Risk factors for unplanned readmission within 30 days after pediatric neurosurgery: a nationwide analysis of 9799 procedures from the American College of Surgeons National Surgical Quality Improvement Program

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  • Department of Neurological Surgery, The University of Alabama at Birmingham, Alabama
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OBJECTIVE

Hospital readmission rate is increasingly used as a quality outcome measure after surgery. The purpose of this study was to establish, using a national database, the baseline readmission rates and risk factors for patient readmission after pediatric neurosurgical procedures.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program–Pediatric database was queried for pediatric patients treated by a neurosurgeon between 2012 and 2013. Procedures were categorized by current procedural terminology (CPT) code. Patient demographics, comorbidities, preoperative laboratory values, operative variables, and postoperative complications were analyzed via univariate and multivariate techniques to find associations with unplanned readmissions within 30 days of the primary procedure.

RESULTS

A total of 9799 cases met the inclusion criteria, 1098 (11.2%) of which had an unplanned readmission within 30 days. Readmission occurred 14.0 ± 7.7 days postoperatively (mean ± standard deviation). The 4 procedures with the highest unplanned readmission rates were CSF shunt revision (17.3%; CPT codes 62225 and 62230), repair of myelomeningocele > 5 cm in diameter (15.4%), CSF shunt creation (14.1%), and craniectomy for infratentorial tumor excision (13.9%). The lowest unplanned readmission rates were for spine (6.5%), craniotomy for craniosynostosis (2.1%), and skin lesion (1.0%) procedures. On multivariate regression analysis, the odds of readmission were greatest in patients experiencing postoperative surgical site infection (SSI; deep, organ/space, superficial SSI, and wound disruption: OR > 12 and p < 0.001 for each). Postoperative pneumonia (OR 4.294, p < 0.001), urinary tract infection (OR 4.262, p < 0.001), and sepsis (OR 2.616, p = 0.006) also independently increased the readmission risk. Independent patient risk factors for unplanned readmission included Native American race (OR 2.363, p = 0.019), steroid use > 10 days (OR 1.411, p = 0.010), oxygen supplementation (OR 1.645, p = 0.010), nutritional support (OR 1.403, p = 0.009), seizure disorder (OR 1.250, p = 0.021), and longer operative time (per hour increase, OR 1.059, p = 0.029).

CONCLUSIONS

This study may aid in identifying patients at risk for unplanned readmission following pediatric neurosurgery, potentially helping to focus efforts at lowering readmission rates, minimizing patient risk, and lowering costs for health care systems.

ABBREVIATIONS

ACS = American College of Surgeons; ASA = American Society of Anesthesiologists; AST = aspartate transaminase; BUN = blood urea nitrogen; CPT = current procedural terminology; CVA = cerebrovascular accident; DVT = deep venous thrombosis; HIPAA = Health Insurance Portability and Accountability Act; ICD-9 = International Classification of Diseases, Ninth Revision; MMC = myelomeningocele; NSQIP-P = National Quality Improvement Program–Pediatric; PE = pulmonary embolism; PT = prothrombin time; PTT = partial thromboplastin time; ROC = receiver operating characteristic; SIRS = systemic inflammatory response syndrome; SSI = surgical site infection; UTI = urinary tract infection; WBC = white blood cell.

OBJECTIVE

Hospital readmission rate is increasingly used as a quality outcome measure after surgery. The purpose of this study was to establish, using a national database, the baseline readmission rates and risk factors for patient readmission after pediatric neurosurgical procedures.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program–Pediatric database was queried for pediatric patients treated by a neurosurgeon between 2012 and 2013. Procedures were categorized by current procedural terminology (CPT) code. Patient demographics, comorbidities, preoperative laboratory values, operative variables, and postoperative complications were analyzed via univariate and multivariate techniques to find associations with unplanned readmissions within 30 days of the primary procedure.

RESULTS

A total of 9799 cases met the inclusion criteria, 1098 (11.2%) of which had an unplanned readmission within 30 days. Readmission occurred 14.0 ± 7.7 days postoperatively (mean ± standard deviation). The 4 procedures with the highest unplanned readmission rates were CSF shunt revision (17.3%; CPT codes 62225 and 62230), repair of myelomeningocele > 5 cm in diameter (15.4%), CSF shunt creation (14.1%), and craniectomy for infratentorial tumor excision (13.9%). The lowest unplanned readmission rates were for spine (6.5%), craniotomy for craniosynostosis (2.1%), and skin lesion (1.0%) procedures. On multivariate regression analysis, the odds of readmission were greatest in patients experiencing postoperative surgical site infection (SSI; deep, organ/space, superficial SSI, and wound disruption: OR > 12 and p < 0.001 for each). Postoperative pneumonia (OR 4.294, p < 0.001), urinary tract infection (OR 4.262, p < 0.001), and sepsis (OR 2.616, p = 0.006) also independently increased the readmission risk. Independent patient risk factors for unplanned readmission included Native American race (OR 2.363, p = 0.019), steroid use > 10 days (OR 1.411, p = 0.010), oxygen supplementation (OR 1.645, p = 0.010), nutritional support (OR 1.403, p = 0.009), seizure disorder (OR 1.250, p = 0.021), and longer operative time (per hour increase, OR 1.059, p = 0.029).

CONCLUSIONS

This study may aid in identifying patients at risk for unplanned readmission following pediatric neurosurgery, potentially helping to focus efforts at lowering readmission rates, minimizing patient risk, and lowering costs for health care systems.

Unplanned hospital readmissions after surgery present medical and financial challenges for health care systems and have emerged as an important measure of health care quality and efficiency.2,14,18 Recent health care reforms have led the Centers for Medicare & Medicaid Services to penalize providers for higher rates of unplanned readmissions.7 Furthermore, unplanned readmissions provide a quality outcome metric that may prove useful in quality improvement, patient risk stratification, and counseling patients and families prior to operations.2,14,18 Previous studies have demonstrated that readmission in pediatric patients can be accurately predicted from preexisting patient conditions and the severity of the condition necessitating admission.3,13

Unplanned readmission has not been well studied in pediatric neurosurgery despite growing attention paid to unplanned readmission as a quality outcome measure. Pediatric neurosurgery had the highest morbidity and mortality rates of any pediatric surgical specialty in a betaphase report of the American College of Surgeons (ACS) National Surgical Quality Improvement Program–Pediatric (NSQIPP) database, indicating a need to assess patient risk factors for complications, readmission, and other outcome measures in neurosurgery.4 Previous studies have investigated return to the health care system (readmission or reoperation) after pediatric neurosurgery at a single institution9,21,26 and 30-day outcomes after pediatric shunt surgery;20 to our knowledge, however, no study has used a national, multiinstitutional patient database with followup to analyze risk factors for readmission after any pediatric neurosurgical procedure. Identifying the baseline rate of readmission for common pediatric neurosurgical procedures is useful to provide a benchmark for quality improvement efforts. Additionally, examining the risk factors for unplanned readmission will facilitate evidence-based patient risk stratification by health care systems to develop guidelines to reduce the likelihood of unplanned readmission.

