Could Big Data Apps Prevent the Next Pandemic?
There’s no denying it: big data is growing, and its impact can be felt in almost every industry. But despite its massive presence, the healthcare sector has been slower than others to embrace data and all of its applications. With such vast amounts of patient and provider information available to work with, health organizations and their leaders can struggle with knowing where to start and how to best use it.
“The biggest challenges in healthcare are fragmented data and data quality,” says Julius Bogdan, North American vice president of analytics for The Healthcare Information and Management Systems Society (HIMSS).1
Indeed, there are significant opportunities to gather, streamline, and effectively wield the massive amounts of health-related data that’s collected every day. Yet for all of the promise and applications of data analytics in healthcare, there is yet to be a truly successful, large-scale big data app to bring its benefits to a convenient, user-friendly platform. Taking it a step further, it’s hard not to imagine how an app like this—fully global, accessible, and optimized—could improve the way we handle the next major health crisis.
The Current State of Data In Healthcare
It’s important to note that while there’s certainly room for improvement in healthcare data management and analytics, it isn’t nonexistent. There are highly valuable systems for logging and storing patient data (Epic, Cerner, MEDITECH), sharing treatment options and results (PubMed, the U.S. National Institutes of Health), tracking and analyzing pathogens (Nextstrain, Global Initiative on Sharing All Influenza Data, Advancing Real-Time Infection Control Network), and much more, but none that quite wholly deliver data-driven personalized medicine on a larger scale.1
What Big Data Apps Can Offer
As part of our mission to push boundaries in Health Tech and continuously advance our skills, we at EmergingEd decided to take a look at how the creation of big data apps could help us prepare for (and potentially prevent) the next health crisis.
Before we start parsing out the possible outcomes of a technology like this, there are some assumptions we would need to make about any potential big data apps. First, they would need to be globally adopted and easily accessible to fulfill the intended outcomes. They would also need to be standardized, yet fully adaptable for every country’s language, demographic data, measurement system, prescription names, and other varying inputs. Lastly, they would have to honor the privacy of all submitted health information, including that of the healthcare professionals who will likely be using the platform the most.
1. Track Emerging Viruses/Illnesses
In hindsight, there are many things we as a country and planet could have done differently at the beginning of the COVID-19 pandemic. However, one saving grace came in the fact that after the first SARS-CoV-2 genome was sequenced and published, scientists acted quickly to obtain as much information about the virus as possible, gather it all in one place, and make it publicly accessible. This allowed more laboratories, researchers, and public health experts to study the genome and use their findings to develop prevention and treatment plans, identify variants, and ultimately develop a vaccine.2
In a similar way, health-focused big data apps could help to identify mounting public health risks and spread the word as quickly and clearly as possible, whether it would be to a neighboring country or a different continent. With this advance notice, countries and their governing bodies could begin prevention plans and/or more adequately prepare themselves for the oncoming illness. This might mean expanding hospital wards, hiring more nurses, or producing more personal protective equipment on the front end rather than as a reaction to the spreading virus.
2. Find the Best Course of Treatment
If the process above hasn’t been implemented or cannot function, then there still would be hope to curb the negative effects as infections spread. Within minutes, healthcare workers would be able to access all diagnosis and treatment data from countries that had already dealt with the virus and adapt their care accordingly.
However, large-scale public health crises aren’t the only possible use for these apps. Let’s say a patient is being diagnosed with a rare form of cancer. Since there aren’t many other patients and treatment plans to which they can compare, the patient’s doctor will likely press forward with their own well-informed recommendations. But with the global repository gathered by a big data app, a doctor can quickly and easily browse what has already been proven to work from somewhere else in the world, even if it hasn’t been widely dispersed yet. Additionally, doctors and specialists can provide information on what alternative treatments, up-and-coming medicines, or homeopathic remedies have produced results so far.
3. Identify and Locate the Best Facilities
In healthcare systems like in the United States, providing good patient outcomes is crucial for overall success; funding, talent recruitment, and rankings are all contingent upon how well you perform for your patients. With success and failure rates more openly documented and available on an app, patients could not only see which providers offer the best level of care, but also which ones are best for their specific type of care (e.g., a rare form of cancer). For providers that are under-performing, this could help signal a need for additional funding, labor, or equipment.
4. Diversify Our Data
While it’s certainly easier to collect and analyze data from one region, it won’t provide as comprehensive of a picture as we would need to address another worldwide pandemic. With a globally-adopted big data app, it would diversify the available data not only in terms of the sources from which it would come (e.g., hospitals, senior care centers, non-profits), but also the types of people from whom we gather information.
By tracking how a virus affects people in various parts of the world, we might also be able to identify risk factors for an illness that we hadn’t been able to before. A larger pool of physical and demographic data would show trends in age, sex, ethnicity, pre-existing conditions, and geographic location that could lead to deeper conclusions—for example, environmental factors, such as humidity or drought, might affect respiratory illnesses more dramatically than we previously thought. With this information, we could work to address those factors or provide relief to areas that would be affected the most.
5. Monitor Hiring/Labor Shortages
An ongoing issue in the COVID-19 pandemic is the limited supply of available, qualified healthcare professionals to care for the sheer volume of patients. In situations like these, there’s a great opportunity to use regional and local data to generate predictive analytics.
Essentially, predictive analytics could help leaders assess and adjust staffing requirements to meet the peaks and valleys of infection rates. Monitoring the staff counts at different facilities, in conjunction with the predicted impact the virus could have on that region, would help ensure there are enough medical personnel in place to handle the anticipated caseload. With the right data, the scheduling process can even be automated, freeing up scheduling staff and ensuring minimum requirements are met for Full-time Equivalent (FTE) commitments.
Embrace the Future of Health Tech
As you can see, there’s a lot of potential in our current technology. If the promise of big data apps and influencing the healthcare landscape appeals to you, don’t ignore your instinct. With $3.1 billion invested in digital health ventures in just the first quarter of 2020, health tech is flush with opportunity for those who have the skills to fill these new roles.3 The good news is that you don’t need to have any specific healthcare experience to get started—explore our site and find out how EmergingEd’s healthcare technology courses can give you the career advantage you need.
Sources:
- Retrieved on January 25, 2022, from asm.org/Articles/2020/October/SARS-CoV-2-Sequencing-Data-The-Devil-Is-in-the-Gen
- Retrieved on January 25, 2022, from himss.org/resources/top-trends-big-data-healthcare
- Retrieved on January 25, 2022, from fiercehealthcare.com/tech/digital-health-funding-off-to-a-record-start-2020-what-will-be-impact-covid
