Big data is generating a lot of hype in every sector and it is becoming a hot and trending topic in the developed world. The knowledge about it, preparedness and the know-how to incorporate it into healthcare systems continues to be a challenge and headache to healthcare professionals and leaders. But yet it presents many opportunities on both cost-effectiveness and improving patient outcomes. Big data is simply defined as 3Vs, big data- Volume, Velocity and Variety. Today, our healthcare system is still doing plenty without big data, including meeting analytics and reporting needs. We haven’t even come close to stretching the limits of what healthcare analytics can accomplish with traditional relational databases—and using these databases effectively is a more valuable focus than worrying about big data. But as the demand for precision medicine and the use of sensors and wearable go high, big data solutions will be in need. Below are few areas where big data can be leveraged. PREVENTING MEDICATION ERRORS Medication errors are a serious problem in hospitals and other healthcare organisations. Because humans will always make the occasional error (even something as simple as choosing the wrong medication in a pull-down menu), patients sometimes end up with the wrong medication—which could cause harm, or even death. Big data can help reduce these error rates dramatically by analysing the patient’s records with all medications prescribed, and flagging anything that seems out of place. Unfortunately, as with many big data initiatives in healthcare, there are some roadblocks to widespread adoption. Due to the age of many healthcare IT systems, implementation of these devices can be slow to catch on. Additionally, healthcare data is very sensitive, and organisations have to be very careful about security and compliance with regulatory bodies. IDENTIFYING HIGH-RISK PATIENTS Many healthcare systems have to contend with high rates of patients repeatedly using the emergency department, which drives up healthcare costs and does not lead to better care or outcomes for these patients. Using predictive analytics, some hospitals and clinics have been able to reduce the number of ER visits by identifying high-risk patients and offering customised, patient-centric care. Currently, one of the major hurdles to overcome in identifying high-risk patients is lack of data. Overall, there are simply too few data points, making it near impossible to get an accurate picture of the real risks, as well as the reasons for these risks. REDUCING HOSPITAL COSTS AND WAIT TIMES There is enormous potential for cutting costs with big data in healthcare. There’s also an opportunity to reduce wait times—something that costs everyone money. There are so many ways hospitals could cut costs using predictive analytics. A good example is how Babyl-Rwanda is addressing this issue by providing online consultations using phones on a low price, comparing with the hospital’s cost and the time one spends at the hospital. Hospital budgets are complex, and though the ROI (return on investment) potential is high, some organisations are simply not ready to invest in big data. They may be replacing old equipment with new cutting-edge technology or allocating money elsewhere, despite the fact that they could save millions. ENHANCING PATIENT ENGAGEMENT AND OUTCOMES Consumer interest in devices that monitor steps taken, hours slept, heart rate, and other data on a daily basis shows that introducing these devices as a physician aid could help improve patient engagement and outcomes. New wearables can track specific health trends and relay them back to the cloud where they can be monitored by a pharmacist or physician. This can be helpful for everything from asthma to blood pressure, and help patients stay independent and reduce unnecessary doctors’ or pharmacists’ visits. The use of big data in healthcare still presents many roadblocks, such as the technical expertise required to use it and a lack of robust, integrated security surrounding it. And with the cautious approach many hospitals take to change, and an overwhelming number of possible applications, many administrators are overwhelmed and unsure of where to start. But as more healthcare organisations jump on board with big data, these practices will become the norm rather than the exception. editorial@newtimes.co.rw