The purpose of this study was to analyze patient and operative risk factors for unplanned readmission within 30 days of primary pediatric neurosurgical procedures by using a national surgical patient database with follow-up.

Methods

Data Source

The ACS-NSQIP-P is a nationwide, prospectively collected patient database with over 50 participating institutions and more than 300 patient variables.1 It includes the following de-identified and Health Insurance Portability and Accountability Act (HIPAA)–compliant variable categories: patient demographics, comorbidities, operative variables, preoperative lab values, primary procedure current procedural terminology (CPT) codes, International Classification of Diseases, Ninth Revision (ICD-9) codes, and 30-day postoperative events such as readmission, reoperation, mortality, and complications.

Rates of discrepancies between data abstractors are less than 2% as data abstractors are trained by the ACS to ensure the collection of high-quality data.1 Patient followup is performed by telephone or letter for a maximum of 30 days after discharge.1 Previous studies have shown that the NSQIP-P achieved 91.4% confirmed 30-day followup.4 Institutional participation in the NSQIP is associated with reductions in postoperative adverse events11 and allows for a more thorough risk-adjusted analysis than an institutional administrative database.25 The NSQIP has been shown to capture all-cause and unplanned readmission occurrences more accurately than information from medical records regarding the cause of readmission.22 Our institution does not require institutional review board approval for NSQIP studies given that NSQIP data are non-identifiable and HIPAA compliant.24

Data Acquisition

We queried the NSQIP-P database for patients younger than 18 years (at the time of the procedure) who had undergone a procedure performed by a neurosurgeon or pediatric neurosurgeon during the period from 2012 to 2013. Procedures were grouped by CPT codes into the following procedural categories: spine; craniotomy for craniosynostosis; craniotomy for neoplasm; craniotomy for Chiari decompression; shunt or ventricular catheter placement; shunt or ventricular catheter revision, removal, or irrigation; myelomeningocele (MMC) repair; skin lesion; and other. Procedure categories and specific CPT codes within each category are listed in Fig. 1.

FIG. 1.
FIG. 1.

Cohort selection by surgical subspecialty and procedural classification by CPT code. N = number of cases.

Patient demographic information included age, sex, and race. Patient comorbidities of interest included obesity, pulmonary comorbidity, gastrointestinal comorbidity, renal comorbidity, CNS comorbidity, cardiac comorbidity, steroid use (within 30 days before the principal procedure or at the time the patient was being considered as a candidate for surgery; it did not include short-term use, such as a 1-time pulse, limited short course, or taper of ≤ 10 days), chemotherapy within 30 days prior to surgery, radiotherapy within 90 days prior to surgery, open wound (with or without infection), tracheostomy at the time of surgery, immune disease or immunosuppressant use, nutritional support (intravenous or nasogastric tube), bleeding disorder, hematological disorder, current or previous history of malignancy, history of prematurity, intraventricular hemorrhage, preoperative systemic inflammatory response syndrome (SIRS) or sepsis within 48 hours prior to surgery, and congenital malformation of any organ system (a detailed list of conditions included within each NSQIP-P categorical comorbidity variable is shown in Supplement S1).

Operative and hospital variables of interest included hospital length of stay; inpatient or outpatient status; concurrent procedure status; prior operation within 30 days; transfer status; discharge destination; operative time; American Society of Anesthesiologists (ASA) score; blood transfusion; elective, urgent, or emergent triage; and wound classification.

Preoperative lab values of interest included hypoalbuminemia, hyponatremia, hypernatremia, elevated white blood cell (WBC) count, thrombocytopenia, elevated aspartate transaminase (AST), elevated blood urea nitrogen (BUN), abnormal prothrombin time (PT), and abnormal partial thromboplastin time (PTT).

Noted postoperative complications included infections (surgical site infection [SSI], sepsis, urinary tract infection [UTI], pneumonia, central line bloodstream infection), wound disruption, unplanned intubation, renal failure or insufficiency, coma lasting more than 24 hours, cerebrovascular accident (CVA; stroke or intracerebral hemorrhage) or intracranial hemorrhage, seizure, peripheral nerve injury, cardiac arrest, graft or prosthesis failure, deep venous thrombosis (DVT), and pulmonary embolism (PE). The NSQIP-P data on time to postoperative complications were analyzed.

Unplanned readmission is defined in the NSQIP database as “any unplanned readmission for any reason within 30 days of the principal surgical procedure. The readmission has to be classified as an ‘inpatient’ stay by the readmitting hospital, or reported by the patient/family as such.”1 Unplanned readmission is coded in the NSQIP “if the readmission was unplanned.” Previous studies have demonstrated that an unplanned readmission designation in the NSQIP has greater than 95% agreement with hospital chart records regarding planned versus unplanned readmission designation.22

We defined readmission risk factors as any patient characteristic or event (pre- or postoperatively) that increased the likelihood of postoperative readmission. This definition included postoperative complications (for example, SSI) that could also be reasons for readmission.

Data Analysis

Univariate analysis of unplanned readmission outcome association with procedure type, patient demographics, patient comorbidities, preoperative lab values, operative variables, and postoperative complications was performed using the chi-square test, Fisher's exact test, or univariate logistic regression where appropriate. Variables with significance of p ≤ 0.20 in the univariate analyses were then entered into a multivariate analysis via binary logistic regression and were considered independently significant when p ≤ 0.05. As a secondary analysis, we applied a Bonferroni correction to the univariate analysis to correct for the higher risk of Type I error due to the use of over 100 independent variables. In this case, only variables with p ≤ 0.002 in the univariate analysis were entered into the multivariate analysis (the αcorrected value for reaching significance in the Bonferroni correction is calculated by dividing the original α value—in our case, 0.2—by the number of independent variables in the analysis). Receiver operating characteristic (ROC) curve analysis was performed for multivariate regression model validation. Statistical analyses were performed using SPSS version 22.0 (IBM Corp.).

