A lot has been said about the importance of big data in the forthcoming years. Given the COVID-19 pandemic and its limiting impacts on everyday life, it is now also important we understand how big data affects different sectors. If telehealth is the future of healthcare, then this future is unimaginable without big data and analytics.
For those unfamiliar with the term, telehealth is essentially treatment provided to patients remotely. Not only does it cover clinical care, but telehealth supports better health management in communities as well as public health education. All of this has been made possible with the help of big data, which makes for the backbone on which telehealth stands.
Big Data in Telehealth
In some ways, the concept of telehealth is so advanced that it has allowed the healthcare industry to jump forward at an unprecedented pace. Big data is responsible for this and continues to transform the healthcare sector. A real-life example of this is Zambia’s “Visualize No Malaria” plan, which uses data analytics to eliminate life-threatening diseases like malaria from within the country. Some of the ways in which big data is utilized in the healthcare sector include:
Patient Health Tracking
Big data in telemedicine allows for the identification of potential health problems before they escalate into threatening conditions. This development has become even more accessible with the rise of wearable health devices that can collect real-time data, and thus track patients’ health.
Big data, when paired with predictive analytics, allows for robust patient health tracking. Healthcare providers are able to be immediately updated about a patient’s health status, especially in the case of an anomaly. With this data, doctors are able to detect disease earlier, as well as predict possible future outcomes based on data-driven risk scores and through the use of predictive analytics.
Remote Patient Monitoring
Remote patient monitoring differs from general health tracking in that it is aimed at post-discharge patients. While patient health tracking applies to those patients who haven’t been admitted into the hospital, remote patient monitoring is reserved for those who have been admitted into and then discharged from hospital, so as to monitor their health after a procedure. Data about vital patient stats like heart rate, blood pressure, and more, allows better monitoring of patients after their discharge. Remote monitoring negates the need for patients to be physically present for follow-ups, prescription changes, and more.
This is especially useful for elderly patients, saving them from unnecessarily visiting healthcare facilities thus minimizing their risk of contracting a virus. Not only does remote patient monitoring with the use of big data keep the cost of healthcare relatively low, but it also frees up time for overwhelmed healthcare workers, who can, in turn, focus on caring for patients in critical condition.
Accurate Diagnoses and Specialist Outreach
Big data in healthcare allows for diagnoses to be based on actual data collected, as opposed to subjective symptoms as reported by the patient. Thus, diagnoses become more accurate, and also occur in a timely manner. Secondly, from the sheer volume of data uploaded onto the cloud, specialists from all over the world have access to diagnosis data without being constrained by location.
Predicting Trends in Disease
The application of deep learning algorithms to healthcare data can allow professionals to make better predictions about trends in infections. Predictive analytics can also help determine disease progression, and likely geographical spread of disease. In turn, professionals can take preventative action to limit the detrimental effects of infections.
Should You Consider A Career in Data Analytics in Telehealth?
There are several standardized measures taken by institutions to keep up and improve the quality of healthcare. However, in the middle of a global pandemic, it might not be enough. The world is re-assessing how it functions and healthcare systems are being evaluated first. This has resulted in the need for the mainstreaming of telehealth, in turn creating a demand for telehealth workers that can provide care to patients wherever needed without delays.
It’s also no secret that a career in data analytics has a lot to offer. Its future prospects are innumerable, with demand increasing in each sector. Data analytics has the potential to move businesses and change the very face of commerce and life. When data is applied to businesses, it becomes business analytics, consisting of descriptive, diagnostic, prescriptive, and predictive analytics.
Those who have the foresight to combine these facets of data analytics with their background in healthcare will be in high demand as telehealth becomes more widespread. As we saw earlier, big data is indispensable to telehealth and telehealth is invariably the future of healthcare. Given this, developing skills that make you a big data expert while also having some expertise in healthcare can give your career the push it needs. The point to be noted here is that, even though data analytics is growing at a fast pace, you should duly consider your niche while taking it up as a career option. Generalized big data engineers will always be in demand, and you can make a greater difference if you apply data analytics to a niche sector like health.
Many popular careers in medicine have not yet tapped into the potential of big data. However, with the pandemic completely changing the way we live, telehealth has never been more important. In the post-COVID-19 era, healthcare will be forced to accept telehealth as the new normal. Thus, careers in data analytics in telehealth stand to be most rewarding.
Telehealth might be the only way to sustain the advanced deployment of healthcare while the world faces an unanticipated pandemic. No doubt, it is also the future of all healthcare systems. Thus, big data, when paired with telehealth, will continue to revolutionize the healthcare industry.