Prevalence and Causes of Elective Surgical Cancellations: Findings from a Rural Tertiary Hospital in the Eastern Cape, South Africa.

Background: Cancellations of elective surgeries adversely affect the patient, hospital staff, facility, and health system. Cancellations potentially result in hospital financial losses, theatre inefficiency, and substandard patient care. A common benchmark for the cancellation rate of elective surgeries is less than five percent, and most operating rooms fall short of this standard. There is a paucity of data on the rates and causes of elective surgical cancellations in rural, resource-limited settings. This study aimed to determine the prevalence of elective surgery cancellations, the causes for such cancellations, and the surgical disciplines most affected at Nelson Mandela Academic Hospital (NMAH). Methodology: This was an observational, descriptive, cross-sectional review of operating theatre records from January 2019 to July 2019. The prevalence and main causes of elective case cancellations were determined. The causes were classified, and the most affected surgical departments and patient characteristics were identified. Results: The prevalence of elective surgical case cancellations was 14.4% in our hospital, higher than the international benchmark of 5%. Patient-, facility-, and surgical-related factors were the leading causes of cancellations, and avoidable cancellations were mostly surgical- and anaesthetic-related. Ophthalmology was the most affected, followed by gynaecology and general surgery, with plastic surgery being the least affected. The most common patient-related factors were nonattendance and uncontrolled medical conditions, while overbooking was the most common surgical reason. Abnormal investigatory results and unfit status were the most common anaesthetic reasons. Facility-related issues included the lack of theatre time, equipment scarcity or malfunction, and staff unavailability. Most cancellations were unavoidable, but with careful planning, could be avoided. Conclusion and recommendations: This study identified challenges with theatre efficiency in a rural, resource-limited setting that call for the cooperation of multidisciplinary teams of surgeons, anaesthetists, nursing staff, and health care policymakers.

Determining the Minimum Dataset for Surgical Patients in Africa: A Delphi Study.

BACKGROUND: It is often difficult for clinicians in African low- and middle-income countries middle-income countries to access useful aggregated data to identify areas for quality improvement. The aim of this Delphi study was to develop a standardised perioperative dataset for use in a registry. METHODS: A Delphi method was followed to achieve consensus on the data points to include in a minimum perioperative dataset. The study consisted of two electronic surveys, followed by an online discussion and a final electronic survey (four Rounds). RESULTS: Forty-one members of the African Perioperative Research Group participated in the process. Forty data points were deemed important and feasible to include in a minimum dataset for electronic capturing during the perioperative workflow by clinicians. A smaller dataset consisting of eight variables to define risk-adjusted perioperative mortality rate was also described. CONCLUSIONS: The minimum perioperative dataset can be used in a collaborative effort to establish a resource accessible to African clinicians in improving quality of care.

An Evaluation of Severe Anesthetic-Related Critical Incidents and Risks From the South African Paediatric Surgical Outcomes Study: A 14-Day Prospective, Observational Cohort Study of Pediatric Surgical Patients.

BACKGROUND: Severe anesthetic-related critical incident (SARCI) monitoring is an essential component of safe, quality anesthetic care. Predominantly retrospective data from low- and middle-income countries (LMICs) report higher incidence but similar types of SARCI compared to high-income countries (HIC). The aim of our study was to describe the baseline incidence of SARCI in a middle-income country (MIC) and to identify associated risk for SARCI. We hypothesized a higher incidence but similar types of SARCI and risks compared to HICs. METHODS: We performed a 14-day, prospective multicenter observational cohort study of pediatric patients (aged <16 years) undergoing surgery in government-funded hospitals in South Africa, a MIC, to determine perioperative outcomes. This analysis described the incidence and types of SARCI and associated perioperative cardiac arrests (POCAs). We used multivariable logistic regression analysis to identify risk factors independently associated with SARCI, including 7 a priori variables and additional candidate variables based on their univariable performance. RESULTS: Two thousand and twenty-four patients were recruited from May 22 to August 22, 2017, at 43 hospitals. The mean age was 5.9 years (±standard deviation 4.2). A majority of patients during this 14-day period were American Society of Anesthesiologists (ASA) physical status I (66.4%) or presenting for minor surgery (54.9%). A specialist anesthesiologist managed 59% of cases. These patients were found to be significantly younger (P < .001) and had higher ASA physical status (P < .001). A total of 426 SARCI was documented in 322 of 2024 patients, an overall incidence of 15.9% (95% confidence interval [CI], 14.4-17.6). The most common event was respiratory (214 of 426; 50.2%) with an incidence of 8.5% (95% CI, 7.4-9.8). Six children (0.3%; 95% CI, 0.1-0.6) had a POCA, of whom 4 died in hospital. Risks independently associated with a SARCI were age (adjusted odds ratio [aOR] = 0.95; CI, 0.92-0.98; P = .004), increasing ASA physical status (aOR = 1.85, 1,74, and 2.73 for ASA II, ASA III, and ASA IV-V physical status, respectively), urgent/emergent surgery (aOR = 1.35, 95% CI, 1.02-1.78; P = .036), preoperative respiratory infection (aOR = 2.47, 95% CI, 1.64-3.73; P < .001), chronic respiratory comorbidity (aOR = 1.75, 95% CI, 1.10-2.79; P = .018), severity of surgery (intermediate surgery aOR = 1.84, 95% CI, 1.39-2.45; P < .001), and level of hospital (first-level hospitals aOR = 2.81, 95% CI, 1.60-4.93; P < .001). CONCLUSIONS: The incidence of SARCI in South Africa was 3 times greater than in HICs, and an associated POCA was 10 times more common. The risk factors associated with SARCI may assist with targeted interventions to improve safety and to triage children to the optimal level of care.

