Bryce A. Basques

Variations in Data Collection Methods Between National Databases Affect Study Results: A Comparison of the Nationwide Inpatient Sample and National Surgical Quality Improvement Program Databases for Lumbar Spine Fusion Procedures

BACKGROUND There has been an increasing use of national databases to conduct orthopaedic research. Questions regarding the validity and consistency of these studies have not been fully addressed. The purpose of this study was to test for similarity in reported measures between two national databases commonly used for orthopaedic research. METHODS A retrospective cohort study of patients undergoing lumbar spinal fusion procedures during 2009 to 2011 was performed in two national databases: the Nationwide Inpatient Sample and the National Surgical Quality Improvement Program. Demographic characteristics, comorbidities, and inpatient adverse events were directly compared between databases. RESULTS The total numbers of patients included were 144,098 from the Nationwide Inpatient Sample and 8434 from the National Surgical Quality Improvement Program. There were only small differences in demographic characteristics between the two databases. There were large differences between databases in the rates at which specific comorbidities were documented. Non-morbid obesity was documented at rates of 9.33% in the Nationwide Inpatient Sample and 36.93% in the National Surgical Quality Improvement Program (relative risk, 0.25; p < 0.05). Peripheral vascular disease was documented at rates of 2.35% in the Nationwide Inpatient Sample and 0.60% in the National Surgical Quality Improvement Program (relative risk, 3.89; p < 0.05). Similarly, there were large differences between databases in the rates at which specific inpatient adverse events were documented. Sepsis was documented at rates of 0.38% in the Nationwide Inpatient Sample and 0.81% in the National Surgical Quality Improvement Program (relative risk, 0.47; p < 0.05). Acute kidney injury was documented at rates of 1.79% in the Nationwide Inpatient Sample and 0.21% in the National Surgical Quality Improvement Program (relative risk, 8.54; p < 0.05). CONCLUSIONS As database studies become more prevalent in orthopaedic surgery, authors, reviewers, and readers should view these studies with caution. This study shows that two commonly used databases can identify demographically similar patients undergoing a common orthopaedic procedure; however, the databases document markedly different rates of comorbidities and inpatient adverse events. The differences are likely the result of the very different mechanisms through which the databases collect their comorbidity and adverse event data. Findings highlight concerns regarding the validity of orthopaedic database research.

Nationwide Inpatient Sample and National Surgical Quality Improvement Program Give Different Results in Hip Fracture Studies

BackgroundNational databases are being used with increasing frequency to conduct orthopaedic research. However, there are important differences in these databases, which could result in different answers to similar questions; this important potential limitation pertaining to database research in orthopaedic surgery has not been adequately explored.Questions/purposesThe purpose of this study was to explore the interdatabase reliability of two commonly used national databases, the Nationwide Inpatient Sample (NIS) and the National Surgical Quality Improvement Program (NSQIP), in terms of (1) demographics; (2) comorbidities; and (3) adverse events. In addition, using the NSQIP database, we identified (4) adverse events that had a higher prevalence after rather than before discharge, which has important implications for interpretation of studies conducted in the NIS.MethodsA retrospective cohort study of patients undergoing operative stabilization of transcervical and intertrochanteric hip fractures during 2009 to 2011 was performed in the NIS and NSQIP. Totals of 122,712 and 5021 patients were included from the NIS and NSQIP, respectively. Age, sex, fracture type, and lengths of stay were compared. Comorbidities common to both databases were compared in terms of more or less than twofold difference between the two databases. Similar comparisons were made for adverse events. Finally, adverse events that had a greater postdischarge prevalence were identified from the NSQIP database. Tests for statistical difference were thought to be of little value given the large sample size and the resulting fact that statistical differences would have been identified even for small, clinically inconsequential differences resulting from the associated high power. Because it is of greater clinical importance to focus on the magnitude of differences, the databases were compared by absolute differences.ResultsDemographics and hospital lengths of stay were not different between the two databases. In terms of comorbidities, the prevalences of nonmorbid obesity, coagulopathy, and anemia in found in the NSQIP were more than twice those in the NIS; the prevalence of peripheral vascular disease in the NIS was more than twice that in the NSQIP. Four other comorbidities had prevalences that were not different between the two databases. In terms of inpatient adverse events, the frequencies of acute kidney injury and urinary tract infection in the NIS were more than twice those in the NSQIP. Ten other inpatient adverse events had frequencies that were not different between the two databases. Because it does not collect data after patient discharge, it can be implied from the NSQIP data that the NIS does not capture more than ½ of the deaths and surgical site infections occurring during the first 30 postoperative days.ConclusionsThis study shows that two databases commonly used in orthopaedic research can identify similar populations of operative patients but may generate very different results for specific commonly studied comorbidities and adverse events. The NSQIP identified higher rates of morbid obesity, coagulopathy, and anemia. The NIS identified higher rates of peripheral vascular disease, acute kidney injury, and urinary tract infection.Level of EvidenceLevel II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.

