Data To Dollar: How data can be used to optimise healthcare

Technology is evolving at a very fast pace and with the world moving towards digitalisation, the healthcare industry is also keen to quickly embrace the digitalised world. The industry is transforming itself to become more automated and centered around AI/ML. 

This can help transform inefficient pharma and medicine ecosystems into ones that provide inexpensive, fast, and effective solutions for diseases, while democratising the relationship between professionals and patients.

Today everyone has access to some or the other latest diagnostic tools such as wearable health tech gadgets, telemedicine, remote consultation, and intuitive mobile apps. These have contributed to both holistic healthcare and comprehensive user experience. 

Having said that, the focus on the development of better medication and increased usage of data-driven patient care has changed the role of technology in the healthcare sector. Digital technologies are driving remarkable changes in how technology in healthcare services is delivered and received by users across the country, at least in Tier I and II cities. 

However, companies are still acclimatising themselves and are yet to fully embrace these modern technologies since they lack a structured way of collecting and analysing data. This often leads to multiple and unwanted errors, which could also lead to various trade and legal disputes.

Another prominent challenge faced by the healthcare industry is supply chain issues including limited and unpredictable supplies, medicine unavailability, and rising expenditure, which results in the disruption of supply chain. This makes a strong case for capturing accurate data and regularly updating the same to sustain the future of the healthcare ecosystem. 

To address these challenges–forecasting, planning, procurement, and manufacturing are some of the key areas where the healthcare industry would benefit from data intelligence.

For instance, every year we witness a high volume of seasonal diseases that burdens the healthcare infrastructure, early insight into these could help lessen this load. To cater to this, many new-age startups have started focusing on key areas such as manufacturing and streamlining the supply chain.

Additionally, these new-age startups have also adopted the latest technologies such as data science, AI/ML, etc., to anticipate demand and ensure timely delivery of medicines. They are also using customised prescriptive and cognitive analysis solutions to make use of the oceans of available data and transform it into an innovative proactive action plan. 

Along with the above-mentioned use cases, end-to-end visibility is also being maintained to fulfill omnichannel orders, prevent obsolete inventory, maintain safety stock, deliver orders at the right time and place, forecast demand, and a lot more.

In comparison to other industries, the slow pace of embracing data-led solutions in the pharma sector reflects the presence of various challenges such as data security, integrity, and visualisation. 

However, healthcare organisations are keen to adopt new-age technology into their clinical and operational workflow to make significant improvements in their supply chain processes. By identifying and analysing available data, such as participants' demographic and historical data, remote patient monitoring data, and by examining past clinical trial data, big data analytics in the pharma sector can lead to minimised costs and accelerated clinical trials for patient-care.

Data analytics holds the key to unlocking the future of better healthcare for all.