National Quality Improvement Program Research Articles

Leveraging local health system resources to address quality healthcare gaps in sub-Saharan African: lessons from the SafeCare quality improvement programme in Ghana

IntroductionIn low- and-middle-income-countries (LMICs) like Ghana, universal access to quality healthcare remains a mirage and this undermines achievement of sustainable development goal (SDG) 3. The SafeCare Quality Improvement (QI) programme is an initiative of PharmAccess Foundation, a Netherlands-based non-governmental organisation (NGO). In 2009 SafeCare QI programme was launched in Ghana to help address gaps in healthcare quality standards, leveraging existing local resources. Over 600 private and public healthcare facilities are currently enrolled in the programme and is being adopted for nation-wide rollout by government of Ghana and implementing partners.ObjectiveThis paper explored views and experiences of frontline health staff and policy makers on the SafeCare quality improvement programme in Ghana and how local resources were leveraged in its implementation.MethodologyDesign/setting: The evaluation was conducted in 53 private and public healthcare facilities from seven administrative regions of Ghana across the coastal, middle, and northern geopolitical belts. The regions are Ashanti (n = 12), Bono East (n = 8), Bono (n = 3), Greater Accra (n = 12), Oti (n = 4), Savannah (n = 8) and Western (n = 9).Sampling: Quota and purposive sampling techniques were used to sample the healthcare facilities in accordance with the study eligibility criteria. Total of 45 focus group discussions (FGDs) and 47 individual in-depth interviews (IDIs) were conducted among frontline staff and policy makers from government and private local partner institutions.Analysis: Group and individual interviews were audio recorded, transcribed verbatim and thematic content analysis done using Nvivo (version 12.0) software.FindingsOverall, participants perceived the relevance and benefits of the SafeCare programme to be "very satisfactory" while the programme impact, rollout process and success were perceived to be "satisfactory". Quality healthcare standards were perceived to have improved in beneficiary health facilities due to participation in the SafeCare programme. Patient satisfaction, service utilisation and revenue generation in healthcare facilities were also attributed to the SafeCare programme. Proposals were made for harmonisation of existing QI assessment tools to mitigate duplications. Agreed data sharing protocols and interoperability with existing national database were also recommended to promote sustainability. Finally, low staff motivation, high workload, lack of financial and material resources were cited as potential impediments to full compliance with the SafeCare QI standards by healthcare facilities enrolled in the programme.ConclusionsSafeCare QI programme has contributed to QI and adherence to patient safety standards in Ghana. Sustainability is however dependent on continuous government commitment as the programme gets adopted as a national QI programme. Overlaps in content of QI assessment tools ought to be addressed to promote efficiency without compromising quality standards. The SafeCare programme demonstrates that health systems in LMICs have the potential to attain acceptable quality healthcare standards when they take advantage of existing local resources, including private-public partnership (PPP) and peer-learning opportunities.

The feasibility of a novel national quality improvement programme for tobacco dependency treatment pathways in acute UK hospitals

IntroductionThe prevalence of smoking remains stubbornly high in the UK despite comprehensive tobacco control measures. A national quality improvement (QI) approach to enhance the treatment of an estimated 1,000,000 annual hospital admissions of tobacco smokers could provide a new opportunity to improve population health and reduce healthcare demand. Barriers to QI include knowledge, costs and competing demands.This study aimed to evaluate the feasibility and effectiveness of a national QI programme hosted by the British Thoracic Society, focused on improving NHS tobacco dependency treatment in acute hospitals. MethodsThe programme utilised the Model for Improvement as its QI framework and was delivered over a 6-month period. 25 teams from across the UK were upskilled through a series of webinars and coaching sessions and undertook QI projects focused on specific areas of their local tobacco dependency treatment pathways. ResultsResults of the programme demonstrated improvements across the treatment pathway including screening for smoking status, rapid provision of nicotine replacement therapy to prevent nicotine withdrawal, referrals to inpatient tobacco dependency treatment teams and transfers of care to community services. Other programme outcomes included increases in QI knowledge, confidence and attitudes along with enhanced project management skills. ConclusionThis novel, national, online QI programme supported participating multidisciplinary teams in acute trusts across the UK to deliver tobacco dependency treatment pathway improvements using QI tools and methodology. This programme demonstrated the feasibility and effectiveness of delivering a national QI programme, at low cost using a microsystems approach applied to an important area of clinical medicine.

Comparison of a Risk Calculator With Frailty Indices in Patients Undergoing Lung Cancer Resection.