General Compared with Spinal Anesthesia for Total Hip Arthroplasty

BACKGROUND Total hip arthroplasty may be performed under general or spinal anesthesia. The purpose of the current study was to compare perioperative outcomes between anesthetic types for patients undergoing primary elective total hip arthroplasty. METHODS Patients who had undergone primary elective total hip arthroplasty from 2010 to 2012 were identified from the American College of Surgeons National Surgical Quality Improvement Program database. Operating room times, length of stay, thirty-day adverse events, and readmission were compared between patients who had received general anesthesia and those who had received spinal anesthesia. Propensity-adjusted multivariate analysis was used to control for selection bias and baseline patient characteristics. RESULTS A total of 20,936 patients who had undergone total hip arthroplasty met inclusion criteria for this study. Of these, 12,752 patients (60.9%) had received general anesthesia and 8184 patients (39.1%) had received spinal anesthesia. On propensity-adjusted multivariate analyses, general anesthesia for total hip arthroplasty was associated with increased operative time (+12 minutes [95% confidence interval, +11 to +13 minutes]; p < 0.001) and postoperative room time (+5 minutes [95% confidence interval, +4 to +6 minutes]; p < 0.001). General anesthesia was also associated with the occurrence of any adverse event (odds ratio, 1.31 [95% confidence interval, 1.23 to 1.41]; p < 0.001), prolonged postoperative ventilator use (odds ratio, 5.81 [95% confidence interval, 1.35 to 25.06]; p = 0.018), unplanned intubation (odds ratio, 2.17 [95% confidence interval, 1.11 to 4.29]; p = 0.024), stroke (odds ratio, 2.51 [95% confidence interval, 1.02 to 6.20]; p = 0.046), cardiac arrest (odds ratio, 5.04 [95% confidence interval, 1.15 to 22.07]; p = 0.032), any minor adverse event (odds ratio, 1.35 [95% confidence interval, 1.25 to 1.45]; p = 0.001), and blood transfusion (odds ratio, 1.34 [95% confidence interval, 1.25 to 1.45]; p < 0.001). General anesthesia was not associated with any difference in preoperative room time, postoperative length of stay, or readmission. CONCLUSIONS General anesthesia was associated with an increased rate of adverse events and mildly increased operating room times.

Using the ACS-NSQIP to identify factors affecting hospital length of stay after elective posterior lumbar fusion.

Study Design. Retrospective cohort study of the American College of Surgeons National Surgical Quality Improvement Program database from 2005 to 2010 that included 1861 patients who had undergone elective posterior lumbar fusion. Objective. To characterize factors that were independently associated with increased hospital length of stay (LOS) in patients who had undergone elective posterior lumbar fusion. Summary of Background Data. Posterior lumbar spine fusion is a common surgical procedure used to treat lumbar spine pathology. LOS is an important clinical variable and a major determinant of inpatient hospital costs. There is lack of studies in the literature using multivariate analysis to examine specifically the predictors of LOS after elective posterior lumbar fusion. Methods. Patients who underwent elective posterior lumbar fusion from 2005 to 2010 were identified in the American College of Surgeons National Surgical Quality Improvement Program database. Preoperative and intraoperative variables were extracted for each case and a multivariate linear regression was performed to assess the contribution of each variable to LOS. Results. A total of 1861 patients who had undergone elective posterior lumbar fusion were identified. The average age for patients in this cohort was 60.6 ± 13.9 years (mean ± standard deviation) with a body mass index of 30.3 ± 6.2 kg/m2. Of the total patients, 44.7% of patients were male. LOS was in the range from 0 days to 51 days. Multivariate linear regression identified age (P < 0.001), morbid obesity (body mass index ≥ 40 kg/m2, P < 0.001), American Society of Anesthesiologists class (P = 0.001), operative time (P < 0.001), multilevel procedure (P = 0.001), and intraoperative transfusion (P < 0.001) as significant predictors of extended LOS. Conclusion. The identified preoperative and intraoperative variables associated with extended LOS after elective posterior lumbar fusion may be helpful to clinicians for patient counseling and postoperative planning. Level of Evidence: 3

Postoperative length of stay and 30-day readmission after geriatric hip fracture: an analysis of 8434 patients.

