Misdiagnosed illnesses and medical errors cause around 10% of all deaths in the United States. Fortunately, AI is not prone to human errors and can predict and diagnose diseases and dangerous conditions quickly using algorithms and deep learning. In this article, health informatician Dr. Joel Arun Sursas discusses how the development of AI’s healthcare applications will help to reduce medical errors and prevent incorrect prescriptions and misdiagnoses.
AI Provides Valuable Support to Physicians in the Clinical Setting
AI can act as a virtual assistant to practitioners in the often-hectic clinical setting by working as a failsafe and a powerful check against human error. AI algorithms can handle an unlimited number of patient cases in a day. They can accept the delegation of many tasks, giving the physician more time to focus on their patient and their immediate needs. Fatigue and pressure cause many or most human errors and an AI app supports patient interaction and provides an interface that patients can use anywhere they are online. Cancer and eye condition diagnoses particularly benefit from AI and machine learning to confirm or flag diagnoses made by even the most experienced physicians. [1, 2]
AI Is a Vital Tool in Diagnosing Illnesses
Many conditions require an analysis of multiple symptoms and indications. While humans often mistake images or overlook particular tests, AI supports human analysis by studying and comparing images and samples much more efficiently and accurately. 
AI’s Role in Medication and Prescription Management
AI maintains vast databases of medication data by analyzing large data groups and using machine learning to search for common errors, unknown interactions, and potential side effects. AI also manages medication histories of many patients, which allows for the identification of at-risk populations and evaluation of overdose risks. AI streamlines the authorization process for prescriptions and allows for more efficient and accurate delivery of medications at the patient’s pharmacy. 
Algorithms are also powerful tools in ensuring patient compliance with prescribed medications. Physicians can be automatically notified in the event of detected non-compliance. AI also helps practitioners schedule follow up appointments to examine the efficacy of treatments. [1, 3]
Machine learning and AI algorithms can also detect medication errors. AI is not subject to fatigue and can locate and describe many medication errors that can be easily missed in the traditional clinical setting. [1, 3]
AI Applications Designed to Address Error Prevention
There are a growing number of software applications developed to prevent errors and protect patient health. There are software systems that are self-learning and alert physicians if a medication has any negative indications or potential risks. Other programs compare physicians’ proposed treatment plans with previous plans for similar patients. 
About Dr. Joel Arun Sursas
Dr. Joel Arun Sursas is a team leader and facilitator with a proven track record and a niche skill-set developed over the past seven years in his capacity as an established Medical Doctor and Health Informatician. He is most passionate about Medical Informatics, working to bridge the gap between doctors and engineers to improve patient care. His interest in the field emerged when he began working as a Project Officer for PACES — the Patient Care Enhancement System for Singapore Armed Forces (SAF). Dr. Sursas has been instrumental in designing and implementing the largest Electronic Medical Record (EMR) system in Singapore, spanning 53 medical centers, as well as developing a data analytics platform to trend epidemiological data.
We just sent you an email. Please click the link in the email to confirm your subscription!