The Open Workplace Health Standard (OWHS): sickness absence, return to work, wellbeing measurement and benefit provision and use, defined once, in plain language and machine-readable schemas, private by design, free for anyone to implement. Built for the five million UK businesses that will never have a data team.
Payroll data moves between systems because standards exist. Banking got Open Banking. Healthcare got FHIR. But ask what a company's sickness absence actually is, and you get a spreadsheet export whose columns mean whatever the last HR system decided. The function holding the most sensitive data about working people runs on the least structured data in the building.
"Currently, sickness absence is tracked inconsistently, and return-to-work outcomes are rarely measured."
UK Government, Keep Britain Working programme, announcing the Workplace Health Intelligence Unit, July 2026A national unit is now being stood up to collect standardised workplace-health data from employers and providers. OWHS is an open, independent proposal for what that data should look like at the level of an employer's records: aligned to the definitions the UK already trusts, implementable by the smallest employer, and versioned so that when official definitions arrive, they slot in rather than start over. The full argument, including the survey of every existing standard and why none covers this ground, is in the case for a standard; how the specification itself was designed, and what was deliberately left open, is in the design notes.
Version 0.1 defines the entities below as plain JSON Schemas with open code lists. Every field is anchored to a primary source: ONS definitions for absence rates and reasons, the HSE Management Standards for psychosocial domains, the statutory fit note for return-to-work adjustments, and SSP for statutory entitlement.
A record-level absence episode with ONS-comparable semantics, and the return-to-work outcome almost nobody measures today, using the fit note's own adjustment categories.
Survey and validated-instrument results from any vendor's product, with the measurement context that makes scores comparable. Instruments are referenced by citation, never reproduced.
What benefit provision exists for a workforce, statutory and commercial, and aggregate utilisation. Provision and use are modelled in the same vocabulary as measurement.
The only way results leave an organisation: aggregated, suppression-aware, carrying their completion rates and composition so nobody can quietly overstate them.
Versioned mappings from every construct to the HSE Management Standards, ISO 45003, and a reserved namespace for the Workplace Health Intelligence Unit's future definitions.
Reserved, deliberately minimal, until national definitions exist. Signalling alignment without inventing semantics government will define.
The core is vendor-neutral. Product-specific machinery lives in named profiles that extend the core without breaking interoperability; the profile mechanism is part of the specification. For the full entity list, a real record, and the conformance rules on one page, see inside the standard.
Workplace-health data can identify and harm people. So the privacy rules are part of the standard itself: a technically valid payload that violates them is non-conformant, and a conformant producer refuses to emit it.
This is version 0.1, shared ahead of public release with the people whose input matters most. On public release the full specification, schemas and change process (open issues, RFCs, a public decision log) go live on GitHub; until then, request the draft directly and tell us where it breaks.
Read the schemas, try the examples, tell us where they break against your data. Adopting even one entity, or one code list, moves the industry.
The utilisation and return-to-work entities need the people who actually hold this data. We are actively seeking co-stewards so this standard is governed by the industry, not by any one firm.
This proposal was built to be overwritten by official definitions. If you are working on the national picture, we would like to talk.