Objectives: To identify factors associated with increased postoperative length of stay (LOS) and readmission after surgical repair of geriatric hip fractures. Methods: Patients aged 70 years and older who underwent hip fracture surgery from January 2011 through December 2012 were identified in the American College of Surgeons National Surgical Quality Improvement Program database. Patient characteristics were tested for association with postoperative LOS and readmission using bivariate and multivariate analyses. Results: For the 8434 patients with hip fracture identified, the average age was 83.8 ± 5.9 years (mean ± SD), and 26.9% were male. Average postoperative LOS was 5.6 ± 6.0 days. Ten percent were readmitted within the first 30 postoperative days. Increased postoperative LOS of at least 1 full day was associated with increased time from admission to surgery, non–general anesthesia, and procedure type on multivariate analysis. Readmission was associated with increased age, male sex, body mass index ≥35 kg/m2, American Society of Anesthesiologists class ≥3, pulmonary disease, hypertension, steroid use, dependent functional status, and discharge to a facility on multivariate analysis. Conclusions: Ten percent of patients were readmitted after hip fracture repair in this national sample. Preoperative time to surgery, anesthesia type, and implant selection are 3 risk factors for increased LOS that can potentially be modified. A clinically significant risk factor for readmission was body mass index ≥35 kg/m2, which was not associated with increased postoperative LOS. The identified risk factors illuminate opportunities for optimizing care for hip fracture patients aged 70 and older. Level of Evidence: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Patient characteristics associated with increased postoperative length of stay and readmission after elective laminectomy for lumbar spinal stenosis.

Study Design. Retrospective cohort. Objective. To identify factors that were independently associated with increased postoperative length of stay (LOS) and readmission in patients who underwent elective laminectomy for lumbar spinal stenosis. Summary of Background Data. Lumbar spinal stenosis is a common pathology that is traditionally treated with decompressive laminectomy. Risk factors associated with increased LOS and readmission have not been fully characterized for laminectomy. Methods. Patients who underwent laminectomy for lumbar spinal stenosis during 2011 and 2012 were identified from the American College of Surgeons National Surgical Quality Improvement Program database. Patient characteristics were tested for association with LOS and readmission using bivariate and multivariate analyses. Patients with LOS more than 10 days were excluded from the readmission analysis as the American College of Surgeons National Surgical Quality Improvement Program only captures readmissions within 30 postoperative days, and the window for potential readmission was deemed too short for patients staying longer than 10 days. Results. A total of 2358 patients who underwent laminectomy met inclusion criteria. The average age was 66.4 ± 11.7 years (mean ± standard deviation). Average postoperative LOS was 2.1 ± 2.6 days. Of those meeting criteria for readmission analysis, 3.7% of patients (86 of 2339) were readmitted within 30 days postoperatively. Independent risk factors for prolonged LOS were increased age (P < 0.001), increased body mass index (P = 0.004), American Society of Anesthesiologists class 3–4 (P = 0.005), and preoperative hematocrit less than 36.0 (P = 0.001). Independent risk factors for readmission were increased age (P = 0.013), increased body mass index (P = 0.040), American Society of Anesthesiologists class 3–4 (P < 0.001), and steroid use (P = 0.001). The most common reason for readmission was surgical site-related infections (25.0% of patients readmitted in 2012). Conclusion. The identified factors associated with LOS and readmission after lumbar laminectomy may be useful for optimizing patient care. Level of Evidence: 3

Administrative database concerns: accuracy of International Classification of Diseases, Ninth Revision coding is poor for preoperative anemia in patients undergoing spinal fusion.

