Martin von Randow

Does a Functional Activity Programme Improve Function, Quality of Life, and Falls for Residents in Long Term Care? Cluster Randomised Controlled Trial

Objective To assess the effectiveness of an activity programme in improving function, quality of life, and falls in older people in residential care. Design Cluster randomised controlled trial with one year follow-up. Setting 41 low level dependency residential care homes in New Zealand. Participants 682 people aged 65 years or over. Interventions 330 residents were offered a goal setting and individualised activities of daily living activity programme by a gerontology nurse, reinforced by usual healthcare assistants; 352 residents received social visits. Main outcome measures Function (late life function and disability instruments, elderly mobility scale, FICSIT-4 balance test, timed up and go test), quality of life (life satisfaction index, EuroQol), and falls (time to fall over 12 months). Secondary outcomes were depressive symptoms and hospital admissions. Results 473 (70%) participants completed the trial. The programme had no impact overall. However, in contrast to residents with impaired cognition (no differences between intervention and control group), those with normal cognition in the intervention group may have maintained overall function (late life function and disability instrument total function, P=0.024) and lower limb function (late life function and disability instrument basic lower extremity, P=0.015). In residents with cognitive impairment, the likelihood of depression increased in the intervention group. No other outcomes differed between groups. Conclusion A programme of functional rehabilitation had minimal impact for elderly people in residential care with normal cognition but was not beneficial for those with poor cognition. Trial registration Australian Clinical Trials Register ACTRN12605000667617.

Residential aged care in Auckland, New Zealand 1988–2008: do real trends over time match predictions?

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, Aucklands 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.

Promoting Independence in Residential Care: Successful Recruitment for a Randomized Controlled Trial

OBJECTIVES To describe the recruitment strategy and association between facility and staff characteristics and success of resident recruitment for the Promoting Independence in Residential Care (PIRC) trial. DESIGN Cross-sectional study of staff and facility characteristics and recruitment rates within facilities with calculation of cluster effects of multiple measures. SETTING AND PARTICIPANTS Staff of low-level dependency residential care facilities and residents able to engage in a physical activity program in 2 cities in New Zealand. MEASURES A global impression of staff willingness to facilitate research was gauged by research nurses, facility characteristics were measured by staff interview. Relevant outcomes were measured by resident interview and included the following: (1) Function: Late Life FDI scale, timed-up-and-go, FICSIT balance scale and the Elderly Mobility Scale; (2) Quality of Life: EuroQol quality of life scale, Life Satisfaction Index; and (3) falls were assessed by audit of the medical record. Correlation between recruitment rates, facility characteristics and global impression of staff willingness to participate were investigated. Design effects were calculated on outcomes. RESULTS Forty-one (85%) facilities and 682 (83%) residents participated, median age was 85 years (range 65-101), and 74% were women. Participants had complex health problems. Recruitment rates were associated (but did not increase linearly) with the perceived willingness of staff, and were not associated with facility size. Design effects from the cluster recruitment differed according to outcome. CONCLUSIONS The recruitment strategy was successful in recruiting a large sample of people with complex comorbidities and high levels of functional disability despite perceptions of staff reluctance. Staff willingness was related to recruitment success.

Primary Care in an Aging Society: Building and Testing a Microsimulation Model for Policy Purposes

The authors describe the development of a microsimulation model of primary medical care in New Zealand for 2002 and demonstrate its ability to test the impact of demographic ageing, community support, and practitioner repertoire. Micro-level data were drawn from four sources: two iterations of the New Zealand Health Survey (NZHS 1996/1997 and 2002/2003); a national survey of ambulatory care in New Zealand (New Zealand National Primary Medical Care Survey [NPMCS] 2001/ 2002); and the Australian National Health Survey (ANHS). Data from the New Zealand surveys were statistically matched to create a representative synthetic base file of over 13,000 individuals. Probabilities of health experiences and general practitioner (GP) use derived from the ANHS, and of GP activity derived from the NPMCS were applied via a Monte Carlo process to create health histories for the individuals in the base file. Final health care outcomes simulated—the number of visits in a year, the distribution of health conditions, and GP activity levels—were validated against external benchmarks. Policy-relevant scenarios were demonstrated by a forward projection to 2021 and by implementing counterfactuals on key attributes of the synthetic population. The results showed little change in model-predicted health care outcomes. There is potential for this approach to address policy purposes.

Data Matching to Allocate Doctors to Patients in a Microsimulation Model of the Primary Care Process in New Zealand

The authors aimed to use existing data to create a microsimulation model of the primary care process in New Zealand, including realistically simulating the allocation of general practitioners (GPs) to a population sample. This is important because GP behavior is likely to be a major determinant of future cost and service outcomes. Two nationally representative data sets were matched: a sample of GPs and their patients from the National Primary Medical Care Survey (NPMCS) and a population sample from the New Zealand Health Survey (NZHS). Matching involved first dividing the data sets into cells based on common variables. Further variables were then included in a distance function to guide matching within cells. A transportation optimization algorithm allocated GPs based on these—on similarities in patients’ attributes. Statistical matching performed well with high correlations for patient attributes and reduced average absolute rank differences on proportions of patients among GPs compared to random matching. Low Kullback–Leibler (K–L) divergences confirmed that our method of statistical matching had allocated GPs realistically. Models of primary care too frequently omit the role of the practitioner in driving health service outcomes. The authors developed a method to impute characteristics of GPs to a population-based microsimulation model of primary care.