US-based digital patient engagement company CipherHealth has announced a strategic collaboration with Google Cloud to integrate advanced artificial intelligence (AI) technologies into its operations and patient care efforts.
CipherHealth will leverage Google Cloud's Vertex AI platform to develop, train, deploy, and manage AI and machine learning models.
These solutions are claimed to accelerate issue resolution, improve patient experiences, enhance automation, and facilitate two-way communication.
CipherHealth is already using natural language processing for sentiment analysis to enhance patient interactions.
With Google Cloud's Vertex AI, it will have a comprehensive approach to machine learning, using secure and interoperable data.
This enables its data science team to create and integrate machine learning models tailored to various data types, including natural language, voice, vision, and tabular data.
The initiative will be implemented on CipherHealth's HiTrust-certified Evolve Platform.
CipherHealth product senior vice-president Suzie Sfarra said: “Through this doubling down on AI innovation, we're getting closer to our goal of realising a future where human-centric healthcare combines with cutting-edge technology and data-driven intelligence to reshape the healthcare experience.
“We plan to address some of the biggest engagement challenges facing hospitals and healthcare systems.
“We will leverage predictive models to anticipate patient needs and efficiently prioritise patients for rounding, utilise machine learning to target populations at risk by intelligently learning and implementing the best outreach strategies, and optimise interactions everywhere along the care continuum to improve patient outcomes, staff satisfaction, and revenue generation.”
With this partnership, CipherHealth aims to establish personalised care pathways for patients.
This will be done using AI models that engage with patients, analyse their inputs, and provide timely insights to healthcare professionals, ultimately improving the patient experience.
