Healthcare is one of the expensive and critical domain compared to other domains like, retail, manufacturing, banking etc. Each individual piece of information in healthcare can have life or death importance. Providers in healthcare domain are continuously looking for an opportunity to reduce the cost while improving the quality. There are few of the opportunities available like detecting and identifying the disease by adopting to the proactive methods available and making sure the identification of disease or symptom is highly accurate.
Identifying the diseases with high degree of precision has been historically very difficult. However, with the advancement in technologies in computing power, it has been made much easy to compute huge amount of data and thus utilize the potential of Data Science and Machine Learning to find the pattern in huge amount of data and give useful insights which can be used by healthcare professionals to ensure the quality life of the patient.
Time factor is very critical in healthcare domain. Usually healthcare professionals have pre-defined parameters to check for patient while diagnosis due to limited number of output result data and tools available to them and the accuracy of the output may not be too accurate to confirm. Based on this available limited information, healthcare professional take a decision depending on their skills and experience. This decision must be accurate as incorrect decision can result in patient’s getting not appropriate treatment or may even lead to death.
However, with Data Science and Machine Learning, more amount and more parameters of patient diagnosis can be analyzed in lesser time with high degree of precision making it much easier for healthcare professional to take much accurate decision and thus provide appropriate treatment to the patient at the right time.
Data Science has a tremendous potential to unfold the future and predict information in advance. The Patient’s historical and biological data can help doctors to identify the risk of person getting disease in future and thus doctor can provide the preventive measure to avoid person getting that disease in future.
Today, there are so many Healthcare gadgets available in the market that keep track of your daily health activities. Data Science can use this daily health activity information and process it to give you a useful insight. Also with the advancements in sensors that are attached to such healthcare gadgets can be combined with a Machine Learning model which can recognize with high accuracy a pattern for critical conditions like heart attack or respiratory diseases and alert the patient in advance so that appropriate precautions can be taken by the patient.
Improving the drug quality and effective has always been a major challenge for pharmaceutical research companies. The major two hurdle they come across for this is accurate informative analysis report for the patient using the drug and finding the key factors in drug composition that need to be improved in the drug to improve the quality of drug. With the help of Data Science both problems can be solved as Data Science has the great potential to recognize the pattern and find key factors in the available data that play important role. This can help even help pharmaceutical to do what if analysis and thus take appropriate decision to improve the quality and effectiveness of drug.
Data Science eventually contributes to making healthcare more efficient, accessible and personalized by providing option and methods to extract hidden information from unstructured patient data.
Till date, very few healthcare organizations are using Data Science. However, still with only lesser utilization of Data Science in this domain, from predicting treatment outcomes to predicting cure and outcomes of treatment for critical diseases like cancer, Data Science is proven to be an invaluable contribution to this domain. As we utilize more of the Data Science to this domain, surely we can get better insights helping people in this domain to save and cure more lives at much lesser cost and get much better output.
Author: Prashant Gautam
Data Scientist, VOLANSYS Technologies