The industries of healthcare and finance have one thing in common: they are both getting highly interrupted with the advancement of technology, namely data science. And this phenomenon is being highly encouraged as Data Science Helps Human.
In 2017 alone, 3.5 million USD was invested in over 180 health companies. The core of significant transformation in the health industry, therefore, lies in data science.
More than a billion clinical records are being created, for instance, in the US every year. Doctors and life scientists have an immense amount of data to base their studies on.
Moreover, immense volumes of information related to health are made available through the large-scale choice of wearable gadgets. This opens the door to new innovations for more informed, better healthcare.
The main objective for health data scientists working with the healthcare industry is to make sense of this huge data set and derive helpful insights from it so the human body and its issues can be understood better by healthcare providers. Therefore, data science can strongly transform healthcare.
Let us look at 7 benefits of Data Science
Wearable to Monitor and Prevent
Human bodies produce two terabytes worth of data daily. Due to technological advances, it is possible to collect most of this data such as heart rates, blood glucose levels, sleep patterns, stress levels, brain activity, etc. Armed with such volumes of data, data scientists are expediting the limits in health monitoring.
Among the leading tech companies in the world like Qualcomm and IBM, have been pioneering the path to health innovations. Apple too joined this race in 2015 with Research Kit.
Another issue in healthcare that requires special attention and regular observation is the management of chronic diseases. Omada Health targeted this specific issue and opened its first product, which is a preventive medicine plan. This plan aims at transforming the lifestyles of their patients and helps them manage their weight and prevent the dangerous effects of obesity. Both businesses and individuals have adopted it.
Despite such enormous quantities of health data at disposal, the rates of diagnostic failure are still comparatively high. For this case, let’s look at Bruxlab, a Dutch startup, which applies machine learning and data science for diagnostic purposes. Combined with technologies of sound recognition, they diagnose and grade Bruxism symptoms. Bruxism is quite a common disorder but it is overlooked because its symptoms are concealed. Therefore, a mobile app now, helped with data science, presents a way to better diagnose and monitor a disorder.
Transforming Patient Care
The way which scientists gather and evaluate health data when they are looking for symptoms to identify diseases, doctors can do the same with patients and track their clinical duration to confirm their diagnosis. Informed care and personalized treatment, driven by technology can eliminate death rates significantly and develop precise patient records.
From EHR (Electronic Health Records) adoption to genome sequencing improvement, doctors and other health providers now have a lot of data at hand to determine continuous symptom patterns and help add to patient records.
A good example of data science application is to assist healthcare providers to treat their patients better is Oncora Medical. This startup uses archival data from several cancer treatment clinics and the patient’s unique EHR data to offer customized treatment suggestions, depending on the cancer type, previous health reports, and their current condition.
Cancer is among the deadliest and the most common diseases in the world. It has been a consistent subject for research. The number of people getting afflicted by the disease is growing consistently. A healthcare startup in Boston named BERG Health has reshaped cancer medication through inclusive data science application. They use strong algorithms of machine learning they have extracted and evaluated from biological samples provided by more than a thousand patients. With more than 14 trillion information points included in every sample, BERG had enough data to input into the artificial intelligence algorithm.
This resulted in BERG developing the drug BPM 31510 that identifies and triggers the natural damaged cell death by cancer. While testing is still going on regarding the drug, it is clear that data science has transformative potential and technologies of machine learning can greatly contribute to the pharma industry. If this can cause breakthroughs in cancer, then imagine what it can do for other diseases like Ebola or HIV AIDS.
For Efficient Clinical Performance
Predictive analytics and data science is an invaluable tool that can support healthcare providers to enhance the process through which hospital operations are accomplished. A startup from Austin, Texas, CognitiveScale, employs machine learning to enterprise processes in certain industries, including retails, healthcare, and finance. They offer two services: Engage and Amplify. Both are utilized regularly by company level organizations and managed to understand the data sourced from both employees and clients. Thus, the plans give important suggestions and actionable outputs, advancing the organizations to improve production and action.
In the same way, data science can be applied to enhance clinical staff schedules and decrease wait times, manage accounting and supplies, and even develop an efficient engagement plan for epidemics like seasonal flu.
Reducing Risks in Prescription Medicine
An innovative startup named MedAware aims to reduce errors in prescription. The startup claims to have tools that will allow hospitals to save almost 5.6 million USD and eliminate the danger of lethal results. This software system is self-learning; it checks every prescription by comparing it to similar cases stored in the database and lets the doctor know if there are any deviations in the prescriptions.
Cutting Down on Hospital Re-admissions
Complete digitization and transformation through technology help save many industries a lot of money, and it is the same in the healthcare industry as well.
Preventive medicine based on analytics can contribute to the complete reduction of costs, indirectly though. For instance, Clover Health, which is an analytic health insurance company driven by data, claims up to 50% fewer hospital admissions. They use a smart algorithm that identifies at-risk patients and helps orchestrate the required care. Thus, Clover Health saves almost 10,000 USD per each admission on an average.
Moreover, the application of data processing and interpretation mechanisms enables physicians to secure educated decisions, which follows in meaningful profits. For example, data analytics, used to enhance the knee replacement surgery let healthcare providers save more than 1.2 million USD in a year
From foretelling treatment results to counteracting cancer and delivering more effective patient care, data science healthcare has shown to be a valuable addition to the industry’s future. While data science gives methods and tools to obtain authentic content from unregulated patient data, it ultimately provides healthcare more effective, convenient and customised.