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Introduction Rehabilitation assessment and programmes after stroke pay little attention to the so-called `good side', the side ipsilateral to the cerebral infarct. None the less, stroke patients may report clumsiness [...]

Background: multi-morbidity is associated with poor outcomes and increased healthcare utilisation. We aim to identify multi-morbidity patterns and associations with potentially inappropriate prescribing (PIP), subsequent hospitalisation and mortality in octogenarians., Methods: life and Living in Advanced Age; a Cohort Study in New Zealand (LiLACS NZ) examined health outcomes of 421 Māori (indigenous to New Zealand), aged 80-90 and 516 non-Māori, aged 85 years in 2010. Presence of 14 chronic conditions was ascertained from self-report, general practice and hospitalisation records and physical assessments. Agglomerative hierarchical cluster analysis identified clusters of participants with co-existing conditions. Multivariate regression models examined the associations between clusters and PIP, 48-month hospitalisations and mortality., Results: six clusters were identified for Māori and non-Māori, respectively. The associations between clusters and outcomes differed between Māori and non-Māori. In Māori, those in the complex multi-morbidity cluster had the highest prevalence of inappropriately prescribed medications and in cluster 'diabetes' (20% of sample) had higher risk of hospitalisation and mortality at 48-month follow-up. In non-Māori, those in the 'depression-arthritis' (17% of the sample) cluster had both highest prevalence of inappropriate medications and risk of hospitalisation and mortality., Conclusions: in octogenarians, hospitalisation and mortality are better predicted by profiles of clusters of conditions rather than the presence or absence of a specific condition. Further research is required to determine if the cluster approach can be used to target patients to optimise resource allocation and improve outcomes., (© The Author(s) 2017. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For permissions, please email: journals.permissions@oup.com)

Introduction: global population projections forecast large growth in demand for long-term care (LTC) and acute hospital services for older people. Few studies report changes in hospitalisation rates before and after entry into LTC. This study compares hospitalisation rates 1 year before and after LTC entry., Methods: the Older Persons' Ability Level (OPAL) study was a 2008 census-type survey of LTC facilities in Auckland, New Zealand. OPAL resident hospital admissions and deaths were obtained from routinely collected national databases., Results: all 2,244 residents (66% = female) who entered LTC within 12 months prior to OPAL were included. There were 3,363 hospitalisations, 2,424 in 12 months before and 939 in 12 months after entry, and 364 deaths. In the 6 to 12 months before LTC entry, the hospitalisation rate/100 person-years was 67.3 (95% confidence interval [CI] 62.5-72.1). Weekly rates then rose steeply to over 450/100 person-years in the 6 months immediately before LTC entry. In the 6 months after LTC entry, the rate fell to 49.1 (CI 44.9-53.3; RR 0.73 (CI 0.65-0.82, P < 0.0001)) and decreased further 6 to 12 months after entry to 41.1 (CI 37.1-45.1; rate ratio [RR] 0.61 (CI 0.54-0.69, P < 0.0001))., Conclusions: increased hospitalisations a few months before LTC entry suggest functional and medical instability precipitates LTC entry. New residents utilise hospital beds less frequently than when at home before that unstable period. Further research is needed to determine effective interventions to avoid some hospitalisations and possibly also LTC entry., (© The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Introduction: long-term care (LTC) residents have higher hospitalisation rates than non-LTC residents. Rapid decline may follow hospitalisations, hence the importance of preventing unnecessary hospitalisations. Literature describes diagnosis-specific interventions (for cardiac failure, ischaemic heart disease, chronic obstructive pulmonary disease, stroke, pneumonia-termed 'big five' diagnoses), impacting on hospitalisations of older community-dwellers, but few RCTs show reductions in acute admissions from LTC., Methods: LTC facilities with higher than expected hospitalisations were recruited for a cluster-randomised controlled trial (RCT) of facility-based complex, non-disease-specific, 9-month intervention comprising gerontology nurse specialist (GNS)-led staff education, facility benchmarking, GNS resident review and multidisciplinary discussion of residents