The importance of big data in healthcare is slowly becoming more and more visible to various personnel in the healthcare industry. Healthcare is not only one of the biggest industries in the world, but also the most complex. This is why business analytics are crucial in healthcare: for better serving and saving people through the lens of informed decisions that allow the industry to flourish.
Healthcare business analytics helps predict trends in data, which gives meaningful information about possible epidemic outbreaks, prevents danger before it arises, and ultimately, makes healthcare cheaper and more affordable the world over.
Big data essentially lets health professionals treat their industry just as entrepreneurs in any business would. This is theimportance of big data in healthcare; healthcare business analytics give professionals the ability and capability to craft out the best strategies for whatever needs to be done, based on the numbers collected.
It’s not just business analytics in healthcare that big data has allowed us to take advantage of; big data’s impact has been huge on the whole world, consistently for the past two decades. Nearly all public sector and private sector industries improve their functioning using the data collected and analyzed.
When it comes to healthcare business analytics, the possibilities are near-endless, particularly when integrated with the rest of big data’s impact on any given industry and life as we know it today.
What Does Big Data Entail?
Big data literally just means data that is big; voluminous amounts of data, whether structured or unstructured– a data dump so big that the system used to measure, manage, analyze, and assess it has to be specially designed for that task with relevant tools and processes.
With the entire planet online, with multiple smart devices collecting and storing data for a single person and an infinite amount of data fed into a cloud, there is a lot of information available online. Businesses, governments, and industries, especially the healthcare industry, can use this data to better inform their decisions about what moves to make.
There’s an intimate relationship between big data and business analytics in healthcare. The data-processing application software of old cannot cope with the large amount of data available to even a single urban hospital in an average-sized town, especially given that it is in the nature of big data to grow exponentially in size and complexity.
The Possibilities For Business Analytics in Healthcare
Why are healthcare business analytics so important? For one, there are already various ‘big data’ sources; records such as hospital records, a patient’s medical history and records, test reports, medical examinations, and then, of course, data gathered from various hospital equipment and devices. This is all excluding the healthcare business analytics gleaned from data generated from biomedical research, which is all relevant to the field of public healthcare. We can understand the importance of big data in healthcare by the sheer volume of it.
Proper management and proper analysis are required at every step, otherwise, it’s a needle-in-a-haystack situation with a lot of data that we cannot extract any meaningful information from. Thus, the importance of big datain healthcare business analytics doesn’t lie simply in amassing large numbers of… well, numbers, but in handling those challenges in the true spirit of the Internet of Things with high-end tools and computing solutions especially designed to handle business analytics in healthcare.
This requires efficient management and meaningful interpretation of the data being analyzed, which can open up a whole new world of possibilities at every step, quite possibly even revolutionizing the field of healthcare and the healthcare industry. Through better and bigger services and more efficient financial strategies, stronger medical intervention can be provided that is cheaper, more individualized, and personalized, and does not need to sacrifice the whole for the sake of the part, or vice versa. This is the special role and importance of big data, but especially the importance of big data in healthcare.
The Need For Business Analytics In Healthcare
From a financial point of view, the role of business analytics in healthcare becomes transparent. In fact, the importance of big data in healthcare can be most assessed and justified by the need for it and why, without it, things are being run inefficiently; a monetary measure is the most concrete and transparent tool that we can use for these purposes.
In 2018, the cost of the healthcare system in the United States had been steadily increasing for 20 years. The cost accounted for nearly 18% of the total gross domestic product (GDP) of the country and when compared with the predicted benchmark given the size and wealth of the nation, world-famous management consultants McKinsey (utilizing measures of business analytics in healthcare) found out that the costs exceed the estimate by a whopping 600 billion dollars.
With big data available at our disposal, such a situation could be avoided. When costs eclipse our estimates and predictions, let us look to using the tools and process of big data for utilizing data-driven business analytics in healthcare to serve better the patients, the providers, and the public sector industry, and the economy at large.
Healthcare is an evidence-based field. The evidence presented by the data (research, clinical, and empirical) that business analytics in healthcare can provide thus has to be a crucial part of the healthcare industry’s continued survival, progression, successes, and support of all people all over the world. This also opens up the field of healthcare to a truly global outlook, which is very important in this post-2019 world where we know how problems can travel far and wide, quickly, and expansively.
Examples of Business Analytics in Healthcare
The role and importance of big data in healthcare can be best exemplified by looking at the examples of its use.
We can use business analytics in healthcare to predict problems and prevent them, as well as to evaluate and update currently used procedures, improve and make treatment and recovery faster, as well as run a healthcare center in a much more efficient manner.
Let us discuss some specific examples of business analytics in healthcare – this is by no means an exhaustive list, but it is one that underscores the importance of big data in healthcare and the possibilities of business analytics in the field.
Better Patient Engagement
Patient engagement is defined as “a concept that combines a patient’s knowledge, skills, ability and willingness to manage his own health and care with interventions designed to increase activation and promote positive patient behavior”.
While this may sound like a lofty ideal with strenuous steps at every turn, big data makes it near-effortless. The afore-mentioned smart devices that every average person can own make data readily available and easy to disseminate.
This means that patients can be more intimately involved in their own health and recovery, monitoring themselves and their health through smart devices that can track their sleep patterns, count their steps, measure hydration levels and heart rates, and much, much more – and once again, the day is saved, thanks to business analytics in healthcare!
In fact, Kaiser Permanente is reported to have saved around a billion dollars by implementing a big data-backed computer system, also improving cardiovascular disease outcomes.
One tool that helped in this particular instead was electronic health records (EHRs), which we will now discuss as another brilliant example of the efficient use of business analytics in healthcare.
Electronic Health Records
EHRs have been adopted by more than 90% of hospitals in the US. This is one of the most popular applications of business analytics in healthcare, giving each patient a digital and extensive health record that is adjustable by any and all doctors, minimizing paperwork, redundant data, and the cost and time consideration of collecting patient history at each visit, even if at a different location. This also helps us get a bird’s-eye-view of demographic data, data on certain diseases, and the ability to track patterns in the data.
While a lot of us might have heard the term ‘predictive analytics’ before, it is much more than a trendy business intelligence buzzword. Using EHRs, a health service company can easily create a strong database that can be utilized for predictive analytics. In fact, Optum has done exactly that, using electronic health records from more than 80 million patients, and more than 12 million patients with “deterministically-linked claims and EHR data”. This can improve outcomes and patient experience while reducing costs alongside these benefits.
In fact, business analytics in healthcare can even tackle the opioid overdose pandemic, analyzing data from insurance companies and pharmacies to identify risk factors that can accurately assess and predict the potential for opioid abuse in certain individuals.
Thus, the implications of business analytics in healthcare are far-reaching, extensive, and beneficial to both the healthcare industry and those that it serves, as well as the economy of nations and the world all over.