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Patient-Generated Health Data Elements: Developing a Data Model for Preference-Sensitive Conditions

  • Anna Vahteristo
  • , Milla Rosenlund
  • , Niina Reinikainen
  • , Virpi Jylhä
  • , Hanna Kuusisto

Tutkimustuotos: KonferenssiartikkeliTieteellinenvertaisarvioitu

1 Sitaatiot (Scopus)
2 Lataukset (Pure)

Abstrakti

Patient-generated health data (PGHD) refers to data generated by or from patients. Most often, PGHD is verbal and written, but today, it is increasingly digital. PGHD is considered crucial in shared decision-making (SDM), fostering patient empowerment and patients' active participation in health management. Studies have shown that SDM is especially valuable in preference-sensitive conditions such as multiple sclerosis (MS) and epilepsy. This study aimed to enhance the understanding of PGHD elements among people with epilepsy or MS (pwE/MS) by investigating PGHD currently shared and wished to be shared with healthcare professionals (HCPs). We found that pwE/MS consider numerous types of PGHD to be important in decision-making concerning the care. However, there are indications that pwE/MS are lacking the possibility to transmit data digitally. Development of digital health services could facilitate the integration of PGHD into care, but its meaningful use in SDM requires greater recognition and engagement by HCPs.

AlkuperäiskieliEnglanti
OtsikkoMEDINFO 2025 — Healthcare Smart × Medicine Deep
KustantajaIOS Press
Sivut440-444
Vuosikerta329
ISBN (elektroninen)978-1-64368-608-0
DOI - pysyväislinkit
TilaJulkaistu - 2025
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaWorld Congress on Medical and Health