Singapore Health Services (SingHealth) is Singapore's largest group of healthcare institutions. The group was formed in 2000 and consists of four public hospitals, three community hospitals, five national specialty centres and a network of eight polyclinics. The Singapore General Hospital is the largest hospital in the group and serves as the flagship hospital for the cluster.
Introduction While pathogen genomics using next-generation sequencing (NGS) has been recommended by the WHO as an essential tool for national communicable disease surveillance programmes, procurement and supply chain management (PSM) systems for this new technology are still evolving. To assess the status of PSM systems for pathogen genomics, we examined perspectives from end-users and manufacturers across South and Southeast Asia.Methods Between 2022 and 2023, a cross-sectional survey was conducted among institutional partners supporting pathogen genomics among primarily low- and middle-income countries in South and Southeast Asia. This was complemented by qualitative interviews with the major regional NGS manufacturers. A PSM framework was employed to assess sales, procurement, production, distribution and post-sales support. Analyses are expressed as proportions and means or medians for continuous variables.Results A total of 42 partners across 13 countries, 3 genomics manufacturers and 22 laboratory personnel contributed data to this assessment. PSM challenges were reported by all countries and for all sequencing platforms. High costs of equipment and consumables were identified by 85% of respondents. Long equipment purchasing lead times and reagent re-supply times were reported by 69% and 77% of countries, respectively, with reagent resupply times averaging 8 weeks (IQR 6.2-9.0). Additional barriers included customs clearance, variability of import procedures, taxes and duties. Manufacturers reported a range of strategies to respond to PSM bottlenecks, including establishing regional hubs, distributor networks and financing schemes.Conclusion Coordinated national and regional efforts are required to improve PSM systems for pathogen genomic sequencing to enhance timely early disease detection and response capacity in South and Southeast Asia.
BACKGROUND:Current artificial intelligence (AI) models for medical imaging predominantly focus on a single imaging modality and a single disease. Attempts to create multimodal and multi-disease models have resulted in inconsistent clinical accuracy. Furthermore, training these models typically requires large, well labelled datasets, which are costly and labour intensive to prepare. We aimed to train and evaluate an AI model that can interpret diverse imaging modalities across specialties while maintaining robust performance within each modality. METHODS:We developed Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM), a multi-specialty model trained using self-supervised learning and a memory module. MerMED-FM was pretrained on publicly sourced, unlabelled medical images from 12 specialties and seven imaging modalities: chest x-rays, CT, ultrasound, histopathology, colour fundus photography (CFP), optical coherence tomography (OCT), and dermatoscopy. After pretraining, the model was fine-tuned, validated, and evaluated for the diagnosis of a range of diseases on 26 public datasets and five private datasets comprising radiology, histopathology, and ophthalmology images. MerMED-FM was compared against a general-domain vision foundation model, various specialist single-modality foundation models, and a multispecialty foundation model. Models were fine-tuned using 10%, 30%, 50%, and 100% of data, with primary comparative analyses conducted using a 10% label fraction. The primary outcome was the area under the receiver operating characteristic curve (AUROC), which was summarised by imaging modality. FINDINGS:MerMED-FM was trained on around 3·3 million images from 53 publicly available, unlabelled datasets, comprising 713 931 chest x-rays, 292 353 CT slices, 389 885 ultrasound frames, 1 017 712 pathology patches, 333 099 CFP images, 176 719 OCT slices, and 401 059 dermatoscopy images. Strong performance was achieved across all modalities at a label fraction of only 10%, with mean AUROC values of 0·844 for chest x-rays, 0·906 for CT, 0·818 for ultrasound, 0·908 for histopathology, 0·810 for CFP, 0·962 for OCT, and 0·827 for dermatoscopy. INTERPRETATION:MerMED-FM has the potential to be a highly adaptable, versatile, cross-specialty foundation model that enables robust interpretation of medical imaging across diverse medical disciplines. FUNDING:National Medical Research Council, Singapore and the Agency for Science, Technology and Research, Singapore.
