Analytics in Healthcare and the Life Sciences

How exactly is data analytics aiding the Healthcare and Life Sciences Industries?

1)The future of Healthcare and Life Sciences is Personalized Medicine. Personalized Medicine is nothing but prescribing patients medication based on their genomic data. Each person has a unique DNA so the medication recommended based on their genomic data will also be unique and personalized according to their requirements. This type of targeted medication and treatment improves medical services and patient conditions. For these personalized and targeted treatment techniques to work, healthcare data analytics should be appreciated and used more abundantly. Data analytics is making sense of the available data and putting it to good use for the smooth functioning of companies. Healthcare data analytics can be specially used for increasing the precision and accuracy of diagnosis, biomarker discovery, prognosis, and disease subtyping. A combination of data obtained from multi-omics, EHRs, and wearable and implantable devices is important for accurate healthcare data analytics.

2)Improvement of the effectiveness of Clinical Trials. Use of advanced technology to ensure clinical trials are being performed with the generation of quality data that is free from errors, free from any form of inconsistency, outliers, and misinformation. Analysis of big data in healthcare produced by these clinical trials and finally drawing insights is important. Saving time and improving cost efficiency are some of the goals of this type of big data in healthcare analytics.

3)Improving the assessment of risk can be possible. This is an important step in Healthcare and Life Sciences Industries. Some companies receive yearly warnings from MHRA, EMA, and FDA. Healthcare data analytics aids in the establishment of risk management as a continuous process. By analysis of data, one can draw accurate and precise insights. This helps in producing forecasts and predictions of risks. This prediction will prepare a company for such risks before they even take place so the company can take some steps to avoid or overcome them.

4)Enhanced optimization of R&D. R&D is a complicated but important aspect of Healthcare and Life Sciences. The development of the Healthcare and Life Sciences Industries entirely depends on how well the company’s research is going on. Only 0.1% of the drugs used in clinical trials get approved for human use. At every stage of the process, the data available should be analyzed to take such decisions that affect the healthcare systems. The introduction of data analytics in R&D can aid in the rapid data processing of large volumes of data. This will also allow the rapid production of data-driven insights. It has been studied and estimated that utilizing analytics in R&D can reduce costs of development by 15% and expedite the approval process by 6 months. All of this is done whilst improving patient outcomes as well.

What Analytics and Why?

Descriptive, Diagnostic, and Predictive Analytics combined play a major role in the Healthcare and Life Sciences Industries. They aid in experience enhancement, mitigation of risks, business model generation, and maximization of profits. An American company responsible for pharmaceuticals and providing health information technology, medical supplies, and tools of care management declared that customers will be able to access personalized and targeted treatment regimens with the incorporation of data analysis in the Healthcare and Life Sciences sectors. Another European company also declared that by using predictive analytics and IoT (Internet of Things), drug development can be accelerated and outcomes can also be improved tremendously.

According to a survey conducted, 73% of Predictive analytics methods are deployed in overall Healthcare and Life Sciences. 72% of Descriptive or Diagnostic analytics methods are deployed in the overall Healthcare and Life Sciences. 31% of Prescriptive analytics methods are deployed in overall Healthcare and Life Sciences.

85% and 65% of Prescriptive analytics are deployed in the Healthcare and Life Sciences separately. 82% and 66% of Descriptive or Diagnostic analytics are deployed in Healthcare and Life Sciences separately. 36% and 28% of Prescriptive analytics are deployed in Healthcare and Life Sciences separately.

According to more surveys, it indicates that 46% of overall Healthcare and Life Sciences are integrating multiple analytics tools to draw synergies. 43% of them are deciding on the choice of tools/technologies to pick from. 39% of them realized that they require resource skills in the analytics realm. 44% of them can understand the right analysis techniques to be deployed. 54% of these industries ensure a clear execution strategy is set beforehand. 53% of them are choosing the right analytical tools and technologies and finally, 17% of them are partnering with external service providers and data experts.

The Usage of Analytics

33% of Finance and Accounting functions, 19% of Marketing, 18% of Operations like Production, Supply chain, and Support, 13% of Research and Development, 11% of Sales and Presales, 4% of Human Resources, and 2% of Sourcing and Procurement are utilized in overall Healthcare and Life Sciences.

Facing Challenges Head-on

Challenges are inevitable when it comes to the integration of 2 different sectors like Healthcare, Life Sciences, and Analytics. Challenges like the availability of tools, right-skilled resources, available capabilities, and expertise among people are the most common challenges faced by companies. Most Healthcare and Life Sciences organizations generally struggle with the integration of multiple data sets and analytics tools. They require assistance in understanding and choosing the right tools to perform the right analytical techniques according to the current trends. Less than 54% of Healthcare and Life Sciences Industries agree that a clear execution strategy and a detailed roadmap would help in the mitigation or avoidance of challenges faced while using data analytics initiatives. Greater than 60% of the Healthcare Industry favored having the right roadmap and choosing the right people and techniques for analysis.

Impact of Other Technologies

AI and Automation have become an essential part of the data analytics industry. 61% of overall Healthcare and Life Sciences believe that automation will enhance scale analysis which will in turn aid in the improvement of customer experience. They also understand the importance of AI technology in creating new business models.

Conclusion

The Healthcare and Life Sciences Industries now understand the importance of data analytics for the smooth running of their companies. The importance of data analytics lies in the plethora of benefits that it provides to these industries. Integration of Analytics into these sectors is now required. Not just for the aforementioned reasons but also to ensure the future of the Healthcare and Life Sciences Industries can overcome the predicted outcomes and function smoothly with the help of the incorporation of analytics. It is a key digital tool that provides a great range of benefits to the Healthcare and Life Sciences industries. The motive of this integration is similar to the motive of the Healthcare industry which is to save lives and provide better treatment regimens. All of this will be done efficiently in the future, and this incorporation not only benefits the companies but also all the people of the world.