Do risk calculators accurately predict surgical site occurrences?

Application of machine learning algorithms to predict postoperative surgical site infections and surgical site occurrences following inguinal hernia surgery

PURPOSE

This study aimed to develop, validate, and evaluate machine learning (ML) algorithms for predicting Surgical site infections (SSI) and surgical site occurrences (SSO) after elective open inguinal hernia surgery.

METHODS

A cohort of 491 patients who underwent elective open inguinal hernia surgery at Fudan University Affiliated Huadong Hospital between December 2019 and December 2020 was enrolled. To create a strong prediction model, we employed five ML methods: generalized linear model, random forest (RF), support vector machines, neural network, and gradient boosting machine. Based on the best performing model, we devised online calculators to facilitate clinicians' access to a linear predictor for patients. The receiver operating characteristic curve was utilized to evaluate the model's discriminatory capability and predictive accuracy.

RESULTS

The incidence rates of SSI and SSO were 4.68% and 13.44%, respectively. Four variables (diabetes, recurrence, antibiotic prophylaxis, and duration of surgery) were identified for SSI prediction, while four variables (diabetes, size of hernias, albumin levels, and antibiotic prophylaxis) were included for SSO prediction. In the test set, the RF model showed the best predictive ability (SSI: area under the curve (AUC) = 0.849, sensitivity = 0.769, specificity = 0.769, and accuracy = 0.769; SSO: AUC = 0.740, sensitivity = 0.513, specificity = 0.821, and accuracy = 0.667). Online calculators have been developed to assess patients' risk of SSI ( https://wuqian17.shinyapps.io/predictionSSI/ ) and SSO ( https://wuqian17.shinyapps.io/predictionSSO/ ) after surgery.

CONCLUSIONS

This study developed a prediction model for SSI/SSO using ML methods. It holds the potential to facilitate the selection of appropriate treatment options following elective open inguinal hernia surgery.

Lessons learnt from the construction and implementation of a prospective ventral hernia database

PURPOSE

The New England VA Hernia Registry was created in 2011 to prospectively collect relevant details of ventral hernia repairs, with the intention to assess and improve long term outcomes. The goal of this study is to assess registry compliance.

METHODS

All ventral hernia operations performed in five VA hospitals between 2011-2022 were obtained. We assessed compliance at the hospital and surgeon level.

RESULTS

3,516 cases were performed. Overall compliance with registry entry was 37.5%, ranging from 10.8% to 67.2% across hospitals. At the hospital level, there was a negative correlation between average yearly hernia volume per surgeon and registry compliance (r2 = 0.53). Surgeon compliance varied within hospitals and over time.

CONCLUSION

Registry compliance was low and highly variable. Lack of interest, incentives, oversight, and surgeon turnover are possible factors for noncompliance. Building a registry with these factors in mind, providing timely feedback, and conducting frequent audits may improve compliance.

Hernia-to-neck ratio is associated with emergent ventral hernia repair

BACKGROUND

The ratio of hernia size to fascial defect size, termed the hernia-to-neck ratio (HNR), has been proposed as a novel predictive factor for umbilical hernia complications. HNR ≥ 2.5 has been suggested to warrant surgery due to association with bowel strangulation, incarceration, and necrosis. The aim of this study was to evaluate the association between HNR and emergent ventral hernia repair at our institution.

METHODS

A retrospective cohort study was performed of consecutive patients with ventral hernias evaluated at a large safety-net hospital from 2017 to 2019. Patients who required emergent ventral hernia repair were compared to patients who did not require repair at latest follow-up. HNR was calculated using a previously described method: maximal hernia sac size and maximal fascial defect size (termed "hernia neck size") were measured in the sagittal plane on CT scan. Data are described as mean ± standard deviation and median (interquartile range).

RESULTS

A total of 166 patients were included: 84 (51%) required emergent hernia repair and 82 (49%) did not undergo repair. Median follow-up was 19 (8-27) months. Patient groups were similar except the emergent repair group had more males (50% vs. 34%, p = 0.03), umbilical hernias (93% vs. 56%, p < 0.01), recurrent hernias (31% vs. 15%, p < 0.01), and lower mean BMI (34.3 ± 9.9 vs. 39.1 ± 6.5, p < 0.01). Hernia sac size did not differ between groups (5.8 [3.8-8.4] cm vs. 6.1 [3.5-11.8] cm, p = 0.45). Hernia neck size was significantly smaller in the emergent repair group (1.5 [2.3-3.5] cm vs. 3.4 [1.8-6.2] cm, p < 0.01). Hernia-to-neck ratio was significantly higher in the emergent repair group (2.4 [1.8-3.1] vs. 1.7 [1.1-2.9], p < 0.01).