Study Design. Cross-sectional study. Objective. To objectively evaluate the ability of International Classification of Diseases, Ninth Revision (ICD-9) codes, which are used as the foundation for administratively coded national databases, to identify preoperative anemia in patients undergoing spinal fusion. Summary of Background Data. National database research in spine surgery continues to rise. However, the validity of studies based on administratively coded data, such as the Nationwide Inpatient Sample, are dependent on the accuracy of ICD-9 coding. Such coding has previously been found to have poor sensitivity to conditions such as obesity and infection. Methods. A cross-sectional study was performed at an academic medical center. Hospital-reported anemia ICD-9 codes (those used for administratively coded databases) were directly compared with the chart-documented preoperative hematocrits (true laboratory values). A patient was deemed to have preoperative anemia if the preoperative hematocrit was less than the lower end of the normal range (36.0% for females and 41.0% for males). Results. The study included 260 patients. Of these, 37 patients (14.2%) were anemic; however, only 10 patients (3.8%) received an “anemia” ICD-9 code. Of the 10 patients coded as anemic, 7 were anemic by definition, whereas 3 were not, and thus were miscoded. This equates to an ICD-9 code sensitivity of 0.19, with a specificity of 0.99, and positive and negative predictive values of 0.70 and 0.88, respectively. Conclusion. This study uses preoperative anemia to demonstrate the potential inaccuracies of ICD-9 coding. These results have implications for publications using databases that are compiled from ICD-9 coding data. Furthermore, the findings of the current investigation raise concerns regarding the accuracy of additional comorbidities. Although administrative databases are powerful resources that provide large sample sizes, it is crucial that we further consider the quality of the data source relative to its intended purpose. Level of Evidence: 3

Orthopaedic Surgeons Receive the Most Industry Payments to Physicians but Large Disparities are Seen in Sunshine Act Data

BackgroundIndustry payments made to physicians by drug and device manufacturers or group purchasing organizations are now reported to the Centers for Medicare and Medicaid Services (CMS) as a part of the Physician Payments Sunshine Act. Initial reports from the program show that orthopaedic surgeons lead all physician specialties in total and average industry payments. However, before further discussion of these payments and their implications can take place, it remains to be seen whether these figures are a true reflection of the field of orthopaedic surgery in general, rather than the result of a few outlier physicians in the field. In addition, the nature and sources of these funds should be determined to better inform the national dialogue surrounding these payments.Questions/PurposesWe asked: (1) How do industry payments to orthopaedic surgeons compare with payments to physicians and surgeons in other fields, in terms of median payments and the Gini index of disparity? (2) How much do payments to the highest-receiving orthopaedic surgeons contribute to total payments? (3) What kind of industry payments are orthopaedic surgeons receiving? (4) How much do the highest-paying manufacturers contribute to total payments to orthopaedic surgeons?Materials and MethodsWe reviewed the most recent version of the CMS Sunshine Act Open Payments database released on December 19, 2014, containing data on payments made between August 1, 2013 and December 31, 2013. Data on total payments to individual physicians, physician specialty, the types of payments made, and the manufacturers making payments were reviewed. The Gini index of statistical dispersion was calculated for payments made to orthopaedic surgeons and compared with payments made to physicians and surgeons in all other medical specialties. A Gini index of 0 indicates complete equality of payments to everyone in the population, whereas an index of 1 indicates complete inequality, or all income going to one individual.ResultsA total of 15,376 orthopaedic surgeons receiving payments during the 5-month period were identified, accounting for USD 109,846,482. The median payment to orthopaedic surgeons receiving payments was USD 121 (interquartile range, USD 34–619). The top 10% of orthopaedic surgeons receiving payments (1538 surgeons) received at least USD 4160 and accounted for 95% of total payments. Royalties and patent licenses accounted for 69% of all industry payments to orthopaedic surgeons.ConclusionsEven as a relatively small specialty, orthopaedic surgeons received substantial payments from industry (more than USD 110 million) during the 5-month study period. Whether there is a true return of value from these payments remains to be seen; however, future ethical and policy discussions regarding industry payments to orthopaedic surgeons should take into account the large disparities in payments that are present and also the nature of the payments being made. It is possible that patients and policymakers may view industry payments to orthopaedic surgeons more positively in light of these new findings.Level of EvidenceLevel III, Economic and Decision Analysis.

