Using Administrative Databases to Measure Surgical Quality for Rectal Cancer at The Ottawa Hospital from 1996-2010

Purpose: The purpose of this thesis was threefold: 1) To explore the use of text-search methods for identifying rectal cancer patients in large datasets; 2) To examine temporal trends of surgical quality indicators for rectal cancer at a single, tertiary-care institution; 3) To validate the use of administrative codes for identifying rectal cancer patients in population-based datasets.\ud \ud Methods: 1) A text-search algorithm was developed, validated, and applied to all pathology reports at The Ottawa Hospital (TOH) over a 15-year period. Positive records were confirmed through manual chart review, and a gold-standard cohort of all rectal cancer resections performed at TOH was created. 2) Univariate and multivariate analyses were performed to assess temporal trends and associated factors for four (4) key surgical quality indicators. 3) Previously published methods for identifying rectal cancer resections in population-based datasets were validated using the cohort of patients created in Objective 1 as a gold standard.\ud \ud Results: 1) The text-search algorithm had a sensitivity and specificity of 100% and 98.4%, respectively. Because of low disease prevalence, positive predictive value (PPV) was 18.6%. 2) The proportion of resections with successful lymph node retrieval improved significantly over the course of the study period. No change was demonstrated for the remaining 3 surgical quality indicators. 3) Previously described methods that utilize procedure codes to identify rectal cancer resections in large administrative datasets had a sensitivity and specificity of 89.5% and 99.9%, respectively, with a PPV of 64.9%.\ud \ud Conclusions: It is feasible to utilize both procedure codes and text-search methods to identify patients with surgical resections for rectal cancer in administrative datasets. However, these methods are at risk of being inaccurate and resulting cohorts should be validated. Creating large cohorts of rectal cancer patients can be useful for studying a variety of subjects, including surgical quality

The Surgical Site Infection Risk Score (SSIRS): A Model to Predict the Risk of Surgical Site Infections

Surgical site infections (SSI) are an important cause of peri-surgical morbidity with risks that vary extensively between patients and surgeries. Quantifying SSI risk would help identify candidates most likely to benefit from interventions to decrease the risk of SSI.Methods: We randomly divided all surgeries recorded in the National Surgical Quality Improvement Program from 2010 into a derivation and validation population. We used multivariate logistic regression to determine the independent association of patient and surgical covariates with the risk of any SSI (including superficial, deep, and organ space SSI) within 30 days of surgery. To capture factors particular to specific surgeries, we developed a surgical risk score specific to all surgeries having a common first 3 numbers of their CPT code. Results: Derivation (n = 181 894) and validation (n = 181 146) patients were similar for all demographics, past medical history, and surgical factors. Overall SSI risk was 3.9%. The SSI Risk Score (SSIRS) found that risk increased with patient factors (smoking, increased body mass index), certain comorbidities (peripheral vascular disease, metastatic cancer, chronic steroid use, recent sepsis), and operative characteristics (surgical urgency; increased ASA class; longer operation duration; infected wounds; general anaesthesia; performance of more than one procedure; and CPT score). In the validation population, the SSIRS had good discrimination (c-statistic 0.800, 95% CI 0.795–0.805) and calibration. Conclusion: SSIRS can be calculated using patient and surgery information to estimate individual risk of SSI for a broad range of surgery types

Can text-search methods of pathology reports accurately identify patients with rectal cancer in large administrative databases?

Background: The aim of this study is to derive and to validate a cohort of rectal cancer surgical patients within administrative datasets using text-search analysis of pathology reports. Materials and Methods: A text-search algorithm was developed and validated on pathology reports from 694 known rectal cancers, 1000 known colon cancers, and 1000 noncolorectal specimens. The algorithm was applied to all pathology reports available within the Ottawa Hospital Data Warehouse from 1996 to 2010. Identified pathology reports were validated as rectal cancer specimens through manual chart review. Sensitivity, specificity, and positive predictive value (PPV) of the text-search methodology were calculated. Results: In the derivation cohort of pathology reports (n = 2694), the text-search algorithm had a sensitivity and specificity of 100% and 98.6%, respectively. When this algorithm was applied to all pathology reports from 1996 to 2010 (n = 284,032), 5588 pathology reports were identified as consistent with rectal cancer. Medical record review determined that 4550 patients did not have rectal cancer, leaving a final cohort of 1038 rectal cancer patients. Sensitivity and specificity of the text-search algorithm were 100% and 98.4%, respectively. PPV of the algorithm was 18.6%. Conclusions: Text-search methodology is a feasible way to identify all rectal cancer surgery patients through administrative datasets with high sensitivity and specificity. However, in the presence of a low pretest probability, text-search methods must be combined with a validation method, such as manual chart review, to be a viable approach

Comparison of BioLIFT versus LIFT for the treatment of trans-sphincteric anal fistula: a protocol for systematic review and meta-analysis

Introduction Identifying the optimal treatment for anal fistula has been challenging. Since first reported in 2007, the ligation of the intersphincteric fistula tract (LIFT) procedure has reported healing rates between 40% and 95% and is being increasingly adopted. The BioLIFT is an augmentation of the LIFT with an intersphincteric bioprosthetic mesh and has reported healing rates between 69% and 94%. Despite increased costs and potential complications associated with mesh, the evidence comparing healing rates between BioLIFT and LIFT is unknown. This study details the protocol for a systematic review and meta-analysis of BioLIFT and LIFT to compare outcomes associated with each procedure.Methods and analysis MEDLINE, EMBASE and the Cochrane Database will be searched from inception using a search strategy designed by an information specialist. Randomised controlled trials, prospective and retrospective cohort studies, consecutive series, cross-sectional studies and case series with more than five patients will be included. Both comparative and single group studies will be included. The eligible population will be adult patients undergoing BioLIFT or LIFT for trans-sphincteric anal fistula. The primary outcome will be primary healing rate. Secondary outcomes will capture secondary healing rate and complications. Abstract, full text and data extraction will be completed independently and in duplicate by two reviewers. Study risk of bias will be assessed using Risk of Bias In Non-randomized Studies - of Interventions and the Risk of Bias (RoB 2.0) tool. Quality of evidence for outcomes will be evaluated using Grading of Recommendations, Assessment, Development and Evaluations criteria. A meta-analysis will be performed using a random-effects inverse variance model. Subgroup and sensitivity analyses will be explored in relation to complex fistula characteristics and patients who have undergone previous LIFT. Heterogeneity will be assessed using the I2 statistic.Ethics and dissemination This review does not require research ethics board approval. This study will be completed in September 2022. The findings of this study will be disseminated through peer-reviewed international conferences and journals.PROSPERO registration number CRD42020127996