CONCLUSION

This study demonstrated an association between higher HNR and increased risk of emergent ventral hernia repair. Future studies will evaluate the use of HNR to risk-stratify patients with ventral hernias in a safety-net hospital.

Evaluation of the American College of Surgeons National Surgical Quality Improvement Program Risk Calculator to predict outcomes after hysterectomies

OBJECTIVE

To evaluate the American College of Surgeons (ACS) surgical risk calculator's reliability in predicting outcomes in hysterectomies.

METHODS

This is a prospective cohort study at a large community-based hospital. Twenty-one preoperative and postoperative criteria were abstracted from the electronic medical record and entered into the online ACS calculator to determine a risk score. Logistical regression was used to determine the association between risk score and actual outcome. The prediction capability was analyzed with c-statistic, Hosmer-Lemeshow, and Brier score.

RESULTS

A total of 634 hysterectomies were performed during the study period from January to April 2019. Patients were predominantly 55 years old, white (53%) and overweight (body mass index 30). Predicted perioperative adverse events were significantly higher than actual adverse events across all domains. In all, 54/634 (8.5%) patients experienced postoperative urinary tract infection. C-statistics for return to operating room, renal failure, and readmission were 0.607 (95% C Statistic index [CI] 0.370-0.845), 0.882 (95% CI 0.802-0.962), 0.637 (95% CI 0.524-0.750), respectively. Brier scores approached one in all categorical domains.

CONCLUSION

The ACS surgical risk calculator holds the promise of predicting postoperative complications or length of stay for patients undergoing hysterectomy. Further adjustment to this tool is required before it can be advocated for use in the clinical setting.

Evaluating the Inaccuracy of the National Surgical Quality Improvement Project Surgical Risk Calculator in Plastic Surgery: A Meta-analysis of Short-Term Predicted Complications

BACKGROUND

Preoperative surgical risk assessment is a major component of clinical decision making. The ability to provide accurate, individualized risk estimates has become critical because of growing emphasis on quality metrics benchmarks. The American College of Surgeons National Surgical Quality Improvement Project (NSQIP) Surgical Risk Calculator (SRC) was designed to quantify patient-specific risk across various surgeries. Its applicability to plastic surgery is unclear, however, with multiple studies reporting inaccuracies among certain patient populations. This study uses meta-analysis to evaluate the NSQIP SRC's ability to predict complications among patients having plastic surgery.

METHODS

OVID MEDLINE and PubMed were searched for all studies evaluating the predictive accuracy of the NSQIP SRC in plastic surgery, including oncologic reconstruction, ventral hernia repair, and body contouring. Only studies directly comparing SCR predicted to observed complication rates were included. The primary measure of SRC prediction accuracy, area under the curve (AUC), was assessed for each complication via DerSimonian and Laird random-effects analytic model. The I2 statistic, indicating heterogeneity, was judged low (I2 < 50%) or borderline/unacceptably high (I2 > 50%). All analyses were conducted in StataSE 16.1 (StataCorp LP, College Station, Tex).

RESULTS

Ten of the 296 studies screened met criteria for inclusion (2416 patients). Studies were classified as follows: (head and neck: n = 5, breast: n = 1, extremity: n = 1), open ventral hernia repair (n = 2), and panniculectomy (n = 1). Predictive accuracy was poor for medical and surgical complications (medical: pulmonary AUC = 0.67 [0.48-0.87], cardiac AUC = 0.66 [0.20-0.99], venous thromboembolism AUC = 0.55 [0.47-0.63]), (surgical: surgical site infection AUC = 0.55 [0.46-0.63], reoperation AUC = 0.54 [0.49-0.58], serious complication AUC = 0.58 [0.43-0.73], and any complication AUC = 0.60 [0.57-0.64]). Although mortality was accurately predicted in 2 studies (AUC = 0.87 [0.54-0.99]), heterogeneity was high with I2 = 68%. Otherwise, heterogeneity was minimal (I2 = 0%) or acceptably low (I2 < 50%) for all other outcomes.

