Determinants of emergency department utilisation by older adults in Singapore: A systematic review

INTRODUCTION@#Adults aged ≥60 years contribute to disproportionately higher visits to the emergency departments (ED). We performed a systematic review to examine the reasons why older persons visit the ED in Singapore.@*METHODS@#We searched Medline, Embase and Scopus from January 2000 to December 2021 for studies reporting on ED utilisation by older adults in Singapore, and included studies that investigated determinants of ED utilisation. Statistically significant determinants and their effect sizes were extracted. Determinants of ED utilisation were organised using Andersen and Newman's model. Quality of studies was evaluated using Newcastle Ottawa Scale and Critical Appraisal Skills Programme.@*RESULTS@#The search yielded 138 articles, of which 7 were used for analysis. Among the significant individual determinants were predisposing (staying in public rental housing, religiosity, loneliness, poorer coping), enabling (caregiver distress from behavioural and psychological symptoms of dementia) and health factors (multimorbidity in patients with dementia, frailty, primary care visit in last 6 months, better treatment adherence). The 7 included studies are of moderate quality and none of them employed conceptual frameworks to organise determinants of ED utilisation.@*CONCLUSION@#The major determinants of ED utilisation by older adults in Singapore were largely individual factors. Evaluation of societal determinants of ED utilisation was lacking in the included studies. There is a need for a more holistic examination of determinants of ED utilisation locally based on conceptual models of health seeking behaviours.

Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review

BackgroundLittle is known about the role of artificial intelligence (AI) as a decisive technology in the clinical management of COVID-19 patients. We aimed to systematically review and critically appraise the current evidence on AI applications for COVID-19 in intensive care and emergency settings, focusing on methods, reporting standards, and clinical utility. MethodsWe systematically searched PubMed, Embase, Scopus, CINAHL, IEEE Xplore, and ACM Digital Library databases from inception to 1 October 2020, without language restrictions. We included peer-reviewed original studies that applied AI for COVID-19 patients, healthcare workers, or health systems in intensive care, emergency or prehospital settings. We assessed predictive modelling studies using PROBAST (prediction model risk of bias assessment tool) and a modified TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) statement for AI. We critically appraised the methodology and key findings of all other studies. ResultsOf fourteen eligible studies, eleven developed prognostic or diagnostic AI predictive models, all of which were assessed to be at high risk of bias. Common pitfalls included inadequate sample sizes, poor handling of missing data, failure to account for censored participants, and weak validation of models. Studies had low adherence to reporting guidelines, with particularly poor reporting on model calibration and blinding of outcome and predictor assessment. Of the remaining three studies, two evaluated the prognostic utility of deep learning-based lung segmentation software and one studied an AI-based system for resource optimisation in the ICU. These studies had similar issues in methodology, validation, and reporting. ConclusionsCurrent AI applications for COVID-19 are not ready for deployment in acute care settings, given their limited scope and poor quality. Our findings underscore the need for improvements to facilitate safe and effective clinical adoption of AI applications, for and beyond the COVID-19 pandemic.

Coronavirus Disease 2019 (COVID-19): An Evidence Map of Medical Literature

Since the beginning of the COVID-19 outbreak in December 2019, a substantial body of COVID-19 medical literature has been generated. As of May 2020, gaps in the existing literature remain unidentified and, hence, unaddressed. In this paper, we summarise the medical literature on COVID-19 between 1 January and 24 March 2020 using evidence maps and bibliometric analysis in order to systematically identify gaps and propose areas for valuable future research. The examined COVID-19 medical literature originated primarily from Asia and focussed mainly on clinical features and diagnosis of the disease. Many areas of potential research remain underexplored, such as mental health research, the use of novel technologies and artificial intelligence, research on the pathophysiology of COVID-19 within different body systems, and research on indirect effects of COVID-19 on the care of non-COVID-19 patients. Research collaboration at the international level was limited although improvements may aid global containment efforts.

A randomised controlled trial investigating the analgesic efficacy of transversus abdominis plane block for adult laparoscopic appendicectomy

<p><b>INTRODUCTION</b>We conducted a single-centre, prospective randomised clinical trial to investigate the analgesic efficacy of transversus abdominis plane (TAP) block in adult patients undergoing laparoscopic appendicectomy.</p><p><b>METHODS</b>Patients undergoing urgent laparoscopic appendicectomy under general anaesthesia alone (control group) and general anaesthesia supplemented by TAP block (TAP intervention group) were compared. All patients received a multimodal analgesia regime, which included postoperative morphine via a patient-controlled analgesia device. The primary endpoints were morphine consumption at 12 hours and 24 hours postoperatively. Secondary endpoints included pain scores, incidence of nausea and vomiting, and time to hospital discharge. A total of 58 patients were recruited, with 29 patients in each group.</p><p><b>RESULTS</b>Mean postoperative morphine consumption at 12 hours (control group: 11.45 ± 7.64 mg, TAP intervention group: 9.79 ± 8.09 mg; p = 0.4264) and 24 hours (control group: 13.38 ± 8.72 mg, TAP intervention group: 11.31 ± 8.66 mg; p = 0.3686) for the control and TAP intervention groups were not statistically different. Secondary outcomes were also not different between the two groups. Length of stay in the post-anaesthesia care unit was significantly shorter for the TAP intervention group, with a trend toward faster hospital discharge being observed.</p><p><b>CONCLUSION</b>TAP block, a regional anaesthetic procedure performed immediately prior to skin incision for laparoscopic appendicectomy, did not significantly improve postoperative analgesia outcomes.</p>

Medication discrepancies and associated risk factors identified among elderly patients discharged from a tertiary hospital in Singapore

<p><b>INTRODUCTION</b>Medication discrepancies and poor documentation of medication changes (e.g. lack of justification for medication change) in physician discharge summaries can lead to preventable medication errors and adverse outcomes. This study aimed to identify and characterise discrepancies between preadmission and discharge medication lists, to identify associated risk factors, and in cases of intentional medication discrepancies, to determine the adequacy of the physician discharge summaries in documenting reasons for the changes.</p><p><b>METHODS</b>A retrospective clinical record review of 150 consecutive elderly patients was done to estimate the number of medication discrepancies between preadmission and discharge medication lists. The two lists were compared for discrepancies (addition, omission or duplication of medications, and/or a change in dosage, frequency or formulation of medication). The patients' clinical records and physician discharge summaries were reviewed to determine whether the discrepancies found were intentional or unintentional. Physician discharge summaries were reviewed to determine if the physicians endorsed and documented reasons for all intentional medication changes.</p><p><b>RESULTS</b>A total of 279 medication discrepancies were identified, of which 42 were unintentional medication discrepancies (35 were related to omission/addition of a medication and seven were related to a change in medication dosage/frequency) and 237 were documented intentional discrepancies. Omission of the baseline medication was the most common unintentional discrepancy. No reasons were provided in the physician discharge summaries for 54 (22.8%) of the intentional discrepancies.</p><p><b>CONCLUSION</b>Unintentional medication discrepancies are a common occurrence at hospital discharge. Physician discharge summaries often do not have adequate information on the reasons for medication changes.</p>