Hospital Accreditation Status and Treatment Differences Among Black Patients With Colon Cancer.

Importance: Hospital-level factors, such as hospital type or volume, have been demonstrated to play a role in treatment disparities for Black patients with cancer. However, data evaluating the association of hospital accreditation status with differences in treatment among Black patients with cancer are lacking. Objective: To evaluate the association of Commission on Cancer (CoC) hospital accreditation status with receipt of guideline-concordant care and mortality among non-Hispanic Black patients with colon cancer. Design, Setting, and Participants: This population-based cohort study used the National Program of Cancer Registries, which is a multicenter database with data from all 50 states and the District of Columbia, and covers 97% of the cancer population in the US. The participants included non-Hispanic Black patients aged 18 years or older diagnosed with colon cancer between January 1, 2018, and December 31, 2020. Race and ethnicity were abstracted from medical records as recorded by health care facilities and practitioners. The data were analyzed from December 7, 2023, to January 17, 2024. Exposure: CoC hospital accreditation. Main Outcome and Measures: Guideline-concordant care was defined as adequate lymphadenectomy during surgery for patients with stages I to III disease or chemotherapy administration for patients with stage III disease. Multivariable logistic regression models investigated associations with receipt of guideline-concordant care and Cox proportional hazards regression models assessed associations with 3-year cancer-specific mortality. Results: Of 17 249 non-Hispanic Black patients with colon cancer (mean [SD] age, 64.8 [12.8] years; 8724 females [50.6%]), 12 756 (74.0%; mean [SD] age, 64.7 [12.8] years) were treated at a CoC-accredited hospital and 4493 (26.0%; mean [SD] age, 65.1 [12.5] years) at a non-CoC-accredited hospital. Patients treated at CoC-accredited hospitals compared with those treated at non-CoC-accredited hospitals had higher odds of receiving guideline-concordant lymphadenectomy (adjusted odds ratio [AOR], 1.89; 95% CI, 1.69-2.11) and chemotherapy (AOR, 2.31; 95% CI, 1.97-2.72). Treatment at CoC-accredited hospitals was associated with lower cancer-specific mortality for patients with stages I to III disease who received surgery (adjusted hazard ratio [AHR], 0.87; 95% CI, 0.76-0.98) and for patients with stage III disease eligible for chemotherapy (AHR, 0.75; 95% CI, 0.59-0.96). Conclusions and Relevance: In this cohort study of non-Hispanic Black patients with colon cancer, patients treated at CoC-accredited hospitals compared with those treated at non-CoC-accredited hospitals were more likely to receive guideline-concordant care and have lower mortality risk. These findings suggest that increasing access to high-quality guideline-concordant care at CoC-accredited hospitals may reduce variations in cancer treatment and outcomes for underserved populations.

Evidence Review for the American College of Surgeons Quality Verification Part III: Standardization, Protocols, and Achieving Better Outcomes for Patient Care.

BACKGROUND: After decades of experience supporting surgical quality and safety by the American College of Surgeons, the ACS Quality Verification Program (ACS QVP) was developed to help hospitals improve surgical quality and safety. This review is the final installment of a three-part review aimed to synthesize evidence supporting the main principles of the ACS QVP. STUDY DESIGN: Evidence was systematically reviewed for three principles: standardized team-based care across five phases of surgical care, disease-based management, and external regulatory review. MEDLINE was searched for articles published from inception to January 2019 and two reviewers independently screened studies for inclusion in a hierarchical fashion, extracted data, and summarized results in a narrative fashion. A total of 5,237 studies across these three topics were identified. Studies were included if they evaluated the relationship between the standard of interest and patient-level or organization measures within the last twenty years. RESULTS: After applying inclusion criteria, a total of 150 studies in systematic reviews and primary studies were included for assessment. Despite institutional variation in standardized clinical pathways, evidence demonstrated improved outcomes such as reduced length of stay (LOS), costs, and complications. Evidence for multidisciplinary disease-based care protocols was mixed, though trended towards improving patient outcomes such as reduced LOS and readmissions. Similarly, the evidence for accreditation and adherence to external process measures was also mixed, though several studies demonstrated the benefit of accreditation programs on patient outcomes. CONCLUSIONS: The identified literature supports the importance of standardized multidisciplinary and disease-based processes and external regulatory systems to improve quality of care.

Are We Supporting Surgical Quality Improvement in Training and Beyond? A Qualitative Study of Surgical Trainees and Practicing Surgeons.