Patient factors associated with 30-day morbidity, mortality, and length of stay after surgery for subdural hematoma: a study of the American College of Surgeons National Surgical Quality Improvement Program

OBJECTIVE Surgery for subdural hematoma (SDH) is a commonly performed neurosurgical procedure. This study identifies patient characteristics associated with adverse outcomes and prolonged length of stay (LOS) in patients who underwent surgical treatment for SDH. METHODS All patients in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) who were treated via craniotomy or craniectomy for SDH between 2005 and 2012 were identified. Patient demographics, comorbidities, and 30-day outcomes were described. Multivariate regression was used to identify predictors of adverse events. RESULTS A total of 746 surgical procedures performed for SDH were identified and analyzed. Patients undergoing this procedure were 64% male with an average age (± SD) of 70.9 ± 14.1 years. The most common individual adverse events were death (17%) and intubation for more than 48 hours (19%). In total, 34% experienced a serious adverse event other than death, 8% of patients returned to the operating room (OR), and the average hospital LOS was 9.8 ± 9.9 days. In multivariate analysis, reduced mortality was associated with age less than 60 years (relative risk [RR] = 0.47, p = 0.017). Increased mortality was associated with gangrene (RR = 3.5, p = 0.044), ascites (RR = 3.00, p = 0.006), American Society of Anesthesiologists (ASA) Class 4 or higher (RR = 2.34, p = 0.002), coma (RR = 2.25, p < 0.001), and bleeding disorders (RR = 1.87, p = 0.003). Return to the OR was associated with pneumonia (RR = 3.86, p = 0.044), male sex (RR = 1.85, p = 0.015), and delirium (RR = 1.75, p = 0.016). Serious adverse events were associated with ventilator dependence preoperatively (RR = 1.86, p < 0.001), dialysis (RR = 1.44, p = 0.028), delirium (RR = 1.40, p = 0.005), ASA Class 4 or higher (RR = 1.36, p = 0.035), and male sex (RR = 1.29, p = 0.037). Similarly, LOS was increased in ventilator dependent patients by 1.56-fold (p = 0.002), in patients with ASA Class 4 or higher by 1.30-fold (p = 0.006), and in delirious patients by 1.29-fold (p = 0.008). CONCLUSIONS Adverse outcomes are common after surgery for SDH. In this study, 18% of the patients died within 30 days of surgery. Factors associated with adverse outcomes were identified. Patients and families should be counseled about the serious risks of morbidity and death associated with acute traumatic SDH requiring surgery.

Risk Factors for Blood Transfusion with Primary Posterior Lumbar Fusion.

Study Design. Retrospective cohort study. Objective. To identify factors associated with blood transfusion for primary posterior lumbar fusion surgery, and to identify associations between blood transfusion and other postoperative complications. Summary of Background Data. Blood transfusion is a relatively common occurrence for patients undergoing primary posterior lumbar fusion. There is limited information available describing which patients are at increased risk for blood transfusion, and the relationship between blood transfusion and short‐term postoperative outcomes is poorly characterized. Methods. The American College of Surgeons National Surgical Quality Improvement Program (ACS‐NSQIP) database was used to identify patients undergoing primary posterior lumbar fusion from 2011 to 2013. Multivariate analysis was used to find associations between patient characteristics and blood transfusion, along with associations between blood transfusion and postoperative outcomes. Results. Out of 4223 patients, 704 (16.7%) had a blood transfusion. Age 60 to 69 (relative risk [RR] 1.6), age greater than equal to 70 (RR 1.7), American Society of Anesthesiologists class greater than equal to 3 (RR 1.1), female sex (RR 1.1), pulmonary disease (RR 1.2), preoperative hematocrit less than 36.0 (RR 2.0), operative time greater than equal to 310 minutes (RR 2.9), 2 levels (RR 1.6), and 3 or more levels (RR 2.1) were independently associated with blood transfusion. Interbody fusion (RR 0.9) was associated with decreased rates of blood transfusion. Receiving a blood transfusion was significantly associated with any complication (RR 1.7), sepsis (RR 2.6), return to the operating room (RR 1.7), deep surgical site infection (RR 2.6), and pulmonary embolism (RR 5.1). Blood transfusion was also associated with an increase in postoperative length of stay of 1.4 days (P < 0.001). Conclusion. 1 in 6 patients received a blood transfusion while undergoing primary posterior lumbar fusion, and risk factors for these occurrences were characterized. Strategies to minimize blood loss might be considered in these patients to avoid the associated complications. Level of Evidence: 3