ORIGINAL ARTICLE
Hospital Length of Stay After Admission for Traumatic Injury in Canada A Multicenter Cohort Study Lynne Moore, PhD,∗ † Henry Thomas Stelfox, MD, PhD, FRCPC,‡ Alexis F. Turgeon, MD, MSc, FRCPC,∗ § Avery Nathens, MD, PhD,¶ Gilles Bourgeois, MD,|| Jean Lapointe, MD,|| Mathieu Gagn´e, MSc,∗ and Andr´e Lavoie, PhD||
Objective: To describe acute care length of stay (LOS) over all consecutive hospitalizations for the injury and according to level of care [intensive care unit (ICU), intermediate care, general ward], compare observed and expected LOS, and identify predictors of LOS. Background: Prolonged LOS has important consequences in terms of costs and outcome, yet detailed information on LOS after trauma is lacking. Methods: This multicenter retrospective cohort study was based on adults discharged alive from a Canadian trauma system (1999–2010; n = 126,513). Registry data were used to calculate index LOS (LOS in trauma center with highest designation level) and were linked to hospital discharge data to calculate total LOS (all consecutive hospitalizations for the injury). Expected LOS was obtained by matching general provincial discharge statistics to study data by year, age, and sex. Potential predictors of LOS were evaluated using linear regression. Results: Mean index and total LOS were 8.6 and 9.4 days, respectively. ICU, intermediate care unit, and general ward care constituted 8.9%, 2.5%, and 88.6% of total hospital days. Observed mean index and ICU LOS in our trauma patients were 2.9 and 1.3 days longer than expected LOS (P < 0.0001). The strongest determinants of index LOS were discharge destination, age, transfer status, and injury severity. Conclusions: Results suggest that acute care LOS after injury is underestimated when only information on the index hospitalization is used and that ICU or intermediate care constitute an important part of LOS. This information should be used to inform the development of an informative and actionable quality indicator. Keywords: injury, length of stay, acute care, trauma system, intensive care unit, intermediate care unit
recorded annually with 19.5$ billion in acute care hospital costs alone, representing 7% of total hospital costs.2 To improve the quality and efficiency of trauma care, information is needed on resource use. Patient-level information on the real costs of trauma care is unavailable in public health care systems, is often estimated using cost-to-charges ratios in for-profit hospitals, and is heavily influenced by nonclinical processes. Hospital length of stay (LOS) provides an interesting surrogate for resource use, which can be calculated easily using routinely collected data and is more directly actionable than information on costs. LOS has been shown to be influenced by errors in care and adverse events and has been associated with clinical process indicators.3 In addition, quality interventions have been shown to be efficient in reducing LOS3–9 and reductions in LOS lead to important cost savings.10–13 Hospital LOS has been targeted as an important metric to evaluate trauma care.14 However, detailed information on the distribution and determinants of acute care LOS and its components after admission for traumatic injury is required. This information can be used to guide the development and interpretation of a valid, actionable quality indicator based on LOS, which in turn can lead to improvements in the quality and efficiency of trauma care. The objectives of this study were to (i) describe acute care LOS after trauma over all consecutive hospitalizations related to the injury, (ii) describe LOS according to the level of care provided [intensive care unit (ICU), intermediate care unit, and general ward], (iii) compare observed LOS for trauma system admissions to expected LOS according to age-, sex-, and year-matched general provincial admissions, and (iv) identify predictors of LOS and its components.
(Ann Surg 2014;260:179–187)
E
ach year, approximately 212,000 Canadians are hospitalized after injury with associated direct health care costs of 11$ billion.1 In the United States, around 1.9 million injury hospitalizations are From the ∗ Department of Social and Preventative Medicine, Universit´e Laval, Qu´ebec, Canada; †Unit´e de traumatologie-urgence-soins intensifs, Centre de Recherche du CHU de Qu´ebec (Hˆopital de l’Enfant-J´esus), Universit´e Laval, Qu´ebec, Canada; ‡Department of Critical Care Medicine, Medicine and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; §Department of Anesthesiology, Division of Critical Care Medicine, Qu´ebec, Canada; ¶Department of Surgery, St. Michael’s Hospital, University of Toronto, Toronto; and ||Institut national d’excellence en sant´e et en services sociaux, Montr´eal, Qu´ebec, Canada. Disclosure: Canadian Institutes of Health Research: young investigator award (H.T.S. and L.M.) and research grant (L.M.; 110996); Fonds de la recherche du Qu´ebec - Sant´e: clinician-scientist award (A.F.T.). The authors declare no conflicts of interest. Reprints: Lynne Moore, PhD, Research Center of the CHU de Qu´ebec (Hˆopital de l’Enfant-J´esus), Traumatologie–Urgence–Soins Intensifs (Trauma– Emergency–Critical Care Medicine Unit), 1401, 18e rue, local H-012a, QC G1J 1Z4. E-mail: [email protected] C 2014 by Lippincott Williams & Wilkins Copyright ISSN: 0003-4932/14/26001-0179 DOI: 10.1097/SLA.0000000000000624
Annals of Surgery r Volume 260, Number 1, July 2014
METHODS Study Population This multicenter, retrospective cohort study was based on the inclusive trauma system of the province of Qu´ebec, Canada (population 8 million). The Qu´ebec trauma system was instated in 1993 and involves regionalized care from urban level I trauma centers to rural community hospitals. All level I centers are trauma teaching hospitals. Trauma center designations are based on American College of Surgeons criteria and are revised periodically with on-site visits.15 Standardized prehospital protocols ensure that major trauma cases are taken to these hospitals and standing agreements regulate interhospital transfers within the system.
Study Data Data were drawn from the Qu´ebec trauma registry. Contribution to the registry is mandatory according to the following uniform inclusion criteria: death after injury, intensive care unit admission, hospital stay for more than 2 days, or transfer from another hospital. Registry data are extracted from patient files by medical archivists who use standardized coding protocols. Anatomic injury is coded with www.annalsofsurgery.com | 179
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the Abbreviated Injury Scale (AIS) according to guidelines published by the Association for the Advancement of Automotive Medicine.16 The registry is centralized at the Quebec Ministry of Health and is subject to periodic validation. Supervision by a data coordinator, yearly on-going training, an electronic forum of coding queries, and thrice-yearly meetings with key stakeholders are used to ensure data quality. This study was based on adults (aged ≥16 years) discharged alive between 2000 and 2010 from any of the 57 adult trauma centers in the Qu´ebec trauma system for a traumatic injury that met trauma registry inclusion criteria. Patients with isolated hip fractures [defined as an AIS diagnosis code of 851808.3, 851810.3, 851812.3, or 851818.3 in patients 65 years or older with no major secondary injuries (ie, AIS > 1)], were excluded.17 Information on the number of admissions in the 12 months before the index admission and on consecutive acute care stays for the same injury was obtained by linking trauma registry data, via a unique health coverage identifier, to the provincial hospital discharge database that is completed for all hospital admissions.18 The index admission is defined as the admission to the hospital with the highest trauma designation level. Consecutive admissions to acute care stay hospitals for the same injury were identified as any admission to a short-stay hospital with a date of discharge corresponding to the index admission date (transfer-in) or a date of admission corresponded to the index discharge date (transfer-out).
Primary Outcome The primary outcome was LOS in the index hospital, calculated as the number of days between admission and discharge (index LOS). Secondary outcomes were LOS over all consecutive hospitalizations for the same injury (total LOS); LOS according to the level of inhospital care provided (ICU, intermediate care unit, general ward); and expected LOS according to age-, sex-, and year-matched general provincial admissions.
Statistical Analyses LOS has a right-skewed distribution and was therefore described and modeled using a natural-log transformation. LOS is therefore presented using geometric means, which are approximately equivalent to the median.19 Three analyses were performed. First, the distribution of LOS in the index hospital and additional LOS in transfer-in hospitals (hospitals sending patients to the index hospital) and transfer-out hospitals (hospitals receiving patients from the index hospital) was described with histograms. We then calculated the following for the whole study sample and according to strata of patient characteristics: (i) the proportion of patients with more than 1 hospital admission for the same injury and (ii) the proportion of index LOS days covered by ICU care, intermediate care, and general ward care. Second, observed mean index and ICU LOS in trauma patients was compared with expected mean index and ICU LOS according to all provincial admissions. We used estimates of mean index and ICU LOS for all hospital admissions in the province of Qu´ebec by age and sex for the administrative years 1999–2010 for comparison.20 We used all provincial nonelective admissions (all diagnoses) with an LOS more than 2 days to be comparable with patients in our trauma registry. Expected LOS was calculated by matching provincial admission LOS to study data by age, sex, and year. Third, we identified predictors of index, ICU, and intermediate care unit LOS using multilevel linear regression with a random intercept to control for hospital clusters. LOS was modeled using a natural logarithm transformation. The following independent variables were chosen a priori on the basis of factors reported in the literature 21–24 and those considered to be important by the project 180 | www.annalsofsurgery.com
steering committee: age, sex, number of comorbidities, mechanism of injury, maximum AIS score, body region of the most severe injury, Glasgow Coma Scale (GCS) score, respiratory rate (RR), systolic blood pressure (SBP), number of admissions in the 12 months before the index admission, insurance status, discharge destination, year of index admission, designation level of index trauma center, surgery, mechanical ventilation, ICU admission, and transfer status. ICU admission was not included in the model of ICU LOS, and discharge destination was not included in the models of ICU or intermediate care unit LOS. The variable “insurance status” was defined according to the principal payer for each admission among the following: provincial public health insurance [R´egie de l’Assurance maladie du Qu´ebec (RAMQ)], provincial insurance for road accidents [Soci´et´e de l’Assurance Automobile du Qu´ebec (SAAQ)], provincial insurance for work accidents [Commission de la Sant´e et de la S´ecurit´e au Travail (CSST)], and other sources (including federal government, army, and private insurance companies). Transfer status was defined as transfer-in from any acute-care hospital that had admitted the patient or not. Statistical significance was set at 5%. The relative importance of variables for predicting LOS was evaluated using Cohen’s f 2 , a measure of local effect size based on explained variation that is applicable to multilevel multivariate regression models.25,26 Cohen’s f 2 is the proportion of explained variation accounted for by the variable of interest over and above all other variables in the model. As is common in trauma registries, a high proportion of patients had missing physiological data.27 The GCS, SBP, and RR were missing for 57%, 15%, and 38% of data observations, respectively. These data were mostly missing in patients with minor extracranial injury.28 Missing data on the GCS, RR, and SBP were simulated using multiple imputation. The Markov Chain Monte Carlo method was used with a noninformative prior and a single chain to generate 5 imputes for each missing data value. The imputation model included all independent and dependant variables used in the analysis model.
