<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-09-03T10:35:59Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/3B605E30-E99F-47BB-A569-549791034209" ns1:id="3B605E30-E99F-47BB-A569-549791034209"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/1B5E4B5C-0358-4D47-A631-C8C062620182" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A7AFA290-1AB4-429F-B6F1-D334666AB84A" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A7AFA290-1AB4-429F-B6F1-D334666AB84A" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-12-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/0AA0CE6F-8734-4532-B01D-52212A72DBC4" ns1:rel="FUND" ns1:start="2019-06-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">105336</ns2:identifier></ns2:identifiers><ns2:title>Home based digital urinalysis in antenatal pathway</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Healthy.io will be testing smartphone-based home urine testing for antenatal care in 100 women in the Royal United Hospitals Bath NHS Foundation Trust. We aim to assess how smartphone-enabled home urinalysis, combined with home blood pressure measurement, improves patient safety through proteinuria earlier detection, reducing demand on health services by avoiding face-to-face visits and improving patient experience in a cost-effective and scalable way.

Using computer vision and user-centric design, Healthy.io's is the first company to turn the smartphone camera into a clinical-grade medical device. Our urinalysis product (Dip.io) is the first CE accredited and FDA cleared smartphone-enabled automated urinalysis device. Built around the 10 parameter dipstick, a self-testing kit and a smartphone application, the device enables lay users to self-test for protein and other analytes in their urine, in the comfort of their home, with no quality compromise. Our proprietary algorithm and cloud-based service allow for interoperability and integration with any clinical system. Results are immediately available to clinicians for follow-up.

Blood pressure monitoring and urinalysis are part of routine antenatal care. Our 'maternity care box' combines our urinalysis test kit and a blood pressure monitor enabling women to self-test before and if needed, between visits and reliably share results with their midwife.

The study will last 12 months starting July 2019. A maternity care box will be offered to 70 women with uncomplicated pregnancies and 30 women with hypertensive pregnancies. They'll be instructed to conduct the urine test and BP measure before attending their antenatal appointment. Women with hypertensive pregnancies will receive additional Dip.io test kits to increase testing frequency between appointments. Shifting routine testing to the home has the potential to:

Improve women's experience and involvement in their health
Reduce appointment time spent on routine testing to enable midwives to focus on clinical and patient-facing activity.
Mitigate against risks in at-risk pregnancies through more frequent home testing to early detect complications (e.g. preeclampsia).
reduce up to 60% of Day Assessment Unit visits needed for at-risk pregnancies during the third trimester (if normal results).
Embed electronic results directly into clinical record.
This model has been implemented in non-NHS healthcare settings and has received positive feedback from both patients and clinicians. This study will evaluate the feasibility and acceptability of the model in an NHS setting, to generate evidence to help scale the innovation, make product improvements and test the Budget Impact Model designed by Kent Surrey &amp;amp; Sussex AHSN.</ns2:abstractText></ns2:project>