CONCLUSIONS

The NSQIP Universal SRC, aimed at offering individualized quantifiable risk estimates for surgical complications, consistently demonstrated poor risk discrimination in this plastic surgery-focused meta-analysis. The limitations of the SRC are perhaps most pronounced where complex, multidisciplinary reconstructions are needed. Future efforts should identify targets for improving SRC reliability to better counsel patients in the perioperative setting and guide appropriate healthcare resource allocation.

Definitions for Loss of Domain: An International Delphi Consensus of Expert Surgeons

BACKGROUND

No standardized written or volumetric definition exists for 'loss of domain' (LOD). This limits the utility of LOD as a morphological descriptor and as a predictor of peri- and postoperative outcomes. Consequently, our aim was to establish definitions for LOD via consensus of expert abdominal wall surgeons.

METHODS

A Delphi study involving 20 internationally recognized abdominal wall reconstruction (AWR) surgeons was performed. Four written and two volumetric definitions of LOD were identified via systematic review. Panelists completed a questionnaire that suggested these definitions as standardized definitions of LOD. Consensus on a preferred term was pre-defined as achieved when selected by ≥80% of panelists. Terms scoring <20% were removed.

RESULTS

Voting commenced August 2018 and was completed in January 2019. Written definition: During Round 1, two definitions were removed and seven new definitions were suggested, leaving nine definitions for consideration. For Round 2, panelists were asked to select all appealing definitions. Thereafter, common concepts were identified during analysis, from which the facilitators advanced a new written definition. This received 100% agreement in Round 3. Volumetric definition: Initially, panelists were evenly split, but consensus for the Sabbagh method was achieved. Panelists could not reach consensus regarding a threshold LOD value that would preclude surgery.

CONCLUSIONS

Consensus for written and volumetric definitions of LOD was achieved from 20 internationally recognized AWR surgeons. Adoption of these definitions will help standardize the use of LOD for both clinical and academic activities.

Swiss Validation of the Enhanced Recovery After Surgery (ERAS) Database

Background

Enhanced recovery after surgery (ERAS) pathways have considerably improved postoperative outcomes and are in use for various types of surgery. The prospective audit system (EIAS) could be a powerful tool for large-scale outcome research but its database has not been validated yet.

Methods

Swiss ERAS centers were invited to contribute to the validation of the Swiss chapter for colorectal surgery. A monitoring team performed on-site visits by the use of a standardized checklist. Validation criteria were (I) coverage (No. of operated patients within ERAS protocol; target threshold for validation: ≥ 80%), (II) missing data (8 predefined variables; target ≤ 10%), and (III) accuracy (2 predefined variables, target ≥ 80%). These criteria were assessed by comparing EIAS entries with the medical charts of a random sample of patients per center (range 15–20).

Results

Out of 18 Swiss ERAS centers, 15 agreed to have onsite monitoring but 13 granted access to the final dataset. ERAS coverage was available in only 7 centers and varied between 76 and 100%. Overall missing data rate was 5.7% and concerned mainly the variables “urinary catheter removal” (16.4%) and “mobilization on day 1” (16%). Accuracy for the length of hospital stay and complications was overall 84.6%. Overall, 5 over 13 centers failed in the validation process for one or several criteria.

Conclusion

EIAS was validated in most Swiss ERAS centers. Potential patient selection and missing data remain sources of bias in non-validated centers. Therefore, simplified validation of other centers appears to be mandatory before large-scale use of the EIAS dataset.

Supplementary Information

The online version contains supplementary material available at (10.1007/s00268-020-05926-z).

Actionable Risk Model for the Development of Surgical Site Infection after Emergency Surgery

