What Technology Is Required to Create a Chatbot for Patient Care?

Anastasia Morozova
Anastasia Morozova
Chief Operating Officer

New technologies change the way we experience healthcare services.

Patient care digital solutions, such as chatbots, cannot replace real doctors but can bring significant benefits to both healthcare providers/technology vendors and patients.

How can you build a patient care chatbot?

Patient care is a term meaning any interaction between healthcare providers and patients that is focused on curing or any other procedure aimed at improving patient’s physical or mental health.

Today patient care and healthcare services are increasingly delivered with the use of technology.

We have already talked about chatbot techniques for health and fitness brands. This article is going to address the inquiries of our customers who would like to create chatbot for patient care.

healthcare chatbots

What are the types of digital solutions that provide or facilitate patient care?

According to CB Insights, privately-held companies that develop digital health solutions have got about $7.2B of investments.

These organizations target various audiences: from physicians to athletes and insurers, they develop different solutions that facilitate or ever provide patient care.

  • Treatment Planning: Solutions that facilitate patient treatment planning.
  • Supply Management: Tools that help healthcare providers handle the logistics and delivery of medical supplies within their medical institution.
  • Diagnostics: Digital components that allow managing diagnostics equipment or consulting patient regarding their symptoms.
  • Communication: Tools that are aimed at facilitating communication between healthcare professionals and patients (for example, chatbots).
  • EMR/ Practice Management: Special solutions that replace, enhance, or improve traditional health record systems.
  • Surgery: Digital tools for surgeons (for example, Gauss Surgical, a blood loss monitoring system for an iPad).
  • Referrals: Special platforms aimed at helping physicians transfer patients to right healthcare professionals for further treatment.
  • Care Coordination: Patient engagement platforms that allow medical institutions to keep all parties involved in patient treatment coordinated and informed.
  • Patient Experience: Tools that help healthcare providers improve the patient experience.
  • Infection Control: Systems that ensure the proper hygiene (for example, Xenex, disinfection robots equipped with the ultraviolet light).
  • Hospitalization: Tools created for patient intake optimization within medical organizations.
  • Hospital Navigation: Digital tools that help patients navigate within medical buildings.
  • Medication inventory software: Solutions that allow healthcare organizations to efficiently manage their inventory, deliver medication to patients, verify prescriptions.
  • Patient Monitoring: Monitoring status tools for remote or bedside patient.
  • Radiology: Image analysis and visualization software that help physicians make a diagnosis.
Chatbots for healthcare

What are the downsides of existing solutions for patient care?

Despite all benefits of existing digital solutions for patient care, they also have a set of common challenges which technology vendors should take care of.

Let’s consider the most significant downsides in detail.

Complexity

According to a survey by McKinsey, more than 75% of people are ready to use digital healthcare solutions, as long as those solutions meet their requirements and have a convenient level of quality.

However, according to a study by the School of Pharmacy and Chemistry, Kingston University in London, one of the barriers to adoption of mHealth tools is patients’ age and their resistance to new technologies.

The school conducted a study where they offered respondents to use a particular web-based tool. The results showed that the elderliness had turned out to be the only reason why some patients declined using it. Although, in a long-term perspective, the oldness will stop being a problem since “future users” already use digital solutions.

Security

The increasing demand for healthcare services outside medical institutions caused a tremendous growth in mobile patient care.

According to Statista, the worldwide mobile health market will be worth $58.8 billion by 2020 compared to $19.19B in 2016.

However, the Kingston University also determined another serious barrier to adoption of mHealth solutions – the significant lack of security when using mobile smart devices. Mobile healthcare software developers need to ensure that health data is stored safely in their applications.

Lack of personalized approach

According to HealthTap’s press release, over a billion people annually browse the Internet in search of health-related information.

About ten million symptom-related search queries are annually entered on Google. Static content cannot ask follow-up questions, accurately estimate symptoms, or provide users with personalized medical recommendations.

Patients need more competent digital solutions that can provide accurate and personalized recommendations for every person.

What chatbot solutions are desired by consumers and physicians?

Health App Solutions

Imagine a young mother with a two-week-old baby. She isn’t quite sure what baby’s temperature is considered to be abnormal, how hot the water for a baby’s bath should be, or how often it is necessary to feed the baby. Google searches can confuse her and make her worry. Also, some websites can intentionally mislead her trying to make her purchase something. So the safest way to get the answers is to bother her physician.

But these questions don’t necessarily require a physician’s attention. Instant messaging health mobile applications bother physicians the same way phone calls do.

