The US-based Start-up ventured into healthcare in 2017. However, it was difficult initially with low demand for product offerings, high capital investments, and low returns. The lack of a customer base made things all the more challenging. Moreover, the epidemiology analysis model it introduced failed to meet its expectations.
The organization had been aiming at capturing a significant market share of at least around 10% by 2024, with its unique product offerings, but was not able to tap the pulse of the market. The products failed to resonate with the target healthcare customers.
Research Nester used its data-driven analysis for facilitating the use of tools and technologies that integrated the collection, management, and analysis of vast amounts of healthcare data. Its ‘Nest-omics’ model enabled the effective application of Healthcare IT for the start-up and helped it in strategizing its market position.
Research Nester analysts observed that Artificial Intelligence and Machine learning was not being effectively deployed. Patients found the product offerings inconvenient and inaccessible most of the time. Treatment thereby seemed complicated for the general population. The epidemiology analysis model was inaccurate and faulty. The YoY growth of the company showed a continuous dip from 2017 to 2021, as the company valuation fell from ~USD 2 million in 2018 to ~USD 0.50 million in 2019, and finally ~0.25 million by 2022. The owners panicked and turned up to Research Nester as their last resort. The consultants at RNPL weighed the different algorithms based on statistical data to restructure the business model.
In the steadily evolving healthcare landscape, data-driven health insights played a vital role in improving patient outcomes and also drive innovative solutions. The analysts at Research Nester observed that Healthcare IT can be effectively deployed as a game changer for the company. Epidemiology analysis initiatives could be efficiently carried out with the help of cutting-edge technologies. RNPL consultants enabled the use of Electronic Health Records (EHRs), data warehouses, and analytical platforms in the company’s planning and management. The company’s existing Health IT was re-strategized to include efficient processes for disease surveillance, early detection, prevention strategies, and targeted interventions. The strategies enabled accurate results and facilitated better predictive analysis and health outcomes. The efficient use of Artificial Intelligence in Healthcare managed to open new doors for epidemiology analysis for the Start-up and as a result, enabled it to reach its goal of a valuation of ~USD 20 million as of 30th May 2023.