How Big Data Applications In Hospitals Can Help Us Prepare For Future Health Crises - FORBES.COM
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Founder,
President and CEO of Fidelis Marketing Group, overseeing the
promotion of memberships and tours at luxury resorts in Latin America
How Big Data Applications In Hospitals Can Help Us Prepare For Future Health Crises
While the repercussions of
the latest pandemic are a clear cause for concern, they have also highlighted
obvious gaps in the world’s healthcare systems. There’s been no cohesive plan
for treating an unknown illness, and no way — aside from self-reporting — to
track the outcomes on a global scale to see which treatments are the most
effective. As someone with 20 years of experience in data analytics, I believe
this is where big data comes in, and the applications of big data could stretch
much further than just one health crisis.
Applying Big Data Marketing Practices And Infrastructure To Healthcare
The seed for this idea was sown by a dear friend, Todd Rogers, managing partner at a business intelligence and cloud computing platform for vacation ownership. Unfortunately, in 2016 Todd was diagnosed with lung cancer, and while undergoing treatment, he realized that medical professionals don’t have the infrastructure in place to capture — let alone analyze — data on a large scale. While they do have access to medical and scientific journals to learn about new studies and techniques, and textbooks on standard care procedures for various health issues, they don’t necessarily have access to datasets that enable them to see the success rates of each treatment plan on a global scale or as a side-by-side comparison. Because of this, healthcare providers could be missing out on valuable data and the wealth of knowledge it contains that could help to save many lives.
The infrastructure for this wouldn’t necessarily have to be complicated; in fact, I believe it could be simple — all it would take is one of the world’s leading analytics companies to write a simple program that each hospital could enter its data into by category. If the category was "cancer," for example, the hospital could enter the type of cancer, location, medical institution, date diagnosed, patient metrics (age and weight), treatment, duration of treatment, side effects and outcome. This would be compiled on a global scale, and when providers were faced with a patient suffering from the same type of cancer, they could easily search by these metrics and find the most efficient course of treatment that's backed up by data.
Could Big Data Pandemic-Proof The Future?
While the application of such a big data infrastructure couldn’t prevent the emergence of unforeseen illnesses, it could help in early stage detection and the implementation of prevention plans on a global scale, and it could also assist in quickly identifying the most effective treatments. This means that countries could prepare faster and halt emerging viruses before they have a chance to reach pandemic scale.
All diagnosis and treatment data would be readily available, so countries facing early signs of infection and those yet to reach their infection peak could be armed with knowledge around the best course of action to take in treating those who were infected with the virus and could prepare accordingly. They might prepare by ramping up production of personal protective equipment or beginning to convert other buildings into makeshift hospitals to ensure adequate beds would be available when the pandemic reached its peak.
Competitive Hospitals, Better Funding And Commercial Applications
In a for-profit health system like that of the United States, compiling this data could help patients determine which healthcare provider was the most effective at providing certain types of care. If a patient was diagnosed with a rare type of cancer, they would be able to research which hospitals had the best success rate or treatment plans for that type of cancer. This could not only mean that could the patient make an informed choice about the provider they decided to seek treatment with, but it would also ideally mean hospitals would compete to provide the best care possible.
Because a large percentage of healthcare in the United States is funded by the government, the application of big data could also be used to decipher where funds were needed most. This could be done by analyzing available data around success rates, reasons for failure or other metrics. In this scenario, if a hospital cited a lack of equipment or outdated facilities as a reason for the loss of life, the federal government could grant additional funding to that hospital to ensure it was well-equipped to give the best care possible.
Shifting To A Big Data Future
While the shift to utilizing big data in healthcare has started, it’s been slow to catch on; some have used it on a small scale, such as the Paris hospitals that attempted to identify trends around doctor demand through big data analytics to ensure hospitals were well staffed at peak times, or Propeller Health (formerly Asthmapolis), which is utilizing sensors in asthma inhalers to identify asthma trends. Aside from small, isolated use cases like these, I've only seen big data catch on in a larger format when it comes to identifying cost-savings opportunities and in the context of clinical research studies.
As such, the shift to a global-scale, big data future is likely still a way off. However, with the obvious benefits that a global healthcare and treatment database could offer, it’s only a matter of time before we start to see it used on a massive scale — after all, just like the lessons learned from the Spanish Influenza pandemic of 1918, it takes a big event to force change, and perhaps the latest health crisis is that catalyst.
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