<p>This study aimed to identify and appraise published cost-effectiveness analyses of mobile device-based active remote monitoring technologies for long-term conditions. A systematic literature review (PROSPERO: CRD42023406364) identified studies from Medline and Embase (2008 until November 2024). Interventions required frequent patient-reported responses to questions about their condition on a mobile device (smartphone or tablet). Seven cost-effectiveness analyses were identified for six long-term conditions: rheumatoid arthritis; schizophrenia; older adults with complex conditions; cancer; multiple sclerosis; inflammatory bowel disease. Interventions facilitated early intervention to prevent condition worsening (<i>n</i> = 4); self-management (<i>n</i> = 2); and patient-initiated care (<i>n</i> = 1). Intervention costs were estimated by top-down costing (<i>n</i> = 2); bottom-up micro-costing (<i>n</i> = 3) and assumptions (<i>n</i> = 2). Mobile device-based active remote monitoring was cost-effective in six of the seven studies with a high degree of decision uncertainty. The results will help decision-makers, intervention developers and analysts to guide resource allocation, product development and study designs for future mobile device-based monitoring interventions, respectively.</p>

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Active remote monitoring of long-term conditions with mobile devices: a systematic review of cost-effectiveness analyses

  • Sean P. Gavan,
  • Katherine Payne,
  • William G. Dixon,
  • Sabine N. van der Veer,
  • Alexander C. T. Tam,
  • Nick Bansback

摘要

This study aimed to identify and appraise published cost-effectiveness analyses of mobile device-based active remote monitoring technologies for long-term conditions. A systematic literature review (PROSPERO: CRD42023406364) identified studies from Medline and Embase (2008 until November 2024). Interventions required frequent patient-reported responses to questions about their condition on a mobile device (smartphone or tablet). Seven cost-effectiveness analyses were identified for six long-term conditions: rheumatoid arthritis; schizophrenia; older adults with complex conditions; cancer; multiple sclerosis; inflammatory bowel disease. Interventions facilitated early intervention to prevent condition worsening (n = 4); self-management (n = 2); and patient-initiated care (n = 1). Intervention costs were estimated by top-down costing (n = 2); bottom-up micro-costing (n = 3) and assumptions (n = 2). Mobile device-based active remote monitoring was cost-effective in six of the seven studies with a high degree of decision uncertainty. The results will help decision-makers, intervention developers and analysts to guide resource allocation, product development and study designs for future mobile device-based monitoring interventions, respectively.