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Figure 1.
Index Hospitalization Costs Among Patients Stratified by Readmission Status Within 30 Days
Index Hospitalization Costs Among Patients Stratified by Readmission Status Within 30 Days

Shaded boxes indicate interquartile range (25th to 75th percentiles); horizontal lines, maximum and minimum values of data.

Figure 2.
Index Hospitalization Costs for Patients Without Postoperative Complications
Index Hospitalization Costs for Patients Without Postoperative Complications

Shaded boxes indicate interquartile range (25th to 75th percentiles); horizontal lines, maximum and minimum values of data.

Figure 3.
Index Hospitalization Costs Among Surgeons
Index Hospitalization Costs Among Surgeons

Surgeons are stratified by resection type. The horizontal line within the box represents the median value for the index hospitalization costs; the upper and lower limits of the box represent the 75th and 25th percentiles; and the error bars represent the distribution of the values, with the horizontal lines at the ends of the error bars representing the maximum and minimum values.

Table 1.  
Index Hospitalization Quality Measures
Index Hospitalization Quality Measures
Table 2.  
Univariable and Multivariable Analyses of Factors Associated With Readmission
Univariable and Multivariable Analyses of Factors Associated With Readmission
1.
Berry  JG, Hall  DE, Kuo  DZ,  et al.  Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals.  JAMA. 2011;305(7):682-690.PubMedGoogle ScholarCrossref
2.
Lucas  DJ, Pawlik  TM.  Readmission after surgery.  Adv Surg. 2014;48:185-199.PubMedGoogle ScholarCrossref
3.
Epstein  AM, Jha  AK, Orav  EJ.  The relationship between hospital admission rates and rehospitalizations.  N Engl J Med. 2011;365(24):2287-2295.PubMedGoogle ScholarCrossref
4.
Mullen  MG, LaPar  DJ, Daniel  SK, Turrentine  FE, Hanks  JB, Smith  PW.  Risk factors for 30-day hospital readmission after thyroidectomy and parathyroidectomy in the United States: an analysis of National Surgical Quality Improvement Program outcomes.  Surgery. 2014;156(6):1423-1430.PubMedGoogle ScholarCrossref
5.
Lucas  DJ, Haider  A, Haut  E,  et al.  Assessing readmission after general, vascular, and thoracic surgery using ACS-NSQIP.  Ann Surg. 2013;258(3):430-439.PubMedGoogle ScholarCrossref
6.
Kansagara  D, Englander  H, Salanitro  A,  et al.  Risk prediction models for hospital readmission: a systematic review.  JAMA. 2011;306(15):1688-1698.PubMedGoogle ScholarCrossref
7.
Centers for Medicare & Medicaid Services. Readmission reduction program. 2012. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Readmissions-Reduction-Program.html. Modified January 15, 2016. Accessed August 1, 2015.
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Centers for Medicare & Medicaid Services. CMS to improve quality of care during hospital inpatient stays. https://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2014-Fact-sheets-items/2014-08-04-2.html. August 4, 2014. Accessed August 1, 2015.
9.
Ejaz  A, Semenov  E, Spolverato  G,  et al.  Synchronous primary colorectal and liver metastasis: impact of operative approach on clinical outcomes and hospital charges.  HPB (Oxford). 2014;16(12):1117-1126.PubMedGoogle ScholarCrossref
10.
Wick  EC, Shore  AD, Hirose  K,  et al.  Readmission rates and cost following colorectal surgery.  Dis Colon Rectum. 2011;54(12):1475-1479.PubMedGoogle ScholarCrossref
11.
Abdelsattar  ZM, Birkmeyer  JD, Wong  SL.  Variation in Medicare payments for colorectal cancer surgery.  J Oncol Pract. 2015;11(5):391-395.PubMedGoogle ScholarCrossref
12.
Bodenheimer  T, Fernandez  A.  High and rising health care costs, part 4: can costs be controlled while preserving quality?  Ann Intern Med. 2005;143(1):26-31.PubMedGoogle ScholarCrossref
13.