BACKGROUND: We conducted a qualitative study to describe surgeon and surgical trainee perspectives of quality improvement (QI) in training and practice to elucidate how surgeons and trainees interact with barriers and leverage facilitators to learn and conduct QI. STUDY DESIGN: Surgeons and surgical trainees of the American College of Surgeons were recruited via email and snowball sampling to participate in focus groups. Eligible individuals were English speaking surgical trainees or practicing surgeons. We developed a semi-structured focus group protocol to explore barriers and facilitators of quality training and improvement. An inductive thematic approach was used to identify actionable items. RESULTS: Thirty-two surgical trainees and surgeons participated in six focus groups. 28% of participants were trainees (8 residents, 1 fellow) and 72% were practicing surgeons, representing practice settings in university, community, and Veterans Affairs hospitals in urban and suburban regions. Thematic analysis revealed the central theme among trainees was that they lacked necessary support to effectively learn and conduct QI. Dominant sub-themes included lack of formal education, insufficient time, inconsistent mentorship, and maximizing self-sufficiency to promotes success. The central theme among surgeons was that effective QI initiatives require adequate resources and institutional support; however, surgeons in this study were ultimately constrained by institutional limitations. Sub-themes included difficulties in data acquisition and interpretation, financial limitations, workforce and staffing challenges, misaligned stakeholder priorities, and institutional culture. CONCLUSION: This qualitative evaluation further details gaps in QI demonstrated by previous quantitative studies. There is an opportunity to address these gaps with dedicated QI training and mentorship for surgical trainees and by creating a supportive environment with ample resources for surgeons.

Patient-Reported Outcome Measures Within a National Multispecialty Surgical Quality Improvement Program.

Importance: Patient-reported outcome measures (PROMs) are increasingly recognized for their ability to promote patient-centered care, but concerted health information technology (HIT)-enabled PROM implementations have yet to be achieved for national surgical quality improvement. Objective: To evaluate the feasibility of collecting PROMs within a national surgical quality improvement program. Design, Setting, and Participants: This was a pragmatic implementation cohort study conducted from February 2020 to March 2023. Hospitals in the US participating in the American College of Surgeons National Surgical Quality Improvement Program and their patients were included in this analysis. Exposures: Strategies to increase PROM collection rates were identified using the Institute for Healthcare Improvement (IHI) Framework for Spread and the Consolidated Framework for Implementation Research and operationalized with the IHI Model for Improvement's Plan-Do-Study-Act (PDSA) cycles. Main Outcomes and Measures: The primary goal was to accrue more than 30 hospitals and achieve collection rates of 30% or greater in the first 3 years. Logistic regression was used to identify hospital-level factors associated with achieving collection rates of 30% or greater and to identify patient-level factors associated with response to PROMs. Results: At project close, 65 hospitals administered PROMs to 130 365 patients (median [IQR] age, 60.1 [46.2-70.0] years; 77 369 female [59.4%]). Fifteen PDSA cycles were conducted to facilitate implementation, primarily targeting the Consolidated Framework for Implementation Research domains of Inner Setting (ie, HIT platform) and Individuals (ie, patients). The target collection rate was exceeded in quarter 3 (2022). Fifty-eight hospitals (89.2%) achieved collection rates of 30% or greater, and 9 (13.8%) achieved collection rates of 50% or greater. The median (IQR) maximum hospital-level collection rate was 40.7% (34.6%-46.7%). The greatest increases in collection rates occurred when both email and short-message service text messaging were used, communications to patients were personalized with their surgeon's and hospital's information, and the number of reminders increased from 2 to 5. No identifiable hospital characteristic was associated with achieving the target collection rate. Patient age and insurance status contributed to nonresponse. Conclusions and Relevance: Results of this cohort study suggest that the large-scale electronic collection of PROMs into a national multispecialty surgical registry was feasible. Findings suggest that HIT platform functionality and earning patient trust were the keys to success; although, iterative opportunities to increase collection rates and address nonresponse remain. Future work to drive continuous surgical quality improvement with PROMs are ongoing.

Adding Patient-Reported Outcomes to the American College of Surgeons National Surgical Quality Improvement Program: Results of the First 33,842 Patients from 65 Hospitals.