Sensitivity Analyses Sensitivity analyses were performed to evaluate the robustness of results to LOS outliers and to data simulated by multiple imputations. Analyses were thus repeated with LOS truncated at 90 days.29 We then evaluated the association of GCS, RR, and SBP to LOS when observations with missing data were excluded from the multivariate linear regression model. The study was approved by the Research Ethics Committee of the CHU de Qu´ebec (Hˆopital de l’Enfant-J´esus). Analyses were performed with the Statistical Analysis System (Version 9.2: SAS Institute, Cary, North Carolina).
RESULTS Study Population The Qu´ebec trauma registry included 179,916 adults (aged ≥16 years) admitted between April 1, 1998, and March 31, 2010. Of these, 34,454 (19.2%) had isolated hip fractures, 13,572 (7.5%) died in hospital, 5184 (2.9%) resided outside the province, and 193 (0.1%) could not be linked with administrative data. The final study population therefore comprised 126,513 patients with a geometric mean index LOS of 8.6 days [95% confidence interval (CI): 8.6–8.7]. The arithmetic mean index LOS was 13.1 days (95% CI: 13.0–13.2). In the study sample, 38% of patients were 65 years or older, mean Injury Severity Score (ISS) was 10, and 24% of patients had major trauma (ISS > 12). Penetrating trauma represented only 4% of patients.
Acute Care Hospital LOS Overall, 64,262 (50.8%) patients had an index LOS of 1 week or more and 11,422 (9.0%) patients stayed in the index hospital for C 2014 Lippincott Williams & Wilkins
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Annals of Surgery r Volume 260, Number 1, July 2014
Hospital Length of Stay After Injury
FIGURE 1. Distribution of LOS in the index hospital and in transfer-in and transfer-out hospitals. more than 1 month (Fig. 1). Mean index LOS varied with patients’ sociodemographic, clinical, and nonclinical characteristics (Table 1). Mean total LOS was 0.8 days longer than mean index LOS (9.4 vs 8.6, P < 0.0001). A total of 8501 (6.7%) patients had more than 1 hospital stay related to the same injury (Table 1). Of these, 1547 patients (1.1%) were transferred to the index trauma center after being admitted to another hospital and 7143 (5.5%) were discharged from the index center to another acute care hospital. Among patients with multiple admissions for the same injury, mean LOS in the transfer-in hospital was shorter than mean index LOS (2.7 vs 8.6, P < 0.001) whereas mean LOS in the transfer-out hospital was much longer than mean index LOS (20.1 vs 8.6, P < 0.001). The proportion of patients with multiple admissions for the same injury was more than 10% for patients with Maximum AIS 5 or more and those with GCS 8 or less (Table 1). Globally, 11.4% of the index LOS was spent in ICU or intermediate care beds (Table 1). Mean ICU LOS was 3.8 days (95% CI: 3.7–3.8 days), and mean LOS in intermediate care was 4.6 days (95% CI: 4.5–4.7 days). The proportion of the index stay in an ICU bed decreased with age and the number of comorbidities, increased with injury severity and trauma center designation level, was higher for men and patients with head injuries, and decreased slightly over the study period (Table 1). The proportion of the index stay in intermediate care units increased with age and the number of comorbidities, was higher for head-trunk-spine injuries and in level I trauma centers, and increased over the study period.
Expected LOS According to General Provincial Admissions Globally, observed mean LOS in our trauma population was 2.9 days (51%) longer than expected mean LOS according to general provincial admissions (8.6 vs 5.7 days, P < 0.0001). Similarly, observed mean ICU LOS was 1.3 days (52%) longer than expected mean ICU LOS (3.8 vs 2.5 days, P < 0.0001).
model, except trauma center designation level, were statistically significant independent predictors of hospital LOS (Table 2, Fig. 2). The strongest determinants of index LOS were discharge destination (patients discharged to long-term care or rehabilitation stayed on average 5 days longer than those discharged home), age (patients aged 85 or older stayed on average 5.5 days longer than patients aged less than 55 years), transfer status (patients transferred in stayed on average 2.7 days less than direct transports), injury severity (patients with a Maximum AIS of 5 or 6 stayed on average 4.9 days longer than patients with a Maximum AIS of 1 or 2), comorbidities (patients with 3 or more comorbidities stayed on average 4.2 days longer than patients with no comorbidities), body region of the most severe injury (patients with a spine injury stayed on average 3.1 days longer than those with a lower extremity injury), and mechanical ventilation (additional mean LOS of 4.5 days). Predictors did not vary when total rather than index LOS was considered. The most important predictors of ICU stay were mechanical ventilation, injury severity, body region of the most severe injury, and surgery (Table 2, Fig. 2). Unlike index LOS, ICU LOS did vary with the designation level of the index center but did not vary with sex or year of discharge. The most important predictors of intermediate care unit LOS were age, mechanical ventilation, injury severity, and the number of comorbidities. Intermediate care unit LOS did not vary by GCS, RR, SBP, insurance status, surgery, or transfer status.
Sensitivity Analyses Truncating LOS outliers did not lead to any important change in crude or adjusted mean LOS overall or in any category of explanatory variables and had little influence on coefficients and standard errors in the multivariate linear regression model. The association between GCS/RR/SBP and LOS did not change significantly in a model restricted to observations with no missing physiological data.
DISCUSSION Predictors of Hospital LOS Collectively, predictors explained 38% of the variation in index LOS, 35% of the variation in ICU LOS, and 13% of the variation in intermediate care unit LOS. All risk factors entered into the multivariate C 2014 Lippincott Williams & Wilkins
In this multicenter retrospective cohort study, we observed that acute care LOS after traumatic injury was underestimated by 10% when only days in the index hospital were considered. In addition, stays in ICU and intermediate care units, associated with www.annalsofsurgery.com | 181
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TABLE 1. Index LOS, the Proportion of Patients With Multiple Admissions for the Same Injury, and Percent Index Days in the ICU or Intermediate Care According to Patient Demographics and Injury Characteristics
Variable
N (%)
Overall 126,513 (100) Age 16–54 59,770 (47.2) 55–64 18,376 (14.5) 65–74 15,626 (12.4) 75–84 19,707 (15.6) ≥85 13,034 (10.3) Gender Male 69,513 (54.9) Female 57,000 (45.1) No. comorbidities 0 105,120 (83.1) 1 14,846 (11.7) 2 3908 (3.1) ≥3 2653 (2.1) Mechanism MVC 33,841 (26.8) Fall 73,004 (57.7) Penetrating 4673 (3.7) Other 14,995 (11.8) MAIS 1–2 54,132 (42.8) 3 54,690 (43.2) 4 11,334 (9.0) 5–6 6357 (5.0) Body region of the most severe injury Head 24,152 (19.1) Trunk 20,493 (16.2) Spine 12,589 (10.0) Upper extremities 21,063 (16.7) Lower extremities 48,216 (38.1) GCS 3–8 6245 (4.9) 9–12 2990 (2.4) 13–15 117,278 (92.7) SBP Normal (≥90) 124,691 (98.6) Abnormal (0–89) 1822 (1.4) Respiration rate Normal (10–29) 124,235 (98.2) Abnormal (0–10 and ≥30) 2278 (1.8) Number of admissions in 12 mo before injury 0 105,521 (83.4) 1 13,292 (10.5) 2 4414 (3.5) ≥3 3286 (2.6) Insurance status Provincial public (RAMQ) 76,337 (60.3) Road accidents (SAAQ) 26,026 (20.6) Work accidents (CSST) 6661 (5.3) Other 8955 (7.1) None/Unknown 8534 (6.8) Discharge destination Home 80,700 (63.8) Long stay 7227 (5.7) Rehabilitation 13,386 (10.6) Acute care 7143 (5.6) Other 18,057 (14.3)
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Index LOS (Mean Days)
Multiple Admissions (%)
ICU Stay (% of Index Days)
Intermediate Stay (% of Index Days)
8.6
7.7
8.9
2.5
6.7 8.0 9.6 12.8 15.2
5.4 6.9 7.7 9.2 7.6
15.1 10.1 8.5 4.0 1.5
1.9 1.9 2.4 3.2 3.6
7.8 9.8
6.4 7.1
13.1 4.7
2.5 2.6
8.3 9.6 11.5 12.8
6.1 8.2 8.1 7.8
9.4 7.6 5.8 5.6
2.2 2.9 3.2 2.8
9.0 9.3 6.0 6.2
6.6 7.0 8.6 5.2
18.0 4.4 14.9 11.1
2.4 2.7 1.1 2.0
7.2 8.9 12.0 18.5
4.7 7.4 9.9 12.1
2.4 5.5 21.8 30.6
3.2 1.6 3.4 3.2
9.4 9.6 10.2 6.9 8.4
8.5 5.7 5.2 6.8 6.7
19.8 16.2 7.9 2.1 1.9
3.2 3.1 3.9 2.0 1.7
14.2 11.5 8.4
11.4 9.2 6.4
30.0 22.5 6.3
3.1 3.0 2.5
8.6 14.3
6.7 8.3
8.5 23.0
2.6 2.0
8.6 12.0
6.7 6.8
8.7 19.1
2.5 2.2
8.3 9.6 12.0 12.7
5.1 15.5 9.0 19.4
9.9 5.6 4.7 4.5
2.3 3.1 3.7 3.7
8.6 9.6 6.5 7.9 8.6
7.3 6.8 4.8 3.4 6.7
5.6 18.7 11.9 9.3 4.6
2.9 2.5 1.8 0.7 1.1
7.2 18.9 19.1 9.8 7.8
1.3 1.0 0.6 100.0 1.0
5.8 3.8 18.9 18.4 5.5
1.9 2.8 2.6 5.0 3.6 (continued)
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Annals of Surgery r Volume 260, Number 1, July 2014
Hospital Length of Stay After Injury
TABLE 1. (Continued)
Variable
N (%)
Year index admission 1999–2002 36,827 (29.1) 2003–2006 42,857 (33.9) 2007–2010 46,829 (37.0) Level of index trauma center I 35,969 (28.4) II 26,555 (21.0) III 52,667 (41.6) IV 11,322 (9.0) Surgery No 50,840 (40.2) Yes 75,673 (59.8) Mechanical ventilation No 117,151 (92.6) Yes 9362 (7.4) ICU No 102,556 (81.1) Yes 23,957 (18.9) Transfer No 88,958 (70.3) Yes 37,555 (29.7)
Index LOS (Mean Days)
Multiple Admissions (%)
ICU Stay (% of Index Days)
Intermediate Stay (% of Index Days)
8.4 8.7 8.8
5.8 6.5 7.7
9.8 9.3 7.8
1.7 2.6 3.1
9.1 8.2 8.5 9.1
8.1 7.5 6.0 4.2
15.8 9.9 4.0 5.0
2.0 2.1 2.4 5.6
9.6 8.1
5.4 7.6
5.9 11.1
3.8 1.6
8.1 19.9
6.2 13.2
3.6 35.9
2.5 2.6
7.8 13.3
5.7 10.9
N/A 30.6
2.6 2.3
9.7 6.5
3.3 18.2
6.4 16.5
2.5 2.5
MAIS indicates maximum abbreviated injury scale score; MVC, motor vehicle collision.