While frailty has gained attention for its utility in risk stratification, no studies have directly compared them to existing risk calculators. The objective of this study was to compare the risk stratification of the American College of Surgeons Surgical Risk Calculator (ACS-SRC), the Revised Risk Analysis Index (RAI-rev), and the Modified Frailty Index (5-mFI). The primary outcomes were 30-day postoperative morbidity, 30-day postoperative mortality, unplanned readmission, unplanned reoperation, and discharge disposition other than home. Patients undergoing anatomic lung resection for primary, nonsmall cell lung cancer were identified within the ACS National Quality Improvement Program (ACS NSQIP) database. Tools were compared for discrimination in the primary outcomes. 9663 patients undergoing anatomic lung resection for cancer between 2012 and 2014 were included. The cohort was 53.1% female. Median age at diagnosis was 67 (IQR 59-74) years. Perioperative morbidity and mortality rates were 10.9% (n = 1048) and 1.6% (n = 158). Rates of 30-day postoperative unplanned readmission and reoperation were 7.5% (n = 725) and 4.8% (n = 468). The ACS-SRC had the highest discrimination for all measured outcomes, as measured by the area under the receiver operating curve (AUC) and corresponding confidence interval (95% CI). This included perioperative mortality (AUC 0.74, 95% CI 0.71-0.78), compared to RAI-rev (AUC 0.66, 95% CI 0.62-0.69) and 5-mFI (AUC 0.61, 95% CI 0.57-0.65; p < 0.001). The RAI-rev and 5-mFI had similar discrimination for all measured outcomes. ACS-SRC was the perioperative risk stratification tool with the highest predictive discrimination for adverse, 30-day, postoperative events for patients with cancer treated with anatomic lung resection.

A Bone Health Optimization Framework for Malaysia: a position paper by the Malaysian Bone Health Optimization Network (MyBONe).

Osteoporosis and osteopenia are highly prevalent among older patients scheduled for elective arthroplasties and spinal surgeries. This position paper aims to establish, promote, and standardise effective Bone Health Optimization (BHO) strategies for such patients within orthopaedic practices in Malaysia. It emphasises the need for bone health assessments to be undertaken at the pre-operative, intra-operative, and post-operative stages, with tailored management strategies to meet individual patient needs. A comprehensive literature review was conducted, focusing on articles published from 2019 to 2024. Twelve broad themes were defined including definitions and importance of BHO, epidemiological data, assessment techniques, risk stratification, management strategies, and outcome metrics. Elective surgeries on patients with poor bone health are associated with adverse outcomes, such as periprosthetic fractures, aseptic loosening of implants, and complications after spinal surgeries. This position paper advocates for routine bone health assessments and monitoring during the pre-operative, intra-operative, and post-operative phases. It provides summaries of imaging modalities, risk assessment tools, and techniques for each phase. By adapting the successful "5IQ" approach from secondary fracture prevention, we propose 5IQ-based Clinical Standards for BHO, including 18 Key Performance Indicators. A Malaysian BHO Registry is proposed to benchmark care in real-time and support a national quality improvement programme. Practical resources, such as a BHO algorithm and key practice points, are included. This position paper proposes a paradigm shift in the management of bone health for patients undergoing elective orthopaedic surgery in Malaysia, aiming to improve surgical outcomes and patient care through standardised BHO strategies.

ThP6.15 - 1, 3, and 5-year mortality following emergency laparotomy, can the National Emergency Laparotomy Audit (NELA) or the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) risk calculators predict it? – a retrospective, multi-center, observational, cohort study

Abstract Background Emergency laparotomy (EL) comprises a high-risk group of surgical procedures, associated with a significantly increased risk of death in the following 5 years. EL are performed on a heterogeneous population, of which at least 50% are ≥ 70 years old. Accurate preoperative risk prediction is vital for planning care, patient shared decision, and improving outcomes. To date, no prediction tool can reliably estimate long-term outcomes, including mortality, following an EL. Methods This is a multicenter, retrospective, observational, cohort study that investigated the correlation between actual mortality at 1, 3, and 5 years and predicted 30-day mortality (30-dm) using NELA and ACS-NSQIP risk prediction tools, following EL, in adults aged ≥18, over 2 years, in two UK centers. The sample size was calculated at 385 cases. GraphPad-Prism 10.1.1. was used for statistical analysis. Results 626 cases were analyzed. The male/female ratio was 0.85, age 70 years (55;78); BMI 24.94kg/m² (22;29); preoperative lactate 1.7 mmol/L (1.2;2.6), clinical frailty score 3 (2;4); and Charlson Comorbidity Index 4(2;5) (all data is expressed as median+IQR). The 1, 3, and 5-year survival were 76%, 67%, and 61%, respectively. A perfect positive correlation between NELA and ACS-NSQIP 30-dm and the 1-year actual mortality was found (R²=1). At 3 years only NELA correlated positively to actual mortality (R²=0.23, p&amp;lt;0.05). The 5-year mortality correlated positively with both predictors - NELA: R²=0.61, p&amp;lt;0.001; ACS-NSQIP: R²=0.31, p&amp;lt; 0.05. Conclusion Both NELA and ACS-NSQIP risk calculators can predict mortality at 1,3 and 5 years after an emergency laparotomy, with NELA expressing a stronger correlation.

