Design of a multi-site multi-state clinical trial of home monitoring of chronic disease in the community in Australia
Celler, Branko;
Sparks, Ross;
Nepal, Surya
;
Alem, Leila;
Varnfield, Marlien;
Li, Jane;
Jang-Jaccard, Julian;
McBride, Simon;
Jayasena, Rajiv
2014-12-31
Journal Article
BMC Public Health
14
1270
1471-2458
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.
BioMed Central
Health Care Administration
https://doi.org/10.1186/1471-2458-14-1270
EP175334
Journal article - Refereed
English
Celler, Branko; Sparks, Ross; Nepal, Surya; Alem, Leila; Varnfield, Marlien; Li, Jane; Jang-Jaccard, Julian; McBride, Simon; Jayasena, Rajiv. Design of a multi-site multi-state clinical trial of home monitoring of chronic disease in the community in Australia. BMC Public Health. 2014; 14(1270):1471-2458. https://doi.org/10.1186/1471-2458-14-1270
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