nonoperative and postoperative admissions. Predicted risks of death were estimated from a multivariable model that included Acute Physiology and Chronic Health Evaluation III Acute Physiology Score, intensive care unit admission source, and admission diagnosis.

Graphic Jump Location

The mean predicted risk of death among low-severity admissions was 0.5% and was somewhat higher than the actual death rate of 0.3% (P<.001 [χ2]; 1 df). Of the 62 patients with low severity of illness who died, only 13 (ie, 0.06% of all low-severity admissions) died during the first 4 days following ICU admission. Compared with other patients, patients admitted to the ICU with low severity of illness were younger and more likely to be male (Table 1). In addition, patients with low severity of illness had shorter ICU and hospital lengths of stay. Nonetheless, low-severity admissions accounted for 11.1% of total ICU bed days and 10.3% of total hospital bed days. Among nonoperative admissions, alcohol and other drug overdoses accounted for 40.2% of all low-severity admissions. Indeed, 90.0% of all overdose admissions were classified as low severity; among these patients, the mean length of ICU stay was 2.0±1.6 days, and only 9 patients (0.2%) died. The following 6 other diagnoses accounted for an additional 30.6% of nonoperative low-severity admissions: multiple-site trauma (excluding head or brain) (7.6%), diabetic ketoacidosis (6.7%), head or brain trauma (5.8%), seizures (4.4%), asthma (3.1%), and hypertension (3.0%). Among postoperative admissions, the following 2 diagnoses accounted for 52.3% of low severity admissions: carotid endarterectomy (29.4%) and vertebral laminectomy (22.8%). The following 3 other diagnoses accounted for an additional 19.7% of postoperative low-severity admissions: urinary tract neoplasms (9.3%), peripheral arterial bypass (5.9%), and craniotomy for neoplasm (4.5%).

Table Graphic Jump LocationTable 1. Demographic and Clinical Differences Between Low-Severity and Other Admissions*

Substantial variability in rates of low-severity admission was observed across the 28 hospitals (Figure 2, top and bottom). For nonoperative admissions, rates of low-severity illness ranged from 5.2% to 27.5%; in 23 hospitals, rates were significantly (P<.001) higher or lower than the overall population rate of 16.9%. Even after excluding admissions for alcohol and other drug overdoses, hospital rates ranged from 4.9% to 16.6%, and 14 hospitals had rates significantly higher or lower than the overall rate of 10.9%. For postoperative admissions, rates ranged from 9.4% to 68.0%; in 15 hospitals, rates were significantly higher or lower than the overall rate of 23.6%. Hospital rates in nonoperative and postoperative admissions were moderately correlated (Pearson correlation coefficient, 0.43; P=.02). In addition, variability existed according to teaching status (Figure 2, top and bottom). For example, the mean rate of low-severity admissions was lower in the 5 major teaching hospitals than in the 23 minor teaching and nonteaching hospitals for nonoperative (11.0% vs 18.5%; P<.001) and postoperative (17.7% vs 24.5%; P<.001) admissions. However, mean rates were similar in the 6 minor teaching and 17 nonteaching hospitals (21.4% vs 18.3%, respectively [P=.28], for nonoperative admissions; 25.8% vs 23.9%, respectively [P=.86], for postoperative admissions).

Place holder to copy figure label and caption
Figure 2.

Rates of low-severity intensive care unit admissions (ie, patients with a predicted risk of death of <1%) in individual hospitals for nonoperative (top) and postoperative admissions (bottom). Asterisk indicates hospitals with rates significantly (P<.001) lower or higher than the overall sample rate; horizontal dashed lines, overall rates of low-severity admissions (16.9% for nonoperative and 23.6% for postoperative admissions).

Graphic Jump Location

Correlations between rates of low-severity ICU admission in individual hospitals and hospital SMRs were not significant for nonoperative (R=0.13; P=.50) or postoperative (R=0.16; P=.41) admissions. Thus, hospitals with higher proportions of low-severity admissions did not have lower SMRs.