Birkmeyer  JD, Gust  C, Dimick  JB, Birkmeyer  NJ, Skinner  JS.  Hospital quality and the cost of inpatient surgery in the United States.  Ann Surg. 2012;255(1):1-5.PubMedGoogle ScholarCrossref
14.
Scally  CP, Thumma  JR, Birkmeyer  JD, Dimick  JB.  Impact of surgical quality improvement on payments in Medicare patients.  Ann Surg. 2015;262(2):249-252.PubMedGoogle ScholarCrossref
15.
Charlson  ME, Pompei  P, Ales  KL, MacKenzie  CR.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.  J Chronic Dis. 1987;40(5):373-383.PubMedGoogle ScholarCrossref
16.
Center for Medicare and Medicaid Services. Details for title: FY 2013 Final Rule Tables. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/FY-2013-IPPS-Final-Rule-Home-Page-Items/FY2013-Final-Rule-Tables.html. Accessed August 1, 2015.
17.
Romano  PS, Mark  DH.  Bias in the coding of hospital discharge data and its implications for quality assessment.  Med Care. 1994;32(1):81-90.PubMedGoogle ScholarCrossref
18.
Jencks  SF, Williams  MV, Coleman  EA.  Rehospitalizations among patients in the Medicare fee-for-service program.  N Engl J Med. 2009;360(14):1418-1428.PubMedGoogle ScholarCrossref
19.
Axon  RN, Williams  MV.  Hospital readmission as an accountability measure.  JAMA. 2011;305(5):504-505.PubMedGoogle ScholarCrossref
20.
Tsai  TC, Joynt  KE, Orav  EJ, Gawande  AA, Jha  AK.  Variation in surgical-readmission rates and quality of hospital care.  N Engl J Med. 2013;369(12):1134-1142.PubMedGoogle ScholarCrossref
21.
Gani  F, Lucas  DJ, Kim  Y, Schneider  EB, Pawlik  TM.  Understanding variation in 30-day surgical readmission in the era of accountable care: effect of the patient, surgeon, and surgical subspecialties.  JAMA Surg. 2015;150(11):1042-1049.PubMedGoogle ScholarCrossref
22.
Wennberg  JE.  Practice variations and health care reform: connecting the dots.  Health Aff (Millwood). 2004;(suppl variation):VAR140-VAR144.PubMedGoogle Scholar
23.
Tsai  TC, Orav  EJ, Joynt  KE.  Disparities in surgical 30-day readmission rates for Medicare beneficiaries by race and site of care.  Ann Surg. 2014;259(6):1086-1090.PubMedGoogle ScholarCrossref
24.
Ejaz  A, Kim  Y, Spolverato  G, Taylor  R, Hundt  J, Pawlik  TM.  Understanding drivers of hospital charge variation for episodes of care among patients undergoing hepatopancreatobiliary surgery.  HPB (Oxford). 2015;17(11):955-963.PubMedGoogle ScholarCrossref
25.
Klabunde  CN, Warren  JL, Legler  JM.  Assessing comorbidity using claims data: an overview.  Med Care. 2002;40(8)(suppl):IV-26–IV-35.PubMedGoogle Scholar
26.
Lee  LA, Morell  RC.  Rare complications and national databases.  Anesth Analg. 2009;109(5):1357-1359.PubMedGoogle ScholarCrossref
27.
Gonzalez  AA, Girotti  ME, Shih  T, Wakefield  TW, Dimick  JB.  Reliability of hospital readmission rates in vascular surgery.  J Vasc Surg. 2014;59(6):1638-1643.PubMedGoogle ScholarCrossref
28.
Gonzalez  AA, Shih  T, Dimick  JB, Ghaferi  AA.  Using same-hospital readmission rates to estimate all-hospital readmission rates.  J Am Coll Surg. 2014;219(4):656-663.PubMedGoogle ScholarCrossref
Original Investigation
August 2016

Effect of Index Hospitalization Costs on Readmission Among Patients Undergoing Major Abdominal Surgery

Author Affiliations
  • 1Department of Surgery, University of Illinois Hospital and Health Sciences System, Chicago
  • 2Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland
 

Copyright 2016 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.

JAMA Surg. 2016;151(8):718-724. doi:10.1001/jamasurg.2015.5557
Abstract

Importance  Reduction of postoperative readmissions has been identified as an opportunity for containment of health care costs. To date, the effect of index hospitalization costs on subsequent readmissions, however, has not been examined.

Objectives  To identify the effect of index admission costs on readmission rates and to quantify any potential variation in costs and readmission attributable to the patient, procedure, and surgeon.