Results

A total of 9799 cases met our inclusion criteria, 1098 (11.2%) of which had an unplanned readmission within 30 days. An additional 166 readmissions were planned, making a total of 1264 postoperative readmissions within 30 days. The average time to unplanned readmission after the primary procedure was 14.04 ± 7.74 days (mean ± SD).

Procedures with the highest unplanned readmission rates included replacement or irrigation of ventricular catheter (CPT code 62225, commonly used to describe revision of the proximal catheter of a shunt system, 19.7% readmitted), replacement or revision of CSF shunt (CPT code 62230, used to describe revision of a valve or distal catheter in a shunt system, 16.0% readmitted), MMC repair > 5-cm diameter (CPT code 63706, 15.4% readmitted), creation of CSF shunt (CPT code 62223, 14.1% readmitted), and craniectomy for excision of infratentorial brain tumor (CPT code 61518, 13.9% readmitted). Mortality for 3 of these procedures (MMC repair, shunt placement, and infratentorial tumor excision) was greater than the mortality for the general pediatric neurosurgical population in this study (among the 9799 cases). All but 1 of the 5 procedures with the highest readmission rates were relatively common, with each of the 4 accounting for more than 5% of the total procedures performed (MMC repair > 5 cm accounted for only 1.3% of all procedures). The highest rates of unplanned readmission by procedure are shown in Table 1.

TABLE 1.

Highest 30-day unplanned readmission rates by individual procedure

CPT CodeProcedure DescriptionNo.% of All Procedures% Unplanned Readmissions
62225Replacement or irrigation of ventricular catheter8678.819.7
62230Replacement or revision of CSF shunt152115.516.0
63706Repair of MMC 5-cm diameter1231.315.4
62223CSF shunt creation107210.914.1
61518Craniectomy for infratentorial tumor excision5615.713.9

Rates of unplanned readmission varied significantly according to procedural category (as defined by lists in Fig. 1), ranging from 1.0% for skin lesion procedures to 16.8% for shunt revision, removal, and irrigation procedures. Two procedure categories showed no significant difference in the rate of unplanned readmission compared with all other procedures: craniotomy for neoplasm and other (primarily baclofen pump placement procedures). Procedure category associations with unplanned readmission can be found in Table 2.

TABLE 2.

Procedure category association with unplanned readmission on univariate analysis*

Procedure Category% ReadmittedNo. (%)Crude OR95% CIp Value
Unplanned ReadmissionNo Unplanned Readmission
Shunt/ventricular catheter revision, removal, irrigation16.8471 (42.9)2327 (26.7)2.0581.809–2.340<0.001
MMC repair14.434 (3.1)202 (2.3)1.3440.930–1.9440.117
Shunt/ventricular catheter placement13.4187 (17.0)1205 (13.8)1.2771.079–1.5120.005
Craniotomy for neoplasm11.8157 (14.3)1169 (13.4)1.0760.899–1.2880.426
Other10.636 (3.3)303 (3.5)0.9400.661–1.3350.793
Craniotomy for Chiari malformation7.079 (7.2)1057 (12.1)0.5610.442–0.711<0.001
Spine6.5120 (10.9)1734 (19.9)0.4930.405–0.600<0.001
Craniotomy for craniosynostosis2.113 (1.2)605 (7.0)0.1600.092–0.279<0.001
Skin lesion1.01 (0.1)99 (1.1)0.0790.011–0.568<0.001

Statistical analysis was performed using binary logistic regression and chi-square test. Complete procedure categorization, including CPT codes within each category, appears in Fig. 1.

Unadjusted odds ratio with respect to each variable's null state; that is, the odds ratio is in reference to all other procedures not in that individual category.

Primarily baclofen pump placement (82% of procedures in this category).

Some patient characteristics and demographics, including length of hospitalization, prior operation within 30 days of the current procedure, admission through the emergency room, discharge to home compared to other types of discharges, and Native American race, were significantly different between readmitted and nonreadmitted groups on univariate analysis. No difference was seen for age, neonate status, patient sex, inpatient or outpatient status, white race, African American race, Asian race, Pacific Islander race, unknown race, concurrent procedure, or transfer from an outside hospital or rehab facility. A longer hospitalization was a significant protective factor for unplanned readmission via univariate logistic regression (OR = 0.993 per day increase, 95% CI = 0.987–0.999, p = 0.033). Patient demographics and characteristics are displayed in Table 3.

TABLE 3.

Patient demographic association with unplanned readmission on univariate analysis*

ParameterUnplanned ReadmissionNo Unplanned ReadmissionCrude OR95% CIp Value
Age in yrs (range)5.3 (1.1–12.0)5.8 (1.0–11.9)1.0020.991–1.0130.781
No. of neonates (%)79 (7.2)649 (7.4)0.9620.755–1.2260.807
Total LOS in days (range)3 (2–7)3 (2–5)0.9930.987–0.9990.033
Sex (no. [%])
  Male593 (54.0)4661 (53.6)1.0180.897–1.1540.797
  Female505 (46.0)4040 (46.4)Ref
Reported race (no. [%])0.183
  White813 (74.0)6391 (73.4)Ref
  African American149 (13.6)1157 (13.3)1.0120.841–1.2190.897
  Asian25 (2.3)194 (2.2)1.0130.664–1.5460.952
  Native American12 (1.1)45 (0.5)2.0961.104–3.9790.024
  Pacific Islander2 (0.2)22 (0.2)0.7150.168–3.0450.650
  Unknown97 (8.8)892 (10.2)0.8550.685–1.0670.166
Patient status (no. [%])0.213
  Inpatient1038 (94.5)8135 (93.5)Ref
  Outpatient60 (5.5)566 (6.5)0.8310.632–1.092
Prior operation w/in 30 days (no. [%])62 (5.6)348 (4.0)1.4361.088–1.8960.013
Concurrent procedure (no. [%])54 (4.9)475 (5.4)0.8960.671–1.1960.523
Transfer status (no. [%])<0.001
  Admitted from home, clinic, doctor's office620 (56.5)6117 (70.3)Ref
  Admitted through ER390 (35.5)1852 (21.3)2.0781.812–2.383<0.001
  Transfer from outside hospital or rehab facility88 (8.0)732 (8.4)1.1860.937–1.5020.156
Discharge destination (no. [%])
  Home1067 (97.2)8294 (95.3)Ref
  Other (rehab, separate facility, skilled care, unskilled care)31 (2.8)407 (4.7)0.5920.409–0.8580.006

ER = emergency room; LOS = length of stay; Ref = reference category.