Finally, in analyses of the 12929 patients for whom data were available on the use of ICU-specific interventions, use was substantially lower in low-severity admissions (Table 2). Nevertheless, 28.6% of patients with low severity of illness received 1 or more ICU-specific interventions, including 45.3% of postoperative and 12.1% of nonoperative admissions. The most common intervention was intra-arterial pressure monitoring, which was used in 23.1% of patients with low severity of illness. Excluding intra-arterial pressure monitoring, only 12.1% of postoperative and 11.4% of nonoperative low-severity admissions received 1 or more other interventions.

Table Graphic Jump LocationTable 2. Use of ICU-Specific Treatments in 12929 Patients Admitted From January 1 Through June 31, 1994*

The costs associated with intensive care represent a major component of the United States' health care expenditures, accounting for nearly 1% of total gross domestic product.11,19 However, few previous studies have examined how hospitals use ICU beds or whether such practices vary across individual hospitals. Examining consecutive ICU admissions during 4 years to 28 hospitals in a large metropolitan region, we found that ICUs often are used for patients in whom the risk of death is exceedingly low. Nearly one fifth (19.6%) of the patients in our sample had a predicted risk of death of less than 1%, whereas 40.0% had a predicted risk of death of less than 2%. Although we did not directly measure the appropriateness of ICU admission in these patients, their low in-hospital mortality (particularly during the first 4 days of hospitalization) suggests that many patients with low severity of illness may be treated effectively in non-ICU settings.

Although analyses in a subset of the study sample indicated that 28.6% of patients with low severity of illness received 1 or more interventions that are typically delivered in ICUs, the larger proportion of such patients had low severity of illness and did not receive any active ICU interventions. Moreover, nearly 62.0% of all patients with low severity of illness who received interventions received only a single intervention (intra-arterial blood pressure monitoring), for which effectiveness is poorly studied.

We further found that rates of low-severity ICU admissions exhibited substantial variability across hospitals: roughly 5-fold for nonoperative and 7-fold for postoperative admissions. Results were generally similar if different criteria for low severity were applied. For example, if admissions were classified as low severity when the patient's predicted risk of death was less than 2%, hospital variation in low-severity admissions was nearly 4-fold for nonoperative (12%-46%) and postoperative (24%-83%) admissions.

Two operative (carotid endarterectomy and vertebral laminectomy) and 1 nonoperative (alcohol and other drug overdose) diagnosis accounted for almost half of the low-severity ICU admissions. In patients with carotid endarterectomy, close observation of postoperative blood pressure and neurological status is recommended20,21 because of the incidence of hemodynamic instability22 and postoperative stroke.23 However, no studies have established the effectiveness of the ICU in such patients or the optimal period of ICU observation. Following laminectomy, routine neurological monitoring in an ICU is frequently performed, although the benefit of this practice has been questioned.24 Admission to the ICU may be used in certain institutions to ensure more vigilant neurological observation by nursing personnel.

In patients with drug overdose, routine ICU monitoring has been recommended.25 However, several studies have shown that most patients with overdoses do not require ICU care and that patients at risk for complications can be identified on the basis of simple clinical findings such as electrocardiographic changes, airway compromise, admission vital signs, level of consciousness, and abnormal results of arterial blood gas studies.2628 Although some low-severity ICU admissions may be indicated, formal assessment of the benefits of ICU care in patients with these diagnoses is needed. The results of such analyses would likely have important implications for ICU use.

Although variation in use of ICUs has been poorly studied, our findings appear consistent with those of 2 earlier studies by Knaus et al.18,19 In an analysis of ICU admissions in 1979 to 1981,18 mean predicted risks of death ranged from 10% to 43% across 13 tertiary hospitals; in a follow-up study a decade later of ICU admissions in 40 hospitals,19 the range in predicted risk of death was nearly identical. We suspect that both studies probably would have found substantial hospital variation in the proportion of low-severity admissions. Indeed, in a further analysis of data from the second study, the proportion of admissions who did not receive active ICU treatment (ie, interventions typically delivered in ICUs) varied across hospitals; such patients accounted for less than 20% of ICU admissions at 5 hospitals, 20% to 40% of admissions at 20 hospitals, and more than 40% of admissions at 15 hospitals.28

