Validation of a Risk Prediction Equation for Incident Chronic Kidney Disease in a Hypertensive Non-Diabetes Cohort in Singapore Primary Care Patients.

BACKGROUND: Accurate identification of individuals at risk of developing chronic kidney disease (CKD) may improve clinical care. Nelson et al. developed prediction equations to estimate the risk of incident eGFR of less than 60 mL/min/1.73 m2 in diabetic and non-diabetes patients using data from 34 multinational cohorts. We aim to validate the non-diabetes equation in our local multi-ethnic cohort and develop further prediction models. METHODS: Demographics, clinical and laboratory data of hypertensive non-diabetes patients with baseline eGFR ≥60 mL/min/1.73 m2 on follow-up with primary care clinics between 2010 and 2015 were collected. Follow-up was 5 years from entry to study. We validated Nelson's equation and developed our own model which we subsequently validated. The developmental cohort included patients between 2010 and 2014 while the validation cohort included patients in 2015. Variables included age, sex, eGFR, history of cardiovascular disease, ever smoker, body mass index, albuminuria, cholesterol, and treatment. Primary outcome was incident eGFR <60/min/1.73 m2 within 5 years. Model performance was evaluated by C-statistics and calibration was assessed. RESULTS: In the developmental cohort of 27,800 patients, 2823 (10.2%) developed the outcome during a mean follow-up of 4.4 years while 638 (12.8%) patients developed the outcome in the validation cohort of 4,994 patients. Applicability of Nelson's equation was limited by missing albuminuria, absence of black race, and exclusion of non-hypertensive patients in our cohort. Nonetheless, the modified Nelson's model demonstrated C-statistic of 0.85 (95% CI: 0.84-0.86). The C-statistic of our bespoke model was 0.85 (0.85-0.86) and 0.87 (0.85-0.88) for the developmental cohort and validation cohort, respectively. Calibration was suboptimal as the predicted risk exceeded the observed risk. CONCLUSIONS: The modified Nelson's equation and our locally derived novel model demonstrated high discrimination. Both models may potentially be used in predicting risk of CKD in hypertensive patients who are managed in primary care, allowing for early interventions in high-risk population.

Risk factors for short-term all-cause mortality in patients with end stage renal disease: a scoping review.

OBJECTIVES: There is a lack of prognostic information to guide the prediction of short-term all-cause mortality in patients with end-stage renal disease (ESRD). The aim was to review the risk factors that influenced the risk of short-term all-cause mortality in patients with ESRD. METHODS: MEDLINE, Embase, PubMed, CINAHL, the Cochrane Library and Web of Science databases were searched for articles published between 2000 and 2020. Articles describing risk factors predicting short-term mortality (≤ 3 years) in patients with ESRD were included. Four reviewers independently performed title, abstract, full text screening and data extraction. Assessment of risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool checklist. RESULTS: 20,840 articles were identified and 113 papers were included for this review. Of the 113 papers, 6.2% included only peritoneal dialysis (PD) patients, 67.3% included only hemodialysis (HD) patients, 20.4% included both PD and HD patients, with the remaining papers featuring patients on conservative management or awaiting renal transplant. Risk factors were categorised into 13 domains: 1)demographics/ lifestyle, 2) comorbidities 3)intradialytic blood pressure, 4)biomarkers, 5)cardiovascular measurements, 6)frailty status, 7)medications, 8)treatment related indicators, 9)renal related parameters, 10)health status, 11)cause of ESRD, 12)access to healthcare care/ information and, 13)proxy measures for poor health. C-reactive protein(CRP), age, and functional status were observed to have higher percentage of instances of being significantly associated with all-cause mortality. CONCLUSION: Commonly examined risk factors observed from this review may be used to build a general prognostic model for patients with ESRD, with specific treatment related risk factors added on to enhance the accuracy of the models.

Prognostic Factors of Mortality in Nonchronic Obstructive Pulmonary Disease Chronic Lung Disease: A Scoping Review.