much higher resource intensity than general ward care, were an important component of index LOS. Both index and ICU LOS in the Quebec trauma system were on average 50% longer than LOS for year-, age-, and sex-matched general provincial admissions. Finally, all predictors identified by literature review and expert opinion were statistically significant predictors of LOS, explaining collectively 38% of the variation in index LOS. Predictors did not vary when total rather than index LOS was considered but did vary according to the level of care provided in the index hospital. In particular, designation level of the index hospital was a statistically significant determinant of ICU and intermediate care unit LOS but did not predict index LOS. Mean LOS observed in this study was similar to that reported for major trauma across Canada (8 days) but higher than that reported for hospitals contributing to the US National Trauma Data Bank (between 2 and 7 days for minor through major trauma).27 This may be explained by shorter LOS in for-profit hospitals than not-for-profit hospitals.30 In contrast, median ICU stay in patients with ISS more than 24 was the same in our population as in hospitals contributing to the US National Trauma Data Bank (6 days).27 This is the first study to compare index to total LOS in a trauma population but the underestimation of LOS based only on the index stay has been reported for critical care patients.31 Additional hospital days after transfer have also been shown to influence LOS quality indicators in critical care patients.32 Further research is needed to evaluate the impact of stays outside the index hospital on trauma center performance evaluation results. Interhospital differences in additional LOS days would unfairly advantage hospitals that receive more transfers or discharge patients to other acute care hospitals. We also observed that ICU and intermediate care unit stays account for an important part of index LOS, associated with much higher costs.33,34 Indeed, the cost of an ICU bed is estimated to up to 7 times higher and an intermediate care unit bed up to 5 times higher than a bed on a medical/surgical floor.35,36 A quality indicator based on hospital LOS could overestimate resource use for hospitals that C 2014 Lippincott Williams & Wilkins
discharge patients rapidly from ICU or intermediate care unit beds or that use intermediate wards to offload busy ICUs. The financial implications of these results are important. The average cost per acute care bed day (general ward) is CAN$360.9537 in Canada and USD$1944.77 in the United States.38 The 0.9 additional hospital days due to multiple consecutive admissions for the same injury observed in our study therefore represent on average $288.76 per trauma patient in Canada and $1556 in the United States. Reimbursement schemes based on diagnostic-related groups, such as US Medicare, and pay-for-performance schemes that use on risk-adjusted LOS will therefore unfairly advantage hospitals that more frequently treat patients for only a part of their acute care stay. Furthermore, pay-for-performance schemes that do not account for the level of care provided will not penalize hospitals that overuse ICU care when lower levels of care could be used. Our study suggests that index and ICU LOS in trauma patients is on average 50% higher than expected according to year-, sex-, and age-matched general admissions. This is surprising given that injury is widely perceived as a short-term management problem compared with chronic diseases. However, our results are supported by American Agency for Healthcare Research and Quality statistics, which show that spinal cord injury (22.7 days), crushing/internal injury (6.8 days), intracranial injury (6.6 days), and lower limb fracture (4.8 days) are all associated with higher LOS than the national average (4.6 days).39 The problem of insufficient reimbursement for trauma admissions related to the increased cost of LOS compared with other diagnoses has been highlighted elsewhere.10 Our observation underlines the importance of monitoring LOS in trauma patients and suggests the need for either additional resources for trauma patients or novel care approaches to shorten LOS for injury admissions. Several studies have investigated determinants of index LOS in trauma populations.21–24 As in our study, age, sex, comorbidities, mechanism of injury, body region of the most severe injury, www.annalsofsurgery.com | 183
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TABLE 2. Determinants of Index, Intensive Care Unit (ICU), and Intermediate Care LOS Variable
Index
ICU
Intermediate
6.8 (6.4–7.1) 7.6 (7.2–8.0) 8.7 (8.3–9.2) 10.7 (10.2–11.2) 12.3 (11.7–12.9)
3.4 (3.2–3.7) 3.8 (3.6–4.1) 4.0 (3.8–4.3) 4.0 (3.7–4.3) 4.0 (3.7–4.3)
3.9 (3.1–5.0) 4.3 (3.4–5.5) 4.4 (3.4–5.5) 4.9 (3.9–6.2) 5.9 (4.6–7.5)
8.8 (8.4–9.2) 9.2 (8.8–9.7)
3.8 (3.6–4.1) 3.9 (3.6–4.1)
4.5 (3.6–5.7) 4.7 (3.7–6.0)
7.0 (6.7–7.4) 8.5 (8.1–9.0) 9.8 (9.3–10.3) 11.2 (10.6–11.8)
3.5 (3.2–3.7) 3.9 (3.6–4.1) 4.0 (3.7–4.3) 4.1 (3.8–4.5)
4.0 (3.2–5.1) 4.4 (3.5–5.6) 4.7 (3.7–6.0) 5.5 (4.3–7.0)
9.5 (9.0–9.9) 9.0 (8.6–9.5) 8.5 (8.1–8.9)
4.2 (4.0–4.5) 3.8 (3.5–4.0) 3.6 (3.3–3.8)
4.8 (3.8–6.1) 4.8 (3.8–6.1) 4.3 (3.4–5.5)
6.9 (6.5–7.2) 8.2 (7.9–8.7) 9.8 (9.3–10.3) 11.8 (11.2–12.4)
3.0 (2.8–3.2) 3.3 (3.1–3.5) 4.0 (3.8–4.3) 5.5 (5.1–5.9)
4.1 (3.2–5.2) 4.2 (3.3–5.3) 4.9 (3.9–6.2) 5.5 (4.3–7.0)
8.1 (7.7–8.5) 9.0 (8.6–9.5) 10.8 (10.3–11.4) 7.7 (7.3–8.1) 9.6 (9.2–10.1)
3.5 (3.2–3.7) 4.2 (3.9–4.4) 4.5 (4.2–4.9) 3.6 (3.3–3.8) 3.6 (3.4–3.9)
3.9 (3.1–4.9) 4.3 (3.4–5.5) 5.2 (4.1–6.6) 4.7 (3.7–6.0) 5.1 (4.0–6.5)
9.4 (8.9–9.9) 8.8 (8.3–9.3) 8.8 (8.4–9.2)
4.2 (3.9–4.5) 3.8 (3.5–4.0) 3.6 (3.4–3.9)
4.8 (3.8–6.1) 4.7 (3.6–6.0) 4.4 (3.5–5.6)
8.2 (7.9–8.6) 9.8 (9.3–10.3)
3.6 (3.4–3.8) 4.1 (3.8–4.5)
4.6 (3.6–5.7) 4.7 (3.6–6.1)
8.7 (8.3–9.2) 9.2 (8.8–9.7)
3.7 (3.4–3.9) 4.0 (3.8–4.4)
4.8 (3.9–6.1) 4.4 (3.4–5.7)
8.6 (8.2–9.1) 8.4 (7.9–8.8) 9.3 (8.8–9.8) 9.7 (9.2–10.3)
3.9 (3.7–4.2) 3.8 (3.6–4.1) 3.9 (3.6–4.2) 3.8 (3.5–4.1)
4.3 (3.4–5.4) 4.4 (3.5–5.6) 4.9 (3.8–6.3) 4.9 (3.8–6.3)
8.8 (8.4–9.2) 9.5 (9.0–10.0) 9.5 (9.1–10.0) 8.7 (8.3–9.2) 8.4 (8.0–8.8)
3.7 (3.5–4.0) 3.8 (3.6–4.1) 4.2 (3.9–4.5) 3.8 (3.5–4.0) 3.7 (3.4–4.0)
4.5 (3.5–5.7) 4.7 (3.7–6.0) 4.8 (3.7–6.1) 4.2 (3.2–5.4) 5.0 (3.8–6.7)
7.1 (6.8–7.5) 11.5 (10.9–12.0) 12.3 (11.7–12.9) 7.8 (7.4–8.2) 7.5 (7.2–7.9)
— — — — —
— — — — —
9.2 (8.8–9.7) 9.0 (8.6–9.4) 8.8 (8.4–9.2)
3.8 (3.5–4.0) 3.9 (3.7–4.2) 3.8 (3.6–4.1)
4.4 (3.4–5.5) 4.7 (3.7–6.0) 4.8 (3.8–6.1) (continued)
Adjusted∗
mean (95% CI) Age 16–54 55–64 65–74 75–84 ≥85 Gender Male Female No. comorbidities 0 1 2 ≥3 Mechanism MVC Fall Other MAIS 1–2 3 4 5–6 Body region of the most severe injury Head Trunk Spine Upper extremities Lower extremities GCS 3–8 9–12 13–15 SBP Normal (≥90) Abnormal (0–89) RR Normal (10–29) Abnormal (0–10 and ≥30) No. admissions in 12 mo before injury 0 1 2 ≥3 Insurance status Provincial public (RAMQ) Road accidents (SAAQ) Work accidents (CSST) Other None/Unknown Discharge destination Home Long stay Rehab Acute care Other Year index admission 1999–2002 2003–2006 2007–2009
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Annals of Surgery r Volume 260, Number 1, July 2014
Hospital Length of Stay After Injury
TABLE 2. (Continued) Variable
Index
Level of index trauma center I 9.2 (8.7–9.7) II 9.1 (8.6–9.6) III 8.9 (8.0–10.0) IV 8.7 (7.8–9.7) Surgery No 8.7 (8.3–9.2) Yes 9.2 (8.8–9.7) Mechanical ventilation No 7.0 (6.7–7.4) Yes 11.5 (11.0–12.1) ICU No 8.0 (7.6–8.4) Yes 10.1 (9.6–10.6) Transfer No 10.4 (9.9–11.0) Yes 7.7 (7.4–8.1)
ICU
Intermediate
4.3 (4.0–4.7) 4.1 (3.8–4.4) 3.6 (3.2–4.1) 3.4 (2.9–3.9)
7.0 (5.4–9.2) 5.1 (3.4–7.5) 4.4 (2.8–7.1) 2.9 (1.7–5.1)
3.5 (3.3–3.8) 4.2 (3.9–4.5)
4.5 (3.6–5.8) 4.7 (3.7–6.0)
2.6 (2.4–2.8) 5.7 (5.3–6.1)
3.9 (3.1–4.9) 5.5 (4.3–7.0)
— —
4.8 (3.7–6.0) 4.5 (3.6–5.7)
3.9 (3.7–4.2) 3.8 (3.5–4.0)
4.7 (3.7–5.9) 4.6 (3.6–5.8)
MAIS indicates maximum abbreviated injury scale score; MVC, motor vehicle collision. ∗ Adjusted for all other variables in the table.