Our results are also consistent with those of numerous studies demonstrating regional variations in rates of hospital admission, surgery, and physician expenditures16,2931 or that a substantial proportion of hospital admissions may be inappropriate on clinical grounds.3238 For example, the Rand Health Insurance Study33 found that 23% of medical and surgical admissions from 1974 to 1982 were inappropriate, and that rates of inappropriate admissions varied from 10% to 35% across the 6 US regions studied. In addition, studies of adult populations that were conducted before and after the introduction of prospective payment in 1983 found rates of inappropriate hospitalizations that ranged from 6% to 19%,32 whereas studies of children have found rates of inappropriate admissions and/or hospital days ranging from 20% to 30%.3538

Our findings in a contemporary, community-based cohort indicate that a substantial proportion of patients admitted to ICUs have a very low likelihood of death and may not require ICU care. Our findings further indicate that, even within a single geographic region, substantial variability exists in how ICUs are used in individual hospitals. Although such variability may, in part, be driven by unmeasured clinical differences, differences in physician and hospital practices probably are a much more important factor.32,39 Hospitals may have very different thresholds for admitting patients to ICUs that may reflect differences in administrative policies or levels of staffing on non-ICU wards. For example, the lower rate of low-severity ICU admissions that we observed in major teaching hospitals suggests that the availability of house staff may allow these hospitals to effectively treat sicker patients in non-ICU settings. Alternatively, differences between hospitals may reflect differences in ICU triage pressure due to hospital occupancy and capacity.40,41 Hospitals may preferentially admit patients to the ICU to maintain high ICU occupancy. Although such practices may serve to maintain clinical skills of ICU practitioners or reassure staff that ICU resources are available, they also may lead to higher hospital costs without discernible impact on patient outcomes. Indeed, previous studies suggest the potential cost savings of treating low-risk patients in non-ICU settings.4244

In interpreting our findings, several potential methodological limitations should be considered. First, we did not examine directly the indication for ICU admission or the clinical appropriateness of each admission. Some patients may have been admitted to receive monitoring and/or treatment that could only be provided in ICUs. However, analyses in a subset of study patients indicated that most patients with low severity of illness did not receive ICU-specific interventions. Moreover, other studies that examined use of ICU-specific interventions4547 have found that patients with lower severity of illness have a lower likelihood of receiving such treatment during their ICU stays. For example, Zimmerman et al46 found that Acute Physiology Scores on admission were directly related to the use of ICU interventions by the second day, and that patients with lower scores were more likely to be candidates for intermediate care units.46

Second, our assessments of severity of illness and risk of in-hospital death were based on a normative analysis of patients admitted to the ICU (ie, patients were identified as having a low risk of death because the actual rate of death was low). Thus, our analysis would overestimate the true proportions of low-severity admissions if admission to the ICU led to lower mortality rates. However, the effectiveness of ICU care in patients with low severity of illness is unknown, and several studies indicate that higher-intensity care may be associated with poorer hospital outcomes.48,49 In addition, our assessments of severity incorporated physiologic abnormalities during the first 24 hours of ICU admission. Assessments may have differed if only data available at the time of admission were used. However, previous studies have shown that APACHE III scores based on ICU admission data are generally similar,16 and that admission values of the APACHE III physiologic variables represent the most abnormal value nearly 90% of the time.50 Thus, it is likely that most patients who were classified as having low severity of illness in our study would have been so classified if APACHE III scores were based on admission values.

Third, the scope and definition of intensive care probably varied across hospitals. It is also likely that some hospitals had the capacity to provide some intensive care in non-ICU settings. Such organizational differences may be partly responsible for some of the variation in low-severity admissions across hospitals. Nonetheless, there is also substantial overlap across hospitals in the types of services that would be provided only in an ICU (eg, pulmonary artery pressure monitoring and use of certain vasoactive medications), and admission to an ICU has explicit implications with respect to hospital charges.

