Healthcare providers collect a lot of patient information. This includes electronic health records (EHRs), lab results, imaging, insurance claims, and clinical notes. Before, it was hard to keep this data safe, store it well, and get access to it quickly. Different systems did not work well together. Cloud computing helps by storing and processing data in secure online platforms that can grow as needed.
With cloud services, healthcare organizations do not rely only on local servers. Patient data can be accessed by authorized users from different places. Cloud systems also follow rules like HIPAA to protect patient information. They can combine data from many sources – like EHRs, claims, and medical devices – to create a full picture of a patient’s health. This helps doctors make better decisions.
Research by healthcare IT experts such as Birlasoft shows that mixing EHR and claims data using cloud tools gives doctors better insights. This helps them get correct and timely information. For medical practice managers, this means the practice runs more smoothly. Both doctors and patients benefit from this improvement.
Making clinical decisions needs fast and accurate patient data. In the past, doctors used paper records or systems that did not share data well. This caused delays and made it hard to get all the information. Cloud computing with advanced data platforms is changing that.
A good example is Project Ronin, a system for cancer care that runs on Oracle Cloud Infrastructure (OCI). With cloud tech, doctors get patient data much faster. Project Ronin has cut the time to find data from 20 minutes to less than five. It also requires fewer clicks to see records. This lets doctors spend more time on patients instead of paperwork.
Cloud systems also support large data sharing using standards like HL7 FHIR (Fast Healthcare Interoperability Resources). Over 200 healthcare projects in the U.S. use FHIR now. It lets hospitals, labs, insurance companies, and others share data easily and quickly. This helps doctors get the right data when they need it, which improves diagnosis and treatment plans.
For owners and managers of medical practices, cloud computing offers many benefits. Cloud-based EHR systems improve how doctors work and keep data safe. For example, United Digestive uses AI in their cloud-based eClinicalWorks platform. This helps make daily work better and improves patient results.
Cloud tools help care teams avoid unnecessary hospital stays. They give doctors dashboards and insights about patients. These can show patient trends, risks, and when follow-up is needed. This helps doctors act before problems get worse.
Countries like France use Health Data Lake solutions on the cloud. These store and analyze large healthcare data sets. They help public health monitoring and work well for big health networks.
The healthcare IT market will reach about $570 billion by 2027. This shows how much cloud technology is growing. In the U.S., more healthcare systems will have tools that make clinical and admin tasks easier, reduce mistakes, and help patients stay involved in their care.
AI and workflow automation are important parts of cloud computing in healthcare. Together, they help improve clinical and administrative work.
AI systems can look at complex patient data faster than people. They find patterns and suggest care options based on evidence. Mercy Health uses generative AI to handle patient calls. This includes scheduling appointments and giving follow-up advice. It lowers the need for many phone calls, so staff can focus on patient care.
AI chatbots also help Mercy’s staff by quickly giving information about policies and HR questions. This makes office work faster.
Automation helps with notes and coding too. PatientSource’s Case Notes Module uses electronic notes instead of paper. Paper notes can have mistakes about 25% of the time. Electronic notes can reduce errors and speed up documentation. Tools that pull diagnostic codes (like ICD10 and Hierarchical Condition Categories) from notes also help billing and money management.
Cloud technology gives the power needed to run AI and automation on a large scale. Hosting AI apps in the cloud lets healthcare providers get faster updates, keep data safe, and have steady performance. This is important to keep clinical work going smoothly.
Mercy Health works with Microsoft to use cloud and AI together. Microsoft Azure OpenAI Service helps patients understand lab results in simple language. This helps patients talk better with their doctors and avoid confusion.
Mercy also uses AI to manage patient calls, schedule appointments, and give care advice in one call. This cuts down on repeated calls and makes scheduling easier. They also have smart dashboards that help care teams see what patients need. This might reduce hospital stays that can be avoided.
Across the U.S., many health systems are using cloud platforms not just for clinical decision support but also for telehealth. Cloud-based virtual care tools let doctors reach patients remotely. They also give access to full patient data, which helps keep care continuous and easier for patients and providers.
Cloud computing is becoming key for data management and clinical decision-making in healthcare across the United States. Using cloud with AI and automation helps solve problems like scattered data, slow access to info, and heavy admin work. For practice leaders and IT managers, investing in cloud systems that work well with others and training staff is important to improve patient care and how the practice runs.
Examples from national health systems and private practices show that cloud technology can help healthcare become faster, better, and more accurate. With good planning and use, U.S. medical practices can meet the changing needs of patient care in a digital world.
Microsoft and Mercy are collaborating to use generative AI and digital technologies to improve patient care and clinician efficiency, aiming to transform healthcare delivery.
Generative AI will assist patients in comprehending their lab results and facilitate informed discussions with providers by providing information in simple, conversational language.
AI will assist in handling patient calls for scheduling appointments and provide follow-up recommendations, minimizing the need for additional calls later.
A chatbot will help Mercy employees quickly find important information about policies and procedures, enabling them to focus more on patient care.
Mercy plans to explore over four dozen AI use cases and implement multiple new AI solutions by mid-next year to enhance patient care.
The Microsoft Azure Cloud helps centralize and securely organizes data, allowing Mercy to deliver insights that improve clinical decision-making and patient care.
AI will provide smart dashboards and better visibility into patient needs, helping reduce unnecessary hospital days and enhance operational efficiency.
The hackathon brought together teams from both organizations to co-develop and innovate generative AI use cases aimed at enhancing clinical experiences.
Mercy is recognized as one of the largest U.S. health systems, known for its excellent patient experience and integrated care across multiple states.
Microsoft aims to empower every organization by enabling digital transformation through intelligent cloud and edge technologies, including applications in healthcare.