Comparison of a risk calculator with frailty indices in patients undergoing lung cancer resection.

Perioperative risk stratification is an essential component of preoperative planning for cancer surgery. While frailty has gained attention for its utility in risk stratification, no studies have directly compared it to existing risk calculators. Therefore, the objective of this study was to compare the risk stratification of the American College of Surgeons Surgical Risk Calculator (ACS-SRC), the Revised Risk Analysis Index (RAI-rev), and the Modified Frailty Index (5-mFI). The primary outcomes were 30-day postoperative morbidity, 30-day postoperative mortality, unplanned readmission, unplanned reoperation, and discharge disposition other-than-home. Patients undergoing anatomic lung resection for primary, non-small cell lung cancer were identified within the American College of Surgeons National Quality Improvement Program (ACS NSQIP) database. The ACS-SRC, RAI-rev, and 5-mFI tools were used to predict adverse postoperative events. Tools were compared for discrimination in the primary outcomes. 9663 patients undergoing anatomic lung resection for cancer between 2012 and 2014 were included. The cohort was 53.1% female. Median age at diagnosis was 67 (interquartile range = 59-74) years. Cardiothoracic surgeons performed 89% and general surgeons performed 11.0% of the operations. Perioperative morbidity and mortality rates were 10.9% (n = 1048) and 1.6% (n = 158). Rates of 30-day postoperative unplanned readmission and reoperation were 7.5% (n = 725) and 4.8% (n = 468). The ACS-SRC had the highest discrimination for all measured outcomes, as measured by the area under the receiver operating curve (AUC) and corresponding confidence interval (95% confidence interval [CI]). This included perioperative mortality (AUC = 0.74, 95% CI = 0.71-0.78), compared to RAI-rev (AUC = 0.66, 95% CI = 0.62-0.69) and 5-mFI (AUC = 0.61, 95% CI = 0.57-0.65; p < 0.001). The RAI-rev and 5-mFI had similar discrimination for all measured outcomes. ACS-SRC was the perioperative risk stratification tool with the highest predictive discrimination for adverse, 30-day, postoperative events for patients with cancer treated with anatomic lung resection.

A mobile application for STEMI care optimization: Pilot implementation project report

BackgroundClinical outcomes of patients presenting with STEMI are significantly improved by reducing time from vessel occlusion to coronary blood flow restoration. In an effort to improve outcomes, we developed a secure mobile application, STEMIcathAID, and designed a pilot project implementing the app into the workflow for STEMI patients transfer. The aim of the study is to assess the impact of the app on key metrics for STEMI transfer before (historic) and after app launch. MethodsThe pilot project included physicians, nurses and technicians from the Emergency Medicine and Nursing Departments at the referring center, the catheterization laboratory and transfer center. From July 2021 to February 2023, the referring center activated STEMIcathAID alarms in parallel with the previously established STEMI activation with traditional phone call to transfer center. ResultsOne hundred eleven suspected STEMI calls were activated through the app with 66 accepted and 45 rejected cases; thirty-one STEMI cases with available device time were compared with 42 STEMIs activated through the traditional pathway before the app implementation. Median door-to-device time for STEMIcathAID-assisted transfer decreased from 106 to 86 min (p < 0.001). The significant improvement, 20 min (19%), of the key metric for interhospital transfer resulted in all STEMI cases meeting the AHA goal of door-to-device time ≤ 120 min. In addition, median door-in-door-out time at the referral hospital decreased from 56 to 50 min (p = 0.01). ConclusionsImplementation of a mobile app into STEMI workflow of a large urban healthcare system significantly improved the quality of care for transfer of STEMI patients. Trial registrationAHA Get With The Guidelines-Coronary Artery Disease® (GWTG-CAD) registry is a national quality improvement program and is not subject to the institutional review board approval.