Statistical analysis was performed using Fisher's exact test, chi-square test, or univariate logistic regression, as appropriate. Continuous variables are expressed as the median (25th percentile–75th percentile).

Unadjusted odds ratio; for categorical variables without an explicitly listed reference category, the odds ratio is in reference to cases in which that variable is not true.

Several patient comorbidities were significantly associated with unplanned readmission on univariate analysis, including the presence of any comorbidity, the presence of any non-CNS comorbidity, pulmonary comorbidity (specific conditions significantly associated with readmission: asthma, bronchopulmonary dysplasia, oxygen supplementation, and structural pulmonary abnormality), gastrointestinal comorbidity (specific conditions significantly associated with readmission: esophageal, gastric, or intestinal disease), CNS comorbidity (specific conditions significantly associated with readmission: history of CVA or traumatic brain injury, CNS tumor, developmental delay, cerebral palsy, seizure disorder, and structural CNS abnormality), steroid use > 10 days, chemotherapy within 30 days prior to surgery, radiotherapy within 90 days prior to surgery, open wound, tracheostomy at time of surgery, history of prematurity (specifically, 25–28 weeks gestation), intraventricular hemorrhage, nutritional support, and current or previous malignancy. No difference was observed for obesity, renal comorbidity, cardiac comorbidity, immune disease or immunosuppressant use, bleeding disorder, hematological disorder, gestational period > 28 weeks, SIRS or sepsis within 48 hours prior to surgery, or congenital malformation. Patient comorbidities are shown in Table 4.

TABLE 4.

Patient comorbidities associated with unplanned readmission on univariate analysis*

ParameterNo. (%)Crude OR95% CIp Value
Unplanned ReadmissionNo Unplanned Readmission
Any comorbidity1069 (97.4)7877 (90.5)3.8562.648–5.165<0.001
Any non-CNS comorbidity620 (56.5)3821 (43.9)1.6571.460–1.880<0.001
Obesity, BMI for age145 (13.2)1148 (13.2)1.0010.832–1.2051.000
Pulmonary comorbidity227 (20.7)1481 (17.0)1.2711.087–1.4860.003
  Ventilator dependent37 (3.4)325 (3.7)0.8990.636–1.2700.610
  Pneumonia2 (0.2)20 (0.2)0.7920.185–3.3931.000
  Asthma78 (7.1)501 (5.8)1.2520.977–1.6030.077
  Cystic fibrosis1 (0.1)5 (0.0)1.5850.185–13.5830.510
  Bronchopulmonary dysplasia86 (7.8)492 (5.7)1.4181.117–1.7990.005
  Oxygen support72 (6.6)421 (4.8)1.3801.066–1.7870.019
  Structural pulmonary abnormality71 (6.5)400 (4.6)1.4351.106–1.7870.009
GI comorbidity222 (20.2)1257 (14.4)1.5011.280–1.759<0.001
  Esophageal, gastric, intestinal disease218 (19.8)1228 (14.1)1.5081.285–1.769<0.001
  Biliary, liver, pancreatic disease9 (0.8)54 (0.6)1.3230.652–2.6880.421
Renal comorbidity1 (0.1)7 (0.1)1.1320.139–9.2111.000
  Renal failure1 (0.1)4 (0.0)1.9820.221–17.7490.448
  Dialysis1 (0.1)4 (0.0)1.9820.221–17.7490.448
CNS comorbidity1036 (94.4)7606 (87.4)2.4061.848–3.132<0.001
  Coma >24 hrs0 (0.0)5 (0.0)NANANA
  History of CVA or TBI95 (8.6)534 (6.1)1.4491.153–1.8190.002
  CNS tumor218 (19.8)1360 (15.6)1.3371.140–1.568<0.001
  Developmental delay371 (33.8)2273 (26.1)1.4431.262–1.650<0.001
  Cerebral palsy129 (11.7)704 (8.1)1.5121.239–1.846<0.001
  Neuromuscular disorder112 (10.2)840 (9.6)1.0630.863–1.3090.552
  Seizure disorder254 (23.1)1324 (15.2)3.6292.209–5.961<0.001
  Structural CNS abnormality862 (78.5)6342 (72.9)1.3591.168–1.581<0.001
Cardiac comorbidity126 (11.5)922 (10.6)1.0940.897–1.3330.378
Steroid use138 (12.6)678 (7.8)1.7011.400–2.067<0.001
Chemotherapy w/in 30 days before surgery33 (3.0)109 (1.2)2.4421.646–3.642<0.001
Radiotherapy w/in 90 days before surgery10 (0.9)28 (0.3)2.8471.379–5.8770.008
Open wound (w/or w/o infection)39 (3.6)188 (2.2)1.6681.174–2.3680.007
Tracheostomy at time of surgery32 (2.9)145 (1.7)1.7711.202–2.6110.005
Immune disease or immunosuppressant use13 (1.2)74 (0.8)1.3970.772–2.5270.302
Nutritional support (IV or NG tube)168 (15.3)833 (9.6)1.7061.426–2.041<0.001
Bleeding disorder9 (0.8)53 (0.6)1.3490.663–2.7410.416
Hematological disorder36 (3.3)240 (2.8)1.1950.837–1.7060.332
Current or previous malignancy191 (17.4)1046 (12.0)1.5411.302–1.825<0.001
History of prematurity0.002
  Term birth (≥37 wks gestation)744 (67.8)6167 (70.9)Ref
  33–36 wks gestation97 (8.8)732 (8.4)1.0980.877–1.3760.414
  29–32 wks gestation50 (4.6)378 (4.3)1.0960.809–1.4870.554
  25–28 wks gestation110 (10.0)593 (6.8)1.5381.237–1.911<0.001
  ≤24 wks gestation36 (3.3)241 (2.8)1.2380.865–1.7720.243
  Unknown61 (5.6)590 (6.8)0.8570.651–1.1280.270
Intraventricular hemorrhage141 (12.8)873 (10.0)1.3211.092–1.5980.005
Congenital malformation, any system402 (36.6)3247 (37.3)0.9700.852–1.1050.667
SIRS/sepsis w/in 48 hrs before surgery19 (1.7)130 (1.5)1.1610.714–1.8870.514

BMI = body mass index; GI = gastrointestinal; IV = intravenous; NA = not applicable; NG = nasogastric; TBI = traumatic brain injury.

