The Contribution of Ageing to Hospitalisation Days in Hong Kong: A Decomposition Analysis

Background: Ageing has become a serious challenge in Hong Kong and globally. It has serious implications for health expenditure, which accounts for nearly 20% of overall government expenditure. Here we assess the contribution of ageing and related factors to hospitalisation days in Hong Kong. We used hospital discharge data from all publicly funded hospitals in Hong Kong between 2001 and 2012. Methods: A decomposition method was used to examine the factors that account for the change of total hospitalisation days during the two periods, 2001-2004 and 2004-2012. The five factors include two demographic factors – population size and age-gender composition – and three service components – hospital discharge rate, number of discharge episodes per patient, and average length of stay (LOS) – which are all measured at age-gender group level. In order to assess the health cost burden in the future, we also project the total hospitalisation days up to 2041, for a range of scenarios. Results: During the decreasing period of hospitalisation days (2001-2004), the reduction of LOS contributed to about 60% of the reduction. For the period of increase (2004-2012), ageing is associated with an increase in total hospitalisation days of 1.03 million, followed by an increase in hospital discharge rates (0.67 million), an increase in the number of discharge episodes per patient (0.62 million), and population growth (0.43 million). The reduction of LOS has greatly offset these increases (-2.19 million days), and has become one of the most significant factors in containing the increasing number of hospitalisation days. Projected increases in total hospitalisation days under different scenarios have highlighted that the contribution of ageing will become even more prominent after 2022. Conclusion: Hong Kong is facing increasing healthcare burden caused by the rapid increase in demand for inpatient services due to ageing. Better management of inpatient services with the aim of increasing efficiency and reducing LOS, avoidable hospitalisation and readmission, without compromising patient satisfaction and quality of service, are crucial for containing the rapid and enormous increases in total hospitalisation days for Hong Kong. The results would be relevant to many rapidly ageing societies in this region

Predicting first-episode psychosis patients who will never relapse over 10 years.

BACKGROUND: Although relapse in psychosis is common, a small proportion of patients will not relapse in the long term. We examined the proportion and predictors of patients who never relapsed in the 10 years following complete resolution of positive symptoms from their first psychotic episode. METHOD: Patients who previously enrolled in a 12-month randomized controlled trial on medication discontinuation and relapse following first-episode psychosis (FEP) were followed up after 10 years. Relapse of positive symptoms was operationalized as a change from a Clinical Global Impression scale positive score of <3 for at least 3 consecutive months to a score of ⩾3 (mild or more severe). Baseline predictors included basic demographics, premorbid functioning, symptoms, functioning, and neurocognitive functioning. RESULTS: Out of 178 first-episode patients, 37 (21%) never relapsed during the 10-year period. Univariate predictors (p ⩽ 0.1) of patients who never relapsed included a duration of untreated psychosis (DUP) ⩽30 days, diagnosed with non-schizophrenia spectrum disorders, having less severe negative symptoms, and performing better in logical memory immediate recall and verbal fluency tests. A multivariate logistic regression analysis further suggested that the absence of any relapsing episodes was significantly related to better short-term verbal memory, shorter DUP, and non-schizophrenia spectrum disorders. CONCLUSIONS: Treatment delay and neurocognitive function are potentially modifiable predictors of good long-term prognosis in FEP. These predictors are informative as they can be incorporated into an optimum risk prediction model in the future, which would help with clinical decision making regarding maintenance treatment in FEP

Results of Antiretroviral Treatment Interruption and Intensification in Advanced Multi-Drug Resistant HIV Infection from the OPTIMA Trial

BACKGROUND: Guidance is needed on best medical management for advanced HIV disease with multidrug resistance (MDR) and limited retreatment options. We assessed two novel antiretroviral (ARV) treatment approaches in this setting. METHODS AND FINDINGS: We conducted a 2×2 factorial randomized open label controlled trial in patients with a CD4 count≤300 cells/µl who had ARV treatment (ART) failure requiring retreatment, to two options (a) re-treatment with either standard (≤4 ARVs) or intensive (≥5 ARVs) ART and b) either treatment starting immediately or after a 12-week monitored ART interruption. Primary outcome was time to developing a first AIDS-defining event (ADE) or death from any cause. Analysis was by intention to treat. From 2001 to 2006, 368 patients were randomized. At baseline, mean age was 48 years, 2% were women, median CD4 count was 106/µl, mean viral load was 4.74 log(10) copies/ml, and 59% had a prior AIDS diagnosis. Median follow-up was 4.0 years in 1249 person-years of observation. There were no statistically significant differences in the primary composite outcome of ADE or death between re-treatment options of standard versus intensive ART (hazard ratio 1.17; CI 0.86-1.59), or between immediate retreatment initiation versus interruption before re-treatment (hazard ratio 0.93; CI 0.68-1.30), or in the rate of non-HIV associated serious adverse events between re-treatment options. CONCLUSIONS: We did not observe clinical benefit or harm assessed by the primary outcome in this largest and longest trial exploring both ART interruption and intensification in advanced MDR HIV infection with poor retreatment options. TRIAL REGISTRATION: Clinicaltrials.gov NCT00050089