FIGURE 2. Relative effect of independent variables for predicting index, ICU, and intermediate unit length of hospital stay. †p > 0.05. anatomical injury severity, physiological reaction to injury (GCS, RR, and SBP), and ICU admission have all been identified as independent predictors of LOS or extended LOS.3,40–48 Among the few studies that have included nonclinical, nondemographic factors in predictive models, transfer status,3 insurance status,40,41,43,45 and discharge destination41 have been identified as important determinants of LOS or extended LOS. The longer LOS associated with patients transferred to long-term and rehabilitation can be explained by the chronic lack of resources in long-term care institutions. Little data are available on the determinants of ICU LOS in trauma patients but age, injury severity, comorbidities, mechanical ventilation, and surgery have all been identified as predictors of extended ICU LOS and as in our study, sex was found not to be an independent predictor.49,50 C 2014 Lippincott Williams & Wilkins
We did not identify any studies that have assessed the determinants of intermediate care unit LOS for trauma patients, but our data show that predictive factors differ to those for index or ICU LOS, and that information in the trauma registry explains less variation in intermediate care unit LOS than index or ICU LOS. This probably reflects the fact that the use of intermediate care units is mostly determined by nonclinical factors such as bed availability.
Limitations Potential limitations, which may affect the interpretation of results include missing physiological data, population coverage, variation in the definition of intensive or intermediate care units, and the external validity of results. First, multiple imputation of missing www.annalsofsurgery.com | 185
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Annals of Surgery r Volume 260, Number 1, July 2014
Moore et al
GCS and RR data enabled us to use information on all patients but is based on the assumption that data are missing at random.51 However, results with and without imputed data were similar, and data simulations on this and other trauma registries support the hypothesis that imputed physiological data in trauma registries lead to valid effect estimates.28,52 Second, this study is only based on patients admitted to a trauma center, representing approximately 85% of all major trauma admissions in the province.53 We suspect that patients treated in nondesignated hospitals are older but less severely injured, which may have led to a slight overestimation of mean LOS in this study. Third, the definition of ICU and intermediate care unit beds may vary across hospitals, which could have lead to an under- or overestimation of the proportion of index LOS days in ICU or intermediate care units and to an underestimation of the association between risk factors and ICU or intermediate care unit LOS. Along with other data quality issues, the standardization of such definitions is vital to the validity and reliability of performance evaluations based on LOS. Finally, the results of this study may not generalize well to other health care systems. Indeed, mean LOS varies from one health system to another. In addition, in less well-organized trauma systems, admissions to hospitals before the index stay in a trauma center may be more frequent. However, the similarities in predictors of LOS and ICU LOS across trauma systems in the literature suggest that the determinants of LOS and its components identified in this study are likely to generalize well.
Implications LOS has been criticized as a measure of quality because it is influenced by many nonmedical factors including the availability of postacute care41,45 and has been reported to have minimal impact on the cost of hospital admission.54 However, other authors have reported an important impact of extended LOS on costs,10,45 rehabilitation stays, and functional outcome.55 This study highlights the complexities of LOS that should be taken into account when evaluating trauma centers. For example, to counter the influence of nonclinical factors, adjustment could be made for insurance status and discharge destination. To deal with the problem of multiple admissions for the same injury, a variable representing additional LOS days could be added to the risk adjustment model. Finally, to address different levels of resource use influencing cost, weights could be used to represent days spent in ICU, intermediate, or general ward care. A quality indicator based on LOS would allow us to identify hospitals with higher than expected resource use and to monitor resource use within hospitals or trauma systems over time. This information would then enable stakeholders to identify elements of structure (eg, hospital volume, bed availability), clinical processes (eg, waiting time in the ED), or hospital-based outcomes (eg, complications, unplanned surgery) that explain longer than expected LOS and can be used to plan quality improvement activities.
CONCLUSIONS We have shown that mean acute care LOS after injury is underestimated when only information on the index hospitalization is used but that the determinants of LOS do not change when additional consecutive admissions for the same injury are considered. We also demonstrate that days in ICU and intermediate care units contribute significantly to overall LOS and that the determinants of the latter differ to those identified for index LOS. Finally, we observed that resource use for trauma patients in terms of hospital and ICU days are higher than expected according to general admissions, demonstrating the importance of monitoring LOS in trauma patients. This study provides detailed information on the distribution and determinants of acute care LOS after traumatic injury, which should be considered when evaluating trauma care in terms of resource use. 186 | www.annalsofsurgery.com
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28. Moore L, Lavoie A, LeSage N, et al. Multiple imputation of the Glasgow Coma Score. J Trauma. 2005;59:698–704. 29. Ruffieux C, Paccaud F, Marazzi A. Comparing rules for truncating hospital length of stay. Casemix Q. 2000;2:1–10. 30. Bueno H, Ross JS, Wang Y, et al. Trends in length of stay and short-term outcomes among Medicare patients hospitalized for heart failure, 1993-2006. JAMA. 2010;303:2141–2147. 31. Harrison DA, Brady AR, Rowan K: Case mix, outcome and length of stay for admissions to adult, general critical care units in England, Wales and Northern Ireland: the Intensive Care National Audit & Research Centre Case Mix Programme Database. Crit Care. 2004;8:R99–R111. 32. Hall WB, Willis LE, Medvedev S, et al. The implications of long-term acute care hospital transfer practices for measures of in-hospital mortality and length of stay. Am J Respir Crit Care Med. 2012;185:53–57. 33. Kahn JM, Rubenfeld GD, Rohrbach J, et al. Cost savings attributable to reductions in intensive care unit length of stay for mechanically ventilated patients. Med Care. 2008;46:1226–1233. 34. Candrilli S, Mauskopf J: How much does a hospital day cost? In: 11th Annual International Meeting of the International Society for Pharmacoeconomics and Outcomes Research; May 20–24, 2006; Philadelphia, PA. 35. Kalb PE, Miller DH. Utilization strategies for intensive care units. JAMA. 1989;261:2389–2395. 36. Solberg BC, Dirksen CD, Nieman FH, et al. Changes in hospital costs after introducing an intermediate care unit: a comparative observational study. Crit Care. 2008;12:R68. 37. World Health Organization. Estimates of unit costs for patient services for Canada. Available at http://www.who.int/choice/country/can/cost/en. Accessed March 6, 2013. 38. World Health Organization. Estimates of unit costs for patient services for United States of America. Available at http://www.who.int/choice/country/usa/ cost/en/index.html. Accessed March 06, 2013. 39. HCUP (Healthcare Cost and Utilization Project) Facts and Figures. Average length of stay and average charges. Available at http://www.hcup-us. Accessed ahrq.gov/reports/factsandfigures/facts figures 2006.jsp#ex4 3. January 14, 2014. 40. Shafi S, Barnes S, Nicewander D, et al. Health care reform at trauma centers— mortality, complications, and length of stay. J Trauma. 2010;69:1367–1371.
