Enhancing Service Operator Efficiency in HealthTech
Our client, a leading health tech company, specializes in providing innovative healthcare solutions that integrate with the patient’s lifestyle. They maintain an extensive library of educational videos spanning various health topics, aiming to assist patients with their medical conditions, treatments, and overall well-being
By harnessing video metadata and Natural Language Processing (NLP) technologies, we enabled operators to efficiently offer video content recommendations, addressing the challenge of non-discoverability of videos through text.
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Technologies: BERT, Python, GCP, Slack
Challenge
Digital health provider wants to provide content recommendations fast to patients based on their inquiry. However, for the operators, it is not straightforward to search for this kind of content, especially video one
The client's patient service operators encountered several challenges when recommending video content to patients:
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Information Silos: The videos in the library were not easily discoverable through text searches.
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Operator Burden: Operators were burdened with the manual task of matching patients with relevant video content, often relying on generic or non-specific information provided by patients.
Solution
Our comprehensive solution focused on harnessing video metadata and NLP technologies to empower patient service operators:
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Video Metadata Analysis: We developed advanced video metadata analysis tools to extract meaningful information from each video, including titles, descriptions, tags, and durations. This allowed for categorization based on medical specialties, treatment types, and other relevant criteria.
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Natural Language Processing (NLP): Utilizing NLP models, we created a system capable of comprehending and analyzing patient queries and medical records. This system extracted key terms, topics, and context to bridge the gap between patient needs and video content.
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Recommendation Facilitation: Rather than automated recommendations, our solution focused on aiding operators. We developed a user-friendly interface that displayed relevant video metadata alongside patient queries, streamlining the operator's decision-making process.
Result
The implementation of our solution yielded significant results for our client:
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Enhanced Operator Efficiency: Patient service operators could now make more informed video content recommendations efficiently, significantly reducing the time spent on manual searches.
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Personalization Empowerment: Operators were empowered to provide highly personalized video recommendations based on patients' queries resulting in improved patient engagement and understanding.
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Heightened Patient Satisfaction: Patients reported increased satisfaction levels with the personalized video content provided, leading to improved patient outcomes.
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Informed Decision-Making: The client gained valuable insights into operator decisions, patient preferences, and the demand for specific video content, allowing them to fine-tune their healthcare offerings.