Title: The policy environment of remote patient monitoring: evaluating stakeholders' views

Authors: Rotem Dvir; Carol Goldsmith; Ian Seavey; Arnold Vedlitz; Julie Hammett; Samuel Bonet; Arjun Rao; Karim Zahed; Farzan Sasangohar

Addresses: Institute for Science, Technology and Public Policy (ISTPP), The Bush School of Government and Public Service, Texas A&M University, 77843-4220, USA ' Institute for Science, Technology and Public Policy (ISTPP), The Bush School of Government and Public Service, Texas A&M University, 77843-4220, USA ' Institute for Science, Technology and Public Policy (ISTPP), The Bush School of Government and Public Service, Texas A&M University, 77843-4220, USA ' Institute for Science, Technology and Public Policy (ISTPP), The Bush School of Government and Public Service, Texas A&M University, 77843-4220, USA ' Department of Industrial and Systems Engineering, Texas A&M University, 77843-3131, USA ' Department of Industrial and Systems Engineering, Texas A&M University, 77843-3131, USA ' Department of Industrial and Systems Engineering, Texas A&M University, 77843-3131, USA ' Department of Industrial and Systems Engineering, Texas A&M University, 77843-3131, USA ' Department of Industrial and Systems Engineering, Texas A&M University, 77843-3131, USA

Abstract: Technological innovations in healthcare are becoming more common and offer many benefits. Trust is a central for individuals' views about the efficacy and adoption of technological solutions to improve healthcare. In this study, we explore remote patient monitoring (RPM) devices and how trust in managing institutions and the technology shapes acceptance and adoption for improved healthcare. Data are collected from professional stakeholders (n = 198), managers in public and private organisations who are responsible for administrating RPM devices into the US medical system. We implement multiple imputation to correct for missing data and regression models for analysis. Results show that both dimensions of trust (institutional and technological) are strong predictors of attitudes about different public policy options. We also find that costs affect views of proposed policies. Our findings expand existing knowledge by illustrating the need to consider trust in institutions when designing public healthcare policies that involve innovative technologies like RPM devices.

Keywords: RPM; remote patient monitoring; technology innovations; healthcare policy; research methodology; professional stakeholders; institutional trust; technology trust; regression models; multiple imputation; public policy.

DOI: 10.1504/IJHTM.2023.132455

International Journal of Healthcare Technology and Management, 2023 Vol.20 No.3, pp.249 - 275

Received: 02 Jan 2022
Accepted: 21 Mar 2023
Published online: 20 Jul 2023 *

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