Healthtech startups bet on AI to build electronic health records but adoption in India remains slow – Crypto News

Unlike electronic medical records (EMRs), which are confined to individual hospitals or clinics, EHRs are designed to be accessible across institutions. This interoperability is key to improving diagnosis, treatment, and continuity of care. What’s more, they can be accessed across both privately held and government-operated healthcare providers.

Qure.ai’s voice-based assistant, Aira, transcribes and summarizes patient conversations, nudging healthcare workers to ask better questions and improve diagnosis. “We realized one way to solve for EMRs is by digitising the doctor-patient conversation,” said Prashant Warrier, founder and CEO of Qure.ai. Aira is currently being piloted in Nigeria, Varanasi, and Maharashtra, with plans to expand to Indian public health centres.

Based on the conversation with the patient, Qure’s AI ‘nudges’ healthcare workers, improving the quality of their questions while simultaneously helping provide better diagnoses and remedies.

The company’s AI tools is meant to support frontline workers like Ashas in LMICs. “Here, AI can basically augment their knowledge base; it becomes a game-changing solution,” said Ankit Modi, Qure’s chief product officer.

Qure’s clients include AstraZeneca, the UK’s National Health Service, and ministries of health in Southeast Asia. Backed by Lightspeed, Peak XV, and Merck’s Global Health Innovation Fund, Qure’s FY24 revenue rose to ₹140 crore, narrowing losses to ₹48 crore.

Rural areas

Similarly, Eka.care is a public health records app which works with doctors, patients and hospitals to build electronic medical records (EMRs). The company has been seeing a lot of interest in its products, especially in rural areas. “We’re seeing increasing interest from rural healthcare providers, community health clinics, and CSR-backed initiatives who want to digitize care at the last mile,” said company founder and CEO Vikalp Sahni in a written response toMint.

But rural India brings its own set of challenges, like low bandwidth and poor connectivity. To combat that, Eka.care built a similar tool to Qure’s Aira, which it calls Eka Scribe, an AI-powered voice-to-text tool that converts conversations between doctors and patients into structured prescriptions in real time. The company is also working on offline-first modules, which will then auto-sync to create records once bandwidth access is restored. “The goal is to meet doctors where they are, whether it’s OPDs or if they’re on the move without compromising on medical accuracy or record quality,” Sahni said.

Eka.care last raised $15 million in a Series A round in 2022, led by Hummingbird Ventures. The company’s earliest investors included deeptech-focused Speciale Invest and early-stage VC firm 3one4 Capital. As of September 2022, its valuation was $49.8 million, according to Tracxn.

Similarly, Jivi.ai, backed by former Google Brain head Andrew Ng’s AI fund, is trying to make diagnostics possible and take it a step further.

The company is trying to enter hospital workflows, both in India and the US, where users can have their history taken by the app before connecting them with doctors, thereby creating medical records. “Our strategy is to focus on very large-scale healthcare systems and work with them to solve for a particular use case,” said Jivi founder and chief executive Ankur Jain.

Currently, most of its attempts are in the proof-of-concept (PoC) stage with various hospitals across India and the US. However, Jain declined to share names of companies they’re working with, saying that they were still at the PoC stage and that sales cycles were long.

Investor interest

In India, investor sentiment for companies working on building EMRs and EHRs is cautious, given the low adoption of the technology in hospitals, even in urban ones. Then there’s the rural angle, where hospitals outside metros lack high-speed internet, trained IT staff, and information and communication infrastructure. This, in turn, makes it harder to deploy EMR solutions.

“We seek EMR startups that offer compliant, scalable, and SaaS-based technology. They should provide clear ROI pathways, behavioural adoption mechanisms, and additional services. Ideally, these startups should cater to large institutional clients,” said Sunil Thakur, partner and investment committee member at Quadria Capital, a healthcare-focused private equity firm which invests across South and Southeast Asia.

State of electronic health records in India

The government began working on creating EHRs in 2017 under the National Health Policy. Under it and the National Digital Health Blueprint, the government launched the National Digital Health Mission (now known as Ayushman Bharat Digital Mission, or ABDM).

Since then, adoption has dramatically picked up, but it’s still lagging.

According to the ABDM dashboard created by the government and last updated on 1 September, the total number of Ayushman Bharat Health Accounts (Abha) stands at 804 million. India’s population is 1.4 billion, which means that only about 57% of the population has signed on to participate in the ABDM ecosystem.

Meanwhile, the number of health records linked with Abhas is even lower, at 714 million. Government hospitals account for 55% of those registered with the ABDM, while private hospitals make up 45%.

The path forward

Large-scale deployment of software for the creation of EHRs or even EMRs, for that matter, continues to remain an issue, according to experts. “I’m not seeing anyone at the enterprise level introducing such processes. However, at the startup level, we see people trying to do PoCs to show what they can do,” said Sujay Shetty, global health industries advisory leader at PwC.

Some of this can be attributed to hospitals being wary about AI in their ecosystems because its introduction brings costs and liabilities. What’s more, creating a data infrastructure that can ‘converse’ with AI is expensive. “It’s also a function of the appetite of an institution on how much they want to spend to modernise legacy systems,” said Shetty.

Regulations

Notably, India doesn’t have a healthcare-specific law regarding patient data and privacy, unlike the US, which has its own version, the Health Insurance Portability and Accountability Act (Hippa). Platforms like Qure.ai and Eka.care are regulated by India’s Central Drugs Standard Control Organisation. Data protection, on the other hand, falls under the incoming Digital Personal Data Protection Act (2023).

Qure takes the doctor’s consent to record and transcribe conversations. Eka.care’s Sahni said that their AI products are built with a “consent-first” design in mind. “From Abha-linked records to DocAssist AI suggestions, every action is logged, transparent, and controlled by the doctor or the patient.”

Qure, for example, had to receive Food and Drug Administration approval to sell in US, while in the European Union, the company had to self-certify with CE marking, a process where companies declare their products comply with EU standards.

Startups can access the ABDM programme by accessing a sandbox environment, integrating their technology with the applications within the ABDM ecosystem, and being audited by a committee for both functionality and security. Once companies pass this, they showcase a demo of their product before finally being allowed to go live and link their product with the ABDM ecosystem.

Further, Qure’s Warrier said that the transcription programme was performing well, especially in high background noise or poor device quality conditions, but that there was scope for improvement for the ‘nudge’ aspect of Aira. “Providing the most accurate nudges still needs some work. It’s good, but it can be more accurate, and that’s what we’re working on now.”