Get Quality-Controlled Outcomes with Lower Patient Dropout

High Level Patient Engagement

Research on respiratory illness requires continuous testing of large patient groups. Integrity of data requires reliable monitoring methods. KAMU® provides a solution that works through the whole chain of finding, recruiting, monitoring, treating and retaining patients during the study. Meticulous tracking and reliable adherence during the study are especially important for approval of the new expensive biological medicines.

KAMU Asthma® is a new way of thinking respiratory care. It enables the patient to take a spirometry test at home and track their symptoms and adherence to medication with quick, easy-to-use and comparable questionnaires. Combining data about external triggers to this patient-provided information, KAMU creates reports that help both the patient and the researcher understand the condition better.

Better Outcomes with Patient Reported Data

Get the full experience and benefits of KAMU Asthma with KAMU Spiro

KAMU enables faster and easier recruitment of test cohorts, as the patient can monitor their lungs individually regardless of time and place. When the burden of participating in a test is smaller, the patient dropout number is also lower. User interface, both on the spirometer and the smartphone app, can be modified to hide the actual test result from the patient when needed. The KAMU service supports server-side configurable tasks and reminders for the patient, driving adherence and thus leading to coherent, good-quality data. The platform also provides access to data from 200+ wearable and measurement devices.

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”While KAMU provides us with a possibility to deliver even more patient-friendly digital service and a potential for remote consulting of the asthmatic’s lung condition, it can also help enrich the current data available in our biobank. Combining the comprehensive Real World Data of KAMU user’s lung condition with other patient reported data (e.g. medication, activity, weather) and our current data can result in a unique data set.”