INSIGHTS

If data is the new currency, how do we refine, assimilate, and make data accessible so it helps and not hinders?

Fun fact: hospitals in the US are a data goldmine, generating more than 50 million GB of data each year. Today, only 3% of this data is being leveraged. We’ll leave you to work out the potential that exists.

As health insurers (payors) and providers look to leverage data to better deal with continued inflationary pressures, labour shortages and more importantly an increasing emphasis on customer experience, this statistic is bound to change. However, today they face significant challenges due to data inaccuracy and complexity of handling large datasets which are stored across disparate systems in different data formats. And the solution to this problem lies in advances in AI, integrated with the right data infrastructure and workflows.

Last week, we announced our investment in HiLabs, a leading provider of AI-powered solutions to manage dirty data, unlocking its hidden potential for healthcare transformation. We co-led the round alongside Denali Growth Partners and with participation from our US based sister fund F-Prime Capital.

Secular tailwinds are driving payors to address their provider data accuracy problems

US payors need accurate data for their provider network to publish online provider directories, maintain network adequacy to acquire new business and drive customer satisfaction, and support multiple other downstream processes. Collecting and updating provider data remains largely a manual process. Despite the significant manual effort, a large amount of the provider data listed in online directories has been found to be outdated or wrong. The situation has been exacerbated as healthcare professionals are increasingly moving jobs. The US government has put the onus of ensuring the availability of accurate provider data on the payors. It is taking measures to better protect patients from consequences of erroneous provider data through new legislation and stricter enforcement of earlier rules which penalize payors for data inaccuracies, driving the payors to look for automated solutions which can address the problem.

Payors are collecting more clinical data but face challenges in standardizing and analysing it at scale

Historically, payors have collected limited samples of clinical data, usually in physical form for quality assurance purposes. The move towards value based care models which links payor and provider incentives to clinical outcomes, quality of care, and risk status of patients handled has driven payors to collect more clinical data. This has been enabled by increased penetration of Electronic Medical Record (EMR) software, and improved capabilities to analyse large datasets. The clinical data, however, is available in different formats, uses varying terminologies, and can in many cases contain errors making it challenging for payors to use this data.

Payors want to use other data types available with them to automate processes and help improve performance

Payors have access to other data types such as claims data, prior authorization requests, and value based care linked administrative data which they can use to improve clinical outcomes, member experience and financial performance. These data types also have issues with accuracy and lack of harmonization which the payors are looking to solve.

HiLabs: AI-powered solutions to transform healthcare

HiLabs’ MCheck SaaS platform allows healthcare plans to ingest healthcare data from different sources and in different formats and identify anomalies and potential corrections.

The company currently offers multiple products: MCheck Provider, MCheck Clinical, MCheck Claims, and MCheck VBC, each handling different types of data payors want to work with, making it a one stop solution. The MCheck platform is automated and leverages latest AI/ML techniques to deliver highly accurate results. The technology is being leveraged by some of the largest health insurance companies in the US in their efforts to automate and improve processes. The company’s provider directory management solution, MCheck Provider, is live in most US states, analysing data of over 80% of the country’s healthcare providers and being used by many of the top 15 health insurance companies in the US.

We have closely followed Amit Garg and Neel Butala, and their journey over the last two years as they leveraged tech talent in India and the US to build a best-in-class product suite at HiLabs. We have been extremely impressed by the team’s vision and strong customer traction, and believe that HiLabs’s MCheck platform is uniquely positioned to serve the healthcare ecosystem as it looks to leverage large amounts of data at its disposal.