Indications for spine surgery: validation of an administrative coding algorithm to classify degenerative diagnoses.
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ABSTRACT: Retrospective analysis of Medicare claims linked to a multicenter clinical trial.The Spine Patient Outcomes Research Trial (SPORT) provided a unique opportunity to examine the validity of a claims-based algorithm for grouping patients by surgical indication. SPORT enrolled patients for lumbar disc herniation, spinal stenosis, and degenerative spondylolisthesis. We compared the surgical indication derived from Medicare claims with that provided by SPORT surgeons, the "gold standard."Administrative data are frequently used to report procedure rates, surgical safety outcomes, and costs in the management of spinal surgery. However, the accuracy of using diagnosis codes to classify patients by surgical indication has not been examined.Medicare claims were link to beneficiaries enrolled in SPORT. The sensitivity and specificity of 3 claims-based approaches to group patients on the basis of surgical indications were examined: (1) using the first listed diagnosis; (2) using all diagnoses independently; and (3) using a diagnosis hierarchy on the basis of the support for fusion surgery.Medicare claims were obtained from 376 SPORT participants, including 21 with disc herniation, 183 with spinal stenosis, and 172 with degenerative spondylolisthesis. The hierarchical coding algorithm was the most accurate approach for classifying patients by surgical indication, with sensitivities of 76.2%, 88.1%, and 84.3% for disc herniation, spinal stenosis, and degenerative spondylolisthesis cohorts, respectively. The specificity was 98.3% for disc herniation, 83.2% for spinal stenosis, and 90.7% for degenerative spondylolisthesis. Misclassifications were primarily due to codes attributing more complex pathology to the case.Standardized approaches for using claims data to group patients accurately by surgical indications have widespread interest. We found that a hierarchical coding approach correctly classified more than 90% of spine patients into their respective SPORT cohorts. Therefore, claims data seem to be a reasonably valid approach to classifying patients by surgical indication.3.
<h4>Study design</h4>Retrospective analysis of Medicare claims linked to a multicenter clinical trial.<h4>Objective</h4>The Spine Patient Outcomes Research Trial (SPORT) provided a unique opportunity to examine the validity of a claims-based algorithm for grouping patients by surgical indication. SPORT enrolled patients for lumbar disc herniation, spinal stenosis, and degenerative spondylolisthesis. We compared the surgical indication derived from Medicare claims with that provided by SPORT surg ...[more]
Project description:PURPOSE:A standardized definition for serious opioid overdose has not been clearly established for disease surveillance or assessing the impact of risk mitigation strategies. The purpose of this study was to use medical chart review to clinically validate a claims-based algorithm to identify serious opioid overdose events. METHODS:The algorithm for serious opioid overdose required an opioid poisoning or external cause ICD-9-CM code occurring within 1 day of (a) an adverse effect code for serious central nervous system or respiratory depression or (b) a mechanical ventilation or critical care CPT code. The claims coding algorithm identified a sample of 145 individuals 18 years or older among patients that presented to the emergency department of two large hospitals in metropolitan Atlanta, Georgia from January 2014 to August 2015. Claims-defined cases were evaluated against rigorous clinical definitions for serious opioid overdose using (a) literature-based criteria for typical clinical manifestations of opioid overdose and/or (b) clinical response to the opioid-specific reversal agent naloxone. The positive predictive value (PPV) for a serious opioid overdose was calculated as the percentage of clinically confirmed cases (definite or probable). RESULTS:Among 140 evaluable claims-defined cases, 107 fulfilled clinical criteria for a serious opioid overdose [95 definite and 12 probable; PPV of 76.4% (95% CI 69.4%, 83.5%)]. Among 30 nonconfirmed cases, 20 were polyintoxications involving one or more nonopioid psychoactive agents. CONCLUSIONS:An administrative claims coding algorithm for serious opioid overdose had high clinical predictive performance in a medical chart review.
