Revolutionizing Healthcare with Gen-AI: A case study

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In the ever-evolving landscape of healthcare, the integration of artificial intelligence (AI) is ushering in a new era of data-driven decision-making. At Novel Teams, we’re at the forefront of this revolution, harnessing the power of Generative AI to transform businesses across various industries, with a particular focus on healthcare.

One of our most impactful endeavors has been our partnership with a healthcare client based in Kenya. Their mission to provide high-quality, patient-centered care aligns perfectly with our vision to leverage AI for positive change. One prevalent concern in the region, particularly among women, is maternal health. Take Sarah, for example, a 45-year-old pregnant woman from Nairobi facing the complexities of pregnancy during menopause and hypertension.

Before the implementation of Gen-AI, healthcare in the region faced significant challenges. Limited medical expertise due to a shortage of doctors, coupled with inadequate training for medical officers, led to inconsistent decision-making and compromised patient care. Resource constraints further hindered effective patient management, raising safety concerns, especially in high-risk scenarios. Communication barriers exacerbated these issues, making it difficult for patients to understand and adhere to treatment plans.

However, with the introduction of Gen-AI, we aimed to address these challenges head-on. By equipping medical officers with prompt builders serving as triage personnel and virtual assistants, we provided them with invaluable support in patient care.

These prompt builders guide medical officers in collecting patient demographic details and formulating treatment plans based on evidence-based practices. For Sarah, this meant a structured approach to her complex pregnancy, considering factors like the duration and severity of her hypertension, previous complications, and recent symptoms changes.

Here’s how our AI-driven approach unfolded:

  • Triage Questions: Using the prompt builders, medical officers proposed additional questions tailored to Sarah’s condition, gathering crucial information to inform decision-making.
  • Clinical Decision: With a focus on patient safety, medical officers outlined physical examination components and key findings to monitor and assess Sarah’s well-being, identifying potential complications.
  • Clinical Decision Post Lab Work: Based on symptoms and medical history, medical officers identified likely diagnoses, prioritizing primary concerns and critical conditions requiring immediate attention.
  • AI Bot Assistance: Additionally, the AI bot flagged harmful drug interactions, provided clinical alarms to prevent medical hazards, and offered reminders about necessary investigations or vaccinations.

This structured approach empowered clinical officers to make informed decisions, enhancing their skills and ultimately improving patient outcomes. By prioritizing evidence-based practice and personalized care, we ensured that Sarah and others like her received the attention and treatment they deserved.

At Novel Teams, our commitment to leveraging AI for real-world impact drives us forward. I extend my heartfelt thanks to our dedicated team for their continuous research and innovation, putting AI at the forefront of healthcare and making a tangible difference in people’s lives. Together, we’re shaping a healthier, brighter future.

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