Extended length of stay after surgery: complications, inefficient practice, or sick patients?

Abstract

Importance

With recent health policy focus on shifting risk to providers, hospital leaders are increasing efforts to reduce excessive resource use, such as patients with extended length of stay (LOS) after surgery. However, it is unclear the degree to which extended LOS represents complications, patient illness, or inefficient practice style.

Objective

We sought to examine the influence of complications on hospital extended LOS rate variation after colorectal resections.

Design

Retrospective cohort study.

Setting

Hospitals participating in the 2009 American College of Surgeons National Surgical Quality Improvement Project (199 hospitals)

Participants

Adults undergoing inpatient colorectal resections (N=22,664 patients)

Exposures

Inpatient complications recorded in the ACS-NSQIP dataset. Inpatient complications were identified by their postoperative date of occurrence’s relationship to the patient’s surgical discharge date.

Main outcome measures

Risk-adjusted hospital extended LOS rates, defined as the proportion of patients with hospital stay greater than 75^th percentile for the entire cohort.

Results

Forty-three percent of patients with extended LOS did not have a documented inpatient complication. While there was wide variation in both risk-adjusted extended LOS (15%–35%) and risk-adjusted inpatient complication (12%–29%) rates, there was only weak correlation (Spearman’s rho 0.56) between the two. Only half (52%) of the variation in hospital extended LOS rates was attributable to hospital inpatient complication rates.

Conclusions and Relevance

Much of the variation in hospital risk-adjusted extended LOS rates is not attributable to patient illness or complications and therefore most likely represents differences in practice style. Efforts to reduce excess resource utilization should focus on the efficiency of care, such as increased adoption of enhanced recovery pathways.

INTRODUCTION

With recent policy emphasis on shifting risk to providers, such as bundled payments and pay-for-performance, hospital leaders are looking for ways to improve resource utilization.^1–5 While these policies will encourage hospitals to be more efficient in general, there are few available data to help understand costs after surgery. Because hospitals lack detailed cost data, they commonly use length of stay (LOS) as a proxy for resource utilization. ^6,7 In this context of value-based payment, providers are increasing efforts to better understand and improve resource use and unnecessarily long postoperative hospital stays.

The best strategy to reduce excessive LOS following surgery is unclear, however. There are two common explanations for extended hospital stays following an operation. First, patients experience postoperative complications that extend LOS through management of the complications (e.g. reoperations), so it is possible that provider should focus on preventing and managing complications to improve overall efficiency. However, it is also possible that differences in LOS are due to practice style differences between providers. There is differential adoption of new surgical technologies such as minimally invasive approaches and variable utilization of other efforts to coordinate care processes such as enhanced recovery pathways. ^8,9

A better understanding of the extent to which extended LOS is attributable to patient illness, complications or practice style differences is essential to targeting efforts for improvement. In this context, we studied the relationship between extended postoperative LOS and complications, as well as the extent to which complications account for variation in hospital extended LOS rates.

METHODS

Data source and study population

We analyzed data from the 2009 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) clinical registry. Details regarding data abstraction and quality control have been described previously.¹⁰ Using relevant Current Procedural Terminology codes, we selected adult patients undergoing inpatient laparoscopic or open colorectal resections to form our study cohort.

Outcomes

We examined extended postoperative length of stay (LOS), which we defined as postoperative hospital stay greater than the 75^th percentile. We also examined LOS greater than the 90^th percentile in sensitivity analyses. Hospitals’ extended LOS rates were defined as their proportion of patients with extended LOS. We also assessed complications (wound dehiscence, superficial, deep or organ-space surgical site infection [SSI], myocardial infarction, cardiac arrest, prolonged ventilator requirement, unplanned reintubation, pneumonia, progressive renal insufficiency, acute renal failure, coma, stroke, deep venous thrombosis [DVT] or pulmonary embolism, bleeding requiring greater than 4 units transfusion, graft or prosthetic failure, urinary tract infection [UTI], sepsis or septic shock) and severe complications (those above but excluding DVT, UTI, progressive renal insufficiency and superficial/deep SSI). Because inpatient complications would most likely prolong hospital stay, we focused our assessment on complications occurring before the patient’s discharge date.

Independent Variables

Patient variables recorded in the clinical registry include age, race, sex, indication for operation (from ICD-9 codes), height, weight, functional status, American Society of Anesthesiologists (ASA) class, cardiac, pulmonary, renal, neurologic, endocrine, hematologic and vascular comorbidities, chronic steroid therapy, disseminated cancer, prior operation, 10% or greater weight loss prior to operation, preoperative sepsis, open wound or transfusion requirement, and preoperative laboratory values. We reclassified continuous variables as categorical variables with 5 levels for model entry.

Analysis

We first assessed the proportion of patients with extended LOS that did not experience an inpatient complication or severe complication. We then conducted two hospital analyses: the first assessed the correlation between hospital risk-adjusted extended LOS and complication rates, and the second assessed the extent to which different complications explained the variation in hospital risk-adjusted extended LOS rates.

