Patterns of multi-morbidity and prediction of hospitalisation and all-cause mortality in advanced age.

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 Maori (indigenous to New Zealand), aged 80-90 and 516 non-Maori, 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 Maori and non-Maori, respectively. The associations between clusters and outcomes differed between Maori and non-Maori. In Maori, 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-Maori, 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.

A survey of personal digital assistant use in a sample of New Zealand doctors.

AIM: To gather information about handheld computing hardware and software usage by hospital based doctors in New Zealand (NZ). METHOD: An online tool (SurveyMonkey) was used to conduct the survey from 27 June to 10 September 2010. Distribution of the survey was via an email to all NZ District Health Boards (DHBs). RESULTS: There were 850 responses. About half of respondents (52%) used a personal digital assistant (PDA), 90% using it at least once daily. Usage varied greatly between DHBs (27-100%), perhaps related to institutional support. Among PDA users, the most common applications were the non-clinical; Scheduler (95%), Contacts (97%), and Tasks (83%). Users felt PDAs helped considerably with organisation and time saving. For non-users there were a range of barriers to usage, cost being a large factor. Another major barrier identified by both users and non-users was lack of organisational integration and support. CONCLUSIONS: Half of survey respondents used a PDA. PDA usage of responders from different DHBs varied considerably. Perceived barriers to PDA use included cost and lack of institutional support. A collaborative approach between clinical leadership and Information Technology teams to address barriers may result in increased utility and usage of PDAs in the NZ health system.

Resource usage and outcomes in a facilitated discharge service in Christchurch, New Zealand.

AIM: To describe the type and level of support provided by a facilitated discharge team to frail older patients discharging from a 113-bed elderly rehabilitation hospital and the outcomes achieved. METHOD: Prospective data detailing reasons for referral, services provided and retrospective data on outcomes, were obtained to 90 days post discharge on visits to new patients during 21/2/08 to 15/7/08. RESULTS: Seventy-four patients (mean age 82, 58% female) were included. The mean duration of intervention was 19 days with the most common reasons for referral being poor mobility/falls risk, poor cognition, hygiene concerns. The average number of contacts was 6.5. Patients with the highest number of contacts were those referred with patient anxiety/low confidence (7.4), and family concern (8.4). The most common interventions were family contact and management of carer stress, liaison with medical staff. Unplanned readmission (within 90 days) occurred in 32% whereas 12% and 8% were in residential care or had died respectively. CONCLUSION: Managing the transition from hospital to home for older people requires a large range of interventions, particularly in this highly selected group. Unplanned readmission occurred in a third of this very frail elderly group, yet only 12% needed residential care, suggesting the reasons for readmission could be resolved. Patient or family anxiety resulted in more follow-up visits to patients, and inpatient teams should be mindful of this when planning discharges.