Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore

The LACE index (length of stay, acuity of admission, Charlson comorbidity index, CCI, and number of emergency department visits in preceding 6 months) derived in Canada is simple and may have clinical utility in Singapore to predict readmission risk. We compared the performance of the LACE index with a derived model in identifying 30-day readmissions from a population of general medicine patients in Singapore. Additional variables include patient demographics, comorbidities, clinical and laboratory variables during the index admission, and prior healthcare utilization in the preceding year. 5,862 patients were analysed and 572 patients (9.8%) were readmitted in the 30 days following discharge. Age, CCI, count of surgical procedures during index admission, white cell count, serum albumin, and number of emergency department visits in previous 6 months were significantly associated with 30-day readmission risk. The final logistic regression model had fair discriminative ability c-statistic of 0.650 while the LACE index achieved c-statistic of 0.628 in predicting 30-day readmissions. Our derived model has the advantage of being available early in the admission to identify patients at high risk of readmission for interventions. Additional factors predicting readmission risk and machine learning techniques should be considered to improve model performance

Oral vitamin B12 replacement for the treatment of pernicious anaemia

Many patients with pernicious anaemia are treated with lifelong intramuscular vitamin B12 replacement. As early as the 1950s, there were studies suggesting that oral vitamin B12 replacement may provide adequate absorption. Nevertheless, oral vitamin B12 replacement in patients with pernicious anaemia remains uncommon in clinical practice. The objective of this review is to provide an update on the effectiveness of oral vitamin B12 for the treatment of pernicious anaemia, the recommended dosage and the required frequency of laboratory test and clinical monitoring. Relevant articles were identified by PubMed search from 1 January 1980 to 31 March 2016 and through hand search of relevant reference articles. Two randomised controlled trials, three prospective papers, one systematic review and three clinical reviews fulfilled our inclusion criteria. We found that oral vitamin B12 replacement at 1000mcg daily was adequate to replace vitamin B12 levels in patients with pernicious anaemia. We conclude that oral vitamin B12 is an effective alternative to vitamin B12 intramuscular injections. Patients should be offered this alternative after an informed discussion on the advantages and disadvantages of both treatment options

A systematic review of health status, health seeking behaviour and healthcare utilisation of low socioeconomic status populations in urban Singapore

Abstract Introduction It is well-established that low socioeconomic status (SES) influences one’s health status, morbidity and mortality. Housing type has been used as an indicator of SES and social determinant of health in some studies. In Singapore, home ownership is among the highest in the world. Citizens who have no other housing options are offered heavily subsidised rental housings. Residents staying in such rental housings are characterised by low socioeconomic status. Our aim is to review studies on the association between staying in public rental housing in Singapore and health status. Methods A PubMed and Scopus search was conducted in January 2017 to identify suitable articles published from 1 January 2000 to 31 January 2017. Only studies that were done on Singapore public rental housing communities were included for review. A total of 14 articles including 4 prospective studies, 8 cross-sectional studies and 2 retrospective cohort studies were obtained for the review. Topics addressed by these studies included: (1) Health status; (2) Health seeking behaviour; (3) Healthcare utilisation. Results Staying in public rental housing was found to be associated with poorer health status and outcomes. They had lower participation in health screening, preferred alternative medicine practitioners to western-trained doctors for primary care, and had increased hospital utilisation. Several studies performed qualitative interviews to explore the causes of disparity and concern about cost was one of the common cited reason. Conclusion Staying in public rental housing appears to be a risk marker of poorer health and this may have important public health implications. Understanding the causes of disparity will require more qualitative studies which in turn will guide interventions and the evaluation of their effectiveness in improving health outcome of this sub-population of patients

Effectiveness and feasibility of deprescribing of symptomatic medications in a Singapore rehabilitation hospital

