Humans and Artificial Intelligence in Harmony for Healthcare

Leslie Pagel, Chief Evangelist Officer at Authenticx, discusses the potential of merging artificial intelligence with human engagement in healthcare.

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Published: September 7, 2023

leslie pagel

Leslie Pagel

Navigating healthcare can be a scary proposition. But by weaving together artificial intelligence (AI) and human interaction, healthcare organisations can achieve customer-centricity.

When humans work collaboratively with AI and are included in the machine learning (ML) loop, organisations can effectively hear the voice of the customer (VOC), elevate patient care, foster employee positivity and deliver a higher-quality customer experience.

Pairing AI with humans creates a win-win-win situation for employees, customers and the business.

AI needn’t be feared

AI conjures different images which can generate hope, fear, confusion or a mixture of all three — all valid emotions and part of the human experience.

When we leverage AI for its strengths — like its ability to process vast sums of unstructured information — applying it to challenges healthcare companies face today and using it to gain a deeper understanding of the patient experience, AI becomes a force for good.

It’s a tool that healthcare can use to understand the true patient journey and surface areas of friction and praise. In short, AI helps humans understand humans.

AI’s interactions with humans and technology

The goal of integrating AI into the patient listening activities shouldn’t be to replace humans with machines but instead to harness AI insights for elevating human decision-making. To use AI strategically, humans remain essential for training, alignment, analysis and delivering an exceptional customer experience.

To use AI strategically, humans remain essential for training, alignment, analysis and delivering an exceptional customer experience.

Leveraging AI for understanding the true patient journey requires algorithms and training data. The algorithms are generalised and publicly available. Training data differentiates the output of the AI models and is where companies must consider implicit bias and AI use cases. Data scientists can unintentionally introduce algorithmic biases by using more generalised training data that doesn’t represent an entire, specific industry or population.

By scrutinising training data for the healthcare industry, we can unlock the potential of unbiased and domain-specific applications. Training AI to work with humanlike thinking helps reduce adverse outcomes resulting from bias. Embracing impartiality in AI benefits patients (and customers).

Understanding humans – why healthcare needs industry specific AI

Healthcare conversations are unique and deeply personal. Regulations require the protection of patient identity and privacy.The language includes specialised medical, financial and pharmaceutical terminology.

The nuances of healthcare conversations coupled with the high stakes in healthcare, necessitate that healthcare leaders embrace industry-specific AI — where the training data comes from and is applied to healthcare.

Customer trust and loyalty take time to build and start with listening for purposes of understanding. Healthcare specific AI enables us to listen to healthcare conversations at scale.

Bringing AI to healthcare

When incorporated effectively, AI overcomes the human barriers of listening. It can consume and learn from vast amounts of conversational data otherwise left untapped.

When incorporated effectively, AI overcomes the human barriers of listening.

Healthcare organisations see value in AI for analysing conversations to identify the authentic voice of the customer and employee to gain actionable insights for:

  • Customer loyalty, resulting in increased retention and growth.
  • Associate coaching, leading to higher levels of retention and productivity.
  • Ongoing monitoring, giving healthcare organisations timely insights to changes happening in the industry (whether those changes are created by the business or by an external factor).

Companies have widely monitored sentiment for decades, often via net promoter score (NPS) and similar surveys, but it’s hard to gain deeper context. That’s where AI shines. It’s trained to listen to conversations, identify specific tones and emotions conveyed, and provide context for those calls at scale.

It can even obtain sentiment and emotion at a call’s beginning and end and compare the two — useful for determining whether an agent helped a customer, diffuse a situation or perhaps needs additional training.

Authenticity matters

Capturing a representative, diverse data sample increases the authenticity (and power) of unsolicited feedback. It allows for continuous refinement and enhances healthcare organisations’ abilities to understand the complexities of the humans they employ and serve.

AI collates and crunches the data. The human element uses those data-driven insights to make informed decisions — decisions that empower healthcare organisations to elevate the customer experience.

Tech innovation is powering strategic decision-making in the healthcare industry and enabling teams to listen at scale. As a result, it’s changing how we understand customer emotions and behaviours to drive positive business outcomes.

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