Introduction: Patients with chronic lung disease (CLD) experience a heavy symptom burden at the end of life, but their uptake of palliative care is notably low. Having an understanding of a patient's prognosis would facilitate shared decision making on treatment options and care planning between patients, families, and their clinicians, and complement clinicians' assessments of patients' unmet palliative needs. While literature on prognostication in patients with chronic obstructive pulmonary disease (COPD) has been established and summarized, information for other CLDs remains less consolidated. Summarizing the mortality risk factors for non-COPD CLDs would be a novel contribution to literature. Hence, we aimed to identify and summarize the prognostic factors associated with non-COPD CLDs from the literature. Methods: We conducted a scoping review following published guidelines. We searched MEDLINE, Embase, PubMed, CINAHL, Cochrane Library, and Web of Science for studies published between 2000 and 2020 that described non-COPD CLD populations with an all-cause mortality risk period of up to three years. Only primary studies which reported associations with mortality adjusted through multivariable analysis were included. Results: Fifty-five studies were reviewed, with 53 based on interstitial lung disease (ILD) or connective tissue disease-associated ILD populations and two in bronchiectasis populations. Prognostic factors were classified into 10 domains, with pulmonary function and disease being the largest. Older age, lower forced vital capacity, and lower carbon monoxide diffusing capacity were most commonly investigated and associated with statistically significant increases in mortality risks. Conclusions: This comprehensive overview of prognostic factors for patients with non-COPD CLDs would facilitate the identification and prioritization of candidate factors to predict short-term mortality, supporting tool development for decision making and to identify high-risk patients for palliative needs assessments. Literature focused on patients with ILDs, and more studies should be conducted on other CLDs to bridge the knowledge gap.

Semi-automating abstract screening with a natural language model pretrained on biomedical literature.

We demonstrate the performance and workload impact of incorporating a natural language model, pretrained on citations of biomedical literature, on a workflow of abstract screening for studies on prognostic factors in end-stage lung disease. The model was optimized on one-third of the abstracts, and model performance on the remaining abstracts was reported. Performance of the model, in terms of sensitivity, precision, F1 and inter-rater agreement, was moderate in comparison with other published models. However, incorporating it into the screening workflow, with the second reviewer screening only abstracts with conflicting decisions, translated into a 65% reduction in the number of abstracts screened by the second reviewer. Subsequent work will look at incorporating the pre-trained BERT model into screening workflows for other studies prospectively, as well as improving model performance.

Predicting mortality in patients diagnosed with advanced dementia presenting at an acute care hospital: the PROgnostic Model for Advanced DEmentia (PRO-MADE).

BACKGROUND: Challenges in prognosticating patients diagnosed with advanced dementia (AD) hinders timely referrals to palliative care. We aim to develop and validate a prognostic model to predict one-year all-cause mortality (ACM) in patients with AD presenting at an acute care hospital. METHODS: This retrospective cohort study utilised administrative and clinical data from Tan Tock Seng Hospital (TTSH). Patients admitted to TTSH between 1st July 2016 and 31st October 2017 and identified to have AD were included. The primary outcome was ACM within one-year of AD diagnosis. Multivariable logistic regression was used. The PROgnostic Model for Advanced Dementia (PRO-MADE) was internally validated using a bootstrap resampling of 1000 replications and externally validated on a more recent cohort of AD patients. The model was evaluated for overall predictive accuracy (Nagelkerke's R2 and Brier score), discriminative [area-under-the-curve (AUC)], and calibration [calibration slope and calibration-in-the-large (CITL)] properties. RESULTS: A total of 1,077 patients with a mean age of 85 (SD: 7.7) years old were included, and 318 (29.5%) patients died within one-year of AD diagnosis. Predictors of one-year ACM were age > 85 years (OR:1.87; 95%CI:1.36 to 2.56), male gender (OR:1.62; 95%CI:1.18 to 2.22), presence of pneumonia (OR:1.75; 95%CI:1.25 to 2.45), pressure ulcers (OR:2.60; 95%CI:1.57 to 4.31), dysphagia (OR:1.53; 95%CI:1.11 to 2.11), Charlson Comorbidity Index ≥ 8 (OR:1.39; 95%CI:1.01 to 1.90), functional dependency in ≥ 4 activities of daily living (OR: 1.82; 95%CI:1.32 to 2.53), abnormal urea (OR:2.16; 95%CI:1.58 to 2.95) and abnormal albumin (OR:3.68; 95%CI:2.07 to 6.54) values. Internal validation results for optimism-adjusted Nagelkerke's R2, Brier score, AUC, calibration slope and CITL were 0.25 (95%CI:0.25 to 0.26), 0.17 (95%CI:0.17 to 0.17), 0.76 (95%CI:0.76 to 0.76), 0.95 (95% CI:0.95 to 0.96) and 0 (95%CI:-0.0001 to 0.001) respectively. When externally validated, the model demonstrated an AUC of 0.70 (95%CI:0.69 to 0.71), calibration slope of 0.64 (95%CI:0.63 to 0.66) and CITL of -0.27 (95%CI:-0.28 to -0.26). CONCLUSION: The PRO-MADE attained good discrimination and calibration properties. Used synergistically with a clinician's judgement, this model can identify AD patients who are at high-risk of one-year ACM to facilitate timely referrals to palliative care.

