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The power of a health bot lies in patient administration

Learn how providers can conserve their resources by using healthcare bots for administrative duties such as appointment scheduling, billing and processing payments.

Over the past several years, many new technological innovations in the healthcare industry have come and gone,...

but only a handful of trends matured and achieved widespread adoption among healthcare organizations. Bots are another new development that is piquing the interest of healthcare organizations and attempting to become more than a fleeting trend.

Bots are intelligence systems that can interact with end users via text through websites, short message service and other means to provide a service to users. For a health bot to become an established part of healthcare workflows, it must be defined how the health bot can provide value to user organizations.

Intelligent bots leverage technologies such as artificial intelligence and natural language processing to offer a more natural interaction between humans and systems. These interactions can be with EHRs, lab systems and hospital registration or billing systems.

Large vendors such as Microsoft and IBM have promoted healthcare bots by introducing "bot as a service" platforms. Supported by the current maturity of artificial intelligence, cloud and computing power, a health bot can be used to help with many of the current challenges facing hospitals. The following is a list of several areas in which digital bots can fit and provide value within hospitals systems.

Appointment scheduling: When a bot is used within a scheduling system, it can reduce the complexity of scheduling appointments with a patient's caregiver. A health bot can process specific instructions from patients such as: "Please schedule an appointment with Dr. Smith in two weeks on a Tuesday morning before lunch." Using a bot in this scenario will provide faster appointment scheduling and require fewer human resources to answer incoming appointment calls. Patients that may be hesitant to use the appointment bots will likely be more comfortable once they learn the bots can interpret their text messages. Patients will be able to schedule a follow-up appointment by simply sending texts to their provider's bot.

Billing and payment processing: In recent years, many organizations have offered patients a 24/7 billing hotline to help process payments. Many of these systems are very limited in functionality and only assist with processing a payment. Billing and payment bots can transform the way individuals deal with any of their billing questions. Bots could be able to process payments over text messaging, answer any questions about an account balance and provide additional information regarding services billed to a patient. This will improve the experience of patients in understanding what services they are billed for and hasten the payment process.

Clinical records: Healthcare bots can also provide value in the clinical arena. There are many patients today who are interacting with their chart using Web portals. These individuals are likely to use an interactive clinical bot. A health bot can be programmed to find educational material for patients with a certain condition or present patients with a list of common side effects associated with a medication they've been prescribed and if there is anything that can counteract those side effects.

The full capabilities and amount of use cases for healthcare bots will continue to expand. As healthcare artificial intelligence and natural language processing advance, so too will bots become smarter and more connected. Some immediate results of deploying bots in healthcare are that bots can reduce delays associated with patients being on hold while scheduling appointments on the phone and reduce costs stemming from paying staff to schedule appointments. While the thought of healthcare bots is promising, it is still a new technology and could be the subject of regulations and other challenges on its way to achieving widespread adoption.

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This was last published in May 2016

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