Background: Surgical site infections (SSIs) increase mortality and the economic burden associated with emergency surgery (ES). A reliable and sensitive scoring system to predict SSIs can help guide clinician assessment and patient counseling of post-operative SSI risk. We hypothesized that after quantifying the ES post-operative SSI incidence, readily abstractable parameters can be used to develop an actionable risk stratification scheme. Patients and Methods: We reviewed retrospectively all patients who underwent ES operations at an urban academic hospital system (2005-2013). Comorbidities and operative characteristics were abstracted from the electronic health record (EHR) with a primary outcome of post-operative SSIs. Risk of SSI was calculated using logistic regression modeling and validated using bootstrapping techniques. Beta-coefficients were calculated to correlate risk. A simplified clinical risk assessment tool was derived by assigning point values to the rounded β-coefficients. Results: A total of 4,783 patients with a 13.2% incidence of post-operative SSIs were identified. The strongest risk factors associated with SSIs included acute intestinal ischemia, weight loss, intestinal perforation, trauma-related laparotomy, radiation exposure, previous gastrointestinal surgery, and peritonitis. The assessment tool defined three patient groups based on SSI risk. Post-operative SSI incidence in high-risk patients (34%; score = 6-10) exceeded that of medium- (11.1%; score = 3-5) and low-risk patients (1.5%; score = 1-2) (C statistic = 0.802). Patients with a risk score ≥10 points evidenced the highest post-operative SSI risk (71.9%). Conclusion: Pre-operative identification of ES patient risk for post-operative SSI may inform pre-operative patient counseling and operative planning if the proposed procedure includes medical device implantation. A clinically relevant seven-factor risk stratification model such as this empirically derived one may be suitable to incorporate into the EHR as a decision-support tool.

Predicting Post-operative Complications in Crohn's Disease: an Appraisal of Clinical Scoring Systems and the NSQIP Surgical Risk Calculator

BACKGROUND

Surgery is common in patients with Crohn's disease and can contribute significantly to patient morbidity. The National Surgical Quality Improvement Program surgical risk calculator (NSQIP-SRC) that is currently utilized to predict surgical risk does not take Crohn's disease into account and, as a result, seems to underestimate risk in this patient population. This study aimed to evaluate the accuracy of the NSQIP-SRC in Crohn's disease patients and to evaluate the utility of disease severity scores in predicting surgical risk.

METHODS

Between 2011 and 2017, there were 176 surgical cases involving Crohn's disease patients. Demographic data and 30-day surgical outcomes were collected. Disease severity scores including Harvey Bradshaw Index (HBI), Crohn's Disease Activity Index (CDAI), Simple Endoscopic Score for Crohn's Disease (SES-CD), and NSQIP-SRC risk percentages were calculated.

RESULTS

Patients in remission based on HBI had a complication rate of 8.57% (n = 3), while those with mild or moderate-severe disease had rates of 33.33% (n = 11) and 38.46% (n = 20) respectively (p = 0.0045). In multivariable analysis, those with mild (OR; 8.37, 95% CI; 1.64, 42.78; p = 0.011) or moderate-severe (OR; 11.69, 95% CI; 2.42, 56.46; p = 0.002) disease had increased odds of complication compared to remission. Complication rate was not associated with NSQIP-SRC percent risk of any complication.

CONCLUSION

NSQIP-SRC does not accurately predict risk in patients with CD undergoing surgery. Higher disease activity based on HBI is associated with increased odds of complication and may prove to be more predictive of surgical complication in the Crohn's patient population.

ACS-NSQIP risk calculator predicts cohort but not individual risk of complication following colorectal resection

OBJECTIVE

Compare the ACS-NSQIP risk calculator with institutional risk for colorectal surgery.

METHODS

Actual and predicted outcomes were compared for both cohort and individuals.

RESULTS

For the cohort, the risk calculator was accurate for 7/8 outcomes; there were more serious complications than predicted (19.4 vs 14.7%, p < 0.05). Risk calculator Brier scores and null Brier scores were comparable.

PATIENTS

with better outcomes than predicted were current smokers (OR 4.3 95% CI 1.2-15.4), ASA ≥ 3 (OR 10.4, 95% CI 2.8-39.2), underwent total/subtotal colectomy (OR 3.5, 95% CI 1.1-12.2) or operated by Surgeon 2 (OR 2.9, 95% CI 1.4-11.6). Patients with serious complications who had low predicted risk had low ASA (OR 10.5, 95% CI 1.3-82.6), and underwent operation by Surgeon 2 (OR 11.8, 95% CI 2.5, 55.2).

LIMITATIONS

Single center study, sample size may bias subgroup analyses.

CONCLUSIONS

The ACS NSQIP calculator did not predict outcome better than sample risk.