We started by calculating hospital risk-adjusted extended LOS and complication rates. All risk-adjustment models included patient age, sex, race, ASA class, comorbidities and laboratory variables, as well as procedural (laparoscopic case, emergent procedure) variables to generate predicted outcome probabilities. Model discrimination was fair (c-statistics ranged from 0.774 to 0.818) and calibration was adequate (Hosmer-Lemeshow chi-squared statistics ranged from 6.17 to 15.2).¹¹ Dividing each hospital’s observed outcome rate by the sum of its predicted probabilities generates observed:expected outcome ratios, which when multiplied by the cohort’s outcome rate yield hospitals’ risk-adjusted rates. To further account for random outcome variation, we adjusted hospital risk-adjusted rates using shrinkage estimators derived from hierarchical regression models.^{13, 14} We then used Spearman’s rank correlation test to compare hospital risk-adjusted extended LOS and complication rates.

To assess the extent to which complications explained the variation in risk-adjusted hospital extended LOS rates, we constructed a hierarchical logistic regression model for extended LOS with the hospital specified as the higher level. We serially assessed the proportional change in hospital-level random intercept variance after adding complications (first patient-level complications, then hospital observed complication rates) to the hierarchical model.¹⁴ Finally, we substituted specific severe complication types (surgical site [organ-space SSI or wound dehiscence], pulmonary [unplanned reintubation, prolonged mechanical ventilation, pulmonary embolism and pneumonia], cardiac [cardiac arrest or myocardial infarction], sepsis or septic shock). All models adjusted for patient age, sex, race, ASA class, comorbidities, laboratory values and procedural variables as above.

We performed all analyses using STATA version 12 (StataCorp, College Station, TX). All statistical tests were two-sided with P values < 0.05 considered significant. The study protocol was reviewed and deemed not regulated by the University of Michigan Institutional Review Board.

RESULTS

We identified 22,664 patients undergoing colorectal resections in 199 hospitals participating in ACS-NSQIP in 2009. The median, 75^th and 90^th percentile length of stay (LOS) were 6, 9 and 16 days, respectively. Patients with extended LOS were older, had more comorbidities, underwent more emergent procedures and more often had resections for obstructive etiologies (Table 1). Though patients with extended LOS were more likely to have complications, a large proportion (42.8%) did not have a documented complication or severe complication (55.9%) (Table 1).

Table 1.

Characteristics of 22664 patients undergoing colorectal resections in 199 hospitals participating in ACS-NSQIP in 2009.

	Normal length of stay N=17,576	Extended length of stay N=5,088	p-value
DEMOGRAPHICS
Mean age (years)	61.5	66.2	<0.01
Male (%)	46.3	48.8	<0.01
White (%)	78.5	73.4	<0.01
Independent functional status (%)	93.0	69.3	<0.01
DIAGNOSIS			<0.01
Neoplasm (%)	48.1	33.6
Diverticular disease (%)	28.3	31.4
Obstruction (%)	6.1	11.2
COMORBIDITIES
Median total comorbidities	1.0	3.0	<0.01
Coronary artery disease (%)	6.3	10.6	<0.01
Peripheral vascular disease (%)	1.4	3.5	<0.01
Diabetes (%)	14.5	20.1	<0.01
Chronic obstructive pulmonary disease (%)	5.1	12.7	<0.01
Cerebrovascular disease (%)	6.0	11.8	<0.01
Renal failure/dialysis (%)	1.3	6.3	<0.01
Long-term steroid use (%)	5.5	11.0	<0.01
Preoperative SIRS/sepsis (%)	9.4	34.5	<0.01
OPERATIVE CHARACTERISTICS
Emergency case (%)	11.7	36.5	<0.01
Laparoscopic procedure (%)	40.4	13.6	<0.01
POSTOPERATIVE OUTCOMES
Inpatient complications (%)	7.4	57.2	<0.01
Severe inpatient complications (%)	3.5	44.1	<0.01
Severe surgical site complications	0.3	13.7	<0.01
Pulmonary complications	2.1	30.1	<0.01
Cardiac complications	0.5	3.7	<0.01
Sepsis or septic shock	1.1	21.3	<0.01

SIRS: Systemic inflammatory response syndrome. Surgical site complications include organ-space surgical site infection or wound dehiscence. Pulmonary complications include unplanned reintubation, prolonged mechanical ventilation, pulmonary embolism and pneumonia. Cardiac complications include cardiac arrest requiring cardiopulmonary resuscitation or myocardial infarction

There was wide variation in hospital risk-adjusted outcome rates, but weak correlation between outcomes (Figures 1 and 2). For example, risk-adjusted extended LOS rates (range 14.5%–35.3%) and complication rates (range 12.1%–28.5%) had weak correlation (Spearman’s rho= 0.56, p<0.01) (Figure 2A). The correlation between extended LOS and severe complications was weaker (Spearman’s rho=0.49, p<0.01) (Figure 2B). When extended LOS was defined as the 90^th percentile, the correlation between extended LOS and complications was weaker still (Figure 2C-D).