High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model

Investigations on the influence of nature vs. nurture on Alcoholism (Alcohol Use Disorder) in human have yet to provide a clear view on potential genomic etiologies. To address this issue, we sequenced a replicated animal model system bidirectionally-selected for alcohol preference (AP). This model is uniquely suited to map genetic effects with high reproducibility, and resolution. The origin of the rat lines (an 8-way cross) resulted in small haplotype blocks (HB) with a corresponding high level of resolution. We sequenced DNAs from 40 samples (10 per line of each replicate) to determine allele frequencies and HB. We achieved ~46X coverage per line and replicate. Excessive differentiation in the genomic architecture between lines, across replicates, termed signatures of selection (SS), were classified according to gene and region. We identified SS in 930 genes associated with AP. The majority (50%) of the SS were confined to single gene regions, the greatest numbers of which were in promoters (284) and intronic regions (169) with the least in exon\u27s (4), suggesting that differences in AP were primarily due to alterations in regulatory regions. We confirmed previously identified genes and found many new genes associated with AP. Of those newly identified genes, several demonstrated neuronal function involved in synaptic memory and reward behavior, e.g. ion channels (Kcnf1, Kcnn3, Scn5a), excitatory receptors (Grin2a, Gria3, Grip1), neurotransmitters (Pomc), and synapses (Snap29). This study not only reveals the polygenic architecture of AP, but also emphasizes the importance of regulatory elements, consistent with other complex traits

The Contribution of Ageing to Hospitalisation Days in Hong Kong: A Decomposition Analysis Key Messages

Abstract Background: Ageing has become a serious challenge in Hong Kong and globally. It has serious implications for health expenditure, which accounts for nearly 20% of overall government expenditure. Here we assess the contribution of ageing and related factors to hospitalisation days in Hong Kong. We used hospital discharge data from all publicly funded hospitals in Hong Kong between 2001 and 2012. Methods: A decomposition method was used to examine the factors that account for the change of total hospitalisation days during the two periods, 2001-2004 and 2004-2012. The five factors include two demographic factors -population size and age-gender composition -and three service components -hospital discharge rate, number of discharge episodes per patient, and average length of stay (LOS) -which are all measured at age-gender group level. In order to assess the health cost burden in the future, we also project the total hospitalisation days up to 2041, for a range of scenarios. Results: During the decreasing period of hospitalisation days (2001)(2002)(2003)(2004), the reduction of LOS contributed to about 60% of the reduction. For the period of increase (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012), ageing is associated with an increase in total hospitalisation days of 1.03 million, followed by an increase in hospital discharge rates (0.67 million), an increase in the number of discharge episodes per patient (0.62 million), and population growth (0.43 million). The reduction of LOS has greatly offset these increases (-2.19 million days), and has become one of the most significant factors in containing the increasing number of hospitalisation days. Projected increases in total hospitalisation days under different scenarios have highlighted that the contribution of ageing will become even more prominent after 2022. Conclusion: Hong Kong is facing increasing healthcare burden caused by the rapid increase in demand for inpatient services due to ageing. Better management of inpatient services with the aim of increasing efficiency and reducing LOS, avoidable hospitalisation and readmission, without compromising patient satisfaction and quality of service, are crucial for containing the rapid and enormous increases in total hospitalisation days for Hong Kong. The results would be relevant to many rapidly ageing societies in this region. Implications for policy makers • We quantified the changes in hospitalisation days empirically into various components, using a decomposition analysis. Ageing was found to make the strongest contribution to increasing inpatient demand, and will continue to do so. • The increasing demand for inpatient services due to ageing is a predictable and inevitable phenomenon. Adequately managing length of stay (LOS) in hospital and reducing avoidable hospitalisation and readmission are important, to contain the rate of increasing inpatient demand. Among these, LOS seems to have the largest possibility of further reduction. • The methodology in this paper can readily be adopted in other settings, to assess the contribution of ageing, so that more focused and targeted measures can be developed. Implications for the public In this paper, we made use of data from all publicly funded hospitals in Hong Kong, which has a rapidly ageing population, to quantify empirically and illustrate how changes in population and hospitalisation patterns have affected the demand for inpatient services, as measured by total hospitalisation days. In particular, ageing and population growth would have tremendously increased total hospitalisation days during the past decade, but this increase was offset by the decrease in length of stay (LOS) per hospital visit. However, the effectiveness of measures to reduce LOS has plateaued and ageing is predicted to become much more significant in increasing inpatient demand in the future. Further reduction in LOS, avoidable hospitalisation, and readmission rates, with no adverse influence on the quality of care and patient satisfaction, is crucial to mitigate the high financial pressures on healthcare arising from an ageing population