Design, Setting, and Participants  Retrospective analysis of the medical records of 4114 patients who underwent a colorectal, pancreatic, or hepatic resection from January 1, 2009, to December 31, 2013, at a tertiary care hospital. Readmission was defined as a second hospitalization within 30 days of discharge from the index hospitalization. Final follow-up was completed on April 24, 2014, and data were analyzed from July 1 to August 1, 2015.

Main Outcomes and Measures  Total inpatient costs of the index hospitalization and readmission rates.

Results  Among 4114 patients who met inclusion criteria (2122 women [51.6%] and 1992 men [48.4%]; median [interquartile range (IQR)] age, 59 [49-69] years), 1760 (42.8%) underwent colorectal resection; 1660 (40.4%), pancreatic resection; and 694 (16.9%), hepatic resection. Seven hundred seven patients were readmitted within 30 days (unadjusted readmission rate, 17.2%), including 328 patients (18.6%) for colorectal procedures, 309 patients (18.6%) for pancreatic procedures, and 70 patients (10.1%) for hepatic procedures (P < .001). The median cost of surgery during the index hospitalization was $24 992 and varied by procedure (colorectal, $22 186; pancreatic, $29 175; hepatic, $22 757; P < .001). The median index length of stay was 7 (IQR, 5-11) days and was higher among patients who were eventually readmitted (8 [IQR, 6-13] vs 7 [IQR, 5-11] days; P < .001). Readmitted patients had a higher incidence of perioperative morbidity during the index hospitalization (169 of 707 [23.9%] vs 662 of 3407 [19.4%]; P = .007). On adjusted analysis, an independent association with a higher risk for readmission was found for African American patients (odds ratio [OR], 1.45; 95% CI, 1.17-1.81), those undergoing pancreatic (OR, 1.99; 95% CI, 1.50-2.63) or colorectal (OR, 1.93; 95% CI, 1.46-2.55) resection, and patients with an observed-to-expected index length of stay of greater than 1 (OR, 1.26; 95% CI, 1.05-1.54) (P ≤ .001 for all). Total index hospitalization costs were higher among patients who were readmitted ($21 312 vs $24 321; P < .001). Further, among patients without a complication during the index hospitalization, total costs remained higher among patients who were eventually readmitted ($26 799 vs $22 462; P < .001). At the surgeon level, readmission rates varied among surgeons performing the same procedure (0%-33% among colorectal surgeons, 13%-38%% among pancreatic surgeons, and 8%-33% among hepatic surgeons; P < .001). Similarly, substantial variation in index hospitalization costs was also observed among surgeons performing the same procedure (coefficient of variation, 118.4% for colorectal, 89.0% for pancreatic, and 85.0% for hepatic).

Conclusions and Relevance  Thirty-day readmission rates among patients undergoing major abdominal surgery vary significantly. Higher index hospitalization costs did not translate into lower readmission rates.

Introduction

Unplanned surgical readmissions have been identified as an opportunity for containment of health care costs in addition to a potential indicator of quality of care.1-3 Given that patients undergoing major surgery are at risk for perioperative complications, hospital readmission after surgery is common. Rates range from 5% to 45%, depending on the type of surgery.4,5 Since 2011, the Centers for Medicare & Medicaid Services began using readmission rates as a quality metric and currently imposes a penalty of as much as 3% against hospital reimbursement for higher than expected risk-adjusted readmission rates.6,7 As of 2014, patients undergoing hip and knee arthroplasty were included as part of this Hospital Readmissions Reduction Program, and plans have been made to include patients who undergo coronary artery bypass graft surgery beginning in 2017.8

Although the cost of readmission has a significant financial effect on the use of health care resources, the costs incurred during the index hospitalization are responsible for most health care spending.9-11 Efforts to reduce health care costs have demonstrated that such initiatives can be performed without hindering the quality of patient care.12-14 Given the ballooning costs of health care, improving the value—outcomes per dollar spent—of health care is imperative. Previous work exploring the relationship between hospital finances and postoperative outcomes9 demonstrated significant variation by surgeon among patients undergoing a hepatic or pancreatic resection at Johns Hopkins Hospital. Further, higher costs of care and the variation in costs did not translate into improved immediate perioperative outcomes.9 To our knowledge, however, no study has specifically analyzed the effect of overall index hospitalization costs or spending on subsequent hospital readmissions. Therefore, we sought to analyze the effect of index hospitalization costs on hospital readmission. In addition, we sought to identify and quantify any potential variation in costs and readmission attributable to the patient, procedure, and surgeon among patients undergoing a colorectal, pancreatic, or hepatic resection.

