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)

[1]  S. Ebrahim,et al.  The abbreviated mental test: its use and validity. , 1991, Age and ageing.

[2]  Guy Paré,et al.  Review Paper: Systematic Review of Home Telemonitoring for Chronic Diseases: The Evidence Base , 2007, J. Am. Medical Informatics Assoc..

[3]  Steven Cummins,et al.  Validating Health Impact Assessment: Prediction is difficult (especially about the future) , 2007 .

[4]  Liam J Caffery,et al.  Telehealth services in rural and remote Australia: a systematic review of models of care and factors influencing success and sustainability. , 2016, Rural and remote health.

[5]  Stanton Newman,et al.  The impact of self-monitoring in chronic illness on healthcare utilisation: a systematic review of reviews , 2015, BMC Health Services Research.

[6]  William R. Hersh,et al.  Telehealth: Mapping the Evidence for Patient Outcomes From Systematic Reviews , 2016 .

[7]  Surya Nepal,et al.  Design of a multi-site multi-state clinical trial of home monitoring of chronic disease in the community in Australia , 2014, BMC Public Health.

[8]  Jennifer Dixon,et al.  Effect of telecare on use of health and social care services: findings from the Whole Systems Demonstrator cluster randomised trial , 2013, Age and ageing.

[9]  Angus Morrison-Saunders,et al.  Practitioner Perspectives on the Role of Science in Environmental Impact Assessment , 2003, Environmental management.

[10]  Adam Steventon,et al.  Effect of telehealth on hospital utilisation and mortality in routine clinical practice: a matched control cohort study in an early adopter site , 2016, BMJ Open.

[11]  A. J. Underwood,et al.  Beyond BACI: Experimental designs for detecting human environmental impacts on temporal variations in natural populations , 1991 .

[12]  Heather A Richards,et al.  Creating the foundation data for building a population grouping methodology – lessons learned at the Canadian Institute for Health Information (CIHI) , 2015, BMC Health Services Research.

[13]  B. Wakefield,et al.  Care Coordination/Home Telehealth: the systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. , 2008, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[14]  N. Hardiker,et al.  Telehealth: The effects on clinical outcomes, cost effectiveness and the patient experience: a systematic overview of the literature , 2013 .

[15]  G. Anderson,et al.  The Growing Burden of Chronic Disease in America , 2004, Public health reports.

[16]  P. Bower,et al.  A comprehensive evaluation of the impact of telemonitoring in patients with long-term conditions and social care needs: protocol for the whole systems demonstrator cluster randomised trial , 2011, BMC health services research.