Exploring Healthcare's Electronic Health Record Optimization Further: Artificial Intelligence Adoption
Ditching the paper trail is the new norm! Over a decade ago, the US government pushed for healthcare organizations to adopt electronic health record (EHR) systems through the Health Information Technology for Economic and Clinical Health Act. Now, fueled by artificial intelligence (AI) and machine learning, these digital tools are being optimized to improve clinical workflows, reduce burnout, and uplift care quality.
Christopher Kunney, a health IT strategist, thinks that there's an "energetic wave" of AI-powered optimizations around EHRs. Healthcare providers are realizing that these digital systems can enhance efficiencies, alleviate burnout, and boost patient care.
One essential aspect of clinical workflows is documentation. With AI stepping up, healthcare professionals can look forward to better support and real-time clinical note-taking, thanks to natural language processing capabilities integrated with EHRs. Moreover, machine learning can analyze EHR data to aid health systems in precision medicine, population disease prediction, and streamlined operations.
Yet, despite the digital shift, clinicians don't seem to be excited about it. Dr. Vinay Vaidya, senior vice president and chief medical information officer at Phoenix Children's, notes that though the EHR isn't a loveable companion, it's "just a tool."
Phoenix Children's Combing AI, Data, and EHRs
Phoenix Children's, a prominent pediatric organization, has gone through EHR evolution by integrating more specialties like pulmonology and cardiology into a comprehensive system. Using AI, machine learning, and a data warehouse, the health system turns data from EHRs into valuable insights for clinical workflows, research, and patient care.
AI has been instrumental in predicting health issues, such as malnutrition in children. When malnutrition risk is identified, automatic orders for dietitians and nutritionists to assess the patient are generated without delay. This proactive approach streamlines care and ensures prompt attention for potential malnutrition cases.
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On the other side of the country, Ozarks Healthcare, based in West Plains, Mo., is transforming its EHR systems after transitioning from paper records. Chief Medical Information Officer Dr. Priscilla A. Frase emphasizes that while the EHR journey is far from over, it's crucial to focus on optimizing workflows for providers and staff.
Integrating ambient scribe documentation tools and AI-powered chart summarization, she strives to eliminate redundancies and streamline documentation tasks for both herself and other clinicians.
St. Mary's Healthcare Embraces AI Voice Assistant in EHR Integration
Small healthcare systems like St. Mary's Healthcare are implementing AI-powered documentation tools to foster patient-doctor communication during visits. These tools listen, transcribe, and generate notes in real-time. While manual editing is still required, deeper integration of these tools in the newest version of their EHR platforms will streamline the process.
Healthcare organizations everywhere are becoming savvy about EHR optimizations, whether it's enhancing predictive analytics, improving clinical decision support, or developing AI-powered voice assistants. As technology advances and healthcare embrace progress, striking the ideal balance between medical care and technology will remain a top priority.
Healthcare organizations, such as Phoenix Children's, are leveraging artificial intelligence (AI) and machine learning to transform their EHR systems, turning data into valuable insights for enhancing clinical workflows, research, and patient care. For instance, AI can predict health issues like malnutrition in children, generating automatic orders for assessments by dietitians and nutritionists.
On the other hand, small healthcare systems like St. Mary's Healthcare are integrating AI-powered voice assistants into their EHR platforms to streamline patient-doctor communication during visits, demonstrating the growing emphasis on technology in healthcare. This integration is part of a broader trend of EHR optimizations aimed at improving predictive analytics, clinical decision support, and overall balance between medical care and technology advancements.
