Artificial Intelligence

How Technology is Changing the Face of Healthcare

By Dave Smith, Associate VP of Virtual Medicine, UMass Memorial Health None of us will forget the chaos that COVID-19 unleashed on our daily lives and routines. For years to come, humanity will study the immeasurable impact on our physical ...
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Applying Intelligent Data Share Gateways for Evidence-Based Medicine and Spending

By Gary Zack, Director IT, Geisinger The objective for any business is to run efficient operations to reduce costs. The healthcare industry can benefit by using the same mindset to add value to existing traditional data sharing processes to enhance ...
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The Peril and Promise of mHealth

By Edmondo Robinson, CDO, Moffitt Cancer Center Mobile health, or “mHealth,” has received an increasing amount of attention recently in connection with approaches to combating the COVID pandemic. mHealth, as defined by the National Institutes of Health (NIH), is a ...
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Data-Driven Medication Utilization Management Tools to Reduce Drug Cost

By Sophia Humphreys, Director, System Pharmacy Clinical Services, Providence St. Joseph Health Covid-19 has financially devastated the healthcare industry, causing an estimated $323 billion in losses for 2020, according to the American Hospital Association. Rising drug costs are a key ...
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The Next Generation of Decision Support Tools and Systems in Healthcare

By Ali Birjandi, VP of Performance Improvement, CHRISTUS Health In Performance Improvement, we are always on the hunt to find faster, better, and cheaper ways to produce goods and services. To this end, assessing and reengineering operations to optimize inputs ...
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Why Healthcare Executives (You!) Should Be Paying Attention to Artificial Intelligence (AI)?

By Sean D Mooney, Ph.D., FACMI, Chief Research Information Officer, UW Medicine The clinics and hospitals you lead accumulated large amounts of patient treatment data since the implementation of EHR systems. The promise of AI and data science in healthcare ...
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Bespoke EHR: Fixing Usability and Physician Burnout One Specialty at a Time

By GQ Zhang, VP & Chief Data Scientist, The University of Texas Health Science Center at Houston (UTHealth) Physician Burnout Physician or clinician burnout, perhaps an underestimated and unintended consequence of the 2009 HITECH Act, negatively impacts patient care, clinician ...
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Achieving your Data and Analytic Ambitions

By Casey Hossa, CIO, Cardinal Innovations Healthcare How do we achieve an organization’s data ambitions by bringing its data and analytics capabilities into alignment? Data and Analytics are often the top priority for nearly all CIOs that I speak with ...
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Adding App Dev Capabilities to Your Data & Analytics

By Alexander G. Izaguirre, Chief Data Officer & VP, NYC Health + Hospitals On May of 2019, I was appointed New York City Health and Hospitals’ (NYC H+H) chief data officer. My first order of business was to lead the ...
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How Big Data and AI are helping sift through data

By Karl Hightower, Chief Data Officer & SVP – Data Products and Services, Novant Health How do you use data to find long-term chronic health problems? Healthcare practitioners function in an event-based system with some discreet data points, but most ...
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Artificial Intelligence (AI) is a recent advancement in technology that uses intelligent machine learning (ML) algorithms and natural language processing (NLP) to make a machine think and act like a human, predict and respond to actions based on available data. Large amounts of data are getting generated every day in almost all industries. AI helps realize the value of scattered, unused, unattended data by comparing the data patterns (similarities and differences) and turning them into meaningful, valuable information. Basically, it supports humans by interpreting the data. Though AI finds its application in all the industries these days, its role in healthcare is crucial since it helps providers deliver the best care a patient needs. AI helps healthcare providers and payers by automating tedious manual processes, which requires minimum to no human intervention. From appointment scheduling using chatbots or Conversational AI, clinical documentation, and administrative workflow to disease diagnosis, treatment and prevention processes, image recognition, drug research, its applications produce error-free reports with minimal investment. AI-based or AI-assisted applications are widely being used in the healthcare industry.