Understanding the role of fear of missing out and deficient self-regulation in sharing of deepfakes on social media: Evidence from eight countries.

Deepfakes are a troubling form of disinformation that has been drawing increasing attention. Yet, there remains a lack of psychological explanations for deepfake sharing behavior and an absence of research knowledge in non-Western contexts where public knowledge of deepfakes is limited. We conduct a cross-national survey study in eight countries to examine the role of fear of missing out (FOMO), deficient self-regulation (DSR), and cognitive ability in deepfake sharing behavior. Results are drawn from a comparative survey in seven South Asian contexts (China, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) and compare these findings to the United States, where discussions about deepfakes have been most relevant. Overall, the results suggest that those who perceive the deepfakes to be accurate are more likely to share them on social media. Furthermore, in all countries, sharing is also driven by the social-psychological trait - FOMO. DSR of social media use was also found to be a critical factor in explaining deepfake sharing. It is also observed that individuals with low cognitive ability are more likely to share deepfakes. However, we also find that the effects of DSR on social media and FOMO are not contingent upon users' cognitive ability. The results of this study contribute to strategies to limit deepfakes propagation on social media.

Emergency department interventions for frailty (EDIFY): improving functional outcomes in older persons at the emergency department through a multicomponent frailty intervention.

OBJECTIVES: emergency department interventions for frailty (EDIFY) delivers frailty-centric interventions at the emergency department (ED). We evaluated the effectiveness of a multicomponent frailty intervention (MFI) in improving functional outcomes among older persons. DESIGN: a quasi-experimental study. SETTING: a 30-bed ED observation unit within a 1,700-bed acute tertiary hospital. PARTICIPANTS: patients aged ≥65 years, categorised as Clinical Frailty Scale 4-6, and planned for discharge from the unit. METHODS: we compared patients receiving the MFI versus usual-care. Data on demographics, function, frailty, sarcopenia, comorbidities and medications were gathered. Our primary outcome was functional status-Modified Barthel Index (MBI) and Lawton's iADL. Secondary outcomes include hospitalisation, ED re-attendance, mortality, frailty, sarcopenia, polypharmacy and falls. Follow-up assessments were at 3, 6 and 12 months. RESULTS: we recruited 140 participants (mean age 79.7 ± 7.6 years; 47% frail and 73.6% completed the study). Baseline characteristics between groups were comparable (each n = 70). For the intervention group, MBI scores were significantly higher at 6 months (mean: 94.5 ± 11.2 versus 88.5 ± 19.5, P = 0.04), whereas Lawton's iADL scores experienced less decline (change-in-score: 0.0 ± 1.7 versus -1.1 ± 1.8, P = 0.001). Model-based analyses revealed greater odds of maintaining/improving MBI in the intervention group at 6 months [odds ratio (OR) 2.51, 95% confidence interval (CI) 1.04-6.03, P = 0.04] and 12 months (OR 2.98, 95% CI 1.18-7.54, P = 0.02). This was similar for Lawton's iADL at 12 months (OR 4.01, 95% CI 1.70-9.48, P = 0.002). ED re-attendances (rate ratio 0.35, 95% CI 0.13-0.90, P = 0.03) and progression to sarcopenia (OR 0.19, 95% CI 0.04-0.94, P = 0.04) were also lower at 6 months. CONCLUSIONS: the MFI delivered to older persons at the ED can possibly improve functional outcomes and reduce ED re-attendances while attenuating sarcopenia progression.

Variation in coded frailty syndromes in secondary care administrative data: an international retrospective exploratory study.

