Big Data has been responsible for bringing in a sea of changes and advancements in various fields, be it marketing, finance, governance, or healthcare. The proper analysis of such large sets of unstructured and diverse data lets us access information that would otherwise be hidden to us. It helps us find newer methods of solving issues, finding new paths of development, and achieve much more in a shorter span of time than we have in the many past years. Big data along with the disruptive technology of Internet of Things (IoT) is the next big thing.
Big data in healthcare
In the realm of healthcare, big data, with the help of certain analytics, lets us discover patterns that help us in making predictions about certain diseases. Having knowledge beforehand about chances of contracting a disease and ways of preventing it can help in reducing costs and improving patient care in the future. The treatments that stand to gain the most from big data analytics in healthcare are those of chronic diseases, especially the ones like diabetes and mental health. By using big data and IoT together, it is possible to collect personal health records and gauge medical health and fitness levels using wearable devices. The traditional methods of collecting health related information can also help in providing additional useful information.
What can big data collaboration achieve?
Data gathered from both structured, traditional sources, IoT devices, and large sets of unstructured big data information can help in creating new generation tools that can bring to us better insights, dependable recommendations, and real-time feedback. All these will be really beneficial to healthcare practitioners and patients to make informed decisions in a timelier manner with much more evidence in hand. Health and disease management will find a new meaning by allowing doctors to provide more personalized and customized treatment to each patient based on their medical needs. Medication, dosages, tests, and treatments can be tailored to suit each patient and their body structure instead of following a routine procedure which is known to be generally administered irrespective of the situation. Even though the idea of individual, customized patient care might seem like an expensive affair, this is where big data and its analytics come into play. It not only allows doctors to extend effective treatment but also reduces the costs of extending improved care to patients.
Machine learning and artificial intelligence will massively influence the way healthcare is executed in the years to come. This is true for diagnostics, for medical therapy, and for population health management. This issue of Insights will address numerous tough and exciting questions around regulation, the algorithm black box, and what does it all mean for care delivery?
Healthcare digitization is still often perceived as being an endeavour on the level of the individual healthcare system or nation state. While there is some truth in that, it is equally obvious that a global digital health market is evolving, with vast opportunities for IT companies, healthcare providers, med-tech, pharma giants and even charities who are courageous enough to think big. In this edition of the HIMSS Insights eBook, we give these global eHealth champions a platform. Download your copy of the eBook for free today to access the most insightful content and news.
Paper health information presents significant challenges to large hospital environments. Due to the clinical risks that having a predominantly paper health record causes, Mater decided to take action to address the challenges of paper health records, which also resulted in significant increases in efficiency and cost reduction, all pre-dating the commencement of an EMR implementation. HIMSS Asia Pacific speaks with Sallyanne Wissmann, Director Information Management, Mater Health Services, Brisbane, ahead of her presentation at HIMSS AsiaPac18.
RADM (Dr) Tang Kong Choong, Chief of the SAF Medical Corps, gave an update on the recent developments at the organisation and some lessons learnt behind the implementation of the third generation EMR system.