IT Trends and Issues in Healthcare PDF

IT Trends and Issues LIVING IN THE IT ERA - WEEK 16 PREPARED by: Mr. Keith Amiel Basilio Instructor Learning Objectives: 1. To recognize the IT Trends in Issues in the field of Healthcare. 2. To recognize the IT Issues that have emerged in the field of Healthcare.  AI...

IT Trends and Issues LIVING IN THE IT ERA - WEEK 16 PREPARED by: Mr. Keith Amiel Basilio Instructor Learning Objectives: 1. To recognize the IT Trends in Issues in the field of Healthcare. 2. To recognize the IT Issues that have emerged in the field of Healthcare.  AI in Healthcare Artificial Intelligence (AI) is defined as a branch of computer science that aims to enable computer systems to perform various tasks with intelligence similar to humans. In Healthcare, AI is: used to analyze the treatment techniques of various diseases and to prevent them. used in various areas of healthcare such as diagnosis processes, drug research sector, medicine, patient monitoring care centre, etc. helps to gather past data through electronic health records for disease prevention and diagnosis.  AI technologies used in healthcare Machine Learning (Neural Network and Deep Learning): the main use of machine learning technology is precision medicine, which means to predict the best treatment protocols that are likely to be successful on a patient based on different patient characteristics and treatment context. Natural Language Processing: includes creating, understanding, and classifying clinical documents and published research. It also helps in analyzing unstructured clinical notes on patients and preparing reports. Robotics: physical robots are enabled with AI to perform different tasks in the healthcare sector. Nowadays, surgical robots are being used to provide help to surgeons for improving their ability to see, stitch wounds, and so on. Some surgical procedures that use robotic surgery are gynaecologic surgery, prostate surgery and head and neck surgery.  AI technologies used in healthcare Rule-based expert System: collection of it-then rules and is most widely used in the commercial sector. It is also used in Electronic Health Care (EHR) with some set of rules in their system. First, a set of rules is created by human experts and knowledge engineers, and then they implement an easy-to-understand rule-based expert system. This rule is directly proportional to the knowledge domain means if the knowledge is changing, then the rule can be complex and time taking. Robotic process automation (RPA): used to perform repetitive tasks such as updating patient records or billing. It can also be used to extracting data when combined with other technologies. Roles of Artificial Intelligence (AI) in healthcare  IT TRENDS in healthcare Radiology: Because of technology such as Computerized Tomography (CT) and Magnetic Resonance Imaging (MRI), AI in radiology will cut down on the interaction time and allow doctors to see more patients at the same time. Screening: AI is also most widely used in the screening field for the healthcare department. Example is an an AI algorithm named Google DeepMind is also used to detect breast cancer at a very early stage than human experts, so it can be prevented from reaching a severe stage. Further, AI algorithm also helps to detect prostate cancer with more accuracy than human experts. Psychiatry: AI applications are used to study anxiety and depression and are still in a phase of proof-of-concept. These raised various professional, ethical and regulatory questions for the professionals of the healthcare industry.  IT TRENDS in healthcare Primary Care: Primary care is one of the key development areas for AI technologies such as predictive modelling, business analytics, supportive decision making, etc. Decease Diagnosis: Artificial Intelligence (AI) uses Medical Learning Classifiers (MLC's) to substantially aid doctors in patient diagnosis with the help of mass Electronic Health Records. Dermatology: Dermatology is an ample imaging technique that is also more enhanced with the use of Deep Learning in Image Processing, that makes it more efficient and easier as compare to other traditional ways. Also, through the use of AI in image processing, keratinocytes skin cancer has been possible to be detected by face photography.  IT TRENDS in healthcare Drug Interaction: AI algorithm to identify the drug-drug interaction can be improved with the use of Natural Language Processing (NLP). Drug interaction increases the number of medications being taken by a human who takes multiple medicines for their disease. Through Machine Learning, medical science has developed some techniques to extract the drug-drug interaction and their possible effects and causes. Further, Drug-drug interaction can also be identifying through the use of Deep Learning. Manufacturing of Drugs: With the help of Artificial Intelligence (AI), a molecule of a drug for OCD (obsessive-compulsive disorder), treatment becomes easier, which is not feasible in approx. Five years through traditional approaches.  IT TRENDS in healthcare Electronic Health Records (EHR) - the main key factor to develop and digitalize the healthcare sector. - Artificial Intelligence helps to interpret the records and provide updated information about the diseases, differentiate same deceases that mostly medical specialist treats similar like heart attack and myocardial infarction and helps to prepare relevant prescription notes for other patients in future. - EHR can be modified to predict the risk of a decease based on prior data of a patient and their family. The machine also predicts and takes decisions, collects a large number of data and creates a new rule set based on observations, then concludes the diagnosis. This approach helps to collect patient data and find outstanding issues and saves time as compared to other traditional alternatives. Some studies said, predictive modelling of EHR can achieve up to 75% accurate data, and this results in the number of online health records double every five years.  QUESTION: With the continuous IT Trends emerging in the field healthcare, can you see some of the possible issues that may emerge? Sources: Javatpoint. n.d. Artificial Intelligence in Healthcare. https://www.javatpoint.com/artificial-intelligence-in-healthcare? fbclid=IwAR2REM5GkL4UlDZCrtt57a3H0-- LX4bK4VhHwgB3YHkFw6Gcp2bFqenDUbk