selected using standard criteria. In this post hoc exploratory analysis, the outcome was acute hospitalisations for 'big five' diagnoses. Re-randomisation analyses were used for end points during months 1-14. For end points during months 4-14, proportional hazards models are adjusted for within-facility clustering., Results: we recruited 36 facilities with 1,998 residents (1,408 female; mean age 82.9 years); 1,924 were alive at 3 months. The intervention did not impact overall rates of acute hospitalisations or mortality (previously published), but resulted in fewer 'big five' admissions (RR = 0.73, 95% CI = 0.54-0.99; P = 0.043) with no significant difference in the rate of other acute admissions. When considering events occurring after 3 months (only), the intervention group were 34.7% (HR = 0.65; 95% CI = 0.49-0.88; P = 0.005) less likely to have a 'big five' acute admission than controls, with no differences in likelihood of acute admissions for other diagnoses (P = 0.96)., Conclusions: this generic intervention may reduce admissions for common conditions which the literature shows are impacted by disease-specific admission reduction strategies., (© The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: frail older people living in residential long-term care (LTC) have limited life expectancy. Identifying those with poor prognosis may improve management and facilitate transition to a palliative approach to care., Objective: to develop methods for predicting mortality in LTC., Design: a population-based cohort study., Setting: LTC facilities, Auckland, New Zealand., Subjects: five hundred randomly selected older people in a census-type survey of those living in LTC in 2008., Methods: mortality data were obtained from New Zealand Ministry of Health. Two methods for assessing mortality risk were developed using demographic, functional and health service information: (i) two geriatricians blinded to identifying data and to mortality, independently reviewed survey, medications and pre-survey hospitalisations data, and grouped residents according to perceived risk of death within 12 months; (ii) multivariate logistic regression model used the same survey and medication items as the geriatricians., Results: for the geriatricians' assessment, each quintile of perceived risk was associated with a significant increase in mortality (P < 0.001). Area under the curve (AUC) for both physicians was 0.64. The logistic regression model included age, gender, assistance with feeding and requiring night attention, all variables which are easily available from LTC records. AUC for the model was 0.70, but when validated against the entire OPAL cohort, it was 0.65. When either or both geriatrician and the model together predicted high risk of death, 1-year mortality was >50%., Conclusion: two methods with the potential to identify older people with limited prognosis are described. Use of these methods allowed identification of over half of those who died within 12 months., (© The Author 2015. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: in Auckland, New Zealand in 1988, 7.7% of those aged over 65 years lived in licenced residential aged care. Age-specific rates approximately doubled for each 5-year age group after the age of 65 years. Even with changes in policies and market forces since 1988, population increases are forecast to drive large growth in demand. This study shows previously unrecognised 20-year trends in rates of care in a geographically defined population., Methods: four cross-sectional surveys of all facilities (rest homes and hospitals) licenced for long-term care of older people were conducted in Auckland, New Zealand in 1988, 1993, 1998 and 2008. Facility staff completed survey forms for each resident. Numbers of licenced and occupied beds and trends in age-specific and age-standardised rates in residential aged care are reported., Results: over the 20-year period, Auckland's population aged over 65 years increased by 43% (from 91,000 to 130,000) but actual numbers in care reduced slightly. Among those aged over 65 years, the proportion living in care facilities reduced from 1 in 13 to 1 in 18. Age-standardised rates in rest-home level care reduced from 65 to 33 per thousand, and in hospital level care, from 29 to 23 per thousand. Had rates remained stable, over 13,200 people, 74% more than observed, would have been in care in 2008., Conclusion: growth predicted in the residential aged care sector is not yet evident. The introduction of standardised needs assessments before entry, increased availability of home-based services, and growth in retirement villages may have led to reduced utilisation.