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41. Brasel KJ, Lim HJ, Nirula R, et al. Length of stay: an appropriate quality measure? Arch Surg. 2007;142:461–465; discussion 465–466. 42. Ciesla DJ, Sava JA, Kennedy SO, et al. Trauma patients: you can get them in, but you can’t get them out. Am J Surg. 2008;195:78–83. 43. Gabbe BJ, Cameron PA, Wolfe R, et al. Predictors of mortality, length of stay and discharge destination in blunt trauma. ANZ J Surg. 2005;75:650–656. 44. Schwartz RJ, Jacobs LM, Yaezel D. Impact of pre-trauma center care on length of stay and hospital charges. J Trauma. 1989;29:1611–1615. 45. Thomas SN, McGwin G, Jr, Rue LW, III. The financial impact of delayed discharge at a level I trauma center. J Trauma. 2005;58:121–125. 46. MacKenzie EJ, Morris JA, Jr, Edelstein SL. Effect of pre-existing disease on length of hospital stay in trauma patients. J Trauma. 1989;29:757–764; discussion 764–755. 47. Andersen J, Sharkey W, Schwartz ML, et al. Injury severity score, head injury, and patient wait days: contributions to extended trauma patient length of stay. J Trauma. 1992;33:219–220. 48. Jacobs DG, Sarafin JL, Norton HJ, et al. Wasted hospital days impair the value of length-of-stay variables in the quality assessment of trauma care. Am Surg. 2009;75:794–802; discussion 802–793. 49. Ong AW, Omert LA, Vido D, et al. Characteristics and outcomes of trauma patients with ICU lengths of stay 30 days and greater: a seven-year retrospective study. Crit Care. 2009;13:R154. 50. Higgins TL, McGee WT, Steingrub JS, et al. Early indicators of prolonged intensive care unit stay: impact of illness severity, physician staffing, and preintensive care unit length of stay. Crit Care Med. 2003;31:45–51. 51. Little RJA, Rubin DB. Statistical Analysis With Missing Data. 2nd ed. New York, NY: Wiley; 2002. 52. Moore L, Hanley JA, Lavoie A, et al. Evaluating the validity of multiple imputation for missing physiological data in the national trauma data bank. J Emerg Trauma Shock. 2009;2:73–79. 53. Lavoie A, Gagne M, Belcaid A, et al. Trauma registry inclusion criteria and severe injury representativeness. J Trauma. 2008;64:551. 54. Taheri PA, Butz DA, Greenfield LJ. Length of stay has minimal impact on the cost of hospital admission. J Am Coll Surg. 2000;191:123–130. 55. Sirois MJ, Dionne CE, Lavoie A. Regional differences in rehabilitation needs, rehabilitation access, and physical outcomes among multiple trauma survivors. Am J Phys Med Rehabil. 2009;88:387–398.
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Hospital Length of Stay After Admission for Traumatic Injury in Canada A Multicenter Cohort Study Lynne Moore, PhD,∗ † Henry Thomas Stelfox, MD, PhD, FRCPC,‡ Alexis F. Turgeon, MD, MSc, FRCPC,∗ § Avery Nathens, MD, PhD,¶ Gilles Bourgeois, MD,|| Jean Lapointe, MD,|| Mathieu Gagn´e, MSc,∗ and Andr´e Lavoie, PhD||
Objective: To describe acute care length of stay (LOS) over all consecutive hospitalizations for the injury and according to level of care [intensive care unit (ICU), intermediate care, general ward], compare observed and expected LOS, and identify predictors of LOS. Background: Prolonged LOS has important consequences in terms of costs and outcome, yet detailed information on LOS after trauma is lacking. Methods: This multicenter retrospective cohort study was based on adults discharged alive from a Canadian trauma system (1999–2010; n = 126,513). Registry data were used to calculate index LOS (LOS in trauma center with highest designation level) and were linked to hospital discharge data to calculate total LOS (all consecutive hospitalizations for the injury). Expected LOS was obtained by matching general provincial discharge statistics to study data by year, age, and sex. Potential predictors of LOS were evaluated using linear regression. Results: Mean index and total LOS were 8.6 and 9.4 days, respectively. ICU, intermediate care unit, and general ward care constituted 8.9%, 2.5%, and 88.6% of total hospital days. Observed mean index and ICU LOS in our trauma patients were 2.9 and 1.3 days longer than expected LOS (P < 0.0001). The strongest determinants of index LOS were discharge destination, age, transfer status, and injury severity. Conclusions: Results suggest that acute care LOS after injury is underestimated when only information on the index hospitalization is used and that ICU or intermediate care constitute an important part of LOS. This information should be used to inform the development of an informative and actionable quality indicator. Keywords: injury, length of stay, acute care, trauma system, intensive care unit, intermediate care unit
recorded annually with 19.5$ billion in acute care hospital costs alone, representing 7% of total hospital costs.2 To improve the quality and efficiency of trauma care, information is needed on resource use. Patient-level information on the real costs of trauma care is unavailable in public health care systems, is often estimated using cost-to-charges ratios in for-profit hospitals, and is heavily influenced by nonclinical processes. Hospital length of stay (LOS) provides an interesting surrogate for resource use, which can be calculated easily using routinely collected data and is more directly actionable than information on costs. LOS has been shown to be influenced by errors in care and adverse events and has been associated with clinical process indicators.3 In addition, quality interventions have been shown to be efficient in reducing LOS3–9 and reductions in LOS lead to important cost savings.10–13 Hospital LOS has been targeted as an important metric to evaluate trauma care.14 However, detailed information on the distribution and determinants of acute care LOS and its components after admission for traumatic injury is required. This information can be used to guide the development and interpretation of a valid, actionable quality indicator based on LOS, which in turn can lead to improvements in the quality and efficiency of trauma care. The objectives of this study were to (i) describe acute care LOS after trauma over all consecutive hospitalizations related to the injury, (ii) describe LOS according to the level of care provided [intensive care unit (ICU), intermediate care unit, and general ward], (iii) compare observed LOS for trauma system admissions to expected LOS according to age-, sex-, and year-matched general provincial admissions, and (iv) identify predictors of LOS and its components.
(Ann Surg 2014;260:179–187)
E
ach year, approximately 212,000 Canadians are hospitalized after injury with associated direct health care costs of 11$ billion.1 In the United States, around 1.9 million injury hospitalizations are From the ∗ Department of Social and Preventative Medicine, Universit´e Laval, Qu´ebec, Canada; †Unit´e de traumatologie-urgence-soins intensifs, Centre de Recherche du CHU de Qu´ebec (Hˆopital de l’Enfant-J´esus), Universit´e Laval, Qu´ebec, Canada; ‡Department of Critical Care Medicine, Medicine and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; §Department of Anesthesiology, Division of Critical Care Medicine, Qu´ebec, Canada; ¶Department of Surgery, St. Michael’s Hospital, University of Toronto, Toronto; and ||Institut national d’excellence en sant´e et en services sociaux, Montr´eal, Qu´ebec, Canada. Disclosure: Canadian Institutes of Health Research: young investigator award (H.T.S. and L.M.) and research grant (L.M.; 110996); Fonds de la recherche du Qu´ebec - Sant´e: clinician-scientist award (A.F.T.). The authors declare no conflicts of interest. Reprints: Lynne Moore, PhD, Research Center of the CHU de Qu´ebec (Hˆopital de l’Enfant-J´esus), Traumatologie–Urgence–Soins Intensifs (Trauma– Emergency–Critical Care Medicine Unit), 1401, 18e rue, local H-012a, QC G1J 1Z4. E-mail: [email protected] C 2014 by Lippincott Williams & Wilkins Copyright ISSN: 0003-4932/14/26001-0179 DOI: 10.1097/SLA.0000000000000624
Annals of Surgery r Volume 260, Number 1, July 2014
METHODS Study Population This multicenter, retrospective cohort study was based on the inclusive trauma system of the province of Qu´ebec, Canada (population 8 million). The Qu´ebec trauma system was instated in 1993 and involves regionalized care from urban level I trauma centers to rural community hospitals. All level I centers are trauma teaching hospitals. Trauma center designations are based on American College of Surgeons criteria and are revised periodically with on-site visits.15 Standardized prehospital protocols ensure that major trauma cases are taken to these hospitals and standing agreements regulate interhospital transfers within the system.
Study Data Data were drawn from the Qu´ebec trauma registry. Contribution to the registry is mandatory according to the following uniform inclusion criteria: death after injury, intensive care unit admission, hospital stay for more than 2 days, or transfer from another hospital. Registry data are extracted from patient files by medical archivists who use standardized coding protocols. Anatomic injury is coded with www.annalsofsurgery.com | 179
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Annals of Surgery r Volume 260, Number 1, July 2014
Moore et al
the Abbreviated Injury Scale (AIS) according to guidelines published by the Association for the Advancement of Automotive Medicine.16 The registry is centralized at the Quebec Ministry of Health and is subject to periodic validation. Supervision by a data coordinator, yearly on-going training, an electronic forum of coding queries, and thrice-yearly meetings with key stakeholders are used to ensure data quality. This study was based on adults (aged ≥16 years) discharged alive between 2000 and 2010 from any of the 57 adult trauma centers in the Qu´ebec trauma system for a traumatic injury that met trauma registry inclusion criteria. Patients with isolated hip fractures [defined as an AIS diagnosis code of 851808.3, 851810.3, 851812.3, or 851818.3 in patients 65 years or older with no major secondary injuries (ie, AIS > 1)], were excluded.17 Information on the number of admissions in the 12 months before the index admission and on consecutive acute care stays for the same injury was obtained by linking trauma registry data, via a unique health coverage identifier, to the provincial hospital discharge database that is completed for all hospital admissions.18 The index admission is defined as the admission to the hospital with the highest trauma designation level. Consecutive admissions to acute care stay hospitals for the same injury were identified as any admission to a short-stay hospital with a date of discharge corresponding to the index admission date (transfer-in) or a date of admission corresponded to the index discharge date (transfer-out).
