490 results found | searching for "hospitals"
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SMART on FHIR – A Practical Guide to Implementation, Best Practices, and Business Value https://emorphis.health/blogs/smart-on-fhir-guide/ The momentum behind SMART on FHIR is undeniable. According to the U.S. Office of the National Coordinator for Health IT (ONC), nearly 90% of non-federal acute care hospitals now use APIs to enable patient access to their health data through apps, and more than two-thirds have adopted FHIR APIs specifically. Adoption is also rising in patient-facing solutions; hospitals enabling app-based access grew from 68% in 2021 to nearly 80% in 2023-24, while FHIR-based access increased from 56% to almost 70% in the same period. On the developer side, over half of health IT vendors already combine FHIR with OAuth 2.0 to build secure healthcare apps.
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Top Skills to Look for in Outsourced Healthcare Software Developers https://medium.com/@Larisa10/top-skills-to-look-for-in-outsourced-healthcare-software-developers-965682a59767 The healthcare industry is experiencing a rapid digital transformation. Hospitals, clinics, and healthcare providers are increasingly adopting telehealth platforms, electronic health records (EHR), patient engagement apps, and AI-powered analytics. To deliver these solutions efficiently, many organizations are turning to outsourced software developers.
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How to Develop SaaS for Medical Devices? Key Factors To Look Out – Costs, Compliance, and Scalable Solutions https://emorphis.health/blogs/develop-saas-for-medical-devices/ Healthcare technology is undergoing a massive shift, and one of the strongest trends is the adoption of Software-as-a-Service (SaaS) models in medical devices. Companies that develop SaaS for medical devices are not only improving clinical workflows but also creating scalable, cloud-based platforms that can integrate with hospitals, diagnostic tools, and patient monitoring systems.
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The Economics of AI in Healthcare, ROI Models That Work https://emorphis.health/blogs/economics-of-ai-in-healthcare-roi-models/ Many organizations have tested AI pilots, but few have developed a clear understanding of return on investment (ROI). Without a strong financial case, it is difficult for hospitals, payers, or life sciences companies to scale AI adoption. This is where the economics of AI in healthcare becomes a critical conversation.
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Why Healthcare Needs an Accelerative AI Framework (And Not Just AI Tools) https://medium.com/@Larisa10/why-healthcare-needs-an-accelerative-ai-framework-and-not-just-ai-tools-5a54a3df8efb The healthcare industry is undergoing a digital revolution, with Artificial Intelligence (AI) at the forefront. From predictive analytics to medical imaging and chatbots, AI tools are increasingly being adopted by hospitals, providers, and payers. Yet, despite the hype, many organizations find themselves struggling with fragmented implementations.
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How Our Accelerative AI Framework Puts You Ahead of Competition https://emorphis.health/blogs/ai-framework-for-healthcare/ Healthcare today faces unprecedented challenges. Hospitals, clinics, and healthtech companies are under pressure to deliver high-quality patient care, reduce operational costs, and comply with strict regulations. While AI has the potential to transform healthcare, many organizations struggle to adopt AI solutions effectively due to high complexity, integration hurdles, and scalability issues. This is where the Accelerative AI Framework from Emorphis comes in.
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Healthcare IT Trends 2025: The Unstoppable Shift You Can’t Afford to Ignore https://emorphis.health/blogs/healthcare-it-trends/ The healthcare IT trends 2025 showcase a future where technology is the driver of care delivery. From AI documentation and RPM to blockchain-secured data and virtual hospitals, the landscape is shifting fast. Healthcare leaders who adopt modern healthcare IT solutions, invest in digital health platforms, and partner with healthcare IT consulting experts will position themselves as industry leaders. Those who hesitate risk losing competitiveness, efficiency, and patient trust.
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5 AI-Driven Patient Care Use Cases That Every Hospital Should Adopt https://medium.com/@Larisa10/5-ai-driven-patient-care-use-cases-that-every-hospital-should-adopt-91d3741639d9 AI in patient care refers to using machine learning, natural language processing (NLP), and advanced analytics to support clinical decision-making, automate workflows, and personalize treatments. In the context of modern hospitals, AI serves as an intelligent layer over existing systems like EHRs, imaging platforms, and patient engagement tools.
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What Happens After a Hospital Discharge? How AI Agents Are Closing the Care Gaps https://community.nasscom.in/communities/application/what-happens-after-hospital-discharge-how-ai-agents-are-closing-care-gaps This vulnerable period is where there are gaps in communication, coordination, and monitoring surface. While hospitals implement discharge plans, their effectiveness heavily depends on patient behavior, caregiver support, and timely follow-ups. The burden shifts to the patient, often with minimal guidance. Even with digital health tools, most AI implementations today remain passive, offering insights rather than taking action.
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