Data Science in Healthcare: How it helps in Care

Recognizing the upcoming problems is always good when it comes to healthcare. Mainly because no individual is hundred percent safe, irrespective of his or her age, gender, demography or ethnicity. Be it illnesses, accidents, genetic disorders, or mutations, there are enough reasons with which every other person struggles at some stage of his or her life. And that is why we can see people spending tons of money on healthcare plans and various other costs that are incurred in it. One of the best examples is the U.S. healthcare industry. In the US, it has been seen through a study submitted by a McKinsey report that approximately 18 percent of their GDP represents healthcare costs. On the other hand, a survey conducted by Ponemon showed that around the world, roughly 30 percent of data stores healthcare fields.

Data in the Healthcare Industry

Healthcare industry comprise of abundant data of every kind. Be it any sort of basic or primary information, genetics related data, medical records, billing data, articles related to science and research or databases related to care management, you name it and the industry offer everything that is needed for healthcare management. Today’s techno savvy world relies heavily on instant information which is available online wherein almost 72 percent people take references from the internet to seek some or the other kind of medical assistance. For example: Zocdoc. Because of platforms like these, it has become more manageable to keep the track record of the patient’s records in an organized manner in a specific location. And so, the data analytics industry is booming like anything.

Importance of Data Science in Healthcare

Individuals across the world make extensive use of medical and healthcare devices such as an electronic wearable, headbands, pedometers or different types of smartphones. Some rely heavily on instruments like a health care kit, a glucometer or a blood pressure cuff so that the levels of danger of warning signs if any can be tracked well on time. As a result, lot of data gets accumulated which needs to be analyzed several times to reach to a certain conclusion or to assess the information for correct diagnosis of an ailment so that appropriate treatment can be advised to the patient. That is why, a lot of data scientists are needed in the healthcare industry. And so, it has become important for them to attain the entire information about the processes involved in the correct data analysis, statistical record maintenance or machine learning for that matter.

Data Science Revolution in Healthcare industry

Discovery of drugs has revolutionized mankind to a very large extent. In order to develop a new drug, it takes almost a decade or so and costs upto $2.6 billion. In such a scenario, big data plays a crucial role. It gives a platform to the scientists so that they can simulate drug reaction which in turn is likely to get an approval from the department of Food and Drug Administration very easily. Because of this only, a lot of patients are getting benefitted who suffer from mutation related diseases.

Across the world, many startups have come up that are contributing hefty amounts in the research and development of drugs and administration and the testing processes involved. For example, BenevolentAI, a London based company.

Prevention is better than cure

It is rightly said that prevention is better than cure, especially when it comes to healthcare related issues. Because, it takes a lot of time and money to recover from the ailments as well as the costs incurred are humungous. Therefore, it is always wise to take all the precautionary measures so that any sort of potential health hazards can be recognized. Accordingly, preventive measures can be given to the sufferers before their condition becomes a difficult issue or goes out of control.

Many wearable devices and instruments have come in the market that helps to track the symptoms, patterns, the history of a disease and anything related to genetic disorders that are present in an individual causing threats to his or her life. For example, let us take a look at the famous company that deals into digital therapeutics: Omada Health. The company makes use of smart devices which helps to provide correct information to the patients’ ailing from diseases like high cholesterol or hypertension by creating plans catering to the behavior plans for the patients and also provide coaching via internet so that the patients can avoid different health conditions that are chronic in nature.

An organization named propeller health manufactures a tracker that comes with a GPS. The device acts as an inhaler and performs the task of synthesizing data for asthama patients by making use of data which is taken from the Centers for Disease Control and Prevention. Another organization from Canada named Awake Labs makes extensive use of wearables for autism patients so that their parents can be alerted in advance before the meltdown occurs.

Correct Diagnosis and Treatment

Correct diagnosis plays a very important role in healthcare. As per the studies conducted by the National Academies of sciences, Engineering, and Medicine, it has been found out that approximately 12 million US citizens suffer from misdiagnosis that lead to almost life-threatening experiences. Around 80,000 deaths take place merely because of wrong treatments. However, with technologies like medical imaging, data science can be used effectively. Interpretation of MRIs or for that matter X-rays can be done to detect things like tumors or any sort of anomalies. Things like magnetic resonance or spinal tapping too can efficiently utilize to predict the accurate onset of diseases. Besides, internet research can be taken into consideration to understand the signs and symptom of various ailments through search engine results.

Genome project is an excellent example of organized data that helps to conduct open study surveys. By working more on the complexities of human genes, scientists can learn about the best possible treatment methods that can be utilized for drug development.

Post-care is equally essential

Many people undergo surgeries and costly treatments for life-threatening diseases. As a result, they get prone to the risk of complications or towards recurring pain. By monitoring their condition post-treatment, expensive medical after-care can be managed wherein the patients can stay in touch with the doctors in real time and stay safe in the long-run. For example, the Cloudera software offered by Intel. It helps the hospitals to conduct a prediction as to whether a patient needs to be readmitted in the clinic in the coming days or not. EMR data is utilized for that.

Role of Data Science in Hospital Operations

Most of the hospitals across the world face problems with respect to the management of staff, beds and operating rooms. To ensure maximum efficiency, predictive analytics can be utilized to schedule things like bed cleaning, discharge of patients and allotment of hospital beds. There is one more thing called analytics software that helps to streamline the operations in an emergency room. It helps to ensure that a patient admitted in the hospital gets the best possible treatment through effective operation processes.

To cut down the waiting time by approximately 75 percent, Emory University Hospital made use of data science for the prediction of lab tests. Similarly, to streamline billing, business intelligence can be used to identify patients to deal with their finance related issues. It can act as a platform to build a relationship with the insurance departments to coordinate with the patients for their billing related issues. By effective implementation of big data analytics, the Center for Medicare and Medicaid Services was able to save around $210.7 million that actually helped to prevent frauds.

Future of Data Science in Healthcare

Unlike any other industry, healthcare too has certain things with respect to data science. This is mainly because any sort of data related to medical science is often neglected in the hospitals or the administrative departments and not given the due importance to keep it intact and collective at one place. That is why patients too are seen worrying about their health reports and its privacy wherein techno giants like Google has been facing heavy lawsuits because of the usage of sensitive information to target advertisements. Also, people are not sure about the use of algorithms as well as machines when it comes to the outsourcing of association between the doctor and the patient.

Large-sized pharma and biotech companies, research centers, medical start-ups, and hospitals are actively utilizing data science for the better delivery of healthcare services.

Conclusion

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