Project description:BACKGROUND:Determining the primary indication of a surgical procedure can be useful in identifying patients undergoing elective surgery where shared decision-making is recommended. The purpose of this study was to develop and validate an algorithm to identify patients receiving the following combinations of surgical procedure and primary indication as part of a study to promote shared decision-making: (1) knee arthroplasty to treat knee osteoarthritis (KOA); (2) hip arthroplasty to treat hip osteoarthritis (HOA); (3) spinal surgery to treat lumbar spinal stenosis (SpS); and (4) spinal surgery to treat lumbar herniated disc (HD). METHODS:Consecutive surgical procedures performed by participating spine, hip, and knee surgeons at four sites within an integrated care network were included. Study staff reviewed electronic medical records to ascertain a "gold standard" determination of the procedure and primary indication status. Electronic algorithms consisting of ICD-10 and CPT codes for each combination of procedure and indication were then applied to records for each case. The primary measures of validity for the algorithms were the sensitivity and specificity relative to the gold standard review. RESULTS:Participating surgeons performed 790 procedures included in this study. The sensitivity of the algorithms in determining whether a surgical case represented one of the combinations of procedure and primary indication ranged from 0.70 (HD) to 0.92 (KOA). The specificity ranged from 0.94 (SpS) to 0.99 (HOA, KOA). CONCLUSION:The electronic algorithm was able to identify all four procedure/primary indication combinations of interest with high specificity. Additionally, the sensitivity for the KOA cases was reasonably high. For HOA and the spine conditions, additional work is needed to improve the sensitivity of the algorithm to identify the primary indication for each case.
Project description:BackgroundThe incidence of surgery for degenerative cervical spine disease (DCSD) has risen by almost 150% in the USA in the last three decades and stabilized at slightly over 70 operations/100,000 people. There has been significant regional variation in the operation incidences. We aim to assess the diagnosis-based, age-adjusted trends in the operation incidences and the regional variation in Finland between 1999 and 2015.MethodsData from the Finnish Hospital Discharge Register (FHDR), the Cause of Death Register, and the registers of the Social Insurance Institution were combined to analyze all the primary operations for DCSD or rheumatoid atlanto-axial subluxation (rAAS). Combinations of the operative and the diagnosis codes were used to classify the patients into five diagnostic groups.ResultsA total of 19,701 primary operations were included. The age-adjusted operation incidence rose from 21.0 to 36.5/100,000 people between 1999 and 2013 and plateaued thereafter. The incidence of surgery for radiculopathy increased from 13.1 to 23.3 operations/100,000 people, and the incidence of surgery for DCM increased from 5.8 to 7.0 operations/100,000 people. The rise was especially pronounced in surgery for foraminal stenosis, which increased from 5.3 to 12.4 operations/100,000 people. Of the five diagnostic groups, only operations for rAAS declined. Operations increased especially in the 40- to 65-year-old age group. The overall operation incidences varied from 18.3 to 43.1 operations/100,000 people between the university hospitals.ConclusionsThe age-adjusted incidence of surgery for DCSD has risen in Finland by 76%, but the rise has plateaued. Surgery for radiculopathy, especially for foraminal stenosis, increased more steeply than surgery for degenerative medullopathy, with vast regional differences in the operation incidences.
Project description:INTRODUCTION:Postoperative atrial fibrillation (POAF) is a frequent complication of cardiac surgery associated with important morbidity, mortality, and costs. To assess the effectiveness of preventive interventions, an important prerequisite is to have access to accurate measures of POAF incidence. The aim of this study was to develop and validate such a measure. METHODS:A validation study was conducted at two large Canadian university health centers. First, a random sample of 976 (10.4%) patients who had cardiac surgery at these sites between 2010 and 2016 was generated. Then, a reference standard assessment of their medical records was performed to determine their true POAF status on discharge (positive/negative). The accuracy of various algorithms combining diagnostic and procedure codes from: 1) the current hospitalization, and 2) hospitalizations up to 6 years before the current hospitalization was assessed in comparison with the reference standard. Overall and site-specific estimates of sensitivity, specificity, positive (PPV), and negative (NPV) predictive values were generated, along with their 95%CIs. RESULTS:Upon manual review, 324 (33.2%) patients were POAF-positive. Our best-performing algorithm combining data from both sites used a look-back window of 6?years to exclude patients previously known for AF. This algorithm achieved 70.4% sensitivity (95%CI: 65.1-75.3), 86.0% specificity (95%CI: 83.1-88.6), 71.5% PPV (95%CI: 66.2-76.4), and 85.4% NPV (95%CI: 82.5-88.0). However, significant site-specific differences in sensitivity and NPV were observed. CONCLUSION:An algorithm based on administrative data can identify POAF patients with moderate accuracy. However, site-specific variations in coding practices have significant impact on accuracy.
