A multi-centre prospective cohort study of patients on the elective waiting list for cardiac surgery during the COVID-19 pandemic

Impact of COVID-19 pandemic on elective care backlog trends, recovery efforts, and capacity needs to address backlogs in Scotland (2013-2023): a descriptive analysis and modelling study

Background

Prioritisation of COVID-19 care led to widespread cancellations of elective care, creating a substantial backlog for healthcare systems worldwide. While the pandemic's impacts on elective hospital waiting lists during the early phase of the pandemic have been described in multiple countries, there is limited research on longer-term impacts and recovery efforts.

Methods

We conducted a country-wide analysis of Scotland's healthcare system over an 11-year period (January 1, 2013-December 31, 2023) to assess the pandemic's impact on the elective care backlog, evaluate recovery efforts, and estimate the capacity increase required to clear the backlog. Our analysis involved assessments at national, elective type, regional, and specialty levels. We used descriptive statistics to compare trends and a statistical modelling approach (Vector Autoregressive model with exogenous variables) to estimate capacity increases needed.

Findings

Waiting lists gradually increased before the pandemic (2013: n = 285,149; 2019: n = 385,859; 35.3% increase over six years) and then rose rapidly during the pandemic (2023: n = 667,749; 73.1% increase over four years). Capacity for elective care dropped substantially during the initial lockdown period (April-June 2020) and had not fully recovered by the end of 2023. These patterns were broadly consistent across Scotland and similar trends were observed when stratified by elective type, region, and specialty. The number of referrals waiting over a year increased from 3056 on December 31, 2019, to 78,243 (>2400% increase) by December 31, 2023. To eliminate the backlog created during the pandemic, a gradual increase in capacity, accumulating to 20% over three years is required. This corresponds to an annual increase of approximately 6.67%, translating to an additional 32,302 cases per year.

Interpretation

Scotland's healthcare system struggled to meet elective care demand pre-pandemic, and the pandemic has worsened an already difficult situation. Pre-pandemic elective care capacity had not been restored by the end of 2023. While substantial additional capacity is necessary, it is crucial to adopt broader system-level strategies to effectively address waiting list backlogs.

Funding

University of Edinburgh's Chancellor Fellowship; Health Data Research UK.

The Barts Surgical Infection Risk (B-SIR) tool: external validation and comparison with existing tools to predict surgical site infection after cardiac surgery

OBJECTIVE

Further to previous development and internal validation of the Barts Surgical Infection Risk (B-SIR) tool, this study sought to explore the external validity of the B-SIR tool and compare it with the Australian Clinical Risk Index (ACRI), and the Brompton and Harefield Infection Score (BHIS).

STUDY DESIGN AND SETTING

This multi-centre retrospective analysis of prospectively collected local data included adult (age ≥18 years) patients undergoing cardiac surgery between January 2018 and December 2019. Pre-pandemic data were used as a reflection of standard practice. Area under the curve (AUC) was used to validate and compare the predictive power of the scores, and calibration was assessed using the Hosmer-Lemeshow test and calibration plots.

RESULTS

In total, 6022 patients from three centres were included in the complete case analysis. The mean age was 66 years, 75% were men and 3.19% developed a surgical site infection (SSI). The B-SIR tool had an area under the curve (AUC) of 0.686 [95% confidence interval (CI) 0.649-0.723], similar to the developmental study (AUC=0.682, 95% CI 0.652-0.713). This was significantly higher than the BHIS AUC of 0.610 (95% CI 0.045-0.109; P<0.001) and the ACRI AUC of 0.614 (95% CI 0.041-0.103; P<0.001). After recalibration using a correction factor, the B-SIR tool gave accurate risk predictions (Hosmer-Lemeshow test P=0.423). The multiple imputation result (AUC=0.676, 95% CI 0.639-0.712) was similar to development data, and higher than the ACRI and BHIS.

CONCLUSION

External validation indicated that the B-SIR tool predicted SSI after cardiac surgery better than the ACRI and BHIS. This suggests that the B-SIR tool could be useful for use in routine practice.

Study protocol for a cross-sectional online survey investigating patient preferences and experiences of waiting for elective cardiac surgery

INTRODUCTION

Being on a waiting list for elective (planned) cardiac surgery can be physically and psychologically challenging for patients. Research suggests that stress associated with waiting for surgery is dependent on different individual and contextual factors. However, most data on patients' experiences of waiting for surgery and preferences for waiting list management derives from non-cardiac clinical populations. The aim of the current study is to explore patients' experiences of being on a waiting list for elective cardiac surgery, and their views on how the waiting experience could be improved in the future. This work will inform the patient management strategy during the waiting period for surgery across the four major hospitals in London directly involved in this study, and potentially beyond by transferring learning to other services.