Development of a Clinical Prediction Model for In-hospital Mortality from the South African Cohort of the African Surgical Outcomes Study.

BACKGROUND: Data on the factors that influence mortality after surgery in South Africa are scarce, and neither these data nor data on risk-adjusted in-hospital mortality after surgery are routinely collected. Predictors related to the context or setting of surgical care delivery may also provide insight into variation in practice. Variation must be addressed when planning for improvement of risk-adjusted outcomes. Our objective was to identify the factors predicting in-hospital mortality after surgery in South Africa from available data. METHODS: A multivariable logistic regression model was developed to identify predictors of 30-day in-hospital mortality in surgical patients in South Africa. Data from the South African contribution to the African Surgical Outcomes Study were used and included 3800 cases from 51 hospitals. A forward stepwise regression technique was then employed to select for possible predictors prior to model specification. Model performance was evaluated by assessing calibration and discrimination. The South African Surgical Outcomes Study cohort was used to validate the model. RESULTS: Variables found to predict 30-day in-hospital mortality were age, American Society of Anesthesiologists Physical Status category, urgent or emergent surgery, major surgery, and gastrointestinal-, head and neck-, thoracic- and neurosurgery. The area under the receiver operating curve or c-statistic was 0.859 (95% confidence interval: 0.827-0.892) for the full model. Calibration, as assessed using a calibration plot, was acceptable. Performance was similar in the validation cohort as compared to the derivation cohort. CONCLUSION: The prediction model did not include factors that can explain how the context of care influences post-operative mortality in South Africa. It does, however, provide a basis for reporting risk-adjusted perioperative mortality rate in the future, and identifies the types of surgery to be prioritised in quality improvement projects at a local or national level.

The association between preoperative anemia and postoperative morbidity in pediatric surgical patients: A secondary analysis of a prospective observational cohort study.

BACKGROUND: The prevalence of anemia in the South African pediatric surgical population is unknown. Anemia may be associated with increased postoperative complications. We are unaware of studies documenting these findings in patients in low- and middle-income countries (LMICs). AIM: The primary aim of this study was to describe the association between preoperative anemia and 26 defined postoperative complications, in noncardiac pediatric surgical patients. Secondary aims included describing the prevalence of anemia and risk factors for intraoperative blood transfusion. METHOD: This was a secondary analysis of the South African Paediatric Surgical Outcomes Study, a prospective, observational surgical outcomes study. Inclusion criteria were all consecutive patients aged between 6 months and <16 years, presenting to participating centers during the study period who underwent elective and nonelective noncardiac surgery and had a preoperative hemoglobin recorded. Exclusion criteria were patients aged <6 months, undergoing cardiac surgery, or without a preoperative Hb recorded. To determine whether an independent association existed between preoperative anemia and postoperative complications, a hierarchical stepwise logistic regression was conducted. RESULTS: There were 1094 eligible patients. In children in whom a preoperative Hb was recorded 46.2% had preoperative anemia. Preoperative anemia was independently associated with an increased risk of any postoperative complication (odds ratio 2.0, 95% confidence interval: 1.3-3.1, P = .002). Preoperative anemia (odds ratio 3.6, 95% confidence interval: 1.8-7.1, P < .001) was an independent predictor of intraoperative blood transfusion. CONCLUSION: Preoperative anemia had a high prevalence in a LMIC and was associated with increased postoperative complications. The main limitation of our study is the ability to generalize the results to the wider pediatric surgical population, as these findings only relate to children in whom a preoperative Hb was recorded. Prospective studies are required to determine whether correction of preoperative anemia reduces morbidity and mortality in children undergoing noncardiac surgery.

Critical care admission of South African (SA) surgical patients: Results of the SA Surgical Outcomes Study.

BACKGROUND: Appropriate critical care admissions are an important component of surgical care. However, there are few data describing postoperative critical care admission in resource-limited low- and middle-income countries. OBJECTIVE: To describe the demographics, organ failures, organ support and outcomes of non-cardiac surgical patients admitted to critical care units in South Africa (SA). METHODS: The SA Surgical Outcomes Study (SASOS) was a 7-day national, multicentre, prospective, observational cohort study of all patients ≥16 years of age undergoing inpatient non-cardiac surgery between 19 and 26 May 2014 at 50 government-funded hospitals. All patients admitted to critical care units during this study were included for analysis. RESULTS: Of the 3 927 SASOS patients, 255 (6.5%) were admitted to critical care units; of these admissions, 144 (56.5%) were planned, and 111 (43.5%) unplanned. The incidence of confirmed or strongly suspected infection at the time of admission was 35.4%, with a significantly higher incidence in unplanned admissions (49.1 v. 24.8%, p<0.001). Unplanned admission cases were more frequently hypovolaemic, had septic shock, and required significantly more inotropic, ventilatory and renal support in the first 48 hours after admission. Overall mortality was 22.4%, with unplanned admissions having a significantly longer critical care length of stay and overall mortality (33.3 v. 13.9%, p<0.001). CONCLUSION: The outcome of patients admitted to public sector critical care units in SA is strongly associated with unplanned admissions. Adequate 'high care-dependency units' for postoperative care of elective surgical patients could potentially decrease the burden on critical care resources in SA by 23%. This study was registered on ClinicalTrials.gov (NCT02141867).