Proposal for a national triage system for the management of ventral hernias

Ventral hernia disease is becoming increasingly prevalent and complex. Subspecialisation for patients with challenging conditions requiring surgery has been shown to improve postoperative outcomes. Worldwide, there is an emergence of specialist hernia centres using new and innovative techniques to repair large and complicated ventral hernias. After a national meeting of hernia experts, we present an algorithm to be used as a national triage system for patients with ventral hernias, with the aim of ensuring that patients are operated on by the most appropriate surgeon. Evidence-based clinical risk factors and ventral hernia parameters are used for risk stratification and patient triage. We hope that this algorithm will guide future ventral hernia management in the UK.

A systematic methodological review of reported perioperative variables, postoperative outcomes and hernia recurrence from randomised controlled trials of elective ventral hernia repair: clear definitions and standardised datasets are needed

BACKGROUND

This systematic review assesses the perioperative variables and post-operative outcomes reported by randomised controlled trials (RCTs) of VH repair. This review focuses particularly on definitions of hernia recurrence and techniques used for detection.

OBJECTIVE

Our aim is to identify and quantify the inconsistencies in perioperative variable and postoperative outcome reporting, so as to justify future development of clear definitions of hernia recurrence and a standardised dataset of such variables.

METHODS

The PubMed database was searched for elective VH repair RCTs reported January 1995 to March 2016 inclusive. Three independent reviewers performed article screening, and two reviewers independently extracted data. Hernia recurrence, recurrence rate, timing and definitions of recurrence, and techniques used to detect recurrence were extracted. We also assessed reported post-operative complications, standardised operative outcomes, patient reported outcomes, pre-operative CT scan hernia dimensions, intra-operative variables, patient co-morbidity, and hernia morphology.

RESULTS

31 RCTs (3367 patients) were identified. Only 6 (19.3%) defined hernia recurrence and methods to detect recurrence were inconsistent. Sixty-four different clinical outcomes were reported across the RCTs, with wound infection (30 trials, 96.7%), hernia recurrence (30, 96.7%), seroma (29, 93.5%), length of hospital stay (22, 71%) and haematoma (21, 67.7%) reported most frequently. Fourteen (45%), 11 (35%) and 0 trials reported CT measurements of hernia defect area, width and loss of domain, respectively. No trial graded hernias using generally accepted scales.

CONCLUSION

VH RCTs report peri- and post-operative variables inconsistently, and with poor definitions. A standardised minimum dataset, including definitions of recurrence, is required.

Early outcomes of an enhanced recovery protocol for open repair of ventral hernia

BACKGROUND

Enhanced recovery after surgery (ERAS) protocols are evidence-based quality improvement pathways reported to be associated with improved patient outcomes. The purpose of this study was to compare short-term outcomes for open ventral hernia repair (VHR) before and after implementation of an ERAS protocol.

METHODS

After obtaining IRB approval, surgical databases were searched for VHR cases for two years prior and eleven months after protocol implementation for retrospective review. Groups were compared on perioperative characteristics and clinical outcomes using chi-square, Fisher's exact, or Mann-Whitney U test, as appropriate.

RESULTS

One hundred and seventy-one patients underwent VHR (46 patients with ERAS protocol in place and 125 historic controls). Age, gender, ASA Class, comorbidities, and smoking status were similar between the two groups. Body mass index was lower among ERAS patients (p = .038). ERAS patients had earlier return of bowel function (median 3 vs. 4 days) (p = .003) and decreased incidence of superficial surgical site infection (SSI) (7 vs. 25%) (p = .008) than controls.

CONCLUSION

An ERAS protocol for VHR demonstrated improved patient outcomes. A system-wide culture focused on enhanced recovery is needed to ensure improved patient outcomes.

