10 Tips. How Data Science is Used in Healthcare
10 Tips. How Data Science is Used in Healthcare
One thing we have consistently heard about data science, as revealed in discussions over at runrex.com, is that data science is applicable in pretty much every field and industry out there; which is one of the reasons why data scientists are among the most sort-after professionals out there today. One of these fields is healthcare, where data scientists have been using analytics and machine learning to revolutionize the healthcare industry. This article, with the help of the gurus over at runrex.com, will look to highlight 10 tips on how data science is being used in healthcare.
In wearables
As is revealed in discussion over at runrex.com, the human body generates about 2 terabytes of data daily. Advances in technology now mean that we can collect most of this data, which includes data on sleep patterns, heart rate, stress levels, blood glucose levels, brain activity, and many others. Using AI, machine learning, and big data, data scientists can analyze this raw data and information which can be collected through wearables to glean critical insights. This, as per discussions over at runrex.com, helps doctors detect conditions early and predict possible health issues, allowing for possible preventive care.
Drug discovery
The process of drug development, as covered over at runrex.com, includes extensive research, testing as well as time and money, before a drug can be launched safely into the market. With this in mind, the cost of bringing a drug to market can be as much as $2.6 billion, which is substantial, to say the least. This is another area where data science has been of great help in healthcare, as it leverages various sets of biomedical data from various tests, treatment results, case studies and so forth, across various disciplines. Advanced mathematical algorithms then come into play to create a simulation of how a certain drug would interact with the proteins in the body, predicting the rate of success as discussed over at runrex.com. This simulation helps speed up the drug-testing process, leading to a huge reduction in costs as well as the time of drug development, while also mitigating the risks of failure.
In diagnostics
Another way that data science is used in healthcare is in diagnostics, as explained over at runrex.com. This is because, through data science, analysts can be able to apply deep learning techniques to process extensive clinical and laboratory reports, enabling quicker and more precise diagnoses. It also allows for the detection of early signs of medical issues enabling doctors to provide preventive care and consequently better treatment to patients.
In reducing healthcare costs
Data science also plays an important role in reducing healthcare costs, yet another way in which it is used in the sector. Data scientists, as explained over runrex.com, can look into billing data and information extracted from clinical systems as pertains to charging and variables, identifying areas of potential revenue loss, closing said gaps hence contributing to the lowering of costs. Healthcare providers can also use data science to optimize their supply chains as well as review equipment maintenance to prevent unexpected breakdowns, enabling them to keep costs down. Monitoring patient recovery as well as planning discharge protocols can also help with costs as it will diminish readmissions.
In managing and improving overall public health
As is discussed over at runrex.com, there is a large amount of data that can be found in various sources such as Google Maps, wearables, social media, websites, and many other sources. Data scientists can be able to analyze this data, helping them prepare heatmaps on useful parameters such as health aliments, medical results of people in a given geographical location, population, and so forth. This enables them to understand the signs of an imminent health crisis, such as the coronavirus pandemic, allowing them to make the necessary preparations such as increasing the capacity of medical facilities in given areas and many others.
In enabling optimal staffing
One of the most crucial aspects of healthcare is staffing since understaffed facilities are likely to offer poor medical services, not to mention the fact that the staff working there will be overworked leading to burnout, while those that are overstaffed will have increased costs, as explained over at runrex.com. Data science enables medical facilities to keep optimum staff by using analytics to predict patient visit fluctuations based on historical data collected over the years, creating a pattern in staff allocation that is grounded on admission rates from the past. This ensures that facilities always have optimal staffing as well as helping in the allocation of other resources such as beds.
In enabling precision medicine
Given that we are all born with different biological make-ups, not to mention that we are all raised in different environments, a one-size-fits-all approach to treatment doesn’t make any sense, according to the gurus over at runrex.com. This is where data science comes in, in yet another way in which data science is used in healthcare, as it helps enable precision medicine. With data science, the process of genome sequencing has been reduced to a matter of hours, at a far cheaper price. This opens the door to more tailored treatment, which is more effective making precision medicine the future of healthcare.
In reducing risks in prescription medicine
On top of contributing to diagnostic accuracy and in drug discovery, data science technology is also helping reduce the risks involved in prescription medicine, in yet another way it is used in healthcare. As explained over at runrex.com, when a certain drug is prescribed to a patient, algorithms move to verify the drug with available databases, alerting the physician if it deviates from standard treatment procedures. This helps sidestep potentially lethal complications due to faulty prescriptions.
In improving patient engagement
Nowadays, healthcare organizations place huge importance on a value-based approach to healthcare, with patient engagement playing a significant role in this, according to the folks over at runrex.com. Healthcare providers now see it as crucial to increase patient participation in the treatment process. Data science is playing a big role here, given machine learning, AI, and natural language processing can be used to extract meaningful and actionable insights as well as develop predictive risk scores to improve care coordination, hence improving patient engagement.
In improving cybersecurity in healthcare
As discussions over at runrex.com will tell you, healthcare data is extremely vulnerable to data breaches since personal data such as Social Security Numbers, Medicare information, insurance information, and many others are very lucrative in the black market. One of the challenges faced by healthcare organizations nowadays is ensuring the cybersecurity of health data. To help with this, healthcare organizations are utilizing data analytics tools to flag changes in network traffic or detect the occurrence of cyber-attacks, in yet another way data science is used in healthcare. Additionally, data science helps streamline the insurance claim process, making it faster and more efficient for patients, while identifying fraudulent and inaccurate claims.
The above tips are just some of the ways data science is used in healthcare, with more information on this and other related topics to be found over at runrex.com.