Prediction of overnight stay following shoulder arthroplasty utilizing machine learning

BackgroundTotal shoulder arthroplasty (TSA) has evolved from requiring extended inpatient hospital stays to favoring same-day discharges, influenced by improved surgical techniques, patient optimization, and the risks associated with inpatient stays. The removal of TSA from Medicare's inpatient-only list in 2021 underscores this shift. However, the need for accurate prediction of post-TSA admission remains, as hospital admissions are costly and linked to increased morbidity and mortality. Machine learning algorithms offer potential advantages over traditional predictive models by identifying complex, nonlinear relationships. This study aimed to demonstrate and compare the performance of commonly used machine learning algorithms to predict overnight hospital stay (OHS) admission. MethodsThis study used data from the American College of Surgeons National Quality Improvement Program 2021 database to analyze patients who underwent primary, elective TSA. Patients were divided into short hospital stay of 0-1 days and OHS of >1 day cohorts. Machine learning models, including Random Forest, Artificial Neural Network (ANN), Gradient Boosted Tree, Naïve Bayes, and Support Vector Machine, were trained and validated to predict OHS. The models' predictive capacities were compared using the area under the receiver operating characteristics curve, calibration, and decision curve analysis. ResultsOut of 5811 patients analyzed, 926 (15.9%) were discharged on the same day. The ANN model demonstrated the highest area under the receiver operating characteristics curve (0.811), indicating superior predictive ability. Important variables influencing OHS predictions included operative time, body mass index, functional status, and patient demographics, such as age, race, and home support. Machine learning models showed better predictive performance than multivariate logistic regression. ConclusionMachine learning models, particularly the ANN model, outperform traditional regression methods in predicting post-TSA admission, highlighting their utility in optimizing patient selection for outpatient surgery. These models identify important variables associated with increased risk of OHS, aiding in preoperative planning and patient counseling. Integrating machine learning into clinical practice may enhance surgical outcomes and patient satisfaction while reducing health-care costs.

The Impact of Race/Ethnicity on Disparities in Utilization and Outcomes of Neuraxial Anesthesia for Hip and Femoral Shaft Fractures.

Background/Objectives: The use of neuraxial anesthesia versus general anesthesia for hip fracture surgery remains an active area of research, with recent studies demonstrating mixed findings supporting neuraxial over general anesthesia. The benefits of neuraxial anesthesia have been documented in associated surgeries, including total joint arthroplasty. However, racial disparities in the administration of neuraxial anesthesia have been identified in numerous procedures. We aimed to examine the association of race/ethnicity with neuraxial anesthesia use and the effect of neuraxial anesthesia on length of stay, non-home discharge, 30-day severe adverse events, and rates of readmission among patients undergoing isolated hip and femoral shaft fracture operations. Methods: The American College of Surgeons National Quality Improvement Program database was queried for isolated hip or femoral shaft fractures from 2015 to 2019. Stepwise logistic regression was performed to assess the relationship between race/ethnicity and neuraxial anesthesia use. Within each sex-race stratum, neuraxial anesthesia recipients were propensity-matched to general anesthesia recipients in a 1:2 ratio. Logistic regression and negative binomial regression were performed on the propensity-matched cohort. Results: A total of 12,004 neuraxial and 64,250 general anesthesia hip and femoral shaft fracture patients were identified. Compared to White patients, Black and Hispanic patients were between 0.64 and 0.61 times less likely to receive neuraxial anesthesia over general anesthesia, respectively (p < 0.05). 11,993 patients who received neuraxial anesthesia were propensity matched to 23,946 patients who received general anesthesia. Propensity-matched logistic regressions found that neuraxial anesthesia was associated with decreased length of stay, 30-day severe adverse events, and acute rehab/skilled nursing facility discharge for White patients (p < 0.05 for all), but only decreased length of stay in Black and Hispanic patients (p = 0.01 and p = 0.02, respectively). Conclusions: Notable disparities exist in the administration of neuraxial anesthesia for isolated hip and femoral shaft fracture patients. Hispanic and Black race/ethnicity in particular influences provision of neuraxial anesthesia. Further research is required to understand the degree of effect modification and root causes of regional anesthesia access and benefits for this high-volume patient population.

Concomitant Procedures, Black Race, Male Sex, and General Anesthesia Show Fair Predictive Value for Prolonged Rotator Cuff Repair Operative Time: Analysis of the National Quality Improvement Program Database Using Machine Learning