Primary Outcome The primary outcome was LOS in the index hospital, calculated as the number of days between admission and discharge (index LOS). Secondary outcomes were LOS over all consecutive hospitalizations for the same injury (total LOS); LOS according to the level of inhospital care provided (ICU, intermediate care unit, general ward); and expected LOS according to age-, sex-, and year-matched general provincial admissions.
Statistical Analyses LOS has a right-skewed distribution and was therefore described and modeled using a natural-log transformation. LOS is therefore presented using geometric means, which are approximately equivalent to the median.19 Three analyses were performed. First, the distribution of LOS in the index hospital and additional LOS in transfer-in hospitals (hospitals sending patients to the index hospital) and transfer-out hospitals (hospitals receiving patients from the index hospital) was described with histograms. We then calculated the following for the whole study sample and according to strata of patient characteristics: (i) the proportion of patients with more than 1 hospital admission for the same injury and (ii) the proportion of index LOS days covered by ICU care, intermediate care, and general ward care. Second, observed mean index and ICU LOS in trauma patients was compared with expected mean index and ICU LOS according to all provincial admissions. We used estimates of mean index and ICU LOS for all hospital admissions in the province of Qu´ebec by age and sex for the administrative years 1999–2010 for comparison.20 We used all provincial nonelective admissions (all diagnoses) with an LOS more than 2 days to be comparable with patients in our trauma registry. Expected LOS was calculated by matching provincial admission LOS to study data by age, sex, and year. Third, we identified predictors of index, ICU, and intermediate care unit LOS using multilevel linear regression with a random intercept to control for hospital clusters. LOS was modeled using a natural logarithm transformation. The following independent variables were chosen a priori on the basis of factors reported in the literature 21–24 and those considered to be important by the project 180 | www.annalsofsurgery.com
steering committee: age, sex, number of comorbidities, mechanism of injury, maximum AIS score, body region of the most severe injury, Glasgow Coma Scale (GCS) score, respiratory rate (RR), systolic blood pressure (SBP), number of admissions in the 12 months before the index admission, insurance status, discharge destination, year of index admission, designation level of index trauma center, surgery, mechanical ventilation, ICU admission, and transfer status. ICU admission was not included in the model of ICU LOS, and discharge destination was not included in the models of ICU or intermediate care unit LOS. The variable “insurance status” was defined according to the principal payer for each admission among the following: provincial public health insurance [R´egie de l’Assurance maladie du Qu´ebec (RAMQ)], provincial insurance for road accidents [Soci´et´e de l’Assurance Automobile du Qu´ebec (SAAQ)], provincial insurance for work accidents [Commission de la Sant´e et de la S´ecurit´e au Travail (CSST)], and other sources (including federal government, army, and private insurance companies). Transfer status was defined as transfer-in from any acute-care hospital that had admitted the patient or not. Statistical significance was set at 5%. The relative importance of variables for predicting LOS was evaluated using Cohen’s f 2 , a measure of local effect size based on explained variation that is applicable to multilevel multivariate regression models.25,26 Cohen’s f 2 is the proportion of explained variation accounted for by the variable of interest over and above all other variables in the model. As is common in trauma registries, a high proportion of patients had missing physiological data.27 The GCS, SBP, and RR were missing for 57%, 15%, and 38% of data observations, respectively. These data were mostly missing in patients with minor extracranial injury.28 Missing data on the GCS, RR, and SBP were simulated using multiple imputation. The Markov Chain Monte Carlo method was used with a noninformative prior and a single chain to generate 5 imputes for each missing data value. The imputation model included all independent and dependant variables used in the analysis model.
Sensitivity Analyses Sensitivity analyses were performed to evaluate the robustness of results to LOS outliers and to data simulated by multiple imputations. Analyses were thus repeated with LOS truncated at 90 days.29 We then evaluated the association of GCS, RR, and SBP to LOS when observations with missing data were excluded from the multivariate linear regression model. The study was approved by the Research Ethics Committee of the CHU de Qu´ebec (Hˆopital de l’Enfant-J´esus). Analyses were performed with the Statistical Analysis System (Version 9.2: SAS Institute, Cary, North Carolina).
RESULTS Study Population The Qu´ebec trauma registry included 179,916 adults (aged ≥16 years) admitted between April 1, 1998, and March 31, 2010. Of these, 34,454 (19.2%) had isolated hip fractures, 13,572 (7.5%) died in hospital, 5184 (2.9%) resided outside the province, and 193 (0.1%) could not be linked with administrative data. The final study population therefore comprised 126,513 patients with a geometric mean index LOS of 8.6 days [95% confidence interval (CI): 8.6–8.7]. The arithmetic mean index LOS was 13.1 days (95% CI: 13.0–13.2). In the study sample, 38% of patients were 65 years or older, mean Injury Severity Score (ISS) was 10, and 24% of patients had major trauma (ISS > 12). Penetrating trauma represented only 4% of patients.
Acute Care Hospital LOS Overall, 64,262 (50.8%) patients had an index LOS of 1 week or more and 11,422 (9.0%) patients stayed in the index hospital for C 2014 Lippincott Williams & Wilkins
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Annals of Surgery r Volume 260, Number 1, July 2014
Hospital Length of Stay After Injury
FIGURE 1. Distribution of LOS in the index hospital and in transfer-in and transfer-out hospitals. more than 1 month (Fig. 1). Mean index LOS varied with patients’ sociodemographic, clinical, and nonclinical characteristics (Table 1). Mean total LOS was 0.8 days longer than mean index LOS (9.4 vs 8.6, P < 0.0001). A total of 8501 (6.7%) patients had more than 1 hospital stay related to the same injury (Table 1). Of these, 1547 patients (1.1%) were transferred to the index trauma center after being admitted to another hospital and 7143 (5.5%) were discharged from the index center to another acute care hospital. Among patients with multiple admissions for the same injury, mean LOS in the transfer-in hospital was shorter than mean index LOS (2.7 vs 8.6, P < 0.001) whereas mean LOS in the transfer-out hospital was much longer than mean index LOS (20.1 vs 8.6, P < 0.001). The proportion of patients with multiple admissions for the same injury was more than 10% for patients with Maximum AIS 5 or more and those with GCS 8 or less (Table 1). Globally, 11.4% of the index LOS was spent in ICU or intermediate care beds (Table 1). Mean ICU LOS was 3.8 days (95% CI: 3.7–3.8 days), and mean LOS in intermediate care was 4.6 days (95% CI: 4.5–4.7 days). The proportion of the index stay in an ICU bed decreased with age and the number of comorbidities, increased with injury severity and trauma center designation level, was higher for men and patients with head injuries, and decreased slightly over the study period (Table 1). The proportion of the index stay in intermediate care units increased with age and the number of comorbidities, was higher for head-trunk-spine injuries and in level I trauma centers, and increased over the study period.
Expected LOS According to General Provincial Admissions Globally, observed mean LOS in our trauma population was 2.9 days (51%) longer than expected mean LOS according to general provincial admissions (8.6 vs 5.7 days, P < 0.0001). Similarly, observed mean ICU LOS was 1.3 days (52%) longer than expected mean ICU LOS (3.8 vs 2.5 days, P < 0.0001).
model, except trauma center designation level, were statistically significant independent predictors of hospital LOS (Table 2, Fig. 2). The strongest determinants of index LOS were discharge destination (patients discharged to long-term care or rehabilitation stayed on average 5 days longer than those discharged home), age (patients aged 85 or older stayed on average 5.5 days longer than patients aged less than 55 years), transfer status (patients transferred in stayed on average 2.7 days less than direct transports), injury severity (patients with a Maximum AIS of 5 or 6 stayed on average 4.9 days longer than patients with a Maximum AIS of 1 or 2), comorbidities (patients with 3 or more comorbidities stayed on average 4.2 days longer than patients with no comorbidities), body region of the most severe injury (patients with a spine injury stayed on average 3.1 days longer than those with a lower extremity injury), and mechanical ventilation (additional mean LOS of 4.5 days). Predictors did not vary when total rather than index LOS was considered. The most important predictors of ICU stay were mechanical ventilation, injury severity, body region of the most severe injury, and surgery (Table 2, Fig. 2). Unlike index LOS, ICU LOS did vary with the designation level of the index center but did not vary with sex or year of discharge. The most important predictors of intermediate care unit LOS were age, mechanical ventilation, injury severity, and the number of comorbidities. Intermediate care unit LOS did not vary by GCS, RR, SBP, insurance status, surgery, or transfer status.
Sensitivity Analyses Truncating LOS outliers did not lead to any important change in crude or adjusted mean LOS overall or in any category of explanatory variables and had little influence on coefficients and standard errors in the multivariate linear regression model. The association between GCS/RR/SBP and LOS did not change significantly in a model restricted to observations with no missing physiological data.
