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Ravit Ram Bar-Dea, Co-Founder & CEO

The physiological use of the term ‘blind-spot’ means an obscuration of the visual field or ‘punctum caecum’. It describes the inability for cells to detect light, and therefore for the eye not to see normally. We often use this terminology when it comes to driving a car, or self-awareness. But it is also very true with business clients, and especially healthcare patients.

We should be asking ourselves:

· Are we able to see our patients entirely?

· Where are our blind spots at the patient journey mapping?

· How can we map out the blind spots to be more effective and efficient during the process, and see each individual?

Well-Beat continuously lights the blind spot

Meet patient B.

Patient B. is a 55-year-old diabetic male. He visits the physician once a month, and purchases medication as prescribes. Unfortunately, when he goes home, Patient B. does not take his medication and sometimes does not show up to therapy. During the visits at the clinic Patient B. sits across the physician and nods in agreement, but nothing seems to change.

This is our blind spot – why isn’t Patient B. adhering to treatment?

Well-Beat removes the blind spot.

Well-Beat’s AI engine and machine learning algorithms learn the deep drivers, barriers, maturity (readiness for treatment), and persona behind each individual. Some of these are conscious, some unconscious. The data gathered is then used to guide caregivers as they help patients, by providing them with customizes communication tools: which messages should reach different patients? What should be sent? Under what tone, approach, and frequency?

From the data gathered by Well-Beat’s recommendation engine, we learn that Patient B. is afraid of the medication’s side effects. He never shared this information and it is therefore a fact unknown to the caregiver. Well-Beat learned his readiness for treatment is low.

By combining these elements along with ongoing real-time data, and evaluation using Well-Beat’s friendly recommendation toolbar, we can now help the caregiver. Well-Beat provides the caregiver suggestions on different types of layered communication, including adding a few more in-person appointments to speak about side effects. Well-Beat can also send digitally encouraging messages, that will help support Patient B.: “We are here with you, taking you step by step.”

In between appointments, in support of the conversations between the

patient and clinician, Well-Beat continues with high engagement - without no extra resources!

Although the messages are highly personalized, they are also automatic and lower the dependency on the provider. There is no need for extra healthcare resources. There is no need for extra healthcare resources.

Life is everchanging, and so are people.

Well-Beat’s learning process is adapting to the patient’s lives continuously. The system interprets incoming ongoing information through human and digital feedback, and the recommendation engine then determines the follow-up engagement and communication.

The blind spot is removed over and over, as the patient changes.

Contact me about removing blind spots from patient care

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