PurposeThe purpose of this study is to develop machine learning models using the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database to predict prolonged operative time (POT) for rotator cuff repair (RCR). Furthermore, this study aims to use the trained machine learning (ML) models, cross-referenced with traditional multivariate logistic regression (MLR), to determine the key perioperative variables that may predict POT for RCR. MethodsData were obtained from a large, national database (NSQIP) from 2021. Patients with unilateral RCR procedures were included. Demographic, preoperative, and operative variables were analyzed. A multivariable logistic regression (MLR) model and various other machine learning techniques, including random forest (RF) and artificial neural network (ANN), were compared using area under the curve (AUC), calibration, Brier score, and decision curve analysis. Feature importance was identified from the overall best-performing model. ResultsA total of 6,690 patients met inclusion criteria. The random forest (RF) ML model had the highest AUC upon internal validation (0.706) and the lowest Brier score (0.15), outperforming the other models. The RF model also demonstrated strong performance upon assessment of the calibration curves (Slope = 0.86, Intercept = 0.08) and decision curve analysis. The model identified concomitant procedure, specifically labral repair and biceps tenodesis, as the most important variable for determining POT, followed by age <30 years, Black or African American race, male sex, and general anesthesia. ConclusionsDespite the advanced machine learning models used in this study, the NSQIP dataset was only able to fairly predict POT following RCR. The RF model identified concomitant procedures, specifically labral repair and biceps tenodesis, as the most important variables for determining POT. Additionally, demographic factors such as age <30 years, Black race, and general anesthesia were significant predictors. While male sex was identified as important in the RF model, the MLR model indicated that its predictive value is primarily in conjunction with specific procedures like biceps tenodesis and subacromial decompression.

Machine learning used to determine features of importance linked to overnight stay after patellar tendon repair

PurposeThe purpose of this study is to determine if machine learning is an effective method to identify features of patients who may need a longer postoperative stay following a patellar tendon repair. MethodsThe American College of Surgeons National Quality Improvement Program (ACS-NSQIP) was used to collect 1173 patients who underwent patellar tendon repair. Machine learning (ML) was then applied to determine features of importance in this patient population. Several algorithms were used: Random Forest, Artificial Neural Network, Gradient Boosting, and Support Vector Machine. These were then compared to the American Society of Anesthesiologists (ASA) classification system based logistic regression as a control. ResultsRandom Forest (RF) was determined to be the best performing algorithm, with an AUC of 0.72, accuracy of 77.66 %, and precision of 0.79, and recall of 0.96. All other algorithms performed similarly to the control. RF gave the highest permutation feature importance to age (PFI 0.25), BMI (PFI 0.19), ASA classification (PFI 0.14), hematocrit (PFI 0.12), and height (PFI 0.11). ConclusionsThis study shows that machine learning can be used as a tool to identify features of importance for length of postoperative stay in patients undergoing patellar tendon repair. RF was found to be a better performing model than logistic regression at determining patients predisposed to longer length of stay as determined by AUC. This supported the study's hypothesis that ML can provide an effective method for identifying features of importance in patients requiring a longer postoperative stay after patellar tendon repair.

Delayed elective total shoulder arthroplasty: causes and eventual outcomes.

The purpose of this study is to identify risk factors for delays in planned total shoulder arthroplasty (TSA) and determine the perioperative outcomes of TSAs that experienced a delay. The American College of Surgeons National Quality Improvement Program (NSQIP) database was queried from 2006 to 2019 for primary TSA. Delayed TSA was defined as surgery that occurred greater than one day after hospital admission. Patient demographics, comorbidities, and post-operative complications were collected and compared; the incidence of delayed TSA was analyzed. The delayed patients were older, had a higher BMI, a higher rate of recent prior major surgery, and more comorbidities. Delayed patients had higher rates of postoperative complications, return to the OR, and 30-day readmission. Between 2006 and 2019, the rate of delayed TSA decreased. Surgeons should take care to ensure that patients with comorbidities undergo thorough preoperative clearance to prevent same-day cancellations and postoperative complications.

Short-Term Postoperative Complications in Flexor Tendon Repair: A Subcategory Analysis by Surgical Specialty.

Introduction: We aimed to investigate and compare the 30-day postsurgical complication rates and total operative times for hand or wrist flexor tendon injury repair procedures. Methods: We performed a retrospective cohort analysis of the American College of Surgeon National Quality Improvement Program database between 2015 and 2019. Patients were included in our study if they were 18 years or older and underwent surgical repair of a wrist or hand flexor tendon by a plastic surgeon, general surgeon, or orthopedic surgeon. Primary endpoint of the study was 30-day postsurgical complications. Secondary endpoint included subcategory analysis of 30-day postsurgical complications. Another variable of interest included total operative time. Results: There were 2614 surgeries performed for wrist or hand flexor tendon injury repair during the 5-year period. Orthopedic surgeons performed the majority of the operations (1548, 59.2%). Repair or advancement of the flexor tendon zone 2 without grafts (1284, 49.1%) were the most common surgeries performed. Overall surgical site complication rate was 2%, with no significant associations between the complication and the surgical specialty performing the operation. A significant difference in total operative time between surgical specialties was only found in single flexor tendon repairs (P < .001). Conclusions: Surgical repair for hand and wrist flexor tendon injury is a safe surgical procedure with a low short-term postoperative complication rate. Despite variations in training, complications remain similar between specialties for flexor tendon repairs.