Statistical analysis was performed using Fisher's exact test, chi-square test, or logistic regression, as appropriate.

Unadjusted odds ratio is in reference to the null state for variables without an explicitly defined reference category; that is, the odds ratio is in reference to cases without the comorbidity listed.

Steroid use is defined as the use of oral or parenteral corticosteroid within 30 days prior to the principal procedure or at the time the patient is being considered as a candidate for surgery; it does not include short-term use such as a 1-time pulse, limited short course, or a taper < 10 days.

No preoperative laboratory values were significantly associated with unplanned readmission on univariate analysis. Hypoalbuminemia and elevated WBC count alone met criteria for inclusion in the multivariate model (p < 0.2). No difference was seen for hyponatremia, hypernatremia, thrombocytopenia, elevated AST, elevated BUN, abnormal PT, abnormal PTT, or anemia. Preoperative laboratory values are displayed in Table 5. Of note, not all patients had preoperative laboratory values measured.

TABLE 5.

Preoperative laboratory value association with unplanned readmission on univariate analysis*

Parameter (% w/lab value)No. (%)Crude OR95% CIp Value
Unplanned ReadmissionNo Unplanned Readmission
Hypoalbuminemia (19.7)51 (4.6)320 (3.7)1.2760.943–1.7260.130
Hyponatremia (58.0)42 (3.8)280 (3.2)1.1960.859–1.6650.281
Hypernatremia (58.0)17 (1.5)114 (1.3)1.1850.709–1.9800.486
Elevated WBC count (67.4)78 (7.1)496 (5.7)1.2650.988–1.6200.066
Thrombocytopenia (67.0)57 (5.2)398 (4.6)1.1420.859–1.5190.361
Elevated AST (18.1)14 (1.3)115 (1.3)0.9640.552–1.6851.000
Elevated BUN (55.2)5 (0.4)51 (0.6)0.7760.309–1.9480.831
Abnormal PT (36.4)53 (4.8)370 (4.2)1.1420.850–1.5340.386
Abnormal PTT (37.5)65 (5.9)516 (5.9)0.9980.765–1.3021.000
Anemia (68.2)89 (8.1)618 (7.1)1.1540.915–1.4540.239

Statistical analysis was performed using logistic regression and Fisher's exact test.

Not all patients had the listed preoperative lab measurements recorded; percentage refers to that of the total patient cohort with preoperative lab measurements, normal or abnormal.

Unadjusted odds ratio is in reference to the null state, that is, in relation to cases in which the given lab value is normal.

Operative variables significantly associated with unplanned readmission on univariate analysis included a shorter operation, triage status, and ASA classification. No difference was observed for wound classification over all (p = 0.310); however, dirty and/or infected wound status was entered into the multivariate analysis (p < 0.2). Similarly, perioperative blood transfusion (p = 0.129) was included in the multivariate analysis. Although a longer operation was protective for readmission on univariate logistic regression (OR = 0.960 per hour increase, 95% CI = 0.925–0.995, p = 0.027), a longer operation emerged as an independently significant risk factor for readmission on multivariate analysis (OR = 1.059 per hour increase, 95% CI = 1.006–1.114, p = 0.029). When all variables in the multivariate analysis were accounted for, the protective effect of a longer operation (a 4% decrease in readmission risk per hour increase in operative time) diminished and actually became a risk factor (a 5% increase in readmission risk per hour increase in operative time). This was expected, as longer operations are typically performed in patients with more severe underlying conditions and are more likely to result in postoperative complications. Operative variable analysis is shown in Table 6.

TABLE 6.

Operative variable association with unplanned readmission on univariate analysis*

ParameterUnplanned ReadmissionNo Unplanned ReadmissionCrude OR95% CIp Value
Length of operation in min (range)69 (41–139)82 (47–159)0.9600.925–0.9950.027
Triage (no. [%])<0.001
  Elective685 (62.4)6551 (75.3)Ref
  Emergent248 (22.6)1198 (13.8)1.9801.691–2.318<0.001
  Urgent165 (15.0)952 (10.9)1.6581.380–1.991<0.001
ASA Class (no. [%])<0.001
  I20 (1.8)476 (5.5)Ref
  II334 (30.4)3438 (39.5)2.3121.458–3.667<0.001
  III692 (63.0)4411 (50.7)3.7342.370–5.882<0.001
  IV48 (4.4)346 (4.0)3.3021.925–5.664<0.001
  V0 (0.0)12 (0.1)NANANA
  Unknown4 (0.4)18 (0.2)5.2891.638–17.0770.005
Periop blood transfusion (no. [%])70 (6.4)667 (7.7)0.8200.636–1.0580.129
Wound classification (no. [%])0.310
  Clean1044 (95.1)8362 (96.1)Ref
  Clean-contaminated30 (2.7)206 (2.4)1.1660.791–1.7200.437
  Contaminated9 (0.8)57 (0.7)1.2650.624–2.5620.514
  Dirty or infected15 (1.4)76 (0.9)1.5810.905–2.7610.107

Statistical analysis was performed using Fisher's exact test, chi-square test, or univariate logistic regression, as appropriate. Continuous variables are expressed as the median (25th percentile–75th percentile).

Unadjusted odds ratio; for categorical variables without an explicit reference category, odds ratios are in reference to cases in which the variable is not true (null state).

Postoperative complications (systemic infections or SSIs, seizure, coma, unplanned reintubation, nerve injury, organ failure, graft failure, venous thromboembolism) occurred in 1237 cases (12.6%) and were the strongest predictors of unplanned readmission. Data on days to postoperative complications are displayed in Fig. 2. Complications significantly associated with unplanned readmission on univariate analysis included any complication, any infection (superficial SSI, deep SSI, organ/space SSI, sepsis, UTI, pneumonia, central line–associated bloodstream infection), wound disruption, unplanned intubation, CVA, seizure, graft or prosthesis failure, and DVT. No differences were seen for renal insufficiency, acute renal failure, coma > 24 hours, peripheral nerve injury, PE, or cardiac arrest (some events were not statistically testable due to a prohibitively low number of events). Postoperative complications analysis is displayed in Table 7.

FIG. 2.
FIG. 2.