OBJECTIVES: Challenges with manual methodologies to identify frailty, have led to enthusiasm for utilising large-scale administrative data, particularly standardised diagnostic codes. However, concerns have been raised regarding coding reliability and variability. We aimed to quantify variation in coding frailty syndromes within standardised diagnostic code fields of an international dataset. SETTING: Pooled data from 37 hospitals in 10 countries from 2010 to 2014. PARTICIPANTS: Patients ≥75 years with admission of >24 hours (N=1 404 671 patient episodes). PRIMARY AND SECONDARY OUTCOME MEASURES: Frailty syndrome groups were coded in all standardised diagnostic fields by creation of a binary flag if the relevant diagnosis was present in the 12 months leading to index admission. Volume and percentages of coded frailty syndrome groups by age, gender, year and country were tabulated, and trend analysis provided in line charts. Descriptive statistics including mean, range, and coefficient of variation (CV) were calculated. Relationship to in-hospital mortality, hospital readmission and length of stay were visualised as bar charts. RESULTS: The top four contributors were UK, US, Norway and Australia, which accounted for 75.4% of the volume of admissions. There were 553 595 (39.4%) patient episodes with at least one frailty syndrome group coded. The two most frequently coded frailty syndrome groups were 'Falls and Fractures' (N=3 36 087; 23.9%) and 'Delirium and Dementia' (N=221 072; 15.7%), with the lowest CV. Trend analysis revealed some coding instability over the frailty syndrome groups from 2010 to 2014. The four countries with the lowest CV for coded frailty syndrome groups were Belgium, Australia, USA and UK. There was up to twofold, fourfold and twofold variation difference for outcomes of length of stay, 30-day readmission and inpatient mortality, respectively, across the countries. CONCLUSIONS: Variation in coding frequency for frailty syndromes in standardised diagnostic fields are quantified and described. Recommendations are made to account for this variation when producing risk prediction models.

Singapore's COVID-19 "circuit breaker" interventions: A description of individual-level adoptions of precautionary behaviours.

INTRODUCTION: Effectiveness of COVID-19 control interventions relies significantly on behavioural modifications of its population. Differing adoption rates impacts subsequent COVID-19 control. Hence, positive and sustained behavioural modification is essential for disease control. We describe the adoption rates of behavioural modifications for Singapore's "circuit-breaker" (CB), the national public health response to the COVID-19 crisis, among the general population in the community. METHODS: We conducted an interrupted-time series study using retrospective secondary data. We compared the proportion of Singaporeans who reported adopting specific behaviour modifications before, during and after CB. Behaviours of interest were working from home, performing hand hygiene, using face mask in public, and avoiding crowded areas. We compared change in incidence rates for community COVID-19 cases among the general population across the same time periods. RESULTS: There was an increase in face mask usage (+46.9%, 95% confidence interval [CI] 34.9-58.8, P<0.01) and working from home (+20.4%, 95% CI 11.7-29.2, P<0.01) during CB than before CB in Singapore. Other self-reported behaviours showed no statistically significant difference. Change in daily incidence rates of community COVID-19 cases decreased from additional 0.73 daily case before CB to 0.55 fewer case per day during CB (P<0.01). There was no significant difference among all behaviour adoption rates after CB. Daily incidence of community cases continued to decrease by 0.11 case daily after CB. CONCLUSION: Community incidence of COVID-19 in Singapore decreased during CB and remained low after CB. Use of face masks and social-distancing compliance through working from home increased during CB. However, it is unlikely to influence other sources of COVID-19 such as imported cases or within foreign worker dormitories.

Emergency Department Interventions for Frailty (EDIFY): Front-Door Geriatric Care Can Reduce Acute Admissions.

OBJECTIVES: The EDIFY program was developed to deliver early geriatric specialist interventions at the emergency department (ED) to reduce the number of acute admissions by identifying patients for safe discharge or transfer to low-acuity care settings. We evaluated the effectiveness of EDIFY in reducing potentially avoidable acute admissions. DESIGN: A quasi-experimental study. SETTING: ED of a 1700-bed tertiary hospital. PARTICIPANTS: ED patients aged ≥85 years. MEASUREMENTS: We compared EDIFY interventions versus standard care. Patients with plans for acute admission were screened and recruited. Data on demographics, premorbid function, frailty status, comorbidities, and acute illness severity were gathered. We examined the primary outcome of "successful acute admission avoidance" among the intervention group, which was defined as no ED attendance within 72 hours of discharge from ED, no transfer to an acute ward from subacute-care units (SCU) within 72-hours, or no transfer to an acute ward from the short-stay unit (SSU). Secondary outcomes were rehospitalization, ED re-attendance, institutionalization, functional decline, mortality, and frailty transitions at 1, 3, and 6 months. RESULTS: We recruited 100 participants (mean age 90.0 ± 4.1 years, 66.0% women). There were no differences in baseline characteristics between intervention (n = 43) and nonintervention (n = 57) groups. Thirty-five (81.4%) participants in the intervention group successfully avoided an acute admission (20.9% home, 23.3% SCU, and 44.2% SSU). All participants in the nonintervention group were hospitalized. There were no differences in rehospitalization, ED re-attendance, institutionalization and mortality over the study period. Additionally, we observed a higher rate of progression to a poorer frailty category at all time points among the nonintervention group (1, 3, and 6 months: all P < .05). CONCLUSIONS AND IMPLICATIONS: Results from our single-center study suggest that early geriatric specialist interventions at the ED can reduce potentially avoidable acute admissions without escalating the risk of rehospitalization, ED re-attendance, or mortality, and with possible benefit in attenuating frailty progression.