OBJECTIVES: To investigate the initial set of patient-reported outcomes (PROs) in the ACS NSQIP and their associations with 30-day surgical outcomes. BACKGROUND: PROs provide important information that can be used to improve routine care and facilitate quality improvement. The ACS conducted a demonstration project to capture PROs into the NSQIP to complement clinical data. METHODS: From 2/2020-3/2023, 65 hospitals collected PROMIS measures assessing global health, pain interference, fatigue, and physical function from patients accrued into the NSQIP. Using multivariable mixed regression, we compared the scores of patients with and without 30-day complications and further analyzed scores exceeding one standard deviation (1-SD) worse than national benchmarks. RESULTS: Overall, 33842 patients completed the PROMIS measures a median 58 days (IQR 47-72) postoperatively. Among patients without complications (n=31210), 33.9% had PRO scores 1-SD worse than national benchmarks. Patients with complications were 1.7-times more likely to report worse PROs (95% CI 1.6-1.8). Patients with complications had lower scores for global physical health (adjusted mean difference [AMD] 2.6, 95% CI 2.2-3.0), lower for global mental health (AMD 1.8, 95% CI 1.4-2.2), higher for pain interference (AMD 2.4, 95% CI 2.0-2.8), higher fatigue (AMD 2.7, 95% CI 2.3-3.1), and lower physical function (AMD 3.2, 95% CI 2.8-3.5). CONCLUSIONS: Postoperative complications negatively affect multiple key dimensions of patients' health-related quality of life. PROs were well below national benchmarks for many patients, even among those without complications. Identifying solutions to improve PROs after surgery thus remains a tremendous quality opportunity.

Development and preliminary assessment of a machine learning model to predict myocardial infarction and cardiac arrest after major operations.

INTRODUCTION: Accurate prediction of complications often informs shared decision-making. Derived over 10 years ago to enhance prediction of intra/post-operative myocardial infarction and cardiac arrest (MI/CA), the Gupta score has been criticized for unreliable calibration and inclusion of a wide spectrum of unrelated operations. In the present study, we developed a novel machine learning (ML) model to estimate perioperative risk of MI/CA and compared it to the Gupta score. METHODS: Patients undergoing major operations were identified from the 2016-2020 ACS-NSQIP. The Gupta score was calculated for each patient, and a novel ML model was developed to predict MI/CA using ACS NSQIP-provided data fields as covariates. Discrimination (C-statistic) and calibration (Brier score) of the ML model were compared to the existing Gupta score within the entire cohort and across operative subgroups. RESULTS: Of 2,473,487 patients included for analysis, 25,177 (1.0%) experienced MI/CA (55.2% MI, 39.1% CA, 5.6% MI and CA). The ML model, which was fit using a randomly selected training cohort, exhibited higher discrimination within the testing dataset compared to the Gupta score (C-statistic 0.84 vs 0.80, p < 0.001). Furthermore, the ML model had significantly better calibration in the entire cohort (Brier score 0.0097 vs 0.0100). Model performance was markedly improved among patients undergoing thoracic, aortic, peripheral vascular and foregut surgery. CONCLUSIONS: The present ML model outperformed the Gupta score in the prognostication of MI/CA across a heterogenous range of operations. Given the growing integration of ML into healthcare, such models may be readily incorporated into clinical practice and guide benchmarking efforts.

Identifying Population-Level and Within-Hospital Disparities in Surgical Care.

BACKGROUND: The lack of consensus on equity measurement and its incorporation into quality-assessment programs at the hospital and system levels may be a barrier to addressing disparities in surgical care. This study aimed to identify population-level and within-hospital differences in the quality of surgical care provision. STUDY DESIGN: The analysis included 657 NSQIP participating hospitals with more than 4 million patients (2014 to 2018). Multilevel random slope, random intercept modeling was used to examine for population-level and in-hospital disparities. Disparities in surgical care by Area Deprivation Index (ADI), race, and ethnicity were analyzed for 5 measures: all-case inpatient mortality, all-case urgent readmission, all-case postoperative surgical site infection, colectomy mortality, and spine surgery complications. RESULTS: Population-level disparities were identified across all measures by ADI, 2 measures for Black race (all-case readmissions and spine surgery complications), and none for Hispanic ethnicity. Disparities remained significant in the adjusted models. Before risk adjustment, in all measures examined, within-hospital disparities were detected in: 25.8% to 99.8% of hospitals for ADI, 0% to 6.1% of hospitals for Black race, and 0% to 0.8% of hospitals for Hispanic ethnicity. After risk adjustment, in all measures examined, less than 1.1% of hospitals demonstrated disparities by ADI, race, or ethnicity. CONCLUSIONS: After risk adjustment, very few hospitals demonstrated significant disparities in care. Disparities were more frequently detected by ADI than by race and ethnicity. The lack of substantial in-hospital disparities may be due to the use of postoperative metrics, small sample sizes, the risk adjustment methodology, and healthcare segregation. Further work should examine surgical access and healthcare segregation.