Figure 1.

Risk-adjusted extended length of stay and inpatient complication rates for colon resections in ACS-NSQIP hospitals 2009. X-axis: hospital risk-adjusted outcome ranking. Y-axis: hospital risk-adjusted outcome (percent) with 95% confidence interval

Figure 2.

Correlation between hospital inpatient complication rates and hospital extended length of stay rates for colon resections, ACS-NSQIP 2009

Table 2 shows the proportion of hospital risk-adjusted extended LOS rate variation attributable to complications. Complications explained more of hospital extended LOS rate variation (36.9%) than severe complications (31.2%). Similarly, hospital complication rates explained more (52.0%) extended LOS rate variation than hospital severe complication rates (47.0%). Surgical site and cardiac complications explained extended LOS rate variation equally (35.5% and 35.4%, respectively) and to a greater extent than pulmonary or septic complications (Table 2). When LOS was defined as the 90^th percentile, cardiac complications accounted for more hospital extended LOS rate variation (52.1%) than other complication types (surgical site 47.7%, septic 32.9%, and pulmonary 32.3%).

Table 2.

Relative ability of patient and hospital-level complications to explain variation in hospital extended length of stay rates

	Proportion of extended LOS rate variance explained by complications (%)
	Any inpatient complication	Hospital inpatient complication rate	Any severe inpatient complication	Hospital severe inpatient complication rate
Extended length of stay defined as 75th percentile	36.9	52.0	31.2	47.0
Extended length of stay defined as 90th percentile	40.4	64.2	28.5	63.0
	Proportion of extended LOS rate variance explained by complication type (%)
	Surgical site	Pulmonary	Cardiac	Septic
Extended length of stay defined as 75th percentile	35.5	33.6	35.4	30.4
Extended length of stay defined as 90th percentile	47.7	32.3	52.1	32.9

Surgical site complications include organ-space surgical site infection or wound dehiscence. Pulmonary complications include unplanned reintubation, prolonged mechanical ventilation, pulmonary embolism and pneumonia. Cardiac complications include cardiac arrest requiring cardiopulmonary resuscitation or myocardial infarction

DISCUSSION

With policy initiatives such as bundled payments and pay-for-performance, hospital leaders have increased efforts to reduce excessive resource utilization.^3–5 Postoperative LOS is a common proxy for episode resource use. A better understanding of the relationship between extended LOS and complications will help providers focus efforts to reduce resource utilization. In this study, we found that a considerable proportion of patients with extended LOS do not have documented complications after a common and morbid procedure. There was weak correlation between hospital risk-adjusted extended LOS and complication rates. Moreover, we found that up to 50 percent of the variation in extended LOS is unexplained by hospital complication rates.

Studies using both administrative and clinical registry data have shown that a considerable proportion of patients with apparently uncomplicated hospital courses have extended lengths of stay. ^7,15,16 Conversely, others have shown that patients with “normal” lengths of stay still have clinically relevant complications.¹⁷ Our study affirms these findings and goes further by quantifying how little variation in hospital extended LOS rates is explained by complications, even after accounting for patient illness. These results suggest that much of the variation in resource utilization surrounding surgical episodes may be caused by practice style differences rather than differences in technical quality or sicker patients.

There is increased attention on understanding and implementing measures that address the efficiency of care delivery. In other patient populations, care coordination and extended care facility availability influence LOS to a large degree. ^8,18 For surgical patients, emerging evidence suggests that process interventions like enhanced recovery pathways are effective at reducing LOS without increasing overall complication rates, but the efficacy of such interventions on a large scale remains unclear. ^9,19–22 With different uptake and implementation of enhanced recovery for colectomy patients, it would be reasonable to assume practice style differences underlie at least a portion of the unexplained variation in hospital extended LOS rates.

There are important limitations to our study. First, our dataset lacked colectomy-specific complications that may better explain extended LOS such as prolonged postoperative ileus, though the expected ileus rate for the cohort is far less than the amount of unexplained extended LOS.²³ Second, while our risk-adjustment models accounted for patient illness, procedure type and acuity, we lacked data on factors such as patient rurality, access to transportation, discharge planning and care coordination which undoubtedly influence LOS as well. Third, we analyzed a common gastrointestinal procedure and our results may not apply to different procedures. Fourth, while LOS is a common proxy for hospital resource utilization, price index adjusted total payments remain a more fair measure of resource utilization.⁶ Finally, our data represent a subset of hospitals with a presumed interest in quality improvement and as such our results may not be generalizable to all hospitals.

Much of the variation between hospitals in their resource use remains unexplained after accounting for patient illness and complications. With increasing emphasis on improving the overall efficiency of episode-based care, a better understanding of practice style variation and how it contributes to differences in resource utilization should help guide improvement efforts apart from improving complication rates. In addition to focusing efforts on complication prevention, hospitals should also focus efforts on implementing and refining processes that eliminate inefficient practice.