Estimating Transmission Parameters for COVID-19 Clusters by Using Symptom Onset Data, Singapore, January-April 2020.

We estimated the generation interval distribution for coronavirus disease on the basis of serial intervals of observed infector-infectee pairs from established clusters in Singapore. The short mean generation interval and consequent high prevalence of presymptomatic transmission requires public health control measures to be responsive to these characteristics of the epidemic.

Automated Fastener vs Hand-tied Knots in Heart Valve Surgery: A Systematic Review and Meta-analysis.

BACKGROUND: Although several studies revealed that the Cor-knot automated fastener (LSI Solutions, Victor, NY) reduces aortic cross-clamp and cardiopulmonary bypass times, the influence of the device on postoperative morbidity and mortality still needs to be evaluated. The aim of this study was to verify the hypothesis that the use of the Cor-knot device for heart valve surgery reduces aortic cross-clamp and cardiopulmonary bypass times, and this time saving translates into reduced morbidity and mortality. METHODS: Retrospective cohort studies and randomized controlled trials reporting on the use of the automated fastener vs hand-tied knots were reviewed. The following end points were compared: aortic cross-clamp and cardiopulmonary bypass times, postoperative valvular regurgitation, postoperative ejection fraction, prolonged ventilator support, renal failure, and mortality. RESULTS: Eight studies reporting data on 942 patients were included in the final analysis. The Cor-knot device was associated with shorter cardiopulmonary bypass (mean difference [MD], -11.74; 95% confidence interval [CI], -14.54 to -8.93; P < .00001) and aortic cross-clamp times (MD, -14.36; 95% CI, -19.63 to -9.09; P < .00001) in minimally invasive heart valve procedures. Overall, lower rates of postoperative valvular regurgitation (risk ratio [RR], 0.40; 95% CI, 0.26 to 0.62; P < .0001) and prolonged ventilator support (RR, 0.29; 95% CI, 0.13 to 0.65; P = .003) were observed. No difference was observed in postoperative atrial fibrillation, ejection fraction, renal failure, and mortality. CONCLUSIONS: The use of the Cor-knot device in heart valve surgery reduced aortic cross-clamp and cardiopulmonary bypass times. Furthermore, as compared with hand-tie methods, the automated fastener may lead to decreased rates of prolonged ventilator support and valvular regurgitation while being noninferior in terms of other postoperative outcomes and mortality.

Characterising and predicting persistent high-cost utilisers in healthcare: a retrospective cohort study in Singapore.

OBJECTIVE: We aim to characterise persistent high utilisers (PHUs) of healthcare services, and correspondingly, transient high utilisers (THUs) and non-high utilisers (non-HUs) for comparison, to facilitate stratifying HUs for targeted intervention. Subsequently we apply machine learning algorithms to predict which HUs will persist as PHUs, to inform future trials testing the effectiveness of interventions in reducing healthcare utilisation in PHUs. DESIGN AND SETTING: This is a retrospective cohort study using administrative data from an Academic Medical Centre (AMC) in Singapore. PARTICIPANTS: Patients who had at least one inpatient admission to the AMC between 2005 and 2013 were included in this study. HUs incurred Singapore Dollar 8150 or more within a year. PHUs were defined as HUs for three consecutive years, while THUs were HUs for 1 or 2 years. Non-HUs did not incur high healthcare costs at any point during the study period. OUTCOME MEASURES: PHU status at the end of the third year was the outcome of interest. Socio-demographic profiles, clinical complexity and utilisation metrics of each group were reported. Area under curve (AUC) was used to identify the best model to predict persistence. RESULTS: PHUs were older and had higher comorbidity and mortality. Over the three observed years, PHUs' expenditure generally increased, while THUs and non-HUs' spending and inpatient utilisation decreased. The predictive model exhibited good performance during both internal (AUC: 83.2%, 95% CI: 82.2% to 84.2%) and external validation (AUC: 79.8%, 95% CI: 78.8% to 80.8%). CONCLUSIONS: The HU population could be stratified into PHUs and THUs, with distinctly different utilisation trajectories. We developed a model that could predict at the end of 1 year, whether a patient in our population will continue to be a HU in the next 2 years. This knowledge would allow healthcare providers to target PHUs in our health system with interventions in a cost-effective manner.