Fourth, although low-severity admissions accounted for an important proportion of total days of care, direct estimates of hospital and ICU costs were unavailable. Thus, implications of our findings on actual resource use are uncertain. Lastly, we had no information on health insurance and, as a result, were unable to examine potentially important effects of managed care and captitation on ICU admission practices.51,52

Results of our study may have important implications for improving hospital efficiency and decreasing health care costs. The degree of variation across hospitals suggests that decisions to admit patients to ICUs may be subject to much discretion.53 Because the benefits of ICU care in such patients are unproven, efforts to decrease variability, such as explicit clinical criteria for ICU admission and decision aids to identify patients with low severity of illness that are based on quantitative measures, would be expected to improve the cost-effectiveness of care. The use of similar methods in patients presenting for evaluation of chest pain indicates that patients who are unlikely to benefit from ICU care can be successfully identified and triaged to lower-cost settings.54 Moreover, the small number of diagnoses that accounted for a major proportion of the low-severity admissions in our analysis indicates that methods could be targeted to a few diagnoses and still have a substantial effect. Such highly focused methods may be more effective than previously developed generic guidelines12 that have identified general classes of patients who should be considered ICU candidates. Future studies should examine the impact of such protocols on patient outcomes and the cost of ICU care.

In addition, identification of factors responsible for variations in these admissions may suggest mechanisms for more efficient hospital triage and management strategies. Such factors are likely to include overestimation of risk in patients with low severity of illness,55,56 use of imprecise heuristics,57 fear of litigation from not admitting patients to the ICU if an adverse event occurred, and local practice patterns.

Our findings provide indirect evidence that a large proportion of ICU admissions are discretionary in nature and may be clinically unnecessary or inappropriate. Given the increasing proportion of hospital care being financed through capitated arrangements,58 hospitals and physicians have new incentives to develop and implement clinical criteria to decrease variation in ICU admission practices by identifying patients in whom ICU care may not be effective. The impact of such changes in practices on the cost and quality of care should be evaluated.

Accepted for publication September 30, 1997.

Supported by a Career Development Award from the Health Services Research and Development Service, US Department of Veterans Affairs, Washington, DC (Dr Rosenthal), and in part by Clinical Research Training Grant 97-047-01-PBR for Junior Faculty from the American Cancer Society, Atlanta, Ga (Dr Cooper).

Corresponding author: Gary E. Rosenthal, MD, Case Western Reserve University School of Medicine, Room WG-37, 10900 Euclid Ave, Cleveland, OH 44106-4961.