ObjectiveIn the context of youth gender-related medical decision-making, deliberations around hormone replacement therapy (HRT) are recognized as beginning within the family setting and marked by conversations, negotiations and agreements between transgender and gender diverse (TGD) youth and parents. How Singapore's unique sociocultural context shapes familial negotiations for HRT is not understood from existing literature. The objective of this study is to explore how Singaporean TGD youth and parents reach, or fail to reach, an agreement on HRT.MethodsWe conducted semi-structured in-depth interviews with 13 TGD youths and 5 parents and analyzed the data thematically.ResultsTwo main themes were developed. The first theme, 'adopting a position on HRT', involved seeking information and evaluating it for lived experience (by the youth) and local and family relevance (primarily parents) and deliberating around three considerations, namely infertility risk (youth and parents), possibility of detransitioning (youth and parents), and youth's decision-making capacity (mostly parents). The second theme, 'reaching an agreement or not' unfolded through parental approval, parent-youth compromise, or parental refusal. Compromise included trying Traditional Chinese Medicine first. Parental refusals were driven by religious beliefs and fear of youth's impulsivity. In response, some youth reported pressuring parents to agree to HRT.DiscussionFindings are discussed in the context of Asian values-particularly filial piety, hierarchical family roles, and patrilineal obligations-and how these steer conversations and outcomes. Infertility concerns often reflect intergenerational expectations around family lineage. The possibility of detransitioning may be linked to efforts to safeguard family reputation. Youth pressure on parents to give consent can reflect acute distress following limited options in the Singaporean context. Compromise softened hierarchical expectations and opened space for youth participation. Findings highlight that research on the experience of youth and family can be enriched by considering experiences and settings beyond the ones discussed in the Western-focused literature.
Deep learning (DL) applications in healthcare are expanding beyond proof-of-concept studies. Yet, the extent of its real-world implementation and impact on patient care and clinical workflows remains unclear due to the limited prospective real-world findings. Understanding how DL tools perform in real clinical environments is critical for guiding successful and sustainable deployment. Using a layered methodology with established implementation science frameworks, this systematic review aimed to systematically map the implementation strategies and outcomes of prospective DL implementation studies, proposing recommendations based on identified gaps of relevant studies to serve as a guide for the future implementation of DL systems. 20 articles were included: 3 from radiology, 1 from otolaryngology, 3 from dermatology, and 13 from ophthalmology. All studies assessed clinical outcomes, demonstrating the effectiveness and feasibility of integrating DL systems into existing clinical workflows. Adoption and appropriateness were the most frequently evaluated implementation outcomes; only one study evaluated implementation costs, and none evaluated sustainability. Stakeholder acceptability was only evaluated in 8 studies. Given the paucity of real-world DL implementation research, continued research into the clinical deployment of DL systems using hybrid effectiveness-implementation study designs as a framework is essential to facilitate its seamless and effective adoption into clinical practice.
PURPOSE:Robotic and laparoscopic approaches to rectal cancer surgery yield comparable short-term outcomes; however, comparative inpatient costs, particularly when stratified by tumor level, remain insufficiently characterized. This study compared short-term clinical and pathological outcomes, as well as index hospitalization costs, for minimally invasive surgery in patients with mid and low rectal cancer. METHODS:All consecutive patients with mid (5-10 cm from the anal verge) and low (<5 cm from the anal verge) rectal cancer who underwent elective minimally invasive surgery between January 2018 and December 2023 were identified. One-to-one propensity score matching was performed using the following covariates: age, sex, body mass index, American Society of Anesthesiologists physical status, tumor level, receipt of neoadjuvant therapy, and presence of a defunctioning stoma. Outcomes and cost components were compared overall and stratified by tumor level. RESULTS:After matching, 282 patients were included (laparoscopic surgery, n=141; robotic surgery, n=141). Median operative time was longer in the robotic group (368 minutes vs. 325 minutes, P=0.007), whereas the median postoperative length of stay was similar between groups (6.0 days vs. 6.0 days, P=0.255). Rates of conversion to open surgery, anastomotic leak, 30-day mortality, and 30-day readmission did not differ significantly. Histopathological indicators of resection quality, including lymph node yield, margin clearance, and completeness of total mesorectal excision, were comparable. Mean index hospitalization cost was higher in the robotic group (SGD 37,436 vs. SGD 31,724; difference, SGD 5,713; P=0.008), with a greater difference observed in mid rectal cancer (SGD 8,606; P=0.008) than in low rectal cancer (SGD 1,811; P=0.465). CONCLUSION:Robotic and laparoscopic surgery yielded comparable short-term clinical and pathological outcomes. Although costs were higher with robotic surgery, the cost differential was smaller for low rectal cancer, identifying this subgroup as a priority for prospective evaluation of clinical and economic value.