Postoperative days to complication data (expressed as the mean ± standard error of the mean with n = number of events with data on days to complication). Average time to unplanned readmission was 14.04 ± 7.74 days postoperatively (mean ± standard deviation). CLABI = central line–associated bloodstream infection.

TABLE 7.

Postoperative complications associated with unplanned readmission on univariate analysis*

ComplicationNo. (%)Crude OR95% CIp Value
Unplanned ReadmissionNo Unplanned Readmission
Any complication312 (28.4)404 (4.6)3.3562.895–3.890<0.001
Any infection219 (19.9)205 (2.4)10.3268.431–12.646<0.001
  Superficial SSI52 (4.7)56 (0.6)7.6745.233–11.255<0.001
  Deep SSI23 (2.1)9 (0.1)20.8339.524–45.455<0.001
  Organ/space SSI96 (8.7)37 (0.4)22.43515.268–32.966<0.001
  Sepsis52 (4.7)30 (0.3)14.3699.126–22.623<0.001
  UTI35 (3.2)70 (0.8)4.0602.692–6.122<0.001
  Pneumonia15 (1.4)26 (0.3)4.6212.440–8.752<0.001
  CLABI3 (0.3)6 (0.1)3.6980.991–15.8730.070
Wound dehiscence74 (6.7)43 (0.5)14.5519.937–21.306<0.001
Unplanned intubation20 (1.8)77 (0.9)2.0781.265–3.4120.006
Renal insufficiency0 (0.0)3 (0.0)NANANA
Acute renal failure0 (0.0)0 (0.0)NANANA
Coma >24 hrs0 (0.0)3 (0.0)NANANA
CVA/intracranial hemorrhage11 (1.0)31 (0.4)2.8301.419–5.6470.005
Seizure23 (2.1)51 (0.6)3.6292.209–5.961<0.001
Peripheral nerve injury1 (0.1)11 (0.1)1.3890.179–10.7661.000
Cardiac arrest1 (0.1)5 (0.0)1.5850.185–13.5140.510
Graft or prosthesis failure9 (0.8)4 (0.0)17.8575.525–58.824<0.001
DVT5 (0.4)8 (0.1)4.9711.623–15.2210.010
PE1 (0.1)0 (0.0)NANANA

CLABI = central line–associated bloodstream infection.

Statistical analysis was performed via binary logistic regression and Fisher's exact test.

Unadjusted odds ratio with respect to each variable's null state, that is, cases in which the given complication was not present.

Does not include variables not coded within NSQIP (for example, shunt failure) or perioperative or postoperative blood transfusion requirement.

For shunt operations with the highest readmission rates (CPT codes 62223, 62230, 62225; shown in Table 1), the overall 30-day unplanned readmission rate was 16.3%. Within these 3 shunt operations, the most common reasons for readmission were shunt failure or mechanical device complication (ICD-9 code 996.2, 31.2% of readmissions), need for another shunt procedure (CPT codes 62223–62258, 17.9% of readmissions), and organ or space SSI (8.5% of readmissions). Other less common reasons for readmission among the 3 shunt operations with the highest readmission rate included headache (2.5%), wound disruption (2.1%), and seizure (2.0%). Similarly, in patients who underwent craniectomy for excision of brain infratentorial tumor (CPT code 61518, 30-day unplanned readmission rate of 13.9%), the most common reasons for readmission included hydrocephalus (19.2% of readmissions), wound disruption (11.5% of readmissions), and organ or space SSI (7.7% of readmissions).

Results from the multivariate logistic regression analysis are shown in Table 8. Numerous variables emerged as independently significant risk factors, including (in order of decreasing odds ratio): deep incisional SSI; organ or space SSI; wound disruption; superficial incisional SSI; graft or prosthesis failure; postoperative pneumonia; postoperative UTI; postoperative sepsis; postoperative seizure; Native American race; shunt or ventricular catheter removal, replacement, or irrigation procedure; shunt or ventricular catheter placement procedure; MMC repair procedure; presence of any comorbidity; home discharge; oxygen supplementation; steroid use > 10 days; nutritional support; prior operation within 30 days of the current procedure; transfer from emergency room; preexisting seizure disorder; and longer operative time. Several factors emerged as independently significant protective factors for readmission, including longer hospital stay, spine procedure, and craniotomy for craniosynostosis procedure. Increasing length of stay proved to be a significant protective factor (OR = 0.956 per day increase, 95% CI 0.946–0.966, p < 0.001); however, this variable is not included in Table 8 because of the decreasing time window in which readmission can occur as the length of stay increases. Variables that did not remain in the model when applying a Bonferroni correction for multiple measures were Native American race, oxygen supplementation, home discharge, prior operation within 30 days of index procedure, longer operative time, MMC repair procedures, and shunt placement procedures (marked with daggers in Table 8).

TABLE 8.

Logistic regression analysis of variables independently associated with unplanned readmission*

VariableAdjusted OR95% CIp Value
Deep incisional SSI25.54710.229–63.373<0.001
Organ/space SSI19.15611.618–31.585<0.001
Wound disruption17.58210.750–28.756<0.001
Superficial incisional SSI12.1517.783–18.973<0.001
Graft/prosthesis failure11.0742.882–42.548<0.001
Postop pneumonia4.2942.045–9.017<0.001
Postop UTI4.2622.598–6.992<0.001
Postop sepsis2.6161.321–5.1810.006
Postop seizure2.5321.398–4.5870.002
Native American race2.3631.149–4.8610.019
Shunt/ventricular catheter revision, removal, or irrigation procedure2.2831.679–3.103<0.001
Shunt/ventricular catheter placement procedure2.1281.542–2.937<0.001
MMC procedure1.9791.066–3.6750.031
Presence of any comorbidity1.9431.086–3.4780.025
Home discharge1.8851.208–2.9420.005
Oxygen supplementation1.6451.128–2.3990.010
Steroid use >10 days1.4111.087–1.8310.010
Nutritional support (IV or NG tube)1.4031.088–1.8090.009
Prior operation w/in 30 days of index procedure1.3781.001–1.8970.049
Transfer from ER1.2731.046–1.5490.016
Preexisting seizure disorder1.2501.034–1.5100.021
Operation time (per hr increase)1.0591.006–1.1140.029
Spine procedure0.7030.503–0.9840.040
Craniotomy for craniosynostosis0.2910.151–0.560<0.001

Variables were included for analysis when p ≤ 0.2 by univariate Fisher's exact, chi-square, or univariate logistic regression tests. Variables were considered independently significant when p ≤ 0.05 in multivariate logistic regression.