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Link to Article
Pearce  WH Perioperative monitoring and intensive care of patients undergoing major vascular surgery. Rutherford  RBed.Vascular Surgery. 3rd ed. Philadelphia, Pa WB Saunders Co1989;364- 374
Teplick  RCaldera  DLGilbert  JPCullen  DJ Benefit of elective intensive care admission after certain operations. Anesth Analg. 1983;62572- 577
Link to Article
Towne  JBBernhard  VM The relationship of postoperative hypertension to complications following carotid endarterectomy. Surgery. 1980;88575- 580
Turnipseed  WDBerkoff  HABelzer  FO Postoperative stroke in cardiac and peripheral vascular disease. Ann Surg. 1980;192365- 368
Link to Article
Simeone  FADillin  WH Surgical management of cervical myelopathy: laminectomy. Rothman  RHSimeone  FAeds.The Spine. 3rd ed. Philadelphia, Pa WB Saunders Co1992;625- 630
Linden  CH General considerations in the evaluation and treatment of poisoning. Rippe  JMIrwin  RSAlpert  JSFink  MPeds.Intensive Care Medicine. 2nd ed. Boston, Mass Little Brown & Co Inc1991;1093- 1114
Brett  ASRothschild  NGray  RPerry  M Predicting the clinical course in intentional drug overdose. Arch Intern Med. 1987;147133- 137
Link to Article
Leiken  JBHanashiro  PK Poisonings. Parillo  JEBone  RCeds.Critical Care Medicine Principles of Diagnosis and Management. St Louis, Mo Mosby–Year Book Inc1995;1383- 1414
Zimmerman  JEWagner  DPKnaus  WAWilliams  JFKolakowski  DDraper  EA The use of risk predictions to identify candidates for intermediate care units: implications for intensive care utilization and cost. Chest. 1995;108490- 499
Link to Article
Gittelsohn  APowe  NR Small area variations in health care delivery in Maryland. Health Serv Res. 1995;30295- 317
Wennberg  JEFreeman  JLShelton  RMBubolz  TA Hospital use and mortality among Medicare beneficiaries in Boston and New Haven. N Engl J Med. 1989;3211168- 1173
Link to Article
Restuccia  JSchwartz  MAsh  APayne  S High hospital admission rates and inappropriate care. Health Aff (Millwood). 1996;15156- 163
Link to Article
Payne  SMC Identifying and managing inappropriate hospital utilization. Health Serv Res. 1987;22709- 769
Sui  ALSonnenberg  FAManning  WG  et al.  Inappropriate use of hospitals in a randomized trial of health insurance plans. N Engl J Med. 1986;3151259- 1266
Link to Article
Kemper  KJ Medically inappropriate hospital use in a pediatric population. N Engl J Med. 1988;3181033- 1037
Link to Article
Soulen  JLDuggan  AKDeAngellis  CD Identification of potentially avoidable pediatric hospital use: admitting physician judgment as a complement to utilization review. Pediatrics. 1994;94421- 424
Gloor  JEKissoon  NJoubert  GI Appropriateness of hospitalization in a Canadian pediatric hospital. Pediatrics. 1993;9170- 74
Smith  HESheps  SMatheson  DS Assessing the utilization of in-patient facilities in a Canadian pediatric hospital. Pediatrics. 1993;92587- 593
Havens  PLButler  JCDay  SEMohr  BADavis  JPChusid  MJ Treating measles: the appropriateness of admission to a Wisconsin children's hospital. Am J Public Health. 1993;83379- 384
Link to Article
Stafford  RS The impact of nonclinical factors on repeat cesarean section rates. JAMA. 1991;26559- 63
Link to Article
Kalb  PEMiller  DH Utilization strategies for intensive care units. JAMA. 1989;2612389- 2395
Link to Article
Selker  HPGriggith  JLDorsey  FJD'Agostino  RB How do physicians adapt when the coronary care unit is full? JAMA. 1987;2571181- 1185
Link to Article
Goldman  LCook  EFBrand  DA  et al.  A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med. 1988;318797- 803
Link to Article
Gaspoz  JMLee  THWeinstein  MC  et al.  Cost-effectiveness of a new short-stay unit to "rule out" acute myocardial infarction in low-risk patients. J Am Coll Cardiol. 1994;241249- 1259