Surgical data science: The new knowledge domain

Healthcare in general, and surgery/interventional care in particular, is evolving through rapid advances in technology and increasing complexity of care, with the goal of maximizing the quality and value of care. Whereas innovations in diagnostic and therapeutic technologies have driven past improvements in the quality of surgical care, future transformation in care will be enabled by data. Conventional methodologies, such as registry studies, are limited in their scope for discovery and research, extent and complexity of data, breadth of analytical techniques, and translation or integration of research findings into patient care. We foresee the emergence of surgical/interventional data science (SDS) as a key element to addressing these limitations and creating a sustainable path toward evidence-based improvement of interventional healthcare pathways. SDS will create tools to measure, model, and quantify the pathways or processes within the context of patient health states or outcomes and use information gained to inform healthcare decisions, guidelines, best practices, policy, and training, thereby improving the safety and quality of healthcare and its value. Data are pervasive throughout the surgical care pathway; thus, SDS can impact various aspects of care, including prevention, diagnosis, intervention, or postoperative recovery. The existing literature already provides preliminary results, suggesting how a data science approach to surgical decision-making could more accurately predict severe complications using complex data from preoperative, intraoperative, and postoperative contexts, how it could support intraoperative decision-making using both existing knowledge and continuous data streams throughout the surgical care pathway, and how it could enable effective collaboration between human care providers and intelligent technologies. In addition, SDS is poised to play a central role in surgical education, for example, through objective assessments, automated virtual coaching, and robot-assisted active learning of surgical skill. However, the potential for transforming surgical care and training through SDS may only be realized through a cultural shift that not only institutionalizes technology to seamlessly capture data but also assimilates individuals with expertise in data science into clinical research teams. Furthermore, collaboration with industry partners from the inception of the discovery process promotes optimal design of data products as well as their efficient translation and commercialization. As surgery continues to evolve through advances in technology that enhance delivery of care, SDS represents a new knowledge domain to engineer surgical care of the future.

Patients at High-Risk for Surgical Site Infection

BACKGROUND

Surgical site infections (SSIs) are a significant healthcare quality issue, resulting in increased morbidity, disability, length of stay, resource utilization, and costs. Identification of high-risk patients may improve pre-operative counseling, inform resource utilization, and allow modifications in peri-operative management to optimize outcomes.

METHODS

Review of the pertinent English-language literature.

RESULTS

High-risk surgical patients may be identified on the basis of individual risk factors or combinations of factors. In particular, statistical models and risk calculators may be useful in predicting infectious risks, both in general and for SSIs. These models differ in the number of variables; inclusion of pre-operative, intra-operative, or post-operative variables; ease of calculation; and specificity for particular procedures. Furthermore, the models differ in their accuracy in stratifying risk. Biomarkers may be a promising way to identify patients at high risk of infectious complications.

CONCLUSIONS

Although multiple strategies exist for identifying surgical patients at high risk for SSIs, no one strategy is superior for all patients. Further efforts are necessary to determine if risk stratification in combination with risk modification can reduce SSIs in these patient populations.

Utilization of the NSQIP-Pediatric Database in Development and Validation of a New Predictive Model of Pediatric Postoperative Wound Complications

BACKGROUND

Surgical wound classification, introduced in 1964, stratifies the risk of surgical site infection (SSI) based on a clinical estimate of the inoculum of bacteria encountered during the procedure. Recent literature has questioned the accuracy of predicting SSI risk based on wound classification. We hypothesized that a more specific model founded on specific patient and perioperative factors would more accurately predict the risk of SSI.

STUDY DESIGN

Using all observations from the 2012 to 2014 pediatric National Surgical Quality Improvement Program-Pediatric (NSQIP-P) Participant Use File, patients were randomized into model creation and model validation datasets. Potential perioperative predictive factors were assessed with univariate analysis for each of 4 outcomes: wound dehiscence, superficial wound infection, deep wound infection, and organ space infection. A multiple logistic regression model with a step-wise backwards elimination was performed. A receiver operating characteristic curve with c-statistic was generated to assess the model discrimination for each outcome.

RESULTS

A total of 183,233 patients were included. All perioperative NSQIP factors were evaluated for clinical pertinence. Of the original 43 perioperative predictive factors selected, 6 to 9 predictors for each outcome were significantly associated with postoperative SSI. The predictive accuracy level of our model compared favorably with the traditional wound classification in each outcome of interest.

CONCLUSIONS

The proposed model from NSQIP-P demonstrated a significantly improved predictive ability for postoperative SSIs than the current wound classification system. This model will allow providers to more effectively counsel families and patients of these risks, and more accurately reflect true risks for individual surgical patients to hospitals and payers.

Surgical research using national databases

Recent changes in healthcare and advances in technology have increased the use of large-volume national databases in surgical research. These databases have been used to develop perioperative risk stratification tools, assess postoperative complications, calculate costs, and investigate numerous other topics across multiple surgical specialties. The results of these studies contain variable information but are subject to unique limitations. The use of large-volume national databases is increasing in popularity, and thorough understanding of these databases will allow for a more sophisticated and better educated interpretation of studies that utilize such databases. This review will highlight the composition, strengths, and weaknesses of commonly used national databases in surgical research.