Indicates variables excluded from corrected Bonferroni multivariate logistic regression model due to p value failing to reach α corrected ≤ 0.002 by univariate analysis.

Receiver operating characteristic analysis for validation of the logistic regression model yielded a cstatistic, or area under the curve, of 0.759 (95% CI 0.744–0.775, p < 0.001). An area under the curve ≥ 0.7 by ROC analysis indicates an acceptable multivariate logistic regression model with significantly greater predictive ability than chance alone.

Discussion

We have identified rates of unplanned readmission as well as independent risk factors for readmission in a national pediatric neurosurgical population. To our knowledge, this is the first study in which the NSQIP database has been used to examine rates and risk factors for readmission after pediatric neurosurgery. While previous studies have reported return to system after pediatric neurosurgery at single institutions9,21,26 or after pediatric shunt surgery,20 the statistical power of a large national patient sample may provide a more representative picture of readmission outcomes for general pediatric neurosurgical procedures.

Complications

Postoperative infection, particularly SSI, was the strongest predictor of readmission. This observation is not surprising given that SSI is not uncommon and is associated with significant morbidity and mortality, particularly if not caught and treated early. Surgical site infection has been shown to cause up to 70% of reoperations after pediatric spine surgery17 and is one of the strongest predictors of readmission after pediatric plastic surgery.23 However, the relatively high rate of SSI and readmissions related to SSI could indicate a need to continue to study and improve preventative measures before, during, and after surgery (prophylactic antibiotic use, close monitoring of sterile technique, postoperative wound monitoring or cleaning) to prevent occurrences of SSI and SSI-related return to system. Additionally, wound disruption was a common reason for readmission and was independently associated with readmission.

Shunt failure was the most common ICD-9 diagnosis on readmission. In pediatric neurosurgery, shunt failure is a common and oftentimes unpreventable phenomenon, occurring in approximately 12% of pediatric shunt procedures within 30 days or less,11 and up to 46% of procedures had reported failure rates when the follow-up period lasted up to 1 year.6,10 The 30-day readmission rate for shunt operations (15.7%) in this study is substantially similar to that published in previous work20 and may be useful as a benchmark for future studies aimed at lowering adverse shunt surgery events. As expected, the majority of readmissions after a CSF shunting procedure were related to recurrent shunt difficulties. Aside from shunt failure, however, infection-related readmissions (organ or space SSI and wound disruption) were the most common reasons for readmission among the shunt procedures with the highest readmission rates. These results indicate that measures to prevent SSI and wound disruption could help to reduce unplanned readmission after pediatric neurosurgery.

Readmission occurred, on average, approximately 2 weeks postoperatively. Given that postoperative infections (systemic or SSI) were the strongest predictors of readmission, it is expected that the time course to readmission would follow a course similar to the time required for common infection complications to develop. Again, this finding highlights the need for improved postoperative wound monitoring and better operative wound management to prevent unplanned readmission. The present study supports the notion that ongoing efforts to minimize SSIs in pediatric neurosurgery have the greatest potential to reduce readmission rates.

Patient-Related Factors

The percentage of patients with any comorbidity was 91.3%, and 45.3% of patients had any non-CNS comorbidity. The high comorbidity rate in pediatric neurosurgery relative to that in other specialties could be one possible cause of the higher readmission, morbidity, and mortality rates observed in this specialty relative to the rates in others.4 Comorbidities independently associated with readmission included the presence of any comorbidity, steroid use, oxygen support, nutritional support, and seizure disorder. Chronic steroid use has not been well studied in pediatric populations, although some institutions have initiated steroid avoidance protocols before renal transplantation surgery.15 Nutritional support has been indicated as a risk factor for readmission after pediatric cardiac surgery16 and cleft palate repair.19 The comorbid conditions that have a strong association with unplanned readmission could be used as preoperative risk stratification variables. Patients who are considered high risk based on these findings may benefit from more careful discharge planning or increased outpatient attention in an effort to prevent readmission.

Native American race emerged as an independently significant risk factor for readmission. Native American race has been reported as a risk factor for readmission after orthopedic surgery12 and following sepsis,8 although its association with readmission after pediatric neurosurgical procedures has not been observed to our knowledge. While a plausible explanation for this is not apparent from these data, it is important to note disparities such as this as an area for future study. An important caveat to this observation, however, is that Native American patients make up a very small proportion of the NSQIP sample. Therefore, observations about this population are potentially subject to error given the magnified effect of small numbers of readmissions in a population with a small denominator. Furthermore, we were unable to determine socioeconomic or geographical data from the NSQIP-P data set, both of which may contribute to demographic differences in readmission rates.

Procedure- and Hospital-Related Factors

We observed a higher rate of readmission among procedures related to CSF shunts, MMC repair, and craniotomy for infratentorial tumor excision. These findings are perhaps unsurprising as these procedures are typically performed in patients with multiple comorbidities and often require close follow-up for revisions. Previous studies have shown high rates of return to system in pediatric shunt surgery, with readmission rates similar to those reported here.20 Interestingly, 4 of the 5 procedures with the highest readmission rates accounted for over 40% of all procedures in the NSQIP-P neurosurgery cohort. Of the procedures with the highest readmission rates, operation for MMC repair was the least frequently performed (1.3% of all procedures), and its high readmission rate is expected given the myriad comorbidities that often occur in patients with MMC.5

Emergent or urgent triage status and admission through the emergency department were significant predictors of unplanned readmission on univariate analysis, although emergent or urgent triage was not a predictor on multivariate analysis. These findings are not surprising, yet they may aid in patient risk stratification when ascertaining patient readmission risk preoperatively.

Interestingly, a longer hospital stay was a significant protective factor in multivariate regression. This observation lends credence to the idea that for health care providers the goals of decreased hospital stay and decreased readmission may be competing.14 Efforts to decrease hospital length of stay may lead to increased readmission and vice versa. However, our data capture readmission within 30 days of the primary procedure, not from discharge; therefore, it follows that a longer hospitalization decreases the chance of readmission within 30 days because of a smaller window of time in which readmission (as defined within 30 days of the primary procedure) can occur.

