Microsoft’s recent expansion The increase in artificial intelligence capabilities in healthcare cloud platforms signals a shift that could redefine patient care and streamline healthcare operations.
The tech giant’s move comes as hospitals and clinics struggle with ways to improve care delivery and reduce costs. Industry experts say this digital transformation can reduce medical errors and pave the way for data-driven healthcare.
“By automating routine functions such as appointment scheduling, patient registration and billing processes, AI can reduce the administrative burden for healthcare workers.” Hamed Akbariassistant professor of bioengineering at Santa Clara Universitytold PYMNTS.
Streamline administrative tasks
Microsoft revealed AI-powered healthcare solutions to streamline workflows, improve data integration and deliver better outcomes across the medical industry. The new offering includes AI models for analyzing various medical data and unified data management platforms And customizable Copilot agents for different healthcare tasks.
These improvements extend beyond basic automation. Mika NewtonCEO of xKurenan AI-enabled medical records platform, told PYMNTS that “Advanced tools can help aggregate, structure and synthesize information from electronic health records (EMRs) and health information networks, enabling fast, accessible insights without time-consuming manual data entry or retrieval . .”
For healthcare workers, this could mean spending less time on paperwork and more time with patients. Sara MathewAssociate Director Research & Operations Administration at Weill Cornell Medicinetold PYMNTS that AI could even help with routine questions, freeing up staff to meet more acute patient needs.
The impact of these changes can be significant. Akbari said: “AI-powered chatbots can effectively manage patient queries, freeing up staff to focus their time on more critical patient care responsibilities. Additionally, AI systems can help manage electronic health records (EHRs), improve data accuracy, and improve patient privacy for those who may not feel comfortable sharing their information with others .”
Newton added that AI can “address the labor-intensive and time-consuming pre-authorization process in hospitals, which is performed by administrative staff. By automating and streamlining this workflow, AI can reduce delays and the risk of cancellation of procedures or surgeries, benefiting both hospitals and insurers.”
Improving diagnostic capabilities
The impact of AI in healthcare extends beyond administrative efficiency. Newton said AI-enabled diagnostic tools can analyze large amounts of medical data, “identify patterns that would otherwise go unnoticed” and support healthcare professionals in making informed clinical decisions.
Mathew added that this technology could “enable earlier disease detection and stratification of data based on factors such as race, gender, age and zip code,” potentially improving health outcomes for underserved populations.
This integration of data could lead to more personalized and effective treatment plans. “Using AI to summarize and contextualize medical data allows physicians to focus on personalized treatment plans that are evidence-based and tailored to the patient’s unique needs, leading to better care outcomes and, in many cases , a faster path to recovery.” said Newton.
Mathew sees this as an opportunity to address healthcare disparities: “These data can help hospitals and healthcare systems prioritize underserved populations for screenings and interventions, ensuring that at-risk groups are identified and treated more quickly. As a result, AI can help reduce barriers to care, improve access in historically marginalized communities, and contribute to more equitable health outcomes across the country.”
Integrating AI into healthcare is a challenge. Privacy concerns top the list, with experts highlighting the need for robust data protection measures.
“Protecting this data while ensuring it is anonymized and used responsibly is essential,” Newton said, adding: “Like any other healthcare data system, AI-powered platforms must be protected to ensure patient confidentiality, and security measures are needed to prevent data breaches or misuse of sensitive health information.”
Akbari pointed out even more complexities: “There is a risk of bias in AI algorithms, which could lead to differences in treatment outcomes between different demographic groups.” He added: “Using patient data to train AI models requires robust safeguards to protect sensitive information and ensure compliance with privacy regulations such as HIPAA.”
The potential benefits are significant. said Newton that AI could help create a more coherent treatment plan by “integrating notes from different care team members.” He adds that AI can “process discharge summaries, simplify post-discharge instructions, and create reminders for follow-up appointments to improve continuity of care.”
On the diagnostic front, Akbari suggests that AI can detect conditions not visible to the human eye, which could lead to earlier interventions and better outcomes. He notes: “The application of machine learning algorithms to analyze extensive medical data sets can reveal patterns and insights that may not be immediately apparent to physicians.”
For patients, the successful implementation of AI in healthcare could mean more personalized care, faster diagnoses and better health outcomes. For healthcare providers, this could lead to reduced administrative burdens, more time for patient interaction and powerful new tools for clinical decision-making.
As Akbari puts it, the ultimate goal is clear: “These advances can help expand access to health care to underserved populations who may not have access to advanced medical services.” If achieved, this could be an important step towards more equitable and effective healthcare.
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