Association of quality-of-care indicators with asthma outcomes: A retrospective observational study for asthma care in Singapore.

Introduction: Asthma guidelines have advocated for the use of quality-of-care indicators (QCIs) in asthma management. To improve asthma care, it is important to identify effective QCIs that are actionable. This study aimed to evaluate the effect of the presence of 3 QCIs: asthma education, Asthma Control Test (ACT) and spirometry testing on the time to severe exacerbation (TTSE). Method: Data collected from the SingHealth COPD and Asthma Data Mart (SCDM), including asthma patients managed in 9 SingHealth polyclinics and Singapore General Hospital from January 2015 to December 2020, were analysed. Patients receiving Global Initiative for Asthma (GINA) Steps 3-5 treatment, with at least 1 QCI recorded, and at least 1 severe exacerbation within 1 year before the first QCI record, were included. Data were analysed using multivariate Cox regression and quasi-Poisson regression models. Results: A total of 3849 patients in the registry fulfilled the criteria. Patients with records of asthma education or ACT assessment have a lower adjusted hazard ratio (HR) for TTSE (adjusted HR=0.88, P=0.023; adjusted HR=0.83, P<0.001). Adjusted HR associated with spirometry is higher (adjusted HR=1.22, P=0.026). No QCI was significantly associated with emergency department (ED)/inpatient visits. Only asthma education and ACT showed a decrease in the number of exacerbations for multivariate analysis (asthma education estimate: -0.181, P<0.001; ACT estimate: -0.169, P<0.001). No QCI was significant for the number of exacerbations associated with ED/inpatient visits. Conclusion: Our study suggests that the perfor-mance of asthma education and ACT was associated with increased TTSE and decreased number of exacerbations, underscoring the importance of ensuring quality care in clinical practice.

Why Are Some Male Alcohol Misuse Disorder Patients High Utilisers of Emergency Health Services? An Asian Qualitative Study.

BACKGROUND: Certain alcohol misuse patients heavily utilise the Emergency Department (ED) and Emergency Medical Services (EMS) and may present with intoxication or long-term sequelae of alcohol misuse. Our study explored reasons for repeated ED/EMS utilisation and sought to understand perpetuating and protective factors for drinking. METHODS: Face-to-face semi-structured qualitative interviews were conducted. Participants were recruited from an ED in Singapore. Interviews were audio-recorded, transcribed verbatim and underwent manual thematic analysis. Emergent themes were independently reviewed for agreement. Data from medical records, interview transcripts, and field notes were triangulated for analysis. RESULTS: All participants were male (n = 20) with an average age of 55.6 years (SD = 8.86). Most were unemployed (75%), did not have tertiary education (75%), were divorced (55%), and had pre-existing psychiatric conditions (60%) and chronic cardiovascular conditions (75%). Reasons for utilisation included a perceived need due to symptoms, although sometimes it was bystanders who called the ambulance. ED/EMS was preferred due to the perceived higher quality and speed of care. Persistent drinking was attributed to social and environmental factors, and as a coping mechanism for stressors. Rehabilitation programs and meaningful activities reduced drinking tendencies. CONCLUSION: ED/EMS provide sought-after services for alcohol misuse patients, resulting in high utilisation. Social and medical intervention could improve drinking behaviours and decrease overall ED/EMS utilisation.

Nationwide Alcohol-related visits In Singapore's Emergency departments (NAISE): A retrospective population-level study from 2007 to 2016.

INTRODUCTION: Excessive alcohol consumption is associated with increased morbidity and mortality, and its societal impact is substantial. The Nationwide Alcohol-related visits In Singapore Emergency departments study aims to characterise trends in ED visits involving acute and chronic alcohol consumption between 2007 and 2016. METHODS: Data from the Singapore Ministry of Health, comprising all ED visits in Singapore from 2007 to 2016, were used. The data were aggregated by year and analysed for changes in prevalence and rates of ED visits for acute and chronic alcohol consumption, broken down by age, gender and ethnicity. RESULTS: Over the study period, the number of ED visits involving alcohol consumption increased 98.3%, from 2236 in 2007 to 4433 in 2016. During the same period, the rate per 100 000 population increased 62.4% from 48.7 to 79.1, and total ED-related costs rose by 140%, from 528 680 to 1 269 638 SGD. The increase in alcohol-related visits rates and costs was higher than non-alcohol-related visits rates and costs, which increased by 12.1% and 115% respectively. While trends in acute and chronic alcohol-related ED visits stayed stable amongst women, they rose substantially in men. Older men aged 50-69 show the highest rates and rate of increase for both acute and chronic alcohol-related ED visits. DISCUSSION AND CONCLUSIONS: Alcohol-related visits contributed disproportionately to the increasing number of ED visits in Singapore between 2007 and 2016. Older men form the demographic with the highest rates and increase in rates of alcohol-related ED visits and form a potential group for targeted intervention.