Link to Article
Coleman  MBSirio  CAAngus  DPristas  N Estimating ICU cost savings: reducing low risk-monitored only (LRM) patients using risk adjusted hospital outcome data. Chest. 1996;1107S
Link to Article
Henning  RJMcLish  DDaly  BNearman  HFranklin  CJackson  D Clinical characteristics and resource utilization of ICU patients: implications for organization of intensive care. Crit Care Med. 1987;15264- 269
Link to Article
Zimmerman  JEWagner  DPDraper  EAKnaus  WA Improving intensive care unit discharge decisions: supplementing physician judgment with predictions of next day risk for life support. Crit Care Med. 1994;221373- 1384
Link to Article
Wagner  DPKnaus  WADraper  EA Identification of low-risk monitor admissions to medical-surgical ICUs. Chest. 1987;92423- 429
Link to Article
Udvarhelyi  ISGatsonis  CEpstein  AMPashos  CLNewhouse  JPMcNeil  BJ Acute myocardial infarction in the Medicare population: process of care and clinical outcomes. JAMA. 1992;2682530- 2536
Link to Article
Peterson  EDWright  SMDaley  JThibault  GE Racial variation in cardiac procedure use and survival following acute myocardial infarction in the Department of Veterans Affairs. JAMA. 1994;2711175- 1180
Link to Article
Knaus  WADraper  EAWagner  DPZimmerman  JE APACHE II: a severity of disease classification system. Crit Care Med. 1985;13818- 829
Link to Article
Robinson  JCGardner  LBLuft  HS Health plan switching in anticipation of increased medical care utilization. Med Care. 1993;3143- 51
Link to Article
Manning  WGLeibowitz  AGoldberg  GARogers  WHNewhouse  JP A Controlled Trial of the Effect of a Prepaid Group Practice on the Utilization of Medical Services.  Santa Monica, Calif RAND1987;
Miller  MGMiller  LSFireman  BBlack  SB Variation in practice for discretionary admissions: impact on estimates of quality of hospital care. JAMA. 1994;2711493- 1498
Link to Article
Goldman  LCook  EFJohnson  PABrand  DARouan  GWLee  TH Prediction of the need for intensive care in patients who come to the emergency department with acute chest pain. N Engl J Med. 1996;3341498- 1504
Link to Article
Knaus  WAHarrel  FE  JrLynn  J  et al.  The SUPPORT prognostic model. Ann Intern Med. 1995;122191- 203
Link to Article
McClish  DKPowell  SH How well can physicians estimate mortality in a medical intensive care unit? Med Decis Making. 1989;9125- 132
Link to Article
Dawes  RMFaust  DMeehl  PE Clinical vs actuarial judgment. Science. 1989;2431068- 1074
Link to Article
Robinson  JCCasalino  LP The growth of medical groups paid through capitation in California. N Engl J Med. 1995;3331684- 1687
Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Distribution of predicted risks of in-hospital death in nonoperative and postoperative admissions. Predicted risks of death were estimated from a multivariable model that included Acute Physiology and Chronic Health Evaluation III Acute Physiology Score, intensive care unit admission source, and admission diagnosis.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Rates of low-severity intensive care unit admissions (ie, patients with a predicted risk of death of <1%) in individual hospitals for nonoperative (top) and postoperative admissions (bottom). Asterisk indicates hospitals with rates significantly (P<.001) lower or higher than the overall sample rate; horizontal dashed lines, overall rates of low-severity admissions (16.9% for nonoperative and 23.6% for postoperative admissions).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Demographic and Clinical Differences Between Low-Severity and Other Admissions*
Table Graphic Jump LocationTable 2. Use of ICU-Specific Treatments in 12929 Patients Admitted From January 1 Through June 31, 1994*