Project description:BackgroundEstimating surgical case duration accurately is an important operating room efficiency metric. Current predictive techniques in spine surgery include less sophisticated approaches such as classical multivariable statistical models. Machine learning approaches have been used to predict outcomes such as length of stay and time returning to normal work, but have not been focused on case duration.ObjectiveThe primary objective of this 4-year, single-academic-center, retrospective study was to use an ensemble learning approach that may improve the accuracy of scheduled case duration for spine surgery. The primary outcome measure was case duration.MethodsWe compared machine learning models using surgical and patient features to our institutional method, which used historic averages and surgeon adjustments as needed. We implemented multivariable linear regression, random forest, bagging, and XGBoost (Extreme Gradient Boosting) and calculated the average R2, root-mean-square error (RMSE), explained variance, and mean absolute error (MAE) using k-fold cross-validation. We then used the SHAP (Shapley Additive Explanations) explainer model to determine feature importance.ResultsA total of 3189 patients who underwent spine surgery were included. The institution's current method of predicting case times has a very poor coefficient of determination with actual times (R2=0.213). On k-fold cross-validation, the linear regression model had an explained variance score of 0.345, an R2 of 0.34, an RMSE of 162.84 minutes, and an MAE of 127.22 minutes. Among all models, the XGBoost regressor performed the best with an explained variance score of 0.778, an R2 of 0.770, an RMSE of 92.95 minutes, and an MAE of 44.31 minutes. Based on SHAP analysis of the XGBoost regression, body mass index, spinal fusions, surgical procedure, and number of spine levels involved were the features with the most impact on the model.ConclusionsUsing ensemble learning-based predictive models, specifically XGBoost regression, can improve the accuracy of the estimation of spine surgery times.
Project description:Retrospective administrative database analysis.To determine the impact of glycemic control on perioperative complications and outcomes in patients undergoing degenerative cervical spine surgery.Diabetes mellitus (DM) is a highly prevalent systemic disease that has been shown to increase morbidity and mortality after spine surgery. Few studies have demonstrated negative effects on patients with DM who undergo cervical spine procedures; however, whether glycemic control influences surgical outcome is still unknown.The Nationwide Inpatient Sample was queried from 2002 to 2011. Patients who underwent cervical spine surgery for degenerative conditions were identified using the International Classification of Diseases Ninth Revision, Clinical Modification, codes. Three surgical cohorts were chosen: controlled diabetic, uncontrolled diabetic, and patients without diabetes. Patient demographics, surgical procedures, perioperative complications and postoperative outcomes were assessed.The prevalence of controlled and uncontrolled diabetic patients undergoing degenerative cervical spine surgery had been increasing significantly from 2002 to 2011. Compared with patients without diabetes, uncontrolled diabetic patients had significantly increased odds of respiratory, cardiac, and genitourinary complications. Uncontrolled diabetic patients also had significantly increased risk of pulmonary embolism and postoperative infection. Uncontrolled diabetic patients had increased risk of inpatient mortality (odds ratio = 6.39, 95% confidence interval = 4.09-10.00, P < 0.0001) and increased mean length of stay (almost 5 d) compared with nondiabetic patients. Similarly, controlled diabetic patients increased the odds of perioperative complications; however not nearly to the same degree. Controlled diabetic patients extended the mean length of stay by almost a day (P < 0.0001) and significantly increased costs compared with nondiabetic patients.Poor glycemic control increases the odds of inpatient mortality and perioperative complications in patients undergoing degenerative cervical spine surgery. Controlling DM before degenerative cervical spine surgery may lead to better outcomes and decreased costs.Therapeutic Level 3.
Project description:Background: One of the most frequent complications of spinal surgery is accidental dural tears (ADTs). Minimal access surgical techniques (MAST) have been described as a promising approach to minimizing such complications. ADTs have been studied extensively in connection with open spinal surgery, but there is less literature on minimally invasive spinal surgery (MISS). Materials and Methods: We reviewed 187 patients who had undergone degenerative lumbar spinal surgery using minimally invasive spinal fusions techniques. We analyzed the influence of age, Body Mass Index (BMI), smoking, diabetes, and previous surgery on the rate of ADTs in MISS. Results: Twenty-two patients (11.764%) suffered from an ADT. We recommended bed rest for two and a half to 5 days, depending on the type of repair required and the amount of cerebrospinal fluid (CSF) leakage. We could not find any statistically significant correlation between ADTs and age (p = 0.34,), BMI (p = 0.92), smoking (p = 0.46), and diabetes (p = 0.71). ADTs were significantly more frequent in cases of previous surgery (p < 0.001). None of the patients developed a transcutaneous CSF leak or post-operative infection. Conclusions: The frequency of ADTs in MISS appears comparable to that encountered when using open surgical techniques. Additionally, MAST produces less dead space along the corridor to the spine. Such reduced dead space may not be enough for pseudomeningocele to occur, cerebrospinal fluid to accumulate, and fistula to form. MAST, therefore, provides a certain amount of protection.