Study Limitations

This study has several limitations. First, the NSQIP-P database is limited by the type of data provided by the participating institutions and by the NSQIP categorical variables. Although the NSQIP-P is a national database, the case sample is not necessarily nationally representative. Trauma cases are not included in the database. Certain procedures (for example, CPT code 62201: endoscopic third ventriculostomy with choroid plexus cauterization) are not included either. The severity of categorically coded conditions cannot be ascertained, limiting our ability to associate certain patient conditions with readmission outcomes. Some comorbidities (for example, cardiac risk factors) are insufficiently granular and do not allow for differentiation between different comorbidity subtypes (for example, atrial septal defect vs hypertrophic cardiomyopathy). Facility identifiers are not included in the NSQIP, which prevents analysis of facility outliers with substantially higher or lower rates of readmission. As is the case with many patient databases, preventative preoperative measures are not tracked, probably resulting in overestimation of risk factors. Furthermore, not all patients had their preoperative laboratory values measured; albumin and AST had missing value rates of greater than 80%, limiting our ability to interpret statistical analysis of the differences in preoperative laboratory values between groups. Data on the exact reason (that is, the ICD-9 diagnosis) for readmission in the NSQIP are not always reported or entirely clear. Of the 1098 unplanned readmissions, 746 (67.9%) were directly related to the primary procedure. Of the remaining 32.1% of readmissions unrelated to the primary procedure, the NSQIP data abstractors may not have captured the reason for readmission, which could limit the thoroughness of our readmission reason results. Using readmission as an outcome measure has particular caveats as higher or lower rates of readmission alone may not necessarily indicate poorer or better surgical care quality.

Finally, the large number of variables analyzed increases the risk of Type I error, or false-positive findings. The Bonferroni method of multiple measures correction is very conservative, greatly decreasing the risk of incorrectly rejecting the null hypothesis (Type I error), but at the cost of increasing the risk of incorrectly accepting the null hypothesis (Type II error). In most multivariate logistic regression analyses, a higher α is accepted when selecting variables to include in the model in an effort to avoid inappropriately excluding important variables. Thus, we present the corrected model for reference but base our discussion on the uncorrected model.

Despite these limitations, this study may aid surgeons in identifying procedures and patient risk factors that predispose patients to a higher risk of readmission after pediatric neurosurgery. Patients undergoing longer procedures or procedures related to CSF shunting, MMC repair, or craniectomy for infratentorial brain tumor excision are at greater risk for readmission, especially if they are transferred from the emergency department. Patients undergoing spine procedures or craniotomy for craniosynostosis have a lower risk of readmission compared with those undergoing other procedures. Patients who are Native American, have any preexisting comorbidity, have undergone an operation in the previous 30 days, or have a seizure disorder should be considered at greater risk for unplanned readmission. In addition, patients who require oxygen supplementation, nutritional support, or long-term steroids should also be considered to have a greater risk for readmission. Finally, patients who experience postoperative infection (SSI or systemic infection) should be considered at the greatest risk for readmission. These data may also prove useful for family and patient counseling prior to neurosurgical operations.

Conclusions

This is the first study to use the pediatric NSQIP data to examine hospital readmission after shunt and nonshunt neurosurgical procedures in pediatric patients. Hospital readmission rates in this study are similar to previously published rates from other sources. Unsurprisingly, SSIs and wound-related complications are some of the most important contributors to hospital readmission; therefore, efforts directed at reducing infection may have the greatest impact on readmission.

There is significant readmission rate variability among different procedure categories. Procedures with the highest rates of unplanned readmission were CSF shunt revision or removal, MMC repair, CSF shunt placement, and craniectomy for infratentorial neoplasm. Procedures with the lowest unplanned readmission rates were spine procedures, craniosynostosis craniotomies, and skin lesion procedures.

We have identified many patient-related factors associated with readmission, such as long-term steroid use, the need for nutritional support, and oxygen dependency. While these are not modifiable risk factors, they can be useful in identifying patients at high risk for readmission who could benefit from discharge planning or direct efforts to facilitate safe hospital discharge without readmission.

Acknowledgments

The American College of Surgeons National Surgical Quality Improvement Program and the hospitals participating in the ACS NSQIP are the source of the data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors.

References

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Disclosures

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author Contributions

Conception and design: all authors. Acquisition of data: Sherrod. Analysis and interpretation of data: all authors. Drafting the article: all authors. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Rocque. Statistical analysis: Rocque, Sherrod. Study supervision: Rocque.

Supplemental Information

Online-Only Content

Supplemental material is available with the online version of the article.

  • View in gallery

    Cohort selection by surgical subspecialty and procedural classification by CPT code. N = number of cases.

  • View in gallery

    Postoperative days to complication data (expressed as the mean ± standard error of the mean with n = number of events with data on days to complication). Average time to unplanned readmission was 14.04 ± 7.74 days postoperatively (mean ± standard deviation). CLABI = central line–associated bloodstream infection.

  • 1

    American College of Surgeons: User Guide for the 2013 ACS NSQIP Pediatric Participant Use Data File Chicago, American College of Surgeons, 2014. (https://www.facs.org/~/media/files/quality%20programs/nsqip/peds_puf_userguide_2013ashx) [Accessed February 23, 2016]

    • Search Google Scholar
    • Export Citation
  • 2

    Axon RN, & Williams MV: Hospital readmission as an accountability measure. JAMA 305:504505, 2011

  • 3

    Berry JG, , Hall DE, , Kuo DZ, , Cohen E, , Agrawal R, & Feudtner C, et al.: Hospital utilization and characteristics of patients experiencing recurrent readmissions within children's hospitals. JAMA 305:682690, 2011

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Bruny JL, , Hall BL, , Barnhart DC, , Billmire DF, , Dias MS, & Dillon PW, et al.: American College of Surgeons National Surgical Quality Improvement Program Pediatric: a beta phase report. J Pediatr Surg 48:7480, 2013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5

    Bulbul A, , Can E, , Bulbul LG, , Cömert S, & Nuhoglu A: Clinical characteristics of neonatal meningomyelocele cases and effect of operation time on mortality and morbidity. Pediatr Neurosurg 46:199204, 2010

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6

    Caldarelli M, , Di Rocco C, & La Marca F: Shunt complications in the first postoperative year in children with meningomyelocele. Childs Nerv Syst 12:748754, 1996

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7

    Centers for Medicare and Medicaid Services: Medicare program; revisions to payment policies under the physician fee schedule, clinical laboratory fee schedule, access to identifiable data for the Center for Medicare and Medicaid Innovation models & other revisions to Part B for CY 2015. Fed Regist 79:6754768092, 2014

    • Search Google Scholar
    • Export Citation
  • 8

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