Box Section Ref ID

Key Points

  • Question: Do higher index hospitalization costs after colorectal, pancreatic, or hepatic resection affect the incidence of readmission?

  • Findings: This retrospective analysis of 4114 patients found significant variation in index hospitalization costs and readmission rates. Furthermore, index hospitalization costs were higher among patients who were eventually readmitted compared with those who were not readmitted, even among patients who had no perioperative morbidity.

  • Meaning: Higher index hospitalization costs did not translate into lower readmission rates.

Methods
Study Population and Data Sources

Patients undergoing a colorectal, pancreatic, or hepatic resection from January 1, 2009, to December 31, 2013, at Johns Hopkins Hospital were identified using the corresponding procedure codes from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM). Patient-level variables were collected, including data on age, sex, race/ethnicity, and the presence of a preoperative comorbidity. Patient comorbidity was defined according to the Charlson Comorbidity Index (calculated as number of comorbidities; range, 0-13).15 In addition to patient-level variables, data pertaining to length of stay (LOS), observed-to-expected index LOS (O:E LOS), type of surgery, and development of in-hospital postoperative complications were collected from each patient record. The expected LOS was defined as the calculated geometric mean estimated LOS based on each individual Medicare severity diagnosis-related group for the fiscal year 2014.16 The presence of an in-hospital perioperative complication was ascertained through discharge ICD-9-CM diagnosis codes as previously described17 and included minor infections (urinary tract infections, surgical site infections and Clostridium difficile infections), major infections (sepsis, ventilator-associated pneumonia, and drug-resistant infections), transient ischemic attack, cerebrovascular attack, myocardial infarction, venous thromboembolism events (deep vein thrombosis and pulmonary embolism), and disseminated intravascular coagulation. Final follow-up was completed by April 21, 2014. The institutional review board of The Johns Hopkins University approved this study and waived informed consent for record review. Data were deidentified.

Index hospitalization was defined as the hospitalization in which the procedure of interest was performed. Readmission was defined as a rehospitalization within 30 days of discharge from the index hospitalization. Rehospitalizations that occurred more than 30 days after the index hospitalization and planned rehospitalizations (ie, chemotherapy or diagnostic procedures) were excluded. Patients who did not survive to hospital discharge were also excluded from the study.

Statistical Analysis

Data were analyzed from July 1 to August 1, 2015. Discrete variables were described as medians with interquartile ranges (IQRs), whereas categorical variables were reported as totals and frequencies. Univariable comparisons were assessed using the χ2 test, analysis of variance, or Mann-Whitney test as appropriate. Univariable and multivariable logistic regression models were constructed to determine the association of relevant patient and surgeon variables associated with readmission. The most parsimonious models were created using a stepwise approach that included factors of clinical importance or that were statistically significant on univariable analysis. Variations in the index hospital costs were compared by calculating the coefficient of variation (CV). All analyses were performed using STATA software (version 13.0; StataCorp), and a 2-tailed P < .05 was considered statistically significant.

Results
Baseline Patient Characteristics and Operative Details

The study identified 4114 patients who underwent a colorectal (1760 [42.8%]), pancreatic (1660 [40.4%]), or hepatic (694 [16.9%]) resection and met the inclusion criteria (eTable in the Supplement). The median age of the entire cohort was 59 (IQR, 49-69) years. Most of the patients were women (2122 [51.6%]) and white (3211 [78.1%]). Comorbidities were common, with a median Charlson Comorbidity Index of 2 (IQR, 0-6); 1664 patients (40.4%) had a median Charlson Comorbidity Index of greater than 3.

Index Hospitalization Outcomes and Costs

Total LOS among the entire cohort was 7 (IQR, 5-11) days (Table 1) and varied by resection type (colorectal, 7 [IQR, 5-11] days; pancreatic, 8 [IQR, 6-13] days; hepatic, 5 [IQR, 3-7]; P < .001). Based on the calculated expected LOS, 1733 patients (42.1%) had an O:E LOS of greater than 1. A perioperative complication occurred in 831 patients (20.2%) and was more common after colorectal (390 of 1760 [22.2%]) and pancreatic (336 of 1660 [20.2%]) resections compared with hepatic resections (105 of 694 [15.1%]; P < .001). At the time of discharge, most patients were discharged home (3130 of 4114 [76.1%]), whereas a subset of patients was discharged with home health care services (789 of 4114 [19.2%]) or to a rehabilitation or long-term care facility (194 of 4114 [4.7%]).