Effective Treatment Recommendations for Type 2 Diabetes Management Using Reinforcement Learning: Treatment Recommendation Model Development and Validation.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and its related complications represent a growing economic burden for many countries and health systems. Diabetes complications can be prevented through better disease control, but there is a large gap between the recommended treatment and the treatment that patients actually receive. The treatment of T2DM can be challenging because of different comprehensive therapeutic targets and individual variability of the patients, leading to the need for precise, personalized treatment. OBJECTIVE: The aim of this study was to develop treatment recommendation models for T2DM based on deep reinforcement learning. A retrospective analysis was then performed to evaluate the reliability and effectiveness of the models. METHODS: The data used in our study were collected from the Singapore Health Services Diabetes Registry, encompassing 189,520 patients with T2DM, including 6,407,958 outpatient visits from 2013 to 2018. The treatment recommendation model was built based on 80% of the dataset and its effectiveness was evaluated with the remaining 20% of data. Three treatment recommendation models were developed for antiglycemic, antihypertensive, and lipid-lowering treatments by combining a knowledge-driven model and a data-driven model. The knowledge-driven model, based on clinical guidelines and expert experiences, was first applied to select the candidate medications. The data-driven model, based on deep reinforcement learning, was used to rank the candidates according to the expected clinical outcomes. To evaluate the models, short-term outcomes were compared between the model-concordant treatments and the model-nonconcordant treatments with confounder adjustment by stratification, propensity score weighting, and multivariate regression. For long-term outcomes, model-concordant rates were included as independent variables to evaluate if the combined antiglycemic, antihypertensive, and lipid-lowering treatments had a positive impact on reduction of long-term complication occurrence or death at the patient level via multivariate logistic regression. RESULTS: The test data consisted of 36,993 patients for evaluating the effectiveness of the three treatment recommendation models. In 43.3% of patient visits, the antiglycemic medications recommended by the model were concordant with the actual prescriptions of the physicians. The concordant rates for antihypertensive medications and lipid-lowering medications were 51.3% and 58.9%, respectively. The evaluation results also showed that model-concordant treatments were associated with better glycemic control (odds ratio [OR] 1.73, 95% CI 1.69-1.76), blood pressure control (OR 1.26, 95% CI, 1.23-1.29), and blood lipids control (OR 1.28, 95% CI 1.22-1.35). We also found that patients with more model-concordant treatments were associated with a lower risk of diabetes complications (including 3 macrovascular and 2 microvascular complications) and death, suggesting that the models have the potential of achieving better outcomes in the long term. CONCLUSIONS: Comprehensive management by combining knowledge-driven and data-driven models has good potential to help physicians improve the clinical outcomes of patients with T2DM; achieving good control on blood glucose, blood pressure, and blood lipids; and reducing the risk of diabetes complications in the long term.

Automating the Renal Cell Carcinoma Registry in Singapore: A Case Study on the Integration of the Research Electronic Data Capture System with the Enterprise Data Warehouse.

The renal cell carcinoma registry (RCCR) at the Singapore General Hospital was established in the 1980s. In 2012, the registry transited to a partially automated system using Research Electronic Data Capture (REDCap) and Oracle Business Intelligence Enterprise Edition (OBIEE), which is a platform for retrieval of electronic data from the Electronic Health Intelligence System (eHIntS). A committee was formed of experts from the department of urology and the health services research center, as well as an information technology (IT) team to evaluate the efficacy of the partially automated system. In the 5 years after the new system was implemented, 1,751 cases were recorded in the RCCR. The casefinding completeness increased by 1.9%, the data accuracy rate was 97%, and the efficiency increased by 12%. Strengths of the new system after partial automation were: (1) secure access to the registry via the hospital Web, (2) direct access to REDCap via the electronic medical records system, (3) automated and timely data extraction, and (4) visual presentation of data. On the other hand, we also encountered several challenges in the process of automating the registry, including limited IT support, limited expertise in matching data variables from RCCR and eHIntS, and limited availability and accessibility of eHIntS information for import into REDCap. In summary, despite these challenges, partial automation was achieved with the REDCap/OBIEE system, enhancing efficiency, data security, and data quality.

Caregiving and Its Resulting Effects-The Care Study to Evaluate the Effects of Caregiving on Caregivers of Patients with Advanced Cancer in Singapore.

Informal caregivers (IC) are key to enabling home deaths, where preferred, at the end-of-life. Significant morbidity from advanced cancer can make caregiving burdensome. However, knowledge about the nature of the caregiving burden for caregivers in Singapore is limited. Hence, the key objective in this study was to examine the impact of the caregiving burden on quality of life (QOL), mental health and work capacity among local ICs. Eligible English-speaking ICs of hospitalized advanced cancer patients were recruited through non-random sampling. The Zarit Burden Interview (ZBI), Caregiver Quality of Life Index-Cancer (CQOLC), Center for Epidemiologic Studies Depression Scale-Revised (CESD-R), and Work Productivity and Activity Impairment Questionnaire (WPAI) were interviewer-administered to eligible ICs. Altogether, 16 ICs were surveyed. The mean age of ICs was 43.8 years. Most were children of patients (43.8%), and eight ICs had high burden (ZBI > 17). Those with ZBI > 17 had lower QOL, higher depression scores as well as greater work and activity impairment. In conclusion, high caregiver burden has adverse effects on QOL, mental health and work productivity. Non-physical elements of caregiving (particularly financial and decision-making) and increased number of care roles undertaken by a single IC contribute to high burden. Future interventions for caregiving burden in Singapore should also address the financial and decision-making aspects of caregiving. Outsourcing selected aspects of the caregiving role to community services may reduce the number of caregiving aspects undertaken by a single IC and caregiver burden.