The healthcare cloud platform from Microsoft has recently expanded its artificial intelligence capabilities, indicating a change that has the potential to reinvent patient care and optimize industry processes.
The internet giant’s action coincides with healthcare facilities’ struggles to lower expenses and enhance service delivery. According to specialists in the field, this digital shift has the potential to reduce medical errors and facilitate the delivery of data-driven healthcare.
Hamed Akbari, assistant professor of bioengineering at Santa Clara University, told PYMNTS that artificial intelligence (AI) can reduce the administrative strain on healthcare professionals by automating regular tasks like appointment scheduling, patient registration, and billing processes.
Simplifying Administrative Work
Microsoft presented AI-powered healthcare solutions to enhance data integration, optimize operations, and improve patient outcomes in the medical industry. The new products include unified data management systems, customized Copilot agents for a range of healthcare tasks, and AI models for analyzing diverse medical data.
These developments go beyond simple automation. Advanced tools can help aggregate, structure, and synthesize information from electronic medical records (EMRs) and health information networks, enabling quick, accessible insights without time-consuming manual data entry or retrieval, according to Mika Newton, CEO of xCures, an AI-assisted medical records platform, who spoke with PYMNTS.
This might free up more time for healthcare professionals to spend with patients rather than mired in paperwork. Even routine questions could be helped by AI, according to Sara Mathew, Associate Director of Research & Operations Administration at Weill Cornell Medicine, freeing up staff to handle more urgent patient requirements.
These adjustments could have a significant effect. According to Akbari, AI-powered chatbots can efficiently handle patient enquiries, freeing up staff members’ time for more important patient care duties. AI systems can also help with the management of electronic health records (EHRs), protecting patient privacy for those who might feel uncomfortable sharing their information with others, and improving data accuracy.
Newton went on to say that AI can help with the lengthy and labor-intensive preauthorization procedure that hospital administrative staff members handle. AI can help hospitals and insurers by automating and optimizing this workflow, which lowers the chance of delays and cancellations of procedures or surgeries.
Improving My Diagnostic Skills
Beyond just improving administrative efficiency, AI has a significant impact on healthcare. Newton said that enormous volumes of medical data can be analyzed by AI-assisted diagnostic tools, which can then be used to spot patterns that would otherwise be missed and help medical practitioners make well-informed therapeutic judgments.
Mathew said, “This technology has the potential to improve health outcomes for underserved populations by enabling earlier disease detection and data stratification by factors like race, gender, age, and ZIP Code.”
Treatment strategies that are more effective and individualized may result from this data integration. According to Newton, “the use of AI to summarize and contextualize medical data enables clinicians to focus on evidence-based, patient-specific personalized treatment plans, leading to better care outcomes and, in many cases, a quicker path to recovery.”
With this data, hospitals and healthcare systems may prioritize underprivileged communities for screenings and interventions, ensuring that at-risk groups are recognized and treated more rapidly, according to Mathew, who sees an opportunity to address healthcare inequities. AI can therefore aid in lowering obstacles to care, enhancing accessibility in historically underserved neighborhoods, and promoting more equitable health outcomes across the country.
It’s difficult to incorporate AI into healthcare. Experts emphasize the importance of strong data protection measures, with privacy concerns ranking highest on the list.
Newton added that, similar to any other healthcare data system, AI-powered platforms must be protected to ensure patient confidentiality and that safeguards are required to prevent data breaches or misuse of sensitive health information. Protecting this data while ensuring it is de-identified and used responsibly is crucial.
Additional complexity were highlighted by Akbari, who stated, “AI algorithms run the risk of bias, which could lead to disparities in treatment outcomes across different demographic groups.” “The use of patient data for AI model training requires strong security measures to protect sensitive data and guarantee adherence to privacy laws, like HIPAA,” he continued.
There are a lot of possible advantages. According to Newton, AI could facilitate the creation of a more coherent treatment plan by “integrating notes from various members of the care team.” In order to improve continuity of care, he continues, AI may “process discharge summaries, simplify post-discharge instructions, and create reminders for follow-up appointments.”
