The future prospects for big data in healthcare

As the population continues to increase, as well as life expectancies (with advances in healthcare certainly playing their parts), challenges involving a much larger community to serve will need to be addressed at every part of the healthcare industry, but big data and smart hospitals can make preparing for these changes much more manageable. Here are a few ways data is expected to aid with healthcare management.

Staffing

For the majority of the modern healthcare timeline, choosing how many nurses, doctors, and staff to have on at a given time was pretty steady, with surges in staffing only occurring when large events were happening in a given locale, or when tragic events had already taken place and hospital systems needed to scramble for personnel.

There was always some 'small data' used, just based on local history, but with increases in availability of big data, and a greater willingness to share that data across hospitals, staffing practices and needs can be evaluated over time, and in real time, to ensure the right amount of personnel are present, saving hospitals money regarding to overstaffing, and improving patient care regarding understaffing.

Patient empowerment

The days of answering 100 questions when you get to the hospital are probably still going to be parts of patient healthcare journeys, but the usable data recorded by apps that track things like heart rate, how many steps-per-day people take, and things of the like are legitimate sources of data that can be used by healthcare professionals to increase care for a given patient.

Predictive analytics

Predictive analytics exist wherever data exists, from web security, to college transcripts, and, indeed, all throughout the healthcare sector. When it comes to healthcare management, the data pools are becoming more and more sharable, in the form of Electronic Health Records (EHRs).

With patient approval, data regarding side effects, treatments, patient demographics like age, ethnicity, gender, etc., and results of those treatments can be pooled together to use for future patients who share the same side effects and demographics related to a given ailment. With predictive analytics, doctors across the globe can access deep, deep pools of patient information in order to best inform their decisions regarding a future treatment for a patient.

Digital healthcare

Decades before COVID-19 made telehealth a priority in many cases, it did exist, to some extent. But when integrated with real time data delivery from aforementioned apps and devices that allow for improved patient self-care (and data collection during that self-care), telehealth can really be utilised for many different consultations previously impractical via telephone or videoconferencing.

Ultimately, this can allow for some doctors to do their own work from home, saving space in hospitals and allowing for less travel and costs for patients able to discuss issues from afar.

Less crowded emergency rooms

A frequent consumer issue with hospital care is the scavenger hunt that many patients are put on when trying to find the right care provider in a given healthcare system. Quite often, frustrated patients will just head to the ER, causing time, money, and, most importantly, long waits for people who really do need the emergency room. Big data and analytics can help patients build confidence that the areas they are being triaged to are, indeed, the right ones, ultimately keeping the ERs open for emergency care.

Evolution

Considering its funding and overall purpose, healthcare will continue to have many reasons to dive deeper into big data and diversify the means by which it is utilised to improve patient care. The data industry is expected to grow from $169bn (2018) to $274bn in 2022, with new possibilities being thought up every week, many relevant to healthcare.