Computational Fluid Dynamics Modeling of Hemodynamic Parameters in the Human Diseased Aorta: A Systematic Review.

BACKGROUND: The analysis of the correlation between blood flow and aortic pathology through computational fluid dynamics (CFD) shows promise in predicting disease progression, the effect of operative intervention, and guiding patient treatment. However, to date, there has not been a comprehensive systematic review of the published literature describing CFD in aortic diseases and their treatment. METHODS: This review includes 136 published articles which have investigated the application of CFD in all types of aortic disease (aneurysms, dissections, and coarctation). We took into account case studies of both, treated or untreated pathology, investigated with CFD. We also graded all studies using an author-defined Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach based on the validation method used for the CFD results. RESULTS: There are no randomized controlled trials assessing the efficacy of CFD as applied to aortic pathology, treated or untreated. Although a large number of observational studies are available, those using clinical imaging tools as independent validation of the calculated CFD results exist in far smaller numbers. Only 21% of all studies used clinical imaging as a tool to validate the CFD results and these were graded as high-quality studies. CONCLUSIONS: Contemporary evidence shows that CFD can provide additional hemodynamic parameters such as wall shear stress, vorticity, disturbed laminar flow, and recirculation regions in untreated and treated aortic disease. These have the potential to predict the progression of aortic disease, the effect of operative intervention, and ultimately help guide the choice and timing of treatment to the benefit of patients and clinicians alike.

Stroke Factors Associated with Thrombolysis Use in Hospitals in Singapore and US: A Cross-Registry Comparative Study.

BACKGROUND AND OBJECTIVES: This paper aims to describe and compare the characteristics of 2 stroke populations in Singapore and in St. Louis, USA, and to document thrombolysis rates and contrast factors associated with its uptake in both populations. METHODS: The stroke populations described were from the Singapore Stroke Registry (SSR) in -Singapore and the Cognitive Rehabilitation Research Group Stroke Registry (CRRGSR) in St. Louis, MO, USA. The registries were compared in terms of demographics and stroke risk factor history. Logistic regression was used to determine factors associated with thrombolysis uptake. RESULTS: A total of 39,323 and 8,106 episodes were recorded in SSR and CRRGSR, respectively, from 2005 to 2012. Compared to CRRGSR, patients in SSR were older, male, and from the ethnic majority. Thrombolysis rates in SSR and CRRGSR were 2.5 and 8.2%, respectively, for the study period. History of ischemic heart disease or atrial fibrillation was associated with increased uptake in both populations, while history of stroke was associated with lower uptake. For SSR, younger age and males were associated with increased uptake, while having a history of smoking or diabetes was associated with decreased uptake. For CRRGSR, ethnic minority status was associated with decreased uptake. CONCLUSIONS: The comparison of stroke populations in Singapore and St Louis revealed distinct differences in clinicodemographics of the 2 groups. Thrombolysis uptake was driven by nonethnicity demographics in Singapore. Ethnicity was the only demographic driver of uptake in the CRRGSR population, highlighting the need to target ethnic minorities in increasing access to thrombolysis.

Characterization of high healthcare utilizer groups using administrative data from an electronic medical record database.

