Economic evaluations of eHealth technologies: A systematic review

<div><p>Background</p><p>Innovations in eHealth technologies have the potential to help older adults live independently, maintain their quality of life, and to reduce their health system dependency and health care expenditure. The objective of this study was to systematically review and appraise the quality of cost-effectiveness or utility studies assessing eHealth technologies in study populations involving older adults.</p><p>Methods</p><p>We systematically searched multiple databases (MEDLINE, EMBASE, CINAHL, NHS EED, and PsycINFO) for peer-reviewed studies published in English from 2000 to 2016 that examined cost-effectiveness (or utility) of eHealth technologies. The reporting quality of included studies was appraised using the Consolidated Health Economic Evaluation Reporting Standards statement.</p><p>Results</p><p>Eleven full text articles met the inclusion criteria representing public and private health care systems. eHealth technologies evaluated by these studies includes computerized decision support system, a web-based physical activity intervention, internet-delivered cognitive behavioral therapy, telecare, and telehealth. Overall, the reporting quality of the studies included in the review was varied. Most studies demonstrated efficacy and cost-effectiveness of an intervention using a randomized control trial and statistical modeling, respectively. This review found limited information on the feasibility of adopting these technologies based on economic and organizational factors.</p><p>Conclusions</p><p>This review identified few economic evaluations of eHealth technologies that included older adults. The quality of the current evidence is limited and further research is warranted to clearly demonstrate the long-term cost-effectiveness of eHealth technologies from the health care system and societal perspectives.</p></div

CHEERS statement quality results.

<p>Items: (1) Title, (2) Abstract, (3) Background and Objectives, (4) Target population and subgroups, (5) Setting and Location, (6) Study perspective, (7) Comparators, (8) Time horizon, (9) Discount rate, (10) Choice of health outcomes, (11) Effectiveness, (12) Preference valuation, (13) Estimate resources and costs, (14) Currency, price date, conversion, (15) Choice of model, (16) Assumptions, (17) Analytical methods, (18) Study parameters, (19) Incremental costs and outcomes, (20) Uncertainty—single study or model based, (21) Heterogeneity, (22) Study findings/limitations/generalizability/current knowledge, (23) Source of funding, (24) Conflict of interest.</p

Quality assessment of included studies using CHEERS statement.

<p>Quality assessment of included studies using CHEERS statement.</p

Study selection and identification flowchart.

<p>Study selection and identification flowchart.</p

Characteristics of the included studies.

<p>Characteristics of the included studies.</p

Ratio profiles for all 19 covariates, together with their ratio profile scores

<p><b>Copyright information:</b></p><p>Taken from "Using machine learning algorithms to guide rehabilitation planning for home care clients"</p><p>http://www.biomedcentral.com/1472-6947/7/41</p><p>BMC Medical Informatics and Decision Making 2007;7():41-41.</p><p>Published online 20 Dec 2007</p><p>PMCID:PMC2235834.</p><p></p

Supplemental_File - Geographic Clustering of Admissions to Inpatient Psychiatry among Adults with Cognitive Disorders in Ontario, Canada: Does Distance to Hospital Matter?

<p>Supplemental_File for Geographic Clustering of Admissions to Inpatient Psychiatry among Adults with Cognitive Disorders in Ontario, Canada: Does Distance to Hospital Matter? by Christopher M. Perlman, Jane Law, Hui Luan, Sebastian Rios, Dallas Seitz, and Paul Stolee in The Canadian Journal of Psychiatry</p

Implementation of an interprofessional communication and collaboration intervention to improve care capacity for heart failure management in long-term care

<p>Heart failure affects up to 20% of nursing home residents and is associated with high morbidity, mortality, and transfers to acute care. A major barrier to heart failure management in nursing home settings is limited interprofessional communication. Guideline-based heart failure management programs in nursing homes can reduce hospitalisation rates, though sustainability is limited when interprofessional communication is not addressed. A pilot intervention, ‘Enhancing Knowledge and Interprofessional Care for Heart Failure’, was implemented on two units in two conveniently selected nursing homes to optimise interprofessional care processes amongst the care team. A core heart team was established, and participants received tailored education focused on heart failure management principles and communication processes, as well as weekly mentoring. Our previous work provided evidence for this intervention’s acceptability and implementation fidelity. This paper focuses on the preliminary impact of the intervention on staff heart failure knowledge, communication, and interprofessional collaboration. To determine the initial impact of the intervention on selected staff outcomes, we employed a qualitative design, using a social constructivist interpretive framework. Findings indicated a perceived increase in team engagement, interprofessional collaboration, communication, knowledge about heart failure, and improved clinical outcomes. Individual interviews with staff revealed innovative ways to enhance communication, supporting one another with knowledge and engagement in collaborative practices with residents and families. Engaging teams, through the establishment of core heart teams, was successful to develop interprofessional communication processes for heart failure management. Further steps to be undertaken include assessing the sustainability and effectiveness of this approach with a larger sample.</p