Technology has transformed the entire healthcare industry and has brought about better care for patients as well as created revenue streams for healthcare data monetization. Where it was once seen as a source of expense, it is now emerging as a revenue stream for healthcare organizations. As the industry progresses, hospitals are looking for new ways to utilize the large volumes of data they possess to good use through the generation of new healthcare revenue streams through big data and AI technologies, among others.
The Role of Big Data in Healthcare
Big data in healthcare refers to the vast amounts of structured and unstructured information hospitals collect during patient care, treatments, and operational processes. This information is not only valuable for enhancing patients’ conditions but also has the potential to bring money to healthcare organisations. Realizing that they can monetize it in the best interest of operations and medical research, healthcare providers are sharing and analyzing this data.
Q-Centrix clinical data management company’s recent survey showed that 75% of the hospital chief said that they are already exchanging or intend to exchange the de-identified clinical data for research purposes. This data exchange is a crucial process of the revenue generation process for healthcare data, and it means new partnerships with pharmaceuticals and research organizations.
AI as a Driver of Healthcare Data Monetization
AI has become integral to the way that hospitals address and use data. Originally, AI was used to automate work processes and minimize expenses, the same way modern organizations harness technology. Today, it takes a modern healthcare system to get the most out of data when it is used as a resource. AI tools also aid healthcare providers in creating new relevant revenue sources and efficient working models from big clinical data sets.
An area where AI is already playing an important role is clinical trials. The Q-Centrix report notes that clinical trials often struggle with participant recruitment issues, with 64% of trials not reaching their quotas. CH assistance can solve this problem using patient’s data processing and finding the right candidates for trials more effectively. It also supports the development of new medicine and offers healthcare systems new revenues with collaborations with research institutions.
Turning Cost Centers Into Profit Generators
Managers are turning the traditional cost centers that once threatened many healthcare organizations into revenue drivers. Among the many activities they are currently undertaking to achieve this aim, the most common is healthcare data monetization. Here are some key strategies hospitals are using to generate revenue from their data:
- Selling De-identified Data for Research: One way that hospital can monetise their clinical data is by selling aggregate data to pharmaceutic companies, research institutions and tech firms. Such collaborations not only serve research interests but also open important revenue generating avenues for the associated healthcare systems.
- Collaborating on Clinical Trials: Pharmaceutical companies can also use clinical trials in which hospitals provide data about specific patients to help them produce new medicines. This creates an additional revenue stream for healthcare systems by monetizing healthcare data and providing patients with access to innovative treatments.
- AI-Driven Data Analysis: By applying AI in hospitals, there is an opportunity to obtain a vast amount of data about patients’ outcomes, treatments, efficacy, and operations that can be useful for other parties and sold or licensed. This use of AI is fundamental to the healthcare data monetization business.
Overcoming the Challenges of AI Integration
Interestingly, there is significant capacity for generating revenues in AI and big data; however, healthcare systems must tread carefully on this technology front. If not controlled, there is always risk when using AI models. Such models’ accuracy requires a large investment in IT infrastructure and human capital. As Brian Foy, the chief product officer at Q-Centrix, noted, precision at scale is incredibly difficult, and healthcare systems must ensure that they have the correct systems to support AI safely and efficiently.
The hospitals that will benefit the most are those that are strategic and long-term in their approach to AI. The risks concerning the monetization of healthcare data can, therefore, be effectively managed through collaboration with organizations that already have safe exploration of AI solutions.
Conclusion
Big data and AI have become the new normal; they have shifted the paradigm of operations in the health systems. Hospitals are no longer just the expense centers. They are valuable assets containing information that can be sold in many ways. From using data for academic research purposes with anonymity to being part of trial carriage, monetization of healthcare data is assisting hospitals to open up seemingly new Healthcare revenue streams. Adopting these technologies makes healthcare systems beneficial to the advancement of medicine, patient health care, and financial viability.