The role of multidisciplinary team meeting histopathology review and its impact on revised reports: Analysis of a national quality improvement program.

We conducted the first Irish national study assessing the value of multidisciplinary team meeting review in pathology practice and its impact on error detection before treatment. Public and private pathology laboratories across Ireland capture their quality activities using standardized codes and submit their data to a centralized database (National Quality Assurance Intelligence System) overseen by the National Histopathology Quality Improvement (NHQI) program. A total of 1,437,746 histopathology and cytopathology cases submitted to the NHQI program over a 60-month period (January 2017 to December 2021) were included in this study. Cases were analyzed with respect to multidisciplinary team meeting peer review and the presence of a revised report (amended or corrected report), a surrogate marker for error detection before treatment. Across all cases assessed, 13.74% (197,587) underwent multidisciplinary team meeting discussion. Cases discussed at review had a statistically significantly higher rate of revised reports (1.25% [2470]) than cases not discussed at review (0.16% [1959]) (Pearson χ2, 6619.26; P < .0001; odds ratio, 8.00 [95% CI, 7.54-8.49]). Overall, multidisciplinary team meeting review made it 8 times more likely to detect an error before treatment. Cancer resections had the highest rate of review at 55.29% (46,806), reflecting the prioritization of oncology case discussion at review meetings. The multidisciplinary team meeting review process plays a valuable role in pathology error detection. A pathologist's participation in the review process comes with a clinically significant workload that needs to be recognized for future workforce planning. This study highlighted the positive role pathologists play in enhancing patient safety.

Multiplicative effect of frailty and obesity on postoperative mortality following spine surgery: a deep dive into the frailty, obesity, and Clavien-Dindo dynamic.

Obesity is a global health challenge that affects a large proportion of adults worldwide. Obesity and frailty pose considerable health risks due to their potential to interact and amplify one another's negative effects. Therefore, we sought to compare the discriminatory thresholds of the risk analysis index (RAI), 5-factor modified frailty index (m-FI-5) and patient age for the primary endpoint of postoperative mortality. We included spine surgery patients ≥18 years old, from the American College of Surgeons National Quality Improvement program database from 2012-2020, that were classified as obese. We performed receiver operating characteristic curve analysis to compare the discrimination threshold of RAI, mFI-5, and patient age for postoperative mortality. Proportional hazards risk-adjusted regressions were performed, and Hazard ratios and corresponding 95% Confidence intervals (CI) are reported. Overall, there were 149 163 patients evaluated, and in the ROC analysis for postoperative mortality, RAI showed superior discrimination C-statistic 0.793 (95%CI: 0.773-0.813), compared to mFI-5 C-statistic 0.671 (95%CI 0.650-0.691), and patient age C-statistic 0.686 (95%CI 0.666-0.707). Risk-adjusted analyses were performed, and the RAI had a stepwise increasing effect size across frailty strata: typical patients HR 2.55 (95%CI 2.03-3.19), frail patients HR 3.48 (95%CI 2.49-4.86), and very frail patients HR 4.90 (95%CI 2.87-8.37). We found increasing postoperative mortality effect sizes within Clavein-Dindo complication strata, consistent across obesity categories, exponentially increasing with frailty, and multiplicatively enhanced within CD, frailty and obesity strata. In this study of 149 163 patients classified as obese and undergoing spine procedures in an international prospective surgical database, the RAI demonstrated superior discrimination compared to the mFI-5 and patient age in predicting postoperative mortality risk. The deleterious effects of frailty and obesity were synergistic as their combined effect predicted worse outcomes.

