Evaluating patients access to health data gathered through RPM and wearable systems : literature and digital tools review
Stefanescu, Bianca-Ioana (2026)
Kandidaatintyö
2026
School of Engineering Science, Tietotekniikka
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2026052352478
https://urn.fi/URN:NBN:fi-fe2026052352478
Tiivistelmä
This thesis examines how much control do patients, particularly those with technical and software skills, can realistically exercise over the data generated by RPM systems and wearable devices.
The study combines literature review and a digital tools analysis. The literature review examines research related to RPM technologies, wearable ecosystems, interoperability standards, data governance, and open-source patient empowerment initiatives. The practical analysis evaluates six selected systems: Apple HealthKit, Dexcom, Fitbit, Garmin, Mobistudy, and WatchWitch. The systems are compared based on six criteria: data accessibility, data granularity, API availability, export possibilities, technical barriers, and system openness.
The findings suggest that despite the majority of the systems providing some degree of interoperability and API-based access, meaningful patient control remains restricted by proprietary infrastructures, authorization systems, platform policies, and ecosystem dependencies. Commercial wearable ecosystems generally seem to provide processed platform-defined data rather than unrestricted, raw sensor data. Open-source approaches demonstrate that greater transparency and autonomy is technically possible, however, they often require considerable technical expertise and complex implementation processes.
The thesis concludes that technically skilled patients can achieve greater access to RPM and wearable-generated data, particularly though APIs, interoperability mechanisms, and open-source tools. However, full autonomy over PGHD remains limited by concerns, as well as infrastructural, commercial and policy-based constraints embedded within digital healthcare ecosystems. The findings additionally suggest that the existence of interoperability mechanisms alone does not automatically guarantee meaningful patient autonomy over wearable-generated health data.
The study combines literature review and a digital tools analysis. The literature review examines research related to RPM technologies, wearable ecosystems, interoperability standards, data governance, and open-source patient empowerment initiatives. The practical analysis evaluates six selected systems: Apple HealthKit, Dexcom, Fitbit, Garmin, Mobistudy, and WatchWitch. The systems are compared based on six criteria: data accessibility, data granularity, API availability, export possibilities, technical barriers, and system openness.
The findings suggest that despite the majority of the systems providing some degree of interoperability and API-based access, meaningful patient control remains restricted by proprietary infrastructures, authorization systems, platform policies, and ecosystem dependencies. Commercial wearable ecosystems generally seem to provide processed platform-defined data rather than unrestricted, raw sensor data. Open-source approaches demonstrate that greater transparency and autonomy is technically possible, however, they often require considerable technical expertise and complex implementation processes.
The thesis concludes that technically skilled patients can achieve greater access to RPM and wearable-generated data, particularly though APIs, interoperability mechanisms, and open-source tools. However, full autonomy over PGHD remains limited by concerns, as well as infrastructural, commercial and policy-based constraints embedded within digital healthcare ecosystems. The findings additionally suggest that the existence of interoperability mechanisms alone does not automatically guarantee meaningful patient autonomy over wearable-generated health data.