The proper solution, in this case, is a digital patient care chatbot always supported and continuously trained by physicians.

chatbot for healthcare

The examples of solutions that provide patient care through a conversational interface

Let’s consider some existing digital patient care solutions with conversational interfaces.

Ada

Ada is a mobile app that has a conversational interface intended to help users determine their symptoms and provide them with information on what disease this might be.

The healthcare app also can connect a physician to provide a remote text consultation. After asking a set of detailed questions, an artificial intelligence (AI)-powered app informs users about possible causes of their symptoms and can help them create a digital paper trail for a consultation with a physician.

Sensely

Sensely is an AI-powered healthcare app that helps physicians keep in touch with their patients to prevent readmissions. On the patient side, the app makes short “check-ins” by asking users about their health condition with a schedulable frequency.

The app has voice recognition features, so a user can either talk to the app or type. The information provided by a user is transmitted only to authorized health providers. The app sends reports that can include data from wearables or other devices patients use for health monitoring purposes.

Another significant characteristic of Sensely is that it talks to patients emphatically as if it cares about how a person feels.

Your.MD

Your.MD, an AI-powered mobile app licensed by the National Health Service (NHS), provides users with information about their health condition based on their answers, possible causes, and steps they should take to remedy their illness including visiting a doctor if needed.

By monitoring the correlations in the symptom patterns, Your.MD continuously learns and becomes more helpful to a patient.

chatbot for doctors screenshot

Babylon Health

Babylon Health mobile app allows patients to organize a video consultation with a real doctor. This app is currently under development, and it’s planned to have an AI component to help user pre-screen their health conditions before they assign a consultation with a doctor.

The mobile app will have a voice recognition feature to let users tell about their symptoms instead of typing.

MedWhat

MedWhat is a chatbot that is created to help both patients and physicians make diagnoses faster. A machine learning powered chatbot provides accurate answers to user questions regarding their health condition and possible causes.

Furthermore, MedWhat draws upon medical research and scientific papers to improve its medical expertise.

What is required to create a chatbot for patient care?

Let’s consider some useful features of patient care chatbots.

Information source integration

A patient care chatbot should be able to integrate with a hospital-based medical system to retrieve patient health information and provide personalized recommendations.

Medical records, prescription history, and clinical expertise of doctors will allow a chatbot to offer accurate information about the patient health condition and possible causes.

healthcare chatbot

Check it out: From DIY to Deep Learning: 5 Types of Chatbots and How Much Will It Cost to Develop Them

Natural language processing

To understand human-generated language, a chatbot should integrate with the native language processing (NLP) APIs.

Also, to follow the written text, an AI-powered chatbot with voice recognition will enable users to talk to a virtual assistant. It is especially useful for patients with specific health problems that make it uncomfortable to type.

Natural language generation

Natural language generation or simply NLG will make a chatbot talk like a real human being.

After having processed patient’s query with the NLP, a chatbot would generate additional questions, possible causes of user’s symptoms, or provide health recommendations in the form of enhanced and logical sentences as if it was a message from a real doctor.

This feature will significantly increase user engagement and encourage patients to use your clinic’s health services.

Image recognition

Image recognition will be a huge advantage of an AI-powered chatbot.

Enabling a virtual assistant to recognize some visible or body deviations will be a tremendous step further in a virtual patient consultation.

chatbot-for-health

Sentiment analysis

With virtual assistants being “conversational” and with patients not always aware of being talking to a robot, users are more likely to share their feelings and expectations in messages.

Therefore, privately-held clinics and hospitals can collect feedback from their patients, normalize and aggregate received data to improve the level of their services.

IoT integrations

Patients with specific health problems may use some wearable medical devices that help healthcare professional monitor patient’s health status.

By enabling a chatbot to connect to these wearables through the Internet connection, a virtual assistant will be able to provide a way more accurate recommendations or initiate an emergency communication with a real doctor.

Full compliance with all healthcare standards and regulations

In the case where a chatbot deals with a personal health information (PHI), processes or transmits it to authorized parties, this virtual assistant has to meet all healthcare regulation requirements, such as the Health Insurance Portability and Accountability Act (HIPAA).

All transmitted data should be encrypted and reliably protected from any potential breaches to prevent PHI disclosures.

With rising costs of health insurance, going to see a doctor for every little health concern can be problematic.

AI chatbot application provides answers to your health questions and concerns so you can get the help you need when you need it, and can hopefully cut down on costs.

Patient care chatbots also help medical professionals provide their services faster while saving their time and financial resources.

Jasoren has deep expertise in developing AI-powered chatbots for various industries including healthcare.

With our experience and qualified developers, you will be able to create a compelling digital patient care solution.

To learn more about the development process in our company, read our article here.

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