Quality of Surgical Care Within the Criminal Justice Health Care System

Individuals who are incarcerated represent a vulnerable group due to concerns about their ability to provide voluntary and informed consent, and there are considerable legal protections regarding their participation in medical research. Little is known about the quality of surgical care received by this population. To evaluate perioperative surgical care provided to patients who are incarcerated within the Texas Department of Criminal Justice (TDCJ) and compare their outcomes with that of the general nonincarcerated population. This cohort study analyzed data from patients who were incarcerated within the TDCJ and underwent general or vascular surgery at the University of Texas Medical Branch (UTMB) from 2012 to 2021. Case-specific outcomes for a subset of these patients and for patients in the general academic medical center population were obtained from the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) and compared. Additional quality metrics (mortality index, length of stay index, and excess hospital days) from the Vizient Clinical Data Base were analyzed for patients in the incarcerated and nonincarcerated groups who underwent surgery at UTMB in 2020 and 2021 to provide additional recent data. Patient-specific demographics, including age, sex, and comorbidities were not available for analysis within this data set. Perioperative outcomes (30-day morbidity, mortality, and readmission rates) were compared between the incarcerated and nonincarcerated groups using the Fisher exact test. The sample included data from 6675 patients who were incarcerated and underwent general or vascular surgery at UTMB from 2012 to 2021. The ACS-NSQIP included data (2012-2021) for 2304 patients who were incarcerated and 602 patients who were not and showed that outcomes were comparable between the TDCJ population and that of the general population treated at the academic medical center with regard to 30-day readmission (6.60% vs 5.65%) and mortality (0.91% vs 1.16%). However, 30-day morbidity was significantly higher in the TDCJ population (8.25% vs 5.48%, P = .01). The 2020 and 2021 data from the Vizient Clinical Data Base included 629 patients who were incarcerated and 2614 who were not and showed that the incarcerated and nonincarcerated populations did not differ with regard to 30-day readmission (12.52% vs 11.30%) or morbidity (1.91% vs 2.60%). Although the unadjusted mortality rate was significantly lower in the TDCJ population (1.27% vs 2.68%, P = .04), mortality indexes, which account for case mix index, were similar between the 2 populations (1.17 vs 1.12). Findings of this cohort study suggest that patients who are incarcerated have equivalent rates of mortality and readmission compared with a general academic medical center population. Future studies that focus on elucidating the potential factors associated with perioperative morbidity and exploring long-term surgical outcomes in the incarcerated population are warranted.

Risk-Adjusted Cumulative Sum for Early Detection of Hospitals With Excess Perioperative Mortality

National surgical quality improvement programs lack tools for early detection of quality or safety concerns, which risks patient safety because of delayed recognition of poor performance. To compare the risk-adjusted cumulative sum (CUSUM) with episodic evaluation for early detection of hospitals with excess perioperative mortality. National, observational, hospital-level, comparative effectiveness study of 697 566 patients. Identification of hospitals with excess, risk-adjusted, quarterly 30-day mortality using observed to expected ratios (ie, current criterion standard in the Veterans Affairs Surgical Quality Improvement Program) was compared with the risk-adjusted CUSUM. Patients included in the study underwent a noncardiac operation at a Veterans Affairs hospital, had a record in the Veterans Affairs Surgical Quality Improvement Program (January 1, 2011, through December 31, 2016), and were aged 18 years or older. Number of hospitals identified as having excess risk-adjusted 30-day mortality. The cohort included 697 566 patients treated at 104 hospitals across 24 quarters. The mean (SD) age was 60.9 (13.2) years, 91.4% were male, and 8.6% were female. For each hospital, the median number of quarters detected with observed to expected ratios, at least 1 CUSUM signal, and more than 1 CUSUM signal was 2 quarters (IQR, 1-4 quarters), 8 quarters (IQR, 4-11 quarters), and 3 quarters (IQR, 1-4 quarters), respectively. During 2496 total quarters of data, outlier hospitals were identified 33.3% of the time (830 quarters) with at least 1 CUSUM signal within a quarter, 12.5% (311 quarters) with more than 1 CUSUM signal, and 11.0% (274 quarters) with observed to expected ratios at the end of the quarter. The CUSUM detection occurred a median of 49 days (IQR, 25-63 days) before observed to expected ratio reporting (1 signal, 35 days [IQR, 17-54 days]; 2 signals, 49 days [IQR, 26-61 days]; 3 signals, 58 days [IQR, 44-69 days]; ≥4 signals, 49 days [IQR, 42-69 days]; trend test, P < .001). Of 274 hospital quarters detected with observed to expected ratios, 72.6% (199) were concurrently detected by at least 1 CUSUM signal vs 42.7% (117) by more than 1 CUSUM signal. There was a dose-response relationship between the number of CUSUM signals in a quarter and the median observed to expected ratio (0 signals, 0.63; 1 signal, 1.28; 2 signals, 1.58; 3 signals, 2.08; ≥4 signals, 2.49; trend test, P < .001). This study found that with CUSUM, hospitals with excess perioperative mortality can be identified well in advance of standard end-of-quarter reporting, which suggests episodic evaluation strategies fail to detect out-of-control processes and place patients at risk. Continuous performance evaluation tools should be adopted in national quality improvement programs to prevent avoidable patient harm.

