Data And Analytics In Healthcare: Addressing the 21st-century Challenges To Advance Public Health Using data analytics unlocks valuable business insight for healthcare enterprises that keep them ahead of the curve
Opinions expressed by Entrepreneur contributors are their own.
You're reading Entrepreneur India, an international franchise of Entrepreneur Media.
Big data analytics have taken the health enterprise industry by storm, owing to its potential to develop lucrative therapeutics in a short time frame. COVID-19 and several current health situations have been a big, game-changing moment for healthcare companies, supply chain partners, policymakers and other stakeholders. These situations have forced them to rewire the entire ecosystem to stay apace with the developments. This is where the data analytics tools enter; they have the potential to transform health care in many different ways. According to the Big Data Analytics in Healthcare Market report, the global big data analytics in healthcare market size was valued at $16.87 billion in 2017 and is projected to reach $67.82 billion by 2025, growing at a CAGR of 19.1 per cent from 2018 to 2025.
Healthcare enterprises have been using patient's data to identify patterns, test theories, and understand the efficacy of their solutions. The companies are using data analytics capabilities to understand the nature of a disease, how it spreads, how to control/prevent it, and help predict the potential impacts on society. Data analytics essentially takes petabytes of unstructured data streams as input and makes it easy for healthcare and pharmaceutical companies to process and make sense of their empirical data. As a result, technology helps them make more informed decisions so that they can yield more accurate and cost-effective diagnoses. Here are some ways pharmaceutical and healthcare companies can use data analytics to create business value:
Deliver actionable patient insights
Healthcare data is growing in volume and variety and is spread across various repositories, like, hospitals, medical insurance, life sciences research. As a result, the pharma and healthcare companies waste time just wrangling through this unstructured data rather than accelerating their research. Data analytics addresses this concern by cleaning and processing the data, thus identifying targets and correlations and rendering actionable insights. These insights make it easy for pharma and healthcare businesses to take critical decisions more effectively, enhancing healthcare delivery. Additionally, these companies can also track the outcomes and evaluate their systems against industry benchmarks. As a result, the efficiency gains are not merely a one-time incident but become an integral part of the journey.
Predictive analytics
Scientists have claimed victory against future diseases after successfully decoding the human genome. The marriage of this knowledge to the health data generated by patients would enable clinicians to make better decisions about our care. The two benefits of using predictive analytics: better care and lower costs.
The biggest lesson of the recent global health issues such as COVID-19, SARS, dengue and malaria outbreaks is that pharma and healthcare companies cannot afford merely to react to every emerging situation. They need to track several data streams of local, regional, and global trends, create a database, and then predict various scenarios. Data analytics helps companies develop their predictive models, enabling them to make quicker, intelligent decisions, build partnerships, and resolve bottlenecks before the crisis hits the shore. Such data-driven measures aim to save invaluable lives and allow care to be personalized for each individual. Predictive analytics can classify particular risk factors for diverse populations. This is very useful for patients suffering from multiple ailments with complex medical histories. Data analytics tools can predict, for example, who is at risk of diabetes and thus advise them for additional screenings or weight management.
Electronic Health Record (EHR)
To enable easy patient diagnostics, every patient has their digital record - including medical history, demographics, allergies, a treatment plan for previous illness, laboratory test results, and many others. These EHRs are shared via secured information systems and accessible by doctors or other healthcare professionals, who can implement changes and update the records when needed. In addition to this, EHRs can trigger warnings and reminders to notify them about their next diagnostic visit or appointment with their doctor and track their prescriptions to check if they have been following doctors' orders.
Reduce overall healthcare costs
Healthcare professionals can leverage the EHRs to identify patterns for a comprehensive understanding of the patient's body and health. The insights from this data can aid them in better patient treatment and care. Better patient care translates to a shorter hospital stay or even lesser admissions. As a result, this would help cut healthcare costs for the patients and resources optimization for the hospitals. Further, the data analytics can estimate the individual prices for a treatment which can help in careful treatment planning, thus maximizing the healthcare effectiveness.
Conclusion
The digital transformation in healthcare is accelerating. Data analytics can bring relevant insights that change how healthcare practitioners optimize their services for their patients and develop new solutions that can help resolve their ailments. The ultimate goal for every healthcare enterprise is the wellbeing of patients - a good patient care experience at an optimal cost. These enterprises can make significant strides towards these goals without spending considerably on R&D and other big-ticket heads. Data analytics in healthcare can help streamline unstructured patient data, innovate forward-thinking treatments, reduce costs, and, most importantly, save lives. It is the way forward.