DISCUSSION Predictors of Hospital LOS Collectively, predictors explained 38% of the variation in index LOS, 35% of the variation in ICU LOS, and 13% of the variation in intermediate care unit LOS. All risk factors entered into the multivariate C 2014 Lippincott Williams & Wilkins
In this multicenter retrospective cohort study, we observed that acute care LOS after traumatic injury was underestimated by 10% when only days in the index hospital were considered. In addition, stays in ICU and intermediate care units, associated with www.annalsofsurgery.com | 181
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Annals of Surgery r Volume 260, Number 1, July 2014
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TABLE 1. Index LOS, the Proportion of Patients With Multiple Admissions for the Same Injury, and Percent Index Days in the ICU or Intermediate Care According to Patient Demographics and Injury Characteristics
Variable
N (%)
Overall 126,513 (100) Age 16–54 59,770 (47.2) 55–64 18,376 (14.5) 65–74 15,626 (12.4) 75–84 19,707 (15.6) ≥85 13,034 (10.3) Gender Male 69,513 (54.9) Female 57,000 (45.1) No. comorbidities 0 105,120 (83.1) 1 14,846 (11.7) 2 3908 (3.1) ≥3 2653 (2.1) Mechanism MVC 33,841 (26.8) Fall 73,004 (57.7) Penetrating 4673 (3.7) Other 14,995 (11.8) MAIS 1–2 54,132 (42.8) 3 54,690 (43.2) 4 11,334 (9.0) 5–6 6357 (5.0) Body region of the most severe injury Head 24,152 (19.1) Trunk 20,493 (16.2) Spine 12,589 (10.0) Upper extremities 21,063 (16.7) Lower extremities 48,216 (38.1) GCS 3–8 6245 (4.9) 9–12 2990 (2.4) 13–15 117,278 (92.7) SBP Normal (≥90) 124,691 (98.6) Abnormal (0–89) 1822 (1.4) Respiration rate Normal (10–29) 124,235 (98.2) Abnormal (0–10 and ≥30) 2278 (1.8) Number of admissions in 12 mo before injury 0 105,521 (83.4) 1 13,292 (10.5) 2 4414 (3.5) ≥3 3286 (2.6) Insurance status Provincial public (RAMQ) 76,337 (60.3) Road accidents (SAAQ) 26,026 (20.6) Work accidents (CSST) 6661 (5.3) Other 8955 (7.1) None/Unknown 8534 (6.8) Discharge destination Home 80,700 (63.8) Long stay 7227 (5.7) Rehabilitation 13,386 (10.6) Acute care 7143 (5.6) Other 18,057 (14.3)
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Index LOS (Mean Days)
Multiple Admissions (%)
ICU Stay (% of Index Days)
Intermediate Stay (% of Index Days)
8.6
7.7
8.9
2.5
6.7 8.0 9.6 12.8 15.2
5.4 6.9 7.7 9.2 7.6
15.1 10.1 8.5 4.0 1.5
1.9 1.9 2.4 3.2 3.6
7.8 9.8
6.4 7.1
13.1 4.7
2.5 2.6
8.3 9.6 11.5 12.8
6.1 8.2 8.1 7.8
9.4 7.6 5.8 5.6
2.2 2.9 3.2 2.8
9.0 9.3 6.0 6.2
6.6 7.0 8.6 5.2
18.0 4.4 14.9 11.1
2.4 2.7 1.1 2.0
7.2 8.9 12.0 18.5
4.7 7.4 9.9 12.1
2.4 5.5 21.8 30.6
3.2 1.6 3.4 3.2
9.4 9.6 10.2 6.9 8.4
8.5 5.7 5.2 6.8 6.7
19.8 16.2 7.9 2.1 1.9
3.2 3.1 3.9 2.0 1.7
14.2 11.5 8.4
11.4 9.2 6.4
30.0 22.5 6.3
3.1 3.0 2.5
8.6 14.3
6.7 8.3
8.5 23.0
2.6 2.0
8.6 12.0
6.7 6.8
8.7 19.1
2.5 2.2
8.3 9.6 12.0 12.7
5.1 15.5 9.0 19.4
9.9 5.6 4.7 4.5
2.3 3.1 3.7 3.7
8.6 9.6 6.5 7.9 8.6
7.3 6.8 4.8 3.4 6.7
5.6 18.7 11.9 9.3 4.6
2.9 2.5 1.8 0.7 1.1
7.2 18.9 19.1 9.8 7.8
1.3 1.0 0.6 100.0 1.0
5.8 3.8 18.9 18.4 5.5
1.9 2.8 2.6 5.0 3.6 (continued)
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Annals of Surgery r Volume 260, Number 1, July 2014
Hospital Length of Stay After Injury
TABLE 1. (Continued)
Variable
N (%)
Year index admission 1999–2002 36,827 (29.1) 2003–2006 42,857 (33.9) 2007–2010 46,829 (37.0) Level of index trauma center I 35,969 (28.4) II 26,555 (21.0) III 52,667 (41.6) IV 11,322 (9.0) Surgery No 50,840 (40.2) Yes 75,673 (59.8) Mechanical ventilation No 117,151 (92.6) Yes 9362 (7.4) ICU No 102,556 (81.1) Yes 23,957 (18.9) Transfer No 88,958 (70.3) Yes 37,555 (29.7)
Index LOS (Mean Days)
Multiple Admissions (%)
ICU Stay (% of Index Days)
Intermediate Stay (% of Index Days)
8.4 8.7 8.8
5.8 6.5 7.7
9.8 9.3 7.8
1.7 2.6 3.1
9.1 8.2 8.5 9.1
8.1 7.5 6.0 4.2
15.8 9.9 4.0 5.0
2.0 2.1 2.4 5.6
9.6 8.1
5.4 7.6
5.9 11.1
3.8 1.6
8.1 19.9
6.2 13.2
3.6 35.9
2.5 2.6
7.8 13.3
5.7 10.9
N/A 30.6
2.6 2.3
9.7 6.5
3.3 18.2
6.4 16.5
2.5 2.5
MAIS indicates maximum abbreviated injury scale score; MVC, motor vehicle collision.
much higher resource intensity than general ward care, were an important component of index LOS. Both index and ICU LOS in the Quebec trauma system were on average 50% longer than LOS for year-, age-, and sex-matched general provincial admissions. Finally, all predictors identified by literature review and expert opinion were statistically significant predictors of LOS, explaining collectively 38% of the variation in index LOS. Predictors did not vary when total rather than index LOS was considered but did vary according to the level of care provided in the index hospital. In particular, designation level of the index hospital was a statistically significant determinant of ICU and intermediate care unit LOS but did not predict index LOS. Mean LOS observed in this study was similar to that reported for major trauma across Canada (8 days) but higher than that reported for hospitals contributing to the US National Trauma Data Bank (between 2 and 7 days for minor through major trauma).27 This may be explained by shorter LOS in for-profit hospitals than not-for-profit hospitals.30 In contrast, median ICU stay in patients with ISS more than 24 was the same in our population as in hospitals contributing to the US National Trauma Data Bank (6 days).27 This is the first study to compare index to total LOS in a trauma population but the underestimation of LOS based only on the index stay has been reported for critical care patients.31 Additional hospital days after transfer have also been shown to influence LOS quality indicators in critical care patients.32 Further research is needed to evaluate the impact of stays outside the index hospital on trauma center performance evaluation results. Interhospital differences in additional LOS days would unfairly advantage hospitals that receive more transfers or discharge patients to other acute care hospitals. We also observed that ICU and intermediate care unit stays account for an important part of index LOS, associated with much higher costs.33,34 Indeed, the cost of an ICU bed is estimated to up to 7 times higher and an intermediate care unit bed up to 5 times higher than a bed on a medical/surgical floor.35,36 A quality indicator based on hospital LOS could overestimate resource use for hospitals that C 2014 Lippincott Williams & Wilkins
discharge patients rapidly from ICU or intermediate care unit beds or that use intermediate wards to offload busy ICUs. The financial implications of these results are important. The average cost per acute care bed day (general ward) is CAN$360.9537 in Canada and USD$1944.77 in the United States.38 The 0.9 additional hospital days due to multiple consecutive admissions for the same injury observed in our study therefore represent on average $288.76 per trauma patient in Canada and $1556 in the United States. Reimbursement schemes based on diagnostic-related groups, such as US Medicare, and pay-for-performance schemes that use on risk-adjusted LOS will therefore unfairly advantage hospitals that more frequently treat patients for only a part of their acute care stay. Furthermore, pay-for-performance schemes that do not account for the level of care provided will not penalize hospitals that overuse ICU care when lower levels of care could be used. Our study suggests that index and ICU LOS in trauma patients is on average 50% higher than expected according to year-, sex-, and age-matched general admissions. This is surprising given that injury is widely perceived as a short-term management problem compared with chronic diseases. However, our results are supported by American Agency for Healthcare Research and Quality statistics, which show that spinal cord injury (22.7 days), crushing/internal injury (6.8 days), intracranial injury (6.6 days), and lower limb fracture (4.8 days) are all associated with higher LOS than the national average (4.6 days).39 The problem of insufficient reimbursement for trauma admissions related to the increased cost of LOS compared with other diagnoses has been highlighted elsewhere.10 Our observation underlines the importance of monitoring LOS in trauma patients and suggests the need for either additional resources for trauma patients or novel care approaches to shorten LOS for injury admissions. Several studies have investigated determinants of index LOS in trauma populations.21–24 As in our study, age, sex, comorbidities, mechanism of injury, body region of the most severe injury, www.annalsofsurgery.com | 183
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Annals of Surgery r Volume 260, Number 1, July 2014
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TABLE 2. Determinants of Index, Intensive Care Unit (ICU), and Intermediate Care LOS Variable
Index
ICU
Intermediate
6.8 (6.4–7.1) 7.6 (7.2–8.0) 8.7 (8.3–9.2) 10.7 (10.2–11.2) 12.3 (11.7–12.9)
3.4 (3.2–3.7) 3.8 (3.6–4.1) 4.0 (3.8–4.3) 4.0 (3.7–4.3) 4.0 (3.7–4.3)
3.9 (3.1–5.0) 4.3 (3.4–5.5) 4.4 (3.4–5.5) 4.9 (3.9–6.2) 5.9 (4.6–7.5)
8.8 (8.4–9.2) 9.2 (8.8–9.7)
3.8 (3.6–4.1) 3.9 (3.6–4.1)
4.5 (3.6–5.7) 4.7 (3.7–6.0)
