Chatbots in Healthcare: Improving Patient Engagement and Experience
The dominos fall when chatbots push patients from traditional clinical face-to-face practice to more complicated automated systems. Following Pasquale (2020), we can divide the use of algorithmic systems, such as chatbots, into two strands. First, there are those that use ML ‘to derive new knowledge from large datasets, such as improving diagnostic accuracy from scans and other images’. Second, ‘there are user-facing applications […] which interact with people in real-time’, providing advice and ‘instructions based on probabilities which the tool can derive and improve over time’ (p. 55).
Furthermore, there are work-related and ethical standards in different fields, which have been developed through centuries or longer. For example, as Pasquale argued (2020, p. 57), in medical fields, science has made medicine and practices more reliable, and ‘medical boards developed standards to protect patients from quacks and charlatans’. Thus, one should be cautious when providing and marketing applications such as chatbots to patients. The application should be in line with up-to-date medical regulations, ethical codes and research data. Through chatbots (and their technical functions), we can have only a very limited view of medical knowledge. The ‘rigid’ and formal systems of chatbots, even with the ML bend, are locked in certain a priori models of calculation.
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Hence, every healthcare services provider needs to think about ways of strengthening their digital environment, including chatbots. As the name implies, prescriptive chatbots are used to provide a therapeutic solution to a patient by learning about their needs and symptoms through a conversation. Such chatbot for medical diagnosis usually asks questions and encourages patients to share their symptoms in order to understand their current condition and what kind of treatment is recommended.
And they are also expected to have a market size of nearly 314.3 million by 2023 from USD 122.0 million by 2018. By incorporating more and more human simulation, they can guide the user from a point A to point B. They also allow the user to ask the same question over and over without feeling hesitant. As can be seen from this article, their pros outweigh the challenges significantly.
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This information can be used to identify potential health problems early and to provide patients with timely support. Chatbots can monitor patients with chronic diseases by collecting and analyzing data, such as blood pressure readings and glucose levels. Alerts can be generated for healthcare providers if the Chatbot detects abnormal data patterns, allowing timely intervention. AI chatbot services are available round the clock, providing instant responses to patient inquiries and concerns and ensuring continuous support outside regular working hours.
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