Baseline labs predict adverse postoperative outcomes following metastatic brain tumor resection: Analysis of 5943 patients from a prospective surgical registry (2015–2019)

IntroductionThe present study sought to evaluate the predictive accuracy of preoperative lab values (PLV) on postoperative metastatic brain tumor resection (MBTR) outcomes using data queried from a large prospective international surgical registry, representing over 700 hospitals in 11 countries. MethodsAdult metastatic brain tumor patients (N = 5943) were queried from the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database, from 2015 to 2019, using diagnostic and procedural coding. The relationship between preoperative lab values and key indicators of adverse postoperative outcomes following metastatic brain tumor resection were assessed with univariate and multivariate analyses. Adverse postoperative outcomes of interest included: 30-day mortality, Clavien-Dindo Grade IV (CDIV) complications, extended length of stay (eLOS), and discharge to non-home destination (NHD), as well as secondary outcomes: non-Clavien-Dindo Grade IV complications, unplanned reoperation, and unplanned readmission. ResultsIndependent PLV most strongly associated with 30-day mortality were hypernatremia, increased serum creatinine, and thrombocytopenia. Significant predictors of CDIV complications were hypoalbuminemia and thrombocytopenia. eLOS was associated with hypoalbuminemia, anemia, and hyponatremia. The strongest independent predictors of NHD were anemia, hyperbilirubinemia, and hypoalbuminemia. ConclusionSeveral pre-operative lab values independently predicted worse outcomes for metastatic brain tumor resection patients. Hypoalbuminemia, thrombocytopenia, and anemia had the strongest association with the study's adverse postoperative outcomes. These baseline lab values may be considered for preoperative risk stratification of metastatic brain tumor patients.

Association of Age and Frailty With 30-Day Outcomes Among Patients Undergoing Oral Cavity Cancer Surgery.

To evaluate the impact of age and frailty on 30-day outcomes following surgery for oral squamous cavity carcinoma (OSCC). Retrospective cross-sectional analysis. American College of Surgeons' National Quality Improvement Program (NSQIP) database. Patients who underwent OSCC resection were queried via NSQIP (2015-2020). Cases were stratified by age (18-65, 65-75, and older than 75) as well as by modified frailty index scores (mFI 0, mFI 1, and mFI 2+) for comparative analyses. Univariate and multivariable analyses were conducted to examine demographics, perioperative outcomes, and 30-day postoperative adverse events. A total of 3238 patients who underwent OSCC surgery were identified and categorized as nongeriatric ("NGA," age 18-65), younger geriatric ("YGA," age 65-75), and older geriatric ("OGA," age >75) adults. Compared to NGA, geriatric patients had higher the American Society of Anesthesiologists classification, higher modified frailty index scores, and more comorbidities such as hypertension, congestive heart failure, chronic obstructive disease, and diabetes (p < .001). YGAs and OGAs were also less likely to undergo neck dissection (p < .001), composite resection (p = .006), and free flap reconstruction compared to NGAs (p < .001). When controlling for confounders, age was not independently associated with an increased risk of poor outcomes. On the other hand, frailty was found to be independently associated with a higher risk of adverse events (odds ratio: 1.40 [1.15-1.70], p < .001 for mFI 1, odds ratio: 1.45 [1.04-2.02], p = .027 for mFI 2+). A higher mFI score, not older age, is associated with an increased risk of 30-day complications following OSCC surgery.

Body Mass Index (BMI) Related Morbidity with Thyroid Surgery.

The increase in incidence of thyroid cancer correlates with strict increases in body mass index (BMI) and obesity in the United States. Thyroid hormone dysregulation has been shown to precipitate circulatory volume, peripheral resistance, cardiac rhythm, and even cardiac muscle health. Theoretically, thyroid surgery could precipitate injury to the cardiopulmonary system. The American College of Surgery National Quality Improvement Program database was queried for thyroidectomy cases in the 2007-2020 Participant User files. Continuous and categorical associations between BMI and cardiopulmonary complications were investigated as reported in the database. The query resulted 186,095 cases of thyroidectomy procedures in which the mean age was 51.3 years and sample was 79.3% female. No correlation was evident in univariate and multivariate analyses between BMI and the incidence of postoperative stroke or myocardial infarction. The incidence of complications was extremely low. However, risk of deep venous thrombosis correlated with BMI in the categorical, univariate, and multivariate (OR 1.036, CI 1.014-1.057, p < 0.01) regression analysis. Additionally, increased BMI was associated with increased risk of pulmonary embolism (PE) (OR 1.050 (1.030, 1.069), p < 0.01), re-intubation (OR 1.012 (1.002, 1.023), p = 0.02), and prolonged intubation (OR 1.031 (1.017, 1.045), p < 0.01). Despite the rarity of cardiopulmonary complications during thyroid surgery, patients with very high BMI carry a significant risk of deep venous thrombosis, PE, and prolonged intubation. 3 Laryngoscope, 133:2823-2830, 2023.