Systematic Selection and Prioritization of Communication Channels in the Healthcare Sector Francisco Casaca and Andr´ e Vasconcelos INESC-ID, Instituto Superior T´ ecnico, Avenida Rovisco Pais 1, Lisbon, Portugal Keywords: Communication Channels, Multi-channel, Omni-channel, Chatbot, Seamless Experience, Healthcare. Abstract: Many industries are using multi-channel approaches to bring users and organizations closer. The services provided through these channels can be leveraged by using chatbots, allowing users to have simpler and more natural interactions. However, this entails designing architectures that make services available through mul- tiple channels, while making the users’ experiences coherent, as they switch between them. Media Richness Theory introduces a way to classify the richness of communication channels, resorting to objective factors, however it does not provide a systematic channel selection and prioritization process. To address these needs, this work proposes a systematic approach to select and prioritize communication channels based on six factors: feedback, multiple cues, personal focus, language variety, accessibility and cost. To validate this approach, the systematic process is applied to three use cases in the healthcare domain. 1 INTRODUCTION When interacting with organizations, users resort to a variety of communication channels. These include traditional channels such as face-to-face communica- tion and phone calls, as well as digital channels such as e-mail, web portals, mobile applications and video- conferences (Androutsopoulou et al., 2019). These channels are distinguished by their richness (the ca- pability of providing information with high levels of understanding), which depends on a variety of fac- tors: some of them are objective, such as rapidness of feedback, available modalities, accessibility and cost; whereas others are subjective to the experience of the user, such as familiarity with a particular channel or topic. In recent years, multi-channel and omni-channel approaches have been implemented in many indus- tries (Caroll and Guzm´ an, 2015), allowing consumers to choose from a variety of channels (according to their preferences) and providing a seamless experi- ence when switching between them. Furthermore, some of the communication tasks performed through the aforementioned digital channels have been auto- mated by using task-oriented dialog agents (or chat- bots), which can help users complete tasks using natu- ral language (Jurafsky and Martin, 2000). These sys- tems are simpler to use when compared to GUI ap- plications because they mimic human-human interac- tion. Chatbots have thus the ability to leverage organi- zations’ services by being available through multiple digital communication channels (Androutsopoulou et al., 2019). As a result, organizations can target a higher percentage of the population, by offering their services through channels that are more convenient, natural and easy to use. Healthcare is a domain that can benefit from multi-channel approaches (Laranjo et al., 2018). New channels can be easily integrated with the pre- established workflow, providing services to patients who would not, otherwise be able to access them (Morris et al., 2018). They can also reduce patient travel and allow more frequent follow-ups. 1.1 Context When offering more channels to users, there is one fundamental issue that arises. Since each channel has its own characteristics, not all of them can be applied in the same scenarios. For instance, for use cases in which communication depends on the vocal modality, a channel through which it is only possible to com- municate via text is not suitable. Therefore, it is im- portant to evaluate the suitability of channels regard- ing the desired communication tasks. Additionally, there is the preoccupation of evaluating which chan- nels should be prioritized. 1.2 Objectives The objectives of this work are thus the following: 668 Casaca, F. and Vasconcelos, A. Systematic Selection and Prioritization of Communication Channels in the Healthcare Sector. DOI: 10.5220/0010441706680676 In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 1, pages 668-676 ISBN: 978-989-758-509-8 Copyright c  2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved