Bridging Care Gaps: AI Solutions in Healthcare
Automated clinical decision support tools powered by machine learning are reshaping how healthcare providers identify and prevent diagnostic gaps
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Key takeaways
Automated clinical decision support tools powered by machine learning are reshaping how healthcare providers identify and prevent diagnostic gaps
How can AI solutions in healthcare transform patient care by enhancing clinical decision-making and reducing diagnostic errors? Dr. Arpita Hazra, a Clinical Patient Data Safety Specialist, offers compelling insight into integrating artificial intelligence and machine learning models with Electronic Medical Records (EMR) to bridge care gaps in fast-paced healthcare environments.
"Artificial intelligence and machine learning models can be used to create clinical decision-making support tools that can integrate into the EMR, which can help fill care gaps in busy healthcare settings. This will reduce the incidence of incorrect diagnosis, reduce the delay in diagnosis and delay in treatment for patients, help the providers in ordering the correct diagnostic tests, and help escalate the patient's care when needed," Hazra said.
Artificial intelligence and machine learning models can be used to create clinical decision-making support tools that can integrate into the EMR, which can help fill care gaps in busy healthcare settings.
— Dr. Arpita Hazra, Clinical Patient Data Safety Specialist
About the author
Arpita Hazra, a dedicated physician, combines her medical expertise with a passion for building AI and machine learning models aimed at enhancing patient outcomes. Her boundless energy and unwavering motivation are evident in her multifaceted career. With a profound understanding of clinical data management, health education, public health, and program planning, Arpita has excelled in various domains including project management, patient safety, and risk analysis. Her versatility extends to healthcare consulting and clinical risk consulting, where she brings a wealth of qualitative and quantitative research experience to the table. Arpita is a force in healthcare business development, equipped with technical skills in Power BI, Azure Databricks, SQL, and SAS programming. Her expertise also encompasses healthcare data model architecture development and user acceptance testing (UAT), as well as medical writing. In essence, Arpita Hazra is a well-rounded professional with a mission to bridge medicine and technology for the betterment of patient care and outcomes.