7.0 (6.7–7.4) 8.5 (8.1–9.0) 9.8 (9.3–10.3) 11.2 (10.6–11.8)
3.5 (3.2–3.7) 3.9 (3.6–4.1) 4.0 (3.7–4.3) 4.1 (3.8–4.5)
4.0 (3.2–5.1) 4.4 (3.5–5.6) 4.7 (3.7–6.0) 5.5 (4.3–7.0)
9.5 (9.0–9.9) 9.0 (8.6–9.5) 8.5 (8.1–8.9)
4.2 (4.0–4.5) 3.8 (3.5–4.0) 3.6 (3.3–3.8)
4.8 (3.8–6.1) 4.8 (3.8–6.1) 4.3 (3.4–5.5)
6.9 (6.5–7.2) 8.2 (7.9–8.7) 9.8 (9.3–10.3) 11.8 (11.2–12.4)
3.0 (2.8–3.2) 3.3 (3.1–3.5) 4.0 (3.8–4.3) 5.5 (5.1–5.9)
4.1 (3.2–5.2) 4.2 (3.3–5.3) 4.9 (3.9–6.2) 5.5 (4.3–7.0)
8.1 (7.7–8.5) 9.0 (8.6–9.5) 10.8 (10.3–11.4) 7.7 (7.3–8.1) 9.6 (9.2–10.1)
3.5 (3.2–3.7) 4.2 (3.9–4.4) 4.5 (4.2–4.9) 3.6 (3.3–3.8) 3.6 (3.4–3.9)
3.9 (3.1–4.9) 4.3 (3.4–5.5) 5.2 (4.1–6.6) 4.7 (3.7–6.0) 5.1 (4.0–6.5)
9.4 (8.9–9.9) 8.8 (8.3–9.3) 8.8 (8.4–9.2)
4.2 (3.9–4.5) 3.8 (3.5–4.0) 3.6 (3.4–3.9)
4.8 (3.8–6.1) 4.7 (3.6–6.0) 4.4 (3.5–5.6)
8.2 (7.9–8.6) 9.8 (9.3–10.3)
3.6 (3.4–3.8) 4.1 (3.8–4.5)
4.6 (3.6–5.7) 4.7 (3.6–6.1)
8.7 (8.3–9.2) 9.2 (8.8–9.7)
3.7 (3.4–3.9) 4.0 (3.8–4.4)
4.8 (3.9–6.1) 4.4 (3.4–5.7)
8.6 (8.2–9.1) 8.4 (7.9–8.8) 9.3 (8.8–9.8) 9.7 (9.2–10.3)
3.9 (3.7–4.2) 3.8 (3.6–4.1) 3.9 (3.6–4.2) 3.8 (3.5–4.1)
4.3 (3.4–5.4) 4.4 (3.5–5.6) 4.9 (3.8–6.3) 4.9 (3.8–6.3)
8.8 (8.4–9.2) 9.5 (9.0–10.0) 9.5 (9.1–10.0) 8.7 (8.3–9.2) 8.4 (8.0–8.8)
3.7 (3.5–4.0) 3.8 (3.6–4.1) 4.2 (3.9–4.5) 3.8 (3.5–4.0) 3.7 (3.4–4.0)
4.5 (3.5–5.7) 4.7 (3.7–6.0) 4.8 (3.7–6.1) 4.2 (3.2–5.4) 5.0 (3.8–6.7)
7.1 (6.8–7.5) 11.5 (10.9–12.0) 12.3 (11.7–12.9) 7.8 (7.4–8.2) 7.5 (7.2–7.9)
— — — — —
— — — — —
9.2 (8.8–9.7) 9.0 (8.6–9.4) 8.8 (8.4–9.2)
3.8 (3.5–4.0) 3.9 (3.7–4.2) 3.8 (3.6–4.1)
4.4 (3.4–5.5) 4.7 (3.7–6.0) 4.8 (3.8–6.1) (continued)
Adjusted∗
mean (95% CI) Age 16–54 55–64 65–74 75–84 ≥85 Gender Male Female No. comorbidities 0 1 2 ≥3 Mechanism MVC Fall Other MAIS 1–2 3 4 5–6 Body region of the most severe injury Head Trunk Spine Upper extremities Lower extremities GCS 3–8 9–12 13–15 SBP Normal (≥90) Abnormal (0–89) RR Normal (10–29) Abnormal (0–10 and ≥30) No. admissions in 12 mo before injury 0 1 2 ≥3 Insurance status Provincial public (RAMQ) Road accidents (SAAQ) Work accidents (CSST) Other None/Unknown Discharge destination Home Long stay Rehab Acute care Other Year index admission 1999–2002 2003–2006 2007–2009
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Annals of Surgery r Volume 260, Number 1, July 2014
Hospital Length of Stay After Injury
TABLE 2. (Continued) Variable
Index
Level of index trauma center I 9.2 (8.7–9.7) II 9.1 (8.6–9.6) III 8.9 (8.0–10.0) IV 8.7 (7.8–9.7) Surgery No 8.7 (8.3–9.2) Yes 9.2 (8.8–9.7) Mechanical ventilation No 7.0 (6.7–7.4) Yes 11.5 (11.0–12.1) ICU No 8.0 (7.6–8.4) Yes 10.1 (9.6–10.6) Transfer No 10.4 (9.9–11.0) Yes 7.7 (7.4–8.1)
ICU
Intermediate
4.3 (4.0–4.7) 4.1 (3.8–4.4) 3.6 (3.2–4.1) 3.4 (2.9–3.9)
7.0 (5.4–9.2) 5.1 (3.4–7.5) 4.4 (2.8–7.1) 2.9 (1.7–5.1)
3.5 (3.3–3.8) 4.2 (3.9–4.5)
4.5 (3.6–5.8) 4.7 (3.7–6.0)
2.6 (2.4–2.8) 5.7 (5.3–6.1)
3.9 (3.1–4.9) 5.5 (4.3–7.0)
— —
4.8 (3.7–6.0) 4.5 (3.6–5.7)
3.9 (3.7–4.2) 3.8 (3.5–4.0)
4.7 (3.7–5.9) 4.6 (3.6–5.8)
MAIS indicates maximum abbreviated injury scale score; MVC, motor vehicle collision. ∗ Adjusted for all other variables in the table.
FIGURE 2. Relative effect of independent variables for predicting index, ICU, and intermediate unit length of hospital stay. †p > 0.05. anatomical injury severity, physiological reaction to injury (GCS, RR, and SBP), and ICU admission have all been identified as independent predictors of LOS or extended LOS.3,40–48 Among the few studies that have included nonclinical, nondemographic factors in predictive models, transfer status,3 insurance status,40,41,43,45 and discharge destination41 have been identified as important determinants of LOS or extended LOS. The longer LOS associated with patients transferred to long-term and rehabilitation can be explained by the chronic lack of resources in long-term care institutions. Little data are available on the determinants of ICU LOS in trauma patients but age, injury severity, comorbidities, mechanical ventilation, and surgery have all been identified as predictors of extended ICU LOS and as in our study, sex was found not to be an independent predictor.49,50 C 2014 Lippincott Williams & Wilkins
We did not identify any studies that have assessed the determinants of intermediate care unit LOS for trauma patients, but our data show that predictive factors differ to those for index or ICU LOS, and that information in the trauma registry explains less variation in intermediate care unit LOS than index or ICU LOS. This probably reflects the fact that the use of intermediate care units is mostly determined by nonclinical factors such as bed availability.
Limitations Potential limitations, which may affect the interpretation of results include missing physiological data, population coverage, variation in the definition of intensive or intermediate care units, and the external validity of results. First, multiple imputation of missing www.annalsofsurgery.com | 185
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Annals of Surgery r Volume 260, Number 1, July 2014
Moore et al
GCS and RR data enabled us to use information on all patients but is based on the assumption that data are missing at random.51 However, results with and without imputed data were similar, and data simulations on this and other trauma registries support the hypothesis that imputed physiological data in trauma registries lead to valid effect estimates.28,52 Second, this study is only based on patients admitted to a trauma center, representing approximately 85% of all major trauma admissions in the province.53 We suspect that patients treated in nondesignated hospitals are older but less severely injured, which may have led to a slight overestimation of mean LOS in this study. Third, the definition of ICU and intermediate care unit beds may vary across hospitals, which could have lead to an under- or overestimation of the proportion of index LOS days in ICU or intermediate care units and to an underestimation of the association between risk factors and ICU or intermediate care unit LOS. Along with other data quality issues, the standardization of such definitions is vital to the validity and reliability of performance evaluations based on LOS. Finally, the results of this study may not generalize well to other health care systems. Indeed, mean LOS varies from one health system to another. In addition, in less well-organized trauma systems, admissions to hospitals before the index stay in a trauma center may be more frequent. However, the similarities in predictors of LOS and ICU LOS across trauma systems in the literature suggest that the determinants of LOS and its components identified in this study are likely to generalize well.
Implications LOS has been criticized as a measure of quality because it is influenced by many nonmedical factors including the availability of postacute care41,45 and has been reported to have minimal impact on the cost of hospital admission.54 However, other authors have reported an important impact of extended LOS on costs,10,45 rehabilitation stays, and functional outcome.55 This study highlights the complexities of LOS that should be taken into account when evaluating trauma centers. For example, to counter the influence of nonclinical factors, adjustment could be made for insurance status and discharge destination. To deal with the problem of multiple admissions for the same injury, a variable representing additional LOS days could be added to the risk adjustment model. Finally, to address different levels of resource use influencing cost, weights could be used to represent days spent in ICU, intermediate, or general ward care. A quality indicator based on LOS would allow us to identify hospitals with higher than expected resource use and to monitor resource use within hospitals or trauma systems over time. This information would then enable stakeholders to identify elements of structure (eg, hospital volume, bed availability), clinical processes (eg, waiting time in the ED), or hospital-based outcomes (eg, complications, unplanned surgery) that explain longer than expected LOS and can be used to plan quality improvement activities.
CONCLUSIONS We have shown that mean acute care LOS after injury is underestimated when only information on the index hospitalization is used but that the determinants of LOS do not change when additional consecutive admissions for the same injury are considered. We also demonstrate that days in ICU and intermediate care units contribute significantly to overall LOS and that the determinants of the latter differ to those identified for index LOS. Finally, we observed that resource use for trauma patients in terms of hospital and ICU days are higher than expected according to general admissions, demonstrating the importance of monitoring LOS in trauma patients. This study provides detailed information on the distribution and determinants of acute care LOS after traumatic injury, which should be considered when evaluating trauma care in terms of resource use. 186 | www.annalsofsurgery.com
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