Median total index hospitalization costs were $24 992 (IQR, $19 096-$36 715) for the entire cohort and varied by resection type (colorectal, $22 186; pancreatic, $29 175; hepatic, $22 757; P < .001). As expected, increasing LOS and the presence of an in-hospital complication was associated with an increase in total costs. Patients who experienced an in-hospital complication spent 8 days longer in the hospital compared with patients who did not have a complication (14 [IQR, 9-21] vs 6 [IQR, 5-9] days). The occurrence of a complication resulted in an increase of $19 855 in median hospitalization costs ($42 850 vs $22 995; P < .001). Furthermore, patients undergoing laparoscopic operations had an overall lower median index hospitalization cost compared with patients undergoing an open operation ($17 545 vs $24 769), largely owing to an overall shorter LOS (5 vs 8 days) (P < .001 for both).

Readmission Frequency and Patterns

Among the entire cohort, 707 patients (17.2%) were readmitted within 30 days, most commonly owing to postoperative infection (208 [29.4%]). Patients were more commonly readmitted after a colorectal (328 of 1760 [18.6%]) or a pancreatic (309 of 1660 [18.6%]) resection compared with a liver resection (70 of 694 [10.1%]) (P < .001). Patients who were readmitted had a higher incidence of in-hospital complications (169 of 707 [23.9%]) than those not readmitted within 30 days of index hospitalization discharge (662 of 3407 [19.4%]; P < .001).

At the patient level, the incidence of readmission was higher among patients of minority race/ethnicity (black, 126 of 561 [22.5%]; Asian, 20 of 101 [19.8%]) compared with white patients (525 of 3211 [16.4%]; P < .001). Furthermore, readmission was higher among patients with an O:E LOS of greater than 1 during the index hospitalization (362 of 707 [51.2%] vs 345 of 707 [48.8%]; P < .001) and among patients discharged with home health care services (197 of 789 [25.0%]) or to a rehabilitation or long-term care facility (40 of 194 [20.6%]; P < .001). At the surgeon level, readmission rates varied greatly among surgeons performing the same procedure. For example, surgeon-specific readmission rates ranged from 0% to 33% among colorectal surgeons, 13% to 38% among pancreatic surgeons, and 8% to 33% among hepatic surgeons (eFigure in the Supplement).

After accounting for all measurable confounders, several factors were associated with increased odds of readmission (Table 2). For example, African American patients demonstrated 45% greater odds for readmission compared with white patients (odds ratio [OR], 1.45; 95% CI, 1.16-1.81; P = .001). Similarly, patients undergoing a colorectal (OR, 1.93; 95% CI, 1.46-2.55; P < .001) or a pancreatic (OR, 1.99; 95% CI, 1.50-2.63; P < .001) resection also demonstrated increased odds for readmission. Furthermore, patients with an index hospitalization O:E LOS of greater than 1 (OR, 1.27; 95% CI, 1.05-1.54; P = .02) and patients who incurred costs of greater than the 75th percentile for their procedure type (OR, 1.41; 95% CI, 1.13-1.75; P = .002) during the index admission demonstrated increased odds for readmission.

Variability of Index Hospitalization Costs and Effect on Readmission

Total index hospitalization costs were higher among patients who were eventually readmitted ($29 312) compared with patients who were not readmitted within 30 days of the index hospital discharge ($24 321; P < .001) (Figure 1). This difference is partially owing to the fact that the median index LOS was higher among patients who were eventually readmitted (8 [IQR, 6-13] vs 7 [IQR, 5-11] days; P < .001). Among patients undergoing laparoscopic operations, patients eventually readmitted had higher index hospital costs vs patients who were not readmitted ($19 160 vs $17 463; P = .002). Furthermore, among patients who did not experience a complication during the index hospitalization, total costs were $4337 higher among patients who were eventually readmitted ($26 799 vs $22 462; P < .001).