References

Wennberg  JGittelsohn  A Small area variations in health care delivery. Science. 1973;1821102- 1108
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Wennberg  JEFreeman  JLCulp  WJ Are hospital services rationed in New Haven or over-utilized in Boston? Lancet. 1987;11185- 1189
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Roos  NPRoos  LL High and low surgical rates: risk factors for area residents. Am J Public Health. 1985;75263- 269
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Welch  WPMiller  MEWelch  HG  et al.  Geographic variation in expenditures for physicians' services in the United States. N Engl J Med. 1993;328621- 627
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Chassin  MRKosecoff  JPark  RE  et al.  Does inappropriate use explain geographic variations in the use of health care services? a study of three procedures. JAMA. 1987;2582633- 2637
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Chassin  MRBrook  RHPark  RE  et al.  Variations in the use of medical and surgical services by the Medicare population. N Engl J Med. 1986;314285- 290
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Bernstein  SJLaouri  MHilborne  LH  et al.  Coronary Angiography: A Literature Review and Ratings of Appropriateness and Necessity.  Santa Monica, Calif RAND1992;Publication JRA-03
Leape  LLHilborne  LHKahan  JP  et al.  Coronary Artery Bypass Graft: A Literature Review and Ratings of Appropriateness and Necessity.  Santa Monica, Calif RAND1991;Publication JRA-02
Inglis  ALCoast  JGray  SPeters  TJFrankel  SJ Appropriateness of hospital utilization: the reliability and validity of the intensity-severity-discharge review system in a United Kingdom acute hospital setting. Med Care. 1995;33952- 957
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American Hospital Association, Hospital Statistics, 1994.  Chicago, Ill American Hospital Association1994;
Berenson  RA Intensive Care Units (ICUs): Clinical Outcomes, Costs, and Decision Making.  Washington, DC US Congress Office of Technology Assessment1984;
Society of Critical Care Medicine Ethics Committee, Consensus statement on the triage of critically ill patients. JAMA. 1994;2711200- 1203
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Angus  DCLinde-Zwirble  WTSirio  CA  et al.  The effect of managed care on ICU length of stay: implications for Medicare. JAMA. 1996;2761075- 1082
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Sirio  CATajimi  KATase  C  et al.  A comparison of critical care in Japan and the United States. Crit Care Med. 1992;201207- 1215
Link to Article
Rosenthal  GEHarper  DL Cleveland Health Quality Choice: a model for community-based outcomes assessment. Jt Comm J Qual Improv. 1994;20425- 444
Knaus  WAWagner  DPDraper  EA  et al.  The APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized patients. Chest. 1991;1001619- 1636
Link to Article
Damiano  AMBergner  MDraper  EAKnaus  WAWagner  DP Reliability of a measure of severity of illness: acute physiology of chronic health evaluation, II. J Clin Epidemiol. 1992;4593- 101
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Knaus  WADraper  EAWagner  DPZimmerman  JE An evaluation of outcome from intensive care in major medical centers. Ann Intern Med. 1986;104410- 418
Link to Article
Knaus  WAWagner  DPZimmerman  JEDraper  EA Variations in mortality and length of stay in intensive care units. Ann Intern Med. 1993;118753- 761
Link to Article
Pearce  WH Perioperative monitoring and intensive care of patients undergoing major vascular surgery. Rutherford  RBed.Vascular Surgery. 3rd ed. Philadelphia, Pa WB Saunders Co1989;364- 374
Teplick  RCaldera  DLGilbert  JPCullen  DJ Benefit of elective intensive care admission after certain operations. Anesth Analg. 1983;62572- 577
Link to Article
Towne  JBBernhard  VM The relationship of postoperative hypertension to complications following carotid endarterectomy. Surgery. 1980;88575- 580
Turnipseed  WDBerkoff  HABelzer  FO Postoperative stroke in cardiac and peripheral vascular disease. Ann Surg. 1980;192365- 368
Link to Article
Simeone  FADillin  WH Surgical management of cervical myelopathy: laminectomy. Rothman  RHSimeone  FAeds.The Spine. 3rd ed. Philadelphia, Pa WB Saunders Co1992;625- 630
Linden  CH General considerations in the evaluation and treatment of poisoning. Rippe  JMIrwin  RSAlpert  JSFink  MPeds.Intensive Care Medicine. 2nd ed. Boston, Mass Little Brown & Co Inc1991;1093- 1114
Brett  ASRothschild  NGray  RPerry  M Predicting the clinical course in intentional drug overdose. Arch Intern Med. 1987;147133- 137
Link to Article
Leiken  JBHanashiro  PK Poisonings. Parillo  JEBone  RCeds.Critical Care Medicine Principles of Diagnosis and Management. St Louis, Mo Mosby–Year Book Inc1995;1383- 1414
Zimmerman  JEWagner  DPKnaus  WAWilliams  JFKolakowski  DDraper  EA The use of risk predictions to identify candidates for intermediate care units: implications for intensive care utilization and cost. Chest. 1995;108490- 499