Identifying a common data dictionary across colorectal cancer outcome registries: A mapping exercise to identify opportunities for data dictionary harmonisation.

IMPORTANCE: The development of colorectal cancer outcome registries internationally has been organic, with differing datasets, data definitions and infrastructure across registries which has limited data pooling and international comparison. Currently there is no comprehensive data dictionary identified as a standard. This study is part of an international collaboration that aims to identify areas of data capture and usage which may be optimised to improve understanding of colorectal cancer outcomes. OBJECTIVE: This study aimed to compare and identify commonalities and areas of difference across major colorectal cancer registries. We sought to establish datasets comprising of mutually collected common fields, and a combined comprehensive dataset of all collected fields across major registries to aid in establishing a future colorectal cancer registry database standard. DESIGN AND METHODS: This mixed qualitative and quantitative study compared data dictionaries from three major colorectal cancer outcome registries: Bowel Cancer Outcomes Registry (BCOR) (Australia and New Zealand), National Bowel Cancer Audit (NBOCA) (United Kingdom) and Dutch ColoRectal Audit (DCRA) (Netherlands). Registries were compared and analysed thematically, and a common dataset and combined comprehensive dataset were developed. These generated datasets were compared to data dictionaries from Sweden (SCRCR), Denmark (DCCG), Argentina (BNCCR-A) and the USA (NAACCR and ACS NSQIP). Fields were assessed against prominent quality indicator metrics from the literature and current case-use. RESULTS: We developed a combined comprehensive dataset of 225 fields under seven domains: demographic, pre-operative, operative, post-operative, pathology, neoadjuvant therapy, adjuvant therapy, and follow up/recurrence. A common dataset was developed comprising 38 overlapping fields, showing a low degree of mutually collected data, especially in preoperative, post operative and adjuvant therapy domains. The BNCCR-A, SCRCR and DCCG databases all contained a high percentage of common dataset fields. Fields were poorly comparable when viewed form current quality indicator metrics. CONCLUSION: This study mapped data dictionaries of prominent colorectal cancer registries and highlighted areas of commonality and difference The developed common field dataset provides a foundation for registries to benchmark themselves and work towards harmonisation of data dictionaries. This has the potential to enable meaningful large-scale international outcomes research.

The Accuracy of the NSQIP Universal Surgical Risk Calculator Compared to Operation-Specific Calculators.

Objective: To compare the performance of the ACS NSQIP "universal" risk calculator (N-RC) to operation-specific RCs. Background: Resources have been directed toward building operation-specific RCs because of an implicit belief that they would provide more accurate risk estimates than the N-RC. However, operation-specific calculators may not provide sufficient improvements in accuracy to justify the costs in development, maintenance, and access. Methods: For the N-RC, a cohort of 5,020,713 NSQIP patient records were randomly divided into 80% for machine learning algorithm training and 20% for validation. Operation-specific risk calculators (OS-RC) and OS-RCs with operation-specific predictors (OSP-RC) were independently developed for each of 6 operative groups (colectomy, whipple pancreatectomy, thyroidectomy, abdominal aortic aneurysm (open), hysterectomy/myomectomy, and total knee arthroplasty) and 14 outcomes using the same 80%/20% rule applied to the appropriate subsets of the 5M records. Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), and Hosmer-Lemeshow (H-L) P values, for 13 binary outcomes, and mean squared error for the length of stay outcome. Results: The N-RC was found to have greater AUROC (P = 0.002) and greater AUPRC (P < 0.001) compared to the OS-RC. No other statistically significant differences in accuracy, across the 3 risk calculator types, were found. There was an inverse relationship between the operation group sample size and magnitude of the difference in AUROC (r = -0.278; P = 0.014) and in AUPRC (r = -0.425; P < 0.001) between N-RC and OS-RC. The smaller the sample size, the greater the superiority of the N-RC. Conclusions: While operation-specific RCs might be assumed to have advantages over a universal RC, their reliance on smaller datasets may reduce their ability to accurately estimate predictor effects. In the present study, this tradeoff between operation specificity and accuracy, in estimating the effects of predictor variables, favors the N-R, though the clinical impact is likely to be negligible.