Impact of At-Home Telemonitoring on Health Services Expenditure and Hospital Admissions in Patients With Chronic Conditions: Before and After Control Intervention Analysis.

BACKGROUND: Telemonitoring is becoming increasingly important for the management of patients with chronic conditions, especially in countries with large distances such as Australia. However, despite large national investments in health information technology, little policy work has been undertaken in Australia in deploying telehealth in the home as a solution to the increasing demands and costs of managing chronic disease. OBJECTIVE: The objective of this trial was to evaluate the impact of introducing at-home telemonitoring to patients living with chronic conditions on health care expenditure, number of admissions to hospital, and length of stay (LOS). METHODS: A before and after control intervention analysis model was adopted whereby at each location patients were selected from a list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. Test patients were supplied with a telehealth vital signs monitor and were remotely managed by a trained clinical care coordinator, while control patients continued to receive usual care. A total of 100 test patients and 137 control patients were analyzed. Primary health care benefits provided to Australian patients were investigated for the trial cohort. Time series data were analyzed using linear regression and analysis of covariance for a period of 3 years before the intervention and 1 year after. RESULTS: There were no significant differences between test and control patients at baseline. Test patients were monitored for an average of 276 days with 75% of patients monitored for more than 6 months. Test patients 1 year after the start of their intervention showed a 46.3% reduction in rate of predicted medical expenditure, a 25.5% reduction in the rate of predicted pharmaceutical expenditure, a 53.2% reduction in the rate of predicted unscheduled admission to hospital, a 67.9% reduction in the predicted rate of LOS when admitted to hospital, and a reduction in mortality of between 41.3% and 44.5% relative to control patients. Control patients did not demonstrate any significant change in their predicted trajectory for any of the above variables. CONCLUSIONS: At-home telemonitoring of chronically ill patients showed a statistically robust positive impact increasing over time on health care expenditure, number of admissions to hospital, and LOS as well as a reduction in mortality. TRIAL REGISTRATION: Retrospectively registered with the Australian and New Zealand Clinical Trial Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030 (Archived by WebCite at http://www.webcitation.org/6sxqjkJHW).

Design of a multi-site multi-state clinical trial of home monitoring of chronic disease in the community in Australia.

BACKGROUND: Telehealth services based on at-home monitoring of vital signs and the administration of clinical questionnaires are being increasingly used to manage chronic disease in the community, but few statistically robust studies are available in Australia to evaluate a wide range of health and socio-economic outcomes. The objectives of this study are to use robust statistical methods to research the impact of at home telemonitoring on health care outcomes, acceptability of telemonitoring to patients, carers and clinicians and to identify workplace cultural factors and capacity for organisational change management that will impact on large scale national deployment of telehealth services. Additionally, to develop advanced modelling and data analytics tools to risk stratify patients on a daily basis to automatically identify exacerbations of their chronic conditions. METHODS/DESIGN: A clinical trial is proposed at five locations in five states and territories along the Eastern Seaboard of Australia. Each site will have 25 Test patients and 50 case matched control patients. All participants will be selected based on clinical criteria of at least two hospitalisations in the previous year or four or more admissions over the last five years for a range of one or more chronic conditions. Control patients are matched according to age, sex, major diagnosis and their Socio-Economic Indexes for Areas (SEIFA). The Trial Design is an Intervention control study based on the Before-After-Control-Impact (BACI) design. DISCUSSION: Our preliminary data indicates that most outcome variables before and after the intervention are not stationary, and accordingly we model this behaviour using linear mixed-effects (lme) models which can flexibly model within-group correlation often present in longitudinal data with repeated measures. We expect reduced incidence of unscheduled hospitalisation as well as improvement in the management of chronically ill patients, leading to better and more cost effective care. Advanced data analytics together with clinical decision support will allow telehealth to be deployed in very large numbers nationally without placing an excessive workload on the monitoring facility or the patient's own clinicians. TRIAL REGISTRATION: Registered with Australian New Zealand Clinical Trial Registry on 1st April 2013. Trial ID: ACTRN12613000635763.

Impact of influenza across 27 public emergency departments in Australia: a 5-year descriptive study.

OBJECTIVE: To describe the incidence, characteristics and outcomes of patients with influenza-like symptoms presenting to 27 public hospital emergency departments (EDs) in Queensland, Australia. METHODS: A descriptive retrospective study covering 5 years (2005-9) of historical data from 27 hospital EDs was undertaken. State-wide hospital ED Information System data were analysed. Annual comparisons between influenza and non-influenza cases were made across the southern hemisphere influenza season (June-September) each year. RESULTS: Influenza-related presentations increased significantly over the 5 years from 3.4% in 2005 to 9.4% in 2009, reflecting a 276% relative increase. Differences over time regarding characteristics of patients with influenza-like symptoms, based on the influenza season, occurred for admission rate (decreased over time from 28% in 2005 to 18% in 2009), length of stay (decreased over time from a median of 210 min in 2005 to 164 min in 2009) and access block (increased over time from 33% to 41%). Also, every year there was a significantly (p<0.001) higher percentage of access block in the influenza cohort than in the non-influenza cohort. CONCLUSIONS: Although there was a large increase over time in influenza-related ED presentations, most patients were discharged home from the ED. Special consideration of health service delivery management (eg, establishing an 'influenza clinic border protection and public rollout of vaccination, beginning with those most at risk') for this group of patients is warranted but requires evaluation. These results may inform planning for service delivery models during the influenza season.