Testing models of care for terminally ill people who live alone at home: is a randomised controlled trial the best approach?

This project implemented and evaluated two models of care for terminally ill people living alone at home: installing personal alarms (PA) and providing extra care aide (CA) support. The primary aim was to assess the feasibility of using a randomised controlled trial (RCT) approach with this group. A secondary aim was to assess the potential impact of the models of care on the participants' quality of life, symptom distress, anxiety and depression, and perceived benefits and barriers to their use. The two models of care were piloted in collaboration with Silver Chain Hospice Care Service (SCHCS) in Western Australia during 2009-2010. Using a pilot RCT design, equal numbers of participants were randomised to receive extra CA time, PAs or standard care. Attrition reduced the sample size from 20 in each group to 12, 14 and 17 respectively. The intervention period was between 6 and 12 weeks depending on prognosis. The participants were functionally and psychologically well and the majority lived alone by choice. There were physical and psychological benefits associated with provision of the two models of care, particularly for the group supported by CAs in terms of improved sleeping and appetite. However, the impact was mostly not statistically significant due to small sample sizes. The study has highlighted two methodological challenges: the wide variation in the degree of living alone at home leading to complex inclusion criteria, and an RCT approach with attrition differing across groups and patients not wanting to be included in the assigned group. The RCT approach is not considered appropriate for the 'home alone' palliative care population that would have been better supported by providing each participant with a personalised model of care according to needs. However, the outcomes of the project have prompted changes in SCHCS practice when providing care to these patients.

Measuring symptom distress in palliative care: psychometric properties of the Symptom Assessment Scale (SAS)

Given the variety of palliative care settings within which symptom distress must be assessed, development of a valid and reliable clinical tool that can be simply applied in every day practice is needed. The Symptom Assessment Scale (SAS) uses a 0-10 numerical scale with zero being no symptom and 10 being the worst possible. The key symptoms included in the scale are breathing, bowel problems, appetite problems, pain, insomnia, nausea and fatigue. The instrument is structured to allow either the patient, family member or nurse to assess the symptoms. The scale was tested on 572 cancer patients recruited from five palliative care services in Western Australia. Results indicated that the instrument was brief, clinically useful and was administered with minimal missing data. Internal consistency reliability estimates of the scale ranged from 0.64-0.92 as measured by the Cronbach's alpha co-efficient. Test-retest reliabilities of 0.84-0.92 were obtained using Pearson's correlation co-efficient. The instrument does not provide an in-depth assessment of individual symptoms, but serves as a screening tool to identify troublesome symptoms that warrant attentive and immediate investigation and comprehensive assessment.

Is it feasible and desirable to collect voluntarily quality and outcome data nationally in palliative oncology care?

Hospice/palliative care is a critical component of cancer care. In Australia, more than 85% of people referred to specialized hospice/palliative care services (SHPCS) have a primary diagnosis of cancer, and 60% of people who die from cancer will be referred to SHPCS. The Palliative Care Outcomes Collaboration (PCOC) is an Australian initiative that allows SHPCS to collect nationally agreed-upon measures to better understand quality, safety, and outcomes of care. This article describes data (October 2006 through September 2007) from the first 22 SHPCS, with more than 100 inpatient admissions annually. Data include phase of illness, place of discharge, and, at each transition in place of care, the person's functional status, dependency, and symptom scores. Data are available for 5,395 people for 6,379 admissions. After categorizing by phase of illness and dependency, there remain at the end of each admission 12-fold differences (mean, 26%; range, 4% to 52%) in the percentage of patients who became stable after an unstable phase; seven-fold differences (mean, 22%; range, 6% to 41%) in the percentage of patients with improved symptom scores, five-fold differences (mean, 25%; range, 12% to 64%) in discharge back to the community, four-fold differences (mean, 10%; range, 4% to 16%) in improved function, and three-fold differences in the length of stay (mean, 14 days; range, 6 to 19 days). PCOC shows it is feasible to collect quality national palliative care outcome data voluntarily. Variations in outcomes justify continued enrollment of services. Benchmarking should include all patients whose cancer will cause death and explore observed variations.