Introduction: This study aims to determine the effectiveness, cost savings and feasibility of implementing a systematic process of deprescribing medications for symptomatic management, namely, acid suppressants, laxatives, analgesics and antiemetics for patients of a Singapore rehabilitation hospital. Methods: A total of 200 patients were randomized to a deprescribing intervention ( n = 100) or control (usual care) group ( n = 100). The patient-centred deprescribing process was utilized. Symptomatic medications were deprescribed following initial pharmacist assessment, discussion with doctors and consideration of patients’ preferences regarding discontinuation or dose reduction. Symptom recurrence, adverse drug withdrawal events (ADWEs) and the need for drug re-initiation or initiation of new symptomatic medications after deprescribing were monitored in the first, second and sixth weeks. Results: The mean age of patients was 72.8 years and 68.6 years in the intervention and control groups. There were no significant reductions in the monthly cost and total number of medications between both intervention and control groups. Systematic deprescribing of acid suppressants was the highest among the four target drug classes. Recurrence of pain and re-initiation of analgesics occurred in two out of seven cases of discontinuation. However, no ADWEs or constipation were noted in the intervention group. On average, a total of 19 minutes was required by pharmacists and doctors to complete the deprescribing process. Conclusion: The systematic deprescribing of symptomatic medications did not reduce costs nor the total number of medications. The risk of symptom recurrence and adverse events was negligible. Knowledge, attitudes and collaboration among healthcare professionals regarding deprescribing are critical. Trial registration: Clinicaltrials.gov, number NCT03354845

Predicting 30-Day Readmissions in an Asian Population: Building a Predictive Model by Incorporating Markers of Hospitalization Severity.

To reduce readmissions, it may be cost-effective to consider risk stratification, with targeting intervention programs to patients at high risk of readmissions. In this study, we aimed to derive and validate a prediction model including several novel markers of hospitalization severity, and compare the model with the LACE index (Length of stay, Acuity of admission, Charlson comorbidity index, Emergency department visits in past 6 months), an established risk stratification tool.This was a retrospective cohort study of all patients ≥ 21 years of age, who were admitted to a tertiary hospital in Singapore from January 1, 2013 through May 31, 2015. Data were extracted from the hospital's electronic health records. The outcome was defined as unplanned readmissions within 30 days of discharge from the index hospitalization. Candidate predictive variables were broadly grouped into five categories: Patient demographics, social determinants of health, past healthcare utilization, medical comorbidities, and markers of hospitalization severity. Multivariable logistic regression was used to predict the outcome, and receiver operating characteristic analysis was performed to compare our model with the LACE index.74,102 cases were enrolled for analysis. Of these, 11,492 patient cases (15.5%) were readmitted within 30 days of discharge. A total of fifteen predictive variables were strongly associated with the risk of 30-day readmissions, including number of emergency department visits in the past 6 months, Charlson Comorbidity Index, markers of hospitalization severity such as 'requiring inpatient dialysis during index admission, and 'treatment with intravenous furosemide 40 milligrams or more' during index admission. Our predictive model outperformed the LACE index by achieving larger area under the curve values: 0.78 (95% confidence interval [CI]: 0.77-0.79) versus 0.70 (95% CI: 0.69-0.71).Several factors are important for the risk of 30-day readmissions, including proxy markers of hospitalization severity

Predicting 30-Day Readmissions: Performance of the LACE Index Compared with a Regression Model among General Medicine Patients in Singapore

The LACE index (length of stay, acuity of admission, Charlson comorbidity index, CCI, and number of emergency department visits in preceding 6 months) derived in Canada is simple and may have clinical utility in Singapore to predict readmission risk. We compared the performance of the LACE index with a derived model in identifying 30-day readmissions from a population of general medicine patients in Singapore. Additional variables include patient demographics, comorbidities, clinical and laboratory variables during the index admission, and prior healthcare utilization in the preceding year. 5,862 patients were analysed and 572 patients (9.8%) were readmitted in the 30 days following discharge. Age, CCI, count of surgical procedures during index admission, white cell count, serum albumin, and number of emergency department visits in previous 6 months were significantly associated with 30-day readmission risk. The final logistic regression model had fair discriminative ability c-statistic of 0.650 while the LACE index achieved c-statistic of 0.628 in predicting 30-day readmissions. Our derived model has the advantage of being available early in the admission to identify patients at high risk of readmission for interventions. Additional factors predicting readmission risk and machine learning techniques should be considered to improve model performance