Link to Article
Gittelsohn  APowe  NR Small area variations in health care delivery in Maryland. Health Serv Res. 1995;30295- 317
Wennberg  JEFreeman  JLShelton  RMBubolz  TA Hospital use and mortality among Medicare beneficiaries in Boston and New Haven. N Engl J Med. 1989;3211168- 1173
Link to Article
Restuccia  JSchwartz  MAsh  APayne  S High hospital admission rates and inappropriate care. Health Aff (Millwood). 1996;15156- 163
Link to Article
Payne  SMC Identifying and managing inappropriate hospital utilization. Health Serv Res. 1987;22709- 769
Sui  ALSonnenberg  FAManning  WG  et al.  Inappropriate use of hospitals in a randomized trial of health insurance plans. N Engl J Med. 1986;3151259- 1266
Link to Article
Kemper  KJ Medically inappropriate hospital use in a pediatric population. N Engl J Med. 1988;3181033- 1037
Link to Article
Soulen  JLDuggan  AKDeAngellis  CD Identification of potentially avoidable pediatric hospital use: admitting physician judgment as a complement to utilization review. Pediatrics. 1994;94421- 424
Gloor  JEKissoon  NJoubert  GI Appropriateness of hospitalization in a Canadian pediatric hospital. Pediatrics. 1993;9170- 74
Smith  HESheps  SMatheson  DS Assessing the utilization of in-patient facilities in a Canadian pediatric hospital. Pediatrics. 1993;92587- 593
Havens  PLButler  JCDay  SEMohr  BADavis  JPChusid  MJ Treating measles: the appropriateness of admission to a Wisconsin children's hospital. Am J Public Health. 1993;83379- 384
Link to Article
Stafford  RS The impact of nonclinical factors on repeat cesarean section rates. JAMA. 1991;26559- 63
Link to Article
Kalb  PEMiller  DH Utilization strategies for intensive care units. JAMA. 1989;2612389- 2395
Link to Article
Selker  HPGriggith  JLDorsey  FJD'Agostino  RB How do physicians adapt when the coronary care unit is full? JAMA. 1987;2571181- 1185
Link to Article
Goldman  LCook  EFBrand  DA  et al.  A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med. 1988;318797- 803
Link to Article
Gaspoz  JMLee  THWeinstein  MC  et al.  Cost-effectiveness of a new short-stay unit to "rule out" acute myocardial infarction in low-risk patients. J Am Coll Cardiol. 1994;241249- 1259
Link to Article
Coleman  MBSirio  CAAngus  DPristas  N Estimating ICU cost savings: reducing low risk-monitored only (LRM) patients using risk adjusted hospital outcome data. Chest. 1996;1107S
Link to Article
Henning  RJMcLish  DDaly  BNearman  HFranklin  CJackson  D Clinical characteristics and resource utilization of ICU patients: implications for organization of intensive care. Crit Care Med. 1987;15264- 269
Link to Article
Zimmerman  JEWagner  DPDraper  EAKnaus  WA Improving intensive care unit discharge decisions: supplementing physician judgment with predictions of next day risk for life support. Crit Care Med. 1994;221373- 1384
Link to Article
Wagner  DPKnaus  WADraper  EA Identification of low-risk monitor admissions to medical-surgical ICUs. Chest. 1987;92423- 429
Link to Article
Udvarhelyi  ISGatsonis  CEpstein  AMPashos  CLNewhouse  JPMcNeil  BJ Acute myocardial infarction in the Medicare population: process of care and clinical outcomes. JAMA. 1992;2682530- 2536
Link to Article
Peterson  EDWright  SMDaley  JThibault  GE Racial variation in cardiac procedure use and survival following acute myocardial infarction in the Department of Veterans Affairs. JAMA. 1994;2711175- 1180
Link to Article
Knaus  WADraper  EAWagner  DPZimmerman  JE APACHE II: a severity of disease classification system. Crit Care Med. 1985;13818- 829
Link to Article
Robinson  JCGardner  LBLuft  HS Health plan switching in anticipation of increased medical care utilization. Med Care. 1993;3143- 51
Link to Article
Manning  WGLeibowitz  AGoldberg  GARogers  WHNewhouse  JP A Controlled Trial of the Effect of a Prepaid Group Practice on the Utilization of Medical Services.  Santa Monica, Calif RAND1987;
Miller  MGMiller  LSFireman  BBlack  SB Variation in practice for discretionary admissions: impact on estimates of quality of hospital care. JAMA. 1994;2711493- 1498
Link to Article
Goldman  LCook  EFJohnson  PABrand  DARouan  GWLee  TH Prediction of the need for intensive care in patients who come to the emergency department with acute chest pain. N Engl J Med. 1996;3341498- 1504
Link to Article
Knaus  WAHarrel  FE  JrLynn  J  et al.  The SUPPORT prognostic model. Ann Intern Med. 1995;122191- 203
Link to Article
McClish  DKPowell  SH How well can physicians estimate mortality in a medical intensive care unit? Med Decis Making. 1989;9125- 132
Link to Article
Dawes  RMFaust  DMeehl  PE Clinical vs actuarial judgment. Science. 1989;2431068- 1074
Link to Article
Robinson  JCCasalino  LP The growth of medical groups paid through capitation in California. N Engl J Med. 1995;3331684- 1687
Link to Article

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