BACKGROUND: High utilizers (HUs) are a small group of patients who impose a disproportionately high burden on the healthcare system due to their elevated resource use. Identification of persistent HUs is pertinent as interventions have not been effective due to regression to the mean in majority of patients. This study will use cost and utilization metrics to segment a hospital-based patient population into HU groups. METHODS: The index visit for each adult patient to an Academic Medical Centre in Singapore during 2006 to 2012 was identified. Cost, length of stay (LOS) and number of specialist outpatient clinic (SOC) visits within 1 year following the index visit were extracted and aggregated. Patients were HUs if they exceeded the 90th percentile of any metric, and Non-HU otherwise. Seven different HU groups and a Non-HU group were constructed. The groups were described in terms of cost and utilization patterns, socio-demographic information, multi-morbidity scores and medical history. Logistic regression compared the groups' persistence as a HU in any group into the subsequent year, adjusting for socio-demographic information and diagnosis history. RESULTS: A total of 388,162 patients above the age of 21 were included in the study. Cost-LOS-SOC HUs had the highest multi-morbidity and persistence into the second year. Common conditions among Cost-LOS and Cost-LOS-SOC HUs were cardiovascular disease, acute cerebrovascular disease and pneumonia, while most LOS and LOS-SOC HUs were diagnosed with at least one mental health condition. Regression analyses revealed that HUs across all groups were more likely to persist compared to Non-HUs, with stronger relationships seen in groups with high SOC utilization. Similar trends remained after further adjustment. CONCLUSION: HUs of healthcare services are a diverse group and can be further segmented into different subgroups based on cost and utilization patterns. Segmentation by these metrics revealed differences in socio-demographic characteristics, disease profile and persistence. Most HUs did not persist in their high utilization, and high SOC users should be prioritized for further longitudinal analyses. Segmentation will enable policy makers to better identify the diverse needs of patients, detect gaps in current care and focus their efforts in delivering care relevant and tailored to each segment.

Drivers of hospital expenditure and length of stay in an academic medical centre: a retrospective cross-sectional study.

BACKGROUND: As healthcare expenditure and utilization continue to rise, understanding key drivers of hospital expenditure and utilization is crucial in policy development and service planning. This study aims to investigate micro drivers of hospital expenditure and length of stay (LOS) in an Academic Medical Centre. METHODS: Data corresponding to 285,767 patients and 207,426 inpatient visits was extracted from electronic medical records of the National University of Hospital in Singapore between 2005 to 2013. Generalized linear models and generalized estimating equations were employed to build patient and inpatient visit models respectively. The patient models provide insight on the factors affecting overall expenditure and LOS, whereas the inpatient visit models provide insight on how expenditure and LOS accumulate longitudinally. RESULTS: Although adjusted expenditure and LOS per inpatient visit were largely similar across socio-economic status (SES) groups, patients of lower SES groups accumulated greater expenditure and LOS over time due to more frequent visits. Admission to a ward class with greater government subsidies was associated with higher expenditure and LOS per inpatient visit. Inpatient death was also associated with higher expenditure per inpatient visit. Conditions that drove patient expenditure and LOS were largely similar, with mental illnesses affecting LOS to a larger extent. These observations on condition drivers largely held true at visit-level. CONCLUSIONS: The findings highlight the importance of distinguishing the drivers of patient expenditure and inpatient utilization at the patient-level from those at the visit-level. This allows better understanding of the drivers of healthcare utilization and how utilization accumulates longitudinally, important for health policy and service planning.

Right-Site Care Programme with a community-based family medicine clinic in Singapore: secondary data analysis of its impact on mortality and healthcare utilisation.

OBJECTIVE: Stable patients with chronic conditions could be appropriately cared for at family medicine clinics (FMC) and discharged from hospital specialist outpatient clinics (SOCs). The Right-Site Care Programme with Frontier FMC emphasised care organised around patients in community rather than hospital-based providers, with one identifiable primary provider. This study evaluated impact of this programme on mortality and healthcare utilisation. DESIGN: A retrospective study without randomisation using secondary data analysis of patients enrolled in the intervention matched 1:1 with unenrolled patients as controls. SETTING: Programme was supported by the Ministry of Health in Singapore, a city-state nation in Southeast Asia with 5.6 million population. PARTICIPANTS: Intervention group comprises patients enrolled from January to December 2014 (n=684) and control patients (n=684) with at least one SOC and no FMC attendance during same period. INTERVENTIONS: Family physician in Frontier FMC managed patients in consultation with relevant specialist physicians or fully managed patients independently. Care teams in SOCs and FMC used a common electronic medical records system to facilitate care coordination and conducted regular multidisciplinary case conferences. PRIMARY OUTCOME MEASURES: Deidentified linked healthcare administrative data for time period of January 2011 to December 2017 were extracted. Three-year postenrolment mortality rates and utilisation frequencies and charges for SOC, public primary care centres (polyclinic), emergency department attendances and emergency, non-day surgery inpatient and all-cause admissions were compared. RESULTS: Intervention patients had lower mortality rate (HR=0.37, p<0.01). Among those with potential of postenrolment polyclinic attendance, intervention patients had lower frequencies (incidence rate ratio (IRR)=0.60, p<0.01) and charges (mean ratio (MR)=0.51, p<0.01). Among those with potential of postenrolment SOC attendance, intervention patients had higher frequencies (IRR=2.06, p<0.01) and charges (MR=1.86, p<0.01). CONCLUSIONS: Intervention patients had better survival, probably because their chronic conditions were better managed with close monitoring, contributing to higher total outpatient attendance frequencies and charges.