Project description:Study designRetrospective database analysis.ObjectiveTo assess the effect glycemic control has on perioperative morbidity and mortality in patients undergoing elective degenerative lumbar spine surgery.Summary of background dataDiabetes mellitus (DM) is a prevalent disease of glucose dysregulation that has been demonstrated to increase morbidity and mortality after spine surgery. However, there is limited understanding of whether glycemic control influences surgical outcomes in patients with DM undergoing lumbar spine procedures for degenerative conditions.MethodsThe Nationwide Inpatient Sample was analyzed from 2002 to 2011. Hospitalizations were isolated on the basis of International Classification of Diseases, Ninth Revision, Clinical Modification, procedural codes for lumbar spine surgery and diagnoses codes for degenerative conditions of the lumbar spine. Patients were then classified into 3 cohorts: controlled diabetic, uncontrolled diabetic, and nondiabetic. Patient demographic data, acute complications, and hospitalization outcomes were determined for each cohort.ResultsA total of 403,629 (15.7%) controlled diabetic patients and 19,421 (0.75%) uncontrolled diabetic patients underwent degenerative lumbar spine surgery from 2002 to 2011. Relative to nondiabetic patients, uncontrolled diabetic patients had significantly increased odds of cardiac complications, deep venous thrombosis, and postoperative shock; in addition, uncontrolled diabetic patients also had an increased mean length of stay (approximately, 2.5 d), greater costs (1.3-fold), and a greater risk of inpatient mortality (odds ratio=2.6, 95% confidence interval=1.5-4.8, P<0.0009). Controlled diabetic patients also had increased risk of acute complications and inpatient mortality when compared with nondiabetic patients, but not nearly to the same magnitude as uncontrolled diabetic patients.ConclusionSuboptimal glycemic control in diabetic patients undergoing degenerative lumbar spine surgery leads to increased risk of acute complications and poor outcomes. Patients with uncontrolled DM, or poor glucose control, may benefit from improving glycemic control prior to surgery.Level of evidence3.
Project description:BackgroundValidated administrative codes (CPT and ICD) can permit the use of large databases to study diseases and outcomes. The aim of this study was to validate administrative codes for surgery and obstructive complications in patients with inflammatory bowel disease (IBD).MethodsWe performed a retrospective study of IBD patients within the Veterans Affairs Health Administration (VA) from 2000 to 2015 with administrative codes for bowel surgery and complications validated by chart review. Positive predictive values (PPVs) and negative predictive value (NPV) were calculated.ResultsThe PPV for bowel surgery was 96.4%; PPV of obstruction codes for bowel obstruction was 80.5% (95% confidence interval: 69.1%, 89.2%).ConclusionsCPT and ICD codes for abdominal surgery and obstructive complications can be accurately utilized in IBD patients in VA.
Project description:BackgroundSurgery is the primary treatment for colorectal cancer for both curative and palliative intent. Availability of high quality surgery data is essential for assessing many aspects of the quality of colorectal cancer care. The objective of this study was to determine the quality of different administrative data sources in identifying surgery for colorectal cancer with respect to completeness and accuracy.MethodsAll residents in Alberta, Canada who were diagnosed with invasive colorectal cancer in years 2000-2005 were identified from the Alberta Cancer Registry and included in the study. Surgery data for these patients were obtained from the Cancer Registry (which collects the date of surgery for which the primary tumor was removed) and compared to surgery data obtained from two different administrative data sources: Physician Billing and Hospital Inpatient data. Sensitivity, specificity, positive predictive value, negative predictive value and observed agreement were calculated compared to the Cancer Registry data.ResultsThe Physician Billing data alone or combined with Hospital Inpatient data demonstrated equally high sensitivity (97% for both) and observed agreement with the Cancer Registry data (93% for both) for identifying surgeries. The Hospital Inpatient data, however, had the highest specificity (80%). The positive predictive value varied by disease stage and across data sources for stage IV (99% for stages I-III and 83-89% for stage IV), the specificity is better for colon cancer surgeries (72-85%) than for rectal cancer surgeries (60-73%); validation measures did not vary over time.ConclusionPhysician Billing data identify the colorectal cancer surgery more completely than Hospital Inpatient data although both sources have a high level of completeness.