In a subset analysis of patients undergoing colorectal resection, 180 (10.2%) of these patients were admitted directly from the emergency department, potentially indicating an urgent or emergent operation. After excluding this subset of patients, those undergoing an elective colorectal operation who were eventually readmitted still had longer index LOS (8 vs 6 days) and higher index hospitalization costs ($27 483 vs $21 349) compared with patients who were not readmitted (P < .001 for both). Furthermore, patients undergoing resection for malignant disease (341 [19.4%]) also had higher total index costs if they were eventually readmitted ($27 722 vs $20 048; P < .001).

As represented by the CV, substantial variation in index hospitalization costs was noted by resection type (Figure 2). The CV was highest among patients undergoing a colorectal (118.4%) compared with a pancreatic (89.0%) or a hepatic (85.3%) resection (P < .001). In addition, even among patients who did not develop postoperative complications, the CV for total costs was higher among patients undergoing a colorectal (67.6%) vs a pancreatic (47.8%) or a hepatic (41.6%) resection. Substantial variation in index hospitalization costs was also observed among surgeons performing the same procedure (Figure 3).

Discussion

Reduction of unplanned hospital readmission after major surgery has been identified by hospitals and health care professionals as a potential target to reduce unwanted health care costs.1,3,18 Furthermore, in an era of transparency, surgeon and hospital readmission rates are publicly reported and used as an indicator of the quality of care.1-3 Although the utility of individual hospital and surgeon readmission rates as an accurate indicator of quality of care is debatable, as many as 79% of surgical readmissions have been identified as potentially preventable.6,19,20 Given the increasing costs of health care, increasing efforts to improve the value of care defined as the outcomes per dollar spent to deliver high-quality, low-cost care have been undertaken. Ejaz et al9 previously demonstrated that significant variation exists at the surgeon level in index hospitalization costs among patients after a hepatic or a pancreatic resection. Moreover, the investigators9 found that increased spending did not translate into improved immediate outcomes. The present study expands on this work and is, to our knowledge, the first report to analyze specifically the effect of overall index hospitalization spending and costs and their effect on subsequent hospital readmissions. Among patients undergoing major abdominal surgery, we found significant variation in readmission rates at the patient and surgeon levels. Furthermore, total index hospitalization costs were also noted to vary significantly at the patient, surgeon, and procedure levels. Perhaps more importantly, we identified that higher index hospitalization costs after major abdominal surgery did not yield a lower rate of readmission, even among patients who did not experience a perioperative complication.

Previous studies assessing the in-hospital cost of each episode of surgery have focused largely on the effect of cost on immediate perioperative outcomes.18,19,21 Data from the present study further expand on these previous studies by demonstrating that increased index hospitalization costs did not translate into a lower incidence of readmission after major abdominal surgery. In fact, patients who were readmitted within 30 days of the index hospital discharge had higher total index hospitalization costs by nearly $5000. These results add to the growing body of literature highlighting the mismatch in health care spending and perioperative clinical outcomes. For example, Birkmeyer and colleagues13 previously found that hospitals with high complication rates had significantly higher Medicare payments. A subsequent study14 demonstrated that hospitals that reduced rates of complications over time had significant reductions in Medicare payments. These data reiterate that quality improvements can be implemented while decreasing total health care expenditure (ie, improving the value of health care). Furthermore, although much attention has been focused on the variation in readmission, index hospitalization costs are responsible for most health care costs after surgery.11 These costs compound the large cost of readmission, estimated at $300 million in excess costs annually among patients undergoing colorectal surgery alone.10 Taken together, our results demonstrate the importance of reducing index hospitalization costs and that doing so may also have a potential positive effect on reducing the costs associated with readmission.

Unwanted variations in health care are defined as variations not explained by illness, patient preference, or the dictates of evidenced-based medicine.22 Minimizing this variation is a key component when attempting to improve the value of care. Our data demonstrate that significant variation exists among patients undergoing major abdominal surgery with regard to the incidence of readmission. At the patient level, our multivariable regression model found that African American patients were 45% more likely to be readmitted compared with nonminority patients. These data are consistent with those of several previous studies21,23 that have identified minority race as an independent risk factor for readmission. Gani et al21 reported similar findings, suggesting that this disparity in readmission may be driven by social factors outside the control of the hospital or the surgeon. Furthermore, we noted that patients who had a higher index hospitalization O:E LOS were 1.41 times more likely to be readmitted. These factors remained significant even after controlling for the presence of an in-hospital complication. Collectively, these data should help to identify patients at increased risk for readmission and prompt interventions aimed at reducing this potentially preventable event.

