Video or In-Clinic Consultation? Selection of Attributes as Preparation for a Discrete Choice Experiment Among Key Stakeholders.
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Video or In-Clinic Consultation? Selection of Attributes as Preparation for a Discrete Choice Experiment Among Key Stakeholders.
Patient. 2018 Jun 09;:
Authors: Chudner I, Goldfracht M, Goldblatt H, Drach-Zahavy A, Karkabi K
Abstract
INTRODUCTION: Video consultations (VCs) provide increased accessibility of primary care to remote areas and overall improved care for chronic patients. They also contribute to higher patient satisfaction and improved resource management. Despite these benefits, VC integration into the health system is complex and slow. Understanding the VC-related preferences of three key stakeholders-patients, primary care physicians (PCPs) and policy makers (PMs)-is crucial for achieving optimal implementation.
OBJECTIVE: The aim of this study was to select relevant attributes and levels for a discrete choice experiment (DCE) of stakeholders' choice-VC or traditional in-clinic consultation (I-CC) in primary care.
METHODS: Ten semi-structured focus group interviews and 24 semi-structured individual interviews were conducted. Data analysis was performed inductively, using a thematic content analysis method. An attribute-ranking exercise was then conducted based on the results gleaned from the interviews.
RESULTS: The most important attributes when choosing either VC or I-CC, for both patients and PMs, were: (1) time to next available appointment; (2) time in line before consultation; (3) relationship to PCP; and (4) quality of consultation. For PCPs, the most important attributes were: (1) time in line before consultation; (2) patient's self-management ability; (3) consultation purpose; (4) quality of consultation.
CONCLUSIONS: This qualitative study identified attributes and levels for a DCE quantitative stage among three key stakeholder groups. It adds to the literature of examples of developing DCE attributes, and to literature about the stakeholder benefits in the area of telemedicine in healthcare.
PMID: 29948961 [PubMed - as supplied by publisher]
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