Processing of Electronic Medical Records for Health Services Research in an Academic Medical Center: Methods and Validation.

BACKGROUND: Electronic medical records (EMRs) contain a wealth of information that can support data-driven decision making in health care policy design and service planning. Although research using EMRs has become increasingly prevalent, challenges such as coding inconsistency, data validity, and lack of suitable measures in important domains still hinder the progress. OBJECTIVE: The objective of this study was to design a structured way to process records in administrative EMR systems for health services research and assess validity in selected areas. METHODS: On the basis of a local hospital EMR system in Singapore, we developed a structured framework for EMR data processing, including standardization and phenotyping of diagnosis codes, construction of cohort with multilevel views, and generation of variables and proxy measures to supplement primary data. Disease complexity was estimated by Charlson Comorbidity Index (CCI) and Polypharmacy Score (PPS), whereas socioeconomic status (SES) was estimated by housing type. Validity of modified diagnosis codes and derived measures were investigated. RESULTS: Visit-level (N=7,778,761) and patient-level records (n=549,109) were generated. The International Classification of Diseases, Tenth Revision, Australian Modification (ICD-10-AM) codes were standardized to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) with a mapping rate of 87.1%. In all, 97.4% of the ICD-9-CM codes were phenotyped successfully using Clinical Classification Software by Agency for Healthcare Research and Quality. Diagnosis codes that underwent modification (truncation or zero addition) in standardization and phenotyping procedures had the modification validated by physicians, with validity rates of more than 90%. Disease complexity measures (CCI and PPS) and SES were found to be valid and robust after a correlation analysis and a multivariate regression analysis. CCI and PPS were correlated with each other and positively correlated with health care utilization measures. Larger housing type was associated with lower government subsidies received, suggesting association with higher SES. Profile of constructed cohorts showed differences in disease prevalence, disease complexity, and health care utilization in those aged above 65 years and those aged 65 years or younger. CONCLUSIONS: The framework proposed in this study would be useful for other researchers working with EMR data for health services research. Further analyses would be needed to better understand differences observed in the cohorts.

Inclination towards research and the pursuit of a research career among medical students: an international cohort study.

BACKGROUND: Involvement of clinicians in biomedical research is imperative for the future of healthcare. Several factors influence clinicians' inclination towards research: the medical school experience, exposure to research article reading and writing, and knowledge of research. This cohort study follows up medical students at time of graduation to explore changes in their inclination towards research and pursuing a research career compared to their inclination at time of entry into medical school. METHODS: Students from medical schools in six different countries were enrolled in their first year of school and followed-up upon graduation in their final year. Students answered the same self-administered questionnaire at both time points. Changes in inclination towards research and pursuing a research career were assessed. Factors correlated with these changes were analysed. RESULTS: Of the 777 medical students who responded to the study questionnaire at entry into medical school, 332 (42.7%) completed the follow-up survey. Among these 332 students, there was no significant increase in inclination towards research or pursuing a research career over the course of their medical schooling. Students from a United States based school, in contrast to those from schools other countries, were more likely to report having research role models to guide them (51.5% vs. 0%-26.4%) and to have published in a peer-reviewed journal (75.7% vs. 8.9%-45%). Absence of a role model was significantly associated with a decrease in inclination towards research, while an increased desire to learn more about statistics was significantly associated with an increase in inclination towards pursuing a research career. CONCLUSION: Most medical students did not experience changes in their inclination towards research or pursuing a research career over the course of their medical schooling. Factors that increased their inclination to undertaking research or pursuing a research career were availability of a good role model, and a good knowledge of both the research process and the analytical tools required.