VIDEO GROUP CONSULTATIONS IN GENERAL PRACTICE: TOGETHER 2 EARLY ECONOMIC EVALUATION
Author(s)
Michele Siciliano, MSc1, Luis Beltran Galindo, PhD1, Sara Shashaa, MSc2, Vijay Singh Gc, MPH, PhD1, Susie Foster, MBChB3, Sarah Alderson, PhD4, Chrysanthi Papoutsi, PhD2, Cynthia Iglesias, PhD1.
1University of York, York, United Kingdom, 2University of Oxford, Oxford, United Kingdom, 3Snaith & Rawcliffe Medical Group, Snaith, United Kingdom, 4Oaklands Health Centre, Huddersfield, United Kingdom.
1University of York, York, United Kingdom, 2University of Oxford, Oxford, United Kingdom, 3Snaith & Rawcliffe Medical Group, Snaith, United Kingdom, 4Oaklands Health Centre, Huddersfield, United Kingdom.
OBJECTIVES: Complex digital-based interventions (CDBIs) such as video group consultations (VGCs), are promoted to optimise resource use. The promise associated with these interventions requires robust demonstration. This study explored the feasibility of using early economic evaluation (EEE) methods to inform the design and conduct of a future definitive cost-effectiveness study of VGCs for peri- and post-menopause consultations (PPMC) in English general practice.
METHODS: We developed a decision tree model comparing, from the perspective of the NHS and Personal Social Services, two different models of healthcare provision for PPMC: one including VGC (Model A) and one without VGC (Model B). Input parameters were either sourced from the literature or collected using bespoke data collection tools. These were used to capture resource use from the study sites, and health-related quality of life and PPMC satisfaction from study participants.
RESULTS: EEE methods successfully captured the complexities associated with VGCs in general practice, illustrating the feasibility of this approach for evaluating CDBIs. Preliminary results suggest Model A has the potential to be cost-saving compared to Model B, with PPMC duration emerging as the key cost driver. However, the Probabilistic Sensitivity Analysis indicated substantial uncertainty associated with the preliminary findings. Value of Information analysis suggested it may be worthwhile to conduct a definitive study to assess the value for money of models of provision A vs B for the delivery of PPMC in primary care. The EEE framework provided a systematic approach to identifying data gaps and quantifying uncertainty to guide future research.
CONCLUSIONS: It is feasible to use EEE methods to rigorously explore the value for money of CDBIs such as VGCs. Early definition of the decision problem and a robust assessment of potential cost-effectiveness are essential to inform funding decisions and support the efficient allocation of scarce resources in general practice.
METHODS: We developed a decision tree model comparing, from the perspective of the NHS and Personal Social Services, two different models of healthcare provision for PPMC: one including VGC (Model A) and one without VGC (Model B). Input parameters were either sourced from the literature or collected using bespoke data collection tools. These were used to capture resource use from the study sites, and health-related quality of life and PPMC satisfaction from study participants.
RESULTS: EEE methods successfully captured the complexities associated with VGCs in general practice, illustrating the feasibility of this approach for evaluating CDBIs. Preliminary results suggest Model A has the potential to be cost-saving compared to Model B, with PPMC duration emerging as the key cost driver. However, the Probabilistic Sensitivity Analysis indicated substantial uncertainty associated with the preliminary findings. Value of Information analysis suggested it may be worthwhile to conduct a definitive study to assess the value for money of models of provision A vs B for the delivery of PPMC in primary care. The EEE framework provided a systematic approach to identifying data gaps and quantifying uncertainty to guide future research.
CONCLUSIONS: It is feasible to use EEE methods to rigorously explore the value for money of CDBIs such as VGCs. Early definition of the decision problem and a robust assessment of potential cost-effectiveness are essential to inform funding decisions and support the efficient allocation of scarce resources in general practice.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE610
Topic
Economic Evaluation, Health Service Delivery & Process of Care, Methodological & Statistical Research
Disease
No Additional Disease & Conditions/Specialized Treatment Areas