A reduction in hospital length of stay reduces costs for colorectal surgery: an economic evaluation of the National Surgical Quality Improvement Program in Singapore.

PURPOSE: In 2017, the National Surgical Quality Improvement Program (NSQIP) was introduced in the Department of Colorectal Surgery at Singapore General Hospital as a pilot quality improvement initiative. This study aimed to examine the cost-effectiveness of NSQIP by evaluating its effects on surgical outcomes, length of stay (LOS), and costs. METHODS: We retrospectively reviewed patients undergoing colorectal surgery (2017-2020). Patients were divided into two cohorts: pre-NSQIP (2017-2018) and post-NSQIP (2019-2020). Outcomes evaluated were 30-day postoperative complications, LOS, and costs. Total cost-savings from NSQIP intervention's impact on LOS were estimated using a decision model with a one-way sensitivity analysis. Multivariate logistic regression was performed to identify factors for prolonged LOS. RESULTS: 1905 patients underwent colorectal surgery, with 996 in the pre-NSQIP cohort and 909 in the post-NSQIP cohort. A significant reduction in overall postoperative complications of 4.7% was observed in the post-NSQIP cohort (36.5% vs. 31.8%, p = 0.029). Patients in the post-NSQIP cohort had a shorter median LOS (8.0 vs. 6.0 days, p < 0.001). The implementation of NSQIP resulted in an 8.5% decrease in prolonged LOS > 6 days (p < 0.001), saving S$0.31 million on LOS. Total costs per case were reduced by 20.8% following NSQIP (S$39,539.05 vs. S$31,311.93, p < 0.001). CONCLUSION: Implementing NSQIP has significantly reduced overall postoperative complications, LOS, and costs and achieved cost savings following colorectal surgery.

Perception survey of crisis and emergency risk communication in an acute hospital in the management of COVID-19 pandemic in Singapore.

BACKGROUND: Emergency risk communication is a critical component in emergency planning and response. It has been recognised as significant for planning for and responding to public health emergencies. While there is a growing body of guidelines and frameworks on emergency risk communication, it remains a relatively new field. There has also been limited attention on how emergency risk communication is being performed in public health organisations, such as acute hospitals, and what the associated challenges are. This article seeks to examine the perception of crisis and emergency risk communication in an acute hospital in response to COVID-19 pandemic in Singapore and to identify its associated enablers and barriers. METHODS: A 13-item Crisis and Emergency Risk Communication (CERC) Survey, based on the US Centers for Disease and Control (CDC) CERC framework, was developed and administered to hospital staff during February 24-28, 2020. The survey also included an open-ended question to solicit feedback on areas of CERC in need of improvement. Chi-square test was used for analysis of survey data. Thematic analysis was performed on qualitative feedback. RESULTS: Of the 1154 participants who responded to the survey, most (94.1%) reported that regular hospital updates on COVID-19 were understandable and actionable. Many (92.5%) stated that accurate, concise and timely information helped to keep them safe. A majority (92.3%) of them were clear about the hospital's response to the COVID-19 situation, and 79.4% of the respondents reported that the hospital had been able to understand their challenges and address their concerns. Sociodemographic characteristics, such as occupation, age, marital status, work experience, gender, and staff's primary work location influenced the responses to hospital CERC. Local leaders within the hospital would need support to better communicate and translate hospital updates in response to COVID-19 to actionable plans for their staff. Better communication in executing resource utilization plans, expressing more empathy and care for their staff, and enhancing communication channels, such as through the use of secure text messaging rather than emails would be important. CONCLUSION: CERC is relevant and important in the hospital setting to managing COVID-19 and should be considered concurrently with hospital emergency response domains.

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study.

Purpose: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery. Chatbots could fill a pivotal role in the dissemination and easy accessibility of accurate information in a pandemic. In this study, we developed a multi-lingual NLP-based AI chatbot, DR-COVID, which responds accurately to open-ended, COVID-19 related questions. This was used to facilitate pandemic education and healthcare delivery. Methods: First, we developed DR-COVID with an ensemble NLP model on the Telegram platform (https://t.me/drcovid_nlp_chatbot). Second, we evaluated various performance metrics. Third, we evaluated multi-lingual text-to-text translation to Chinese, Malay, Tamil, Filipino, Thai, Japanese, French, Spanish, and Portuguese. We utilized 2,728 training questions and 821 test questions in English. Primary outcome measurements were (A) overall and top 3 accuracies; (B) Area Under the Curve (AUC), precision, recall, and F1 score. Overall accuracy referred to a correct response for the top answer, whereas top 3 accuracy referred to an appropriate response for any one answer amongst the top 3 answers. AUC and its relevant matrices were obtained from the Receiver Operation Characteristics (ROC) curve. Secondary outcomes were (A) multi-lingual accuracy; (B) comparison to enterprise-grade chatbot systems. The sharing of training and testing datasets on an open-source platform will also contribute to existing data. Results: Our NLP model, utilizing the ensemble architecture, achieved overall and top 3 accuracies of 0.838 [95% confidence interval (CI): 0.826-0.851] and 0.922 [95% CI: 0.913-0.932] respectively. For overall and top 3 results, AUC scores of 0.917 [95% CI: 0.911-0.925] and 0.960 [95% CI: 0.955-0.964] were achieved respectively. We achieved multi-linguicism with nine non-English languages, with Portuguese performing the best overall at 0.900. Lastly, DR-COVID generated answers more accurately and quickly than other chatbots, within 1.12-2.15 s across three devices tested. Conclusion: DR-COVID is a clinically effective NLP-based conversational AI chatbot, and a promising solution for healthcare delivery in the pandemic era.

Validation of first trimester screening for trisomy 21 in Singapore with reference to performance of nasal bone.

INTRODUCTION: The aim of this study is to describe the performance of first trimester screening (FTS) for trisomy 21 using maternal age, serum biochemistry and fetal nuchal translucency (NT) in a single center and to evaluate the effect of nasal bone on screening performance. MATERIAL AND METHODS: In 12,585 singleton pregnancies, the NT and nasal bone were examined. The majority of these mothers also had their serum biochemical markers analyzed. Risk was computed using different combinations of maternal age, biochemistry, NT and nasal bone. Down syndrome cases were confirmed by karyotyping. RESULTS: There were 12,519 normal pregnancies, 31 with trisomy 21 and 35 with other chromosomal abnormalities. Without considering the nasal bone, the combined FTS detected 87.1% of trisomy 21 fetuses (false positive rate 5.1%), using 1:300 as the risk threshold, and this was further improved to 96.8% with the policy that classifies all fetuses with an absent nasal bone as high risk. Subgroup analysis showed that the detection rate would be 90.9%, with a false positive rate of 3.7%, if nasal bone was incorporated in the risk algorithm, compared to 81.8% and a false positive rate of 5.4% if it was not used. DISCUSSION: FTS is very effective in early detection of trisomy 21 in Singapore. The nasal bone is a useful marker that can substantially improve the screening performance.