by Dr. Barry Chaiken
As healthcare information technology professionals, we always look for innovative ways to improve patient care and operational efficiency. One such innovation that has been making waves in the healthcare sector is computer vision, a field of artificial intelligence (AI) that trains computers to interpret and understand the visual world.
Computer vision has the potential to revolutionize many aspects of healthcare, from patient monitoring to administrative tasks and even diagnostics. By automating routine tasks, computer vision can help increase patient throughput, allowing healthcare professionals to focus more on patient care.
Improved Patient Monitoring
Computer vision plays a crucial role in patient monitoring. For instance, computer vision algorithms can monitor patients in intensive care units (ICUs) and alert healthcare professionals if they detect any abnormalities in their condition. This surveillance facilitates early interventions, prevents adverse events, and improves patient outcomes.
Streamlined Administrative Tasks
Scheduling appointments, managing patient records, and other administrative tasks are burdensome and time-consuming. Computer vision automates these tasks, freeing healthcare professionals to spend more time with patients and better apply their higher-level skills. For example, computer vision reads and interprets handwritten notes, reducing the time spent on data entry.
Enhanced Diagnostics
One of the most promising applications of computer vision is in diagnostics. Deep learning models built upon data collected through computer vision provide clinicians with additional tools to detect accurately cancerous lesions in the brain and other systems. In addition, computer vision is now applied to medical imaging to help radiologists make better decisions regarding the treatment of patients.
The Role of Analytics
While computer vision provides the tools to interpret and understand visual data, analytics is the key to unlocking the full potential of this data. By analyzing the data collected through computer vision, healthcare professionals can gain insights into patient health trends, predict potential health issues, and make data-driven decisions to improve patient care.
For instance, by analyzing the data collected from computer vision-based patient monitoring systems, healthcare professionals can identify patterns that may indicate a deterioration in the patient's condition. This analysis allows for early intervention, potentially preventing serious health complications.
Moreover, analytics also helps healthcare organizations optimize their operations. By analyzing patient flow data, healthcare organizations identify bottlenecks and inefficiencies in their processes and take steps to improve them. This improvement leads to increased patient throughput and improved patient satisfaction.
In conclusion, computer vision, coupled with analytics, has the potential to increase patient throughput in clinics and hospitals significantly. By automating routine tasks, enhancing diagnostic capabilities, and providing valuable health insights, computer vision driven AI frees healthcare professionals to focus more on what is most important - providing high-quality patient care.
As healthcare information technology professionals, we are responsible for staying abreast of these technological advancements and leveraging them to improve patient care.
About the Author: Dr. Barry Chaiken
Barry P. Chaiken, MD, MPH has over 25 years’ experience in healthcare information technology, clinical transformation, and business intelligence. He is the Global Head of Healthcare at Versalytix and also President of DocsNetwork Ltd. He has previously worked with the National Institutes of Health, UK National Health Service, McKesson, Infor, and Salesforce/Tableau. Dr. Chaiken is the author of the recently released Navigating the Code: How Technology Transforms the Patient-Physician Journey, a book on healthcare information technology and its potential impact on quality, access, and cost of care.