METHODS AND ANALYSIS

This is a mixed-methods study that will collect quantitative and qualitative data using a cross-sectional online survey. Patients who are on waiting lists for elective surgery across four major cardiac surgery departments in London hospitals, and are at least 18 years old, will be invited by their healthcare team via text message or letter to complete the survey. The target sample size of non-randomly selected participants will be 268. Bivariable and multivariable regression models will be used to assess associations between survey items measuring the impact of the cardiac condition on specific life domains (eg, daily activities, social and family relationships, hobbies, sexual life), anxiety and depression symptoms as measured by the Patient Health Questionnaire-4 and survey items evaluating experiences of health services. Data on experience and preferences for improvements to the waiting experience will be analysed with qualitative content analysis using an inductive approach.

ETHICS AND DISSEMINATION

This study was reviewed and granted ethical approval by the East of England-East Cambridge Research Ethics Committee. Findings from this study will be disseminated through peer-reviewed journals, a research website and social media and with an online event engaging patients, members of the public, healthcare professionals and other relevant stakeholders.

TRIAL REGISTRATION NUMB

NCT05996640.

Surgical Preparedness Index in Orthopaedics During the Coronavirus Disease 2019 (COVID-19) Pandemic

The coronavirus disease 2019 (COVID-19) pandemic has increased the vulnerability of routine surgical procedures and elective surgery preparedness all over the world, with the suspension of most elective surgeries during the pandemic and the backlog of patients currently on waiting lists, especially in publicly funded healthcare systems. On average, at the beginning of the year 2022, about 200 million patients awaited surgery all over the world. By enhancing the strength of surgical preparedness, there is a better chance of strengthening elective surgical systems against shocks such as future pandemics or climate emergencies. We explore the implications, challenges, and strategies of the concept of surgical preparedness to maintain sustainability in the global healthcare system, especially in low- and middle-income countries (LMICs), with the experiences gained during the COVID-19 pandemic.

Effect of COVID-19 on cardiac surgery volumes in Sweden

Objectives. The coronavirus disease 2019 (COVID-19) pandemic, which commenced in 2020, is known to frequently cause respiratory failure requiring intensive care, with occasional fatal outcomes. In this study, we aimed to conduct a retrospective nationwide observational study on the influence of the pandemic on cardiac surgery volumes in Sweden. Results. In 2020, 9.4% (n = 539) fewer patients underwent open-heart operations in Sweden (n = 5169) than during 2019 (n = 5708), followed by a 5.8% (n = 302) increase during 2021 (n = 5471). The reduction was greater than 15% in three of the eight hospitals in Sweden performing open-heart operations. Compared to 2019, in 2020, the waiting times for surgery were longer, and the patients were slightly younger, had better renal function, and a lower European System for Cardiac Operative Risk Evaluation; moreover, few patients had a history of myocardial infarction. However, more patients had insulin-treated diabetes mellitus, hypertension, peripheral vascular disease, reduced left ventricular function, and elevated pulmonary artery pressure. Urgent procedures were more common, but acute surgery was less common in 2020 than in 2019. Early mortality and postoperative complications were low and did not differ during the three years. Conclusion. The 9.4% decrease in the number of heart surgeries performed in Sweden during the 2020 COVID-19 pandemic, compared to 2019, partially recovered during 2021; however, there was no backlog of patients awaiting heart surgery.

The Search for an Outcome Variable That Measures Both Quality and Processes in Cardiac Surgery: Comparing the Quality Process Index and Mortality

BACKGROUND

The translation of a large quantity of data into valuable insights for daily clinical practice is underexplored. A considerable amount of information is overwhelming, making it difficult to distill and assess quality and processes at the hospital level. This study contributes to this necessary translation by developing a Quality Process Index that summarizes clinical data to measure quality and processes.

METHODS

The Quality Process Index was constructed to enable retrospective analyses of quality and process evolution from 2011 to 2021 for various surgery types in the Amsterdam Cardiosurgical Database (n = 5497). It is presented alongside mortality rates, which are the golden standard for quality measurement. The two outcome variables are compared as quality and process measurement options.

RESULTS

Results showed that the mean Quality Process Index appeared rather stable, even though analysis of variance found that the mean Quality Process Index differed significantly over the years (p < 0.001). The 30-day and 120-day mortality rates appeared to fluctuate more, but interestingly, we failed to reject the null hypothesis of equal means. The Quality Process Index and mortality rates were statistically negatively correlated, and the extent of correlation was more pronounced with the 120-day mortality rate, as computed using the Pearson correlation coefficient r (30-day rQPI,30 = -0.07, p < 0.001 and 120-day mortality rates rQPI,120 = -0.12, p < 0.001).

CONCLUSIONS

The Quality Process Index seeks to address the need to translate data for quality and process improvement in healthcare. While mortality remains the most impactful outcome measure, the Quality Process Index provides a more stable and comprehensive measurement of quality and process improvement or deterioration in healthcare. Therefore, the Quality Process Index as a quantification reinforces the understanding of the definition of quality and process improvement.