Healthcare data platforms and interoperability

Making scattered health data usable, by gathering, cleaning and connecting it

Back to the patient in Texas from Industry Vertical 22, Digital health. Over ten years, the patient has seen a skin doctor, a family doctor and a heart specialist, and has had blood tests at two labs. Each one keeps its own records, in its own system. The insurer holds the claims. Some reports were sent by fax. Nobody has the whole picture.

Healthcare produces more data than almost any other industry, and uses less of it. The data is scattered across records, labs, claims and faxes that do not connect to each other. The companies in this Market Segment gather it, clean it and make it usable, for three purposes: care, payment and research. They do it in three ways:

Data platforms

systems that bring a hospital group's or an insurer's data together in one place.

The pipes

software that moves records between systems.

The readers

AI models that read the records themselves.

The buyers are hospital groups, health plans and research organisations. The ability of different health systems to exchange data is called interoperability.

Scattered health data, made usable: one patient's data sits with several doctors, two labs, the insurer's claims and faxed reports; data platforms bring it together, pipes move records between systems, and AI models read the text, for care, payment and research.

Every company named here has posted software engineering jobs in India. Famous companies that don't actively hire software engineers in India are left out.

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What this section holds

What this section holds

The data platforms. Back to the patient's scattered records from the start of this Market Segment.

Innovaccer

with engineers in Delhi, has the most job postings in this Market Segment. It was founded by Indian engineers and builds its product in Noida. It sells a healthcare data platform that brings together a hospital group's or an insurer's data from every source. AI assistants for care managers sit on top.

Health Catalyst

with engineers in Hyderabad, sells the data platform and analytics of American hospitals.

Abacus Insights

with engineers in Pune, sells the same to health plans.

HiLabs

with engineers in Bengaluru and Pune, cleans the data about doctors and members that health plans run on.

The pipes

Founda

with engineers in Bengaluru, and Health Compiler, with engineers in Pune, sell the APIs that connect records to other applications.

eHealth Technologies

with engineers in Hyderabad, fetches records and images for referrals and for clinical trials. (It also appears in Market Segment 25.3, Clinical trial software, in Industry Vertical 25, Pharma and life sciences.)

Concord Technologies

with engineers in Chennai, runs the secure cloud fax through which much of American healthcare still exchanges documents. (It also appears in Market Segment 4.1, Email security and anti-phishing, in Industry Vertical 4, Cybersecurity.)

The readers

Triomics

with engineers in Bengaluru, uses language models to read the records of cancer centres, for research and for care.

Two companies covered mainly in other Market Segments bring research and security:

Truveta

with engineers in Hyderabad, is here for the records of a group of American health systems, with the patients' names and details removed, which is called de-identified data. (More on it in Market Segment 25.7, Real-world evidence (RWE) platforms, in Industry Vertical 25, Pharma and life sciences.)

Clearwater

with engineers in Pune, is here for the security and privacy compliance of health data. (More on it in Market Segment 4.14, Governance, risk and compliance (GRC), in Industry Vertical 4, Cybersecurity.)

The record read by a model.

Most of the information in a patient's record is free text: notes and reports that structured systems could not use. AI models now read it. They turn ten years of notes into data for a trial, a quality measure or a care plan. Triomics and Innovaccer are built on that change. India's data-abstraction centres, where people used to do the same reading by hand, are affected by it.

The record read by a model: AI models read years of free-text notes and turn them into data for a trial, a quality measure or a care plan (Triomics, Innovaccer).

So the patient from the start of this Market Segment finally has a whole picture. Platforms bring the scattered records together, pipes move them between systems, and AI models read what was written in them.

Who they hire

Who these companies hire, and for what, is on What health insurance and billing companies hire for.

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