Significant variation was also noted in total hospitalization costs after colorectal, pancreatic, and hepatic resections. Patients undergoing colorectal surgery had a higher CV in index hospitalization costs (118.4%) compared with patients undergoing a pancreatic (89.0%) or a hepatic (85.3%) resection. The cost-spending variation likely was owing to the high incidence of perioperative morbidity and varying levels of complexity encompassed in patients undergoing colorectal surgery. Accordingly, this cost variation persisted across surgical specialties (CV range, 41.6%-67.6%) among patients who did not have an in-hospital complication after surgery. However, procedure complexity did not explain the entirety of the cost variation seen in the data. In fact, significant variation existed among surgeons performing similar resection types. Although not specifically addressed in this study, a previous report24 found that variations in LOS and operating room, laboratory, radiology, and supply costs were the main drivers of this variation. As such, further studies should be conducted to identify and potentially target unnecessary spending and consequently improve health care quality and value.

The present study has several limitations that should be considered when interpreting the data, most of which are owing to the inherent limitations of administrative data. First, the data did not reflect all clinical and socioeconomic variables likely to be associated with health care costs and readmission. Second, the accuracy of coding for comorbid conditions has been reported to vary in administrative data sets.17,25,26 Similarly, those patients undergoing robotic operations were not captured in this data set. Finally, because the study was performed in a tertiary referral center, readmission rates may be inaccurate; previous studies27,28 have shown that same-hospital readmission rates are often lower than all-hospital readmission rates. This limitation, however, would only underestimate the true burden of readmission after major surgery noted in our analyses.

Conclusions

Readmission among patients undergoing a colorectal, pancreatic, or hepatic resection is common and occurs in more than 1 of 6 patients. Significant variation exists in hospitalization costs after major surgery with significant variation noted by procedure and surgeon. Higher index hospitalization costs did not translate into lower readmission rates. Further studies should aim to target this unwanted variation in health care spending in an effort to lower hospitalization costs without reducing the quality of health care.

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Article Information

Corresponding Author: Timothy M. Pawlik, MD, MPH, PhD, Department of Surgery, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 688, Baltimore, MD 21287 (tpawlik1@jhmi.edu).

Accepted for Publication: December 1, 2015.

Published Online: February 24, 2016. doi:10.1001/jamasurg.2015.5557.

Author Contributions: Dr Pawlik had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Ejaz, Gonzalez, Pawlik.

Acquisition, analysis, or interpretation of data: Ejaz, Gonzalez, Gani.

Drafting of the manuscript: Ejaz, Gani.

Critical revision of the manuscript for important intellectual content: Ejaz, Gonzalez, Pawlik.

Statistical analysis: Ejaz, Gani.

Administrative, technical, or material support: Gani, Pawlik.

Study supervision: Pawlik.

Conflict of Interest Disclosures: None reported.

Previous Presentation: This paper was presented at the 11th Annual Academic Surgical Congress; February 4, 2016; Jacksonville, Florida.

References
1.
Berry  JG, Hall  DE, Kuo  DZ,  et al.  Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals.  JAMA. 2011;305(7):682-690.PubMedGoogle ScholarCrossref
2.
Lucas  DJ, Pawlik  TM.  Readmission after surgery.  Adv Surg. 2014;48:185-199.PubMedGoogle ScholarCrossref
3.
Epstein  AM, Jha  AK, Orav  EJ.  The relationship between hospital admission rates and rehospitalizations.  N Engl J Med. 2011;365(24):2287-2295.PubMedGoogle ScholarCrossref
4.
Mullen  MG, LaPar  DJ, Daniel  SK, Turrentine  FE, Hanks  JB, Smith  PW.  Risk factors for 30-day hospital readmission after thyroidectomy and parathyroidectomy in the United States: an analysis of National Surgical Quality Improvement Program outcomes.  Surgery. 2014;156(6):1423-1430.PubMedGoogle ScholarCrossref
5.
Lucas  DJ, Haider  A, Haut  E,  et al.  Assessing readmission after general, vascular, and thoracic surgery using ACS-NSQIP.  Ann Surg. 2013;258(3):430-439.PubMedGoogle ScholarCrossref
6.
Kansagara  D, Englander  H, Salanitro  A,  et al.  Risk prediction models for hospital readmission: a systematic review.  JAMA. 2011;306(15):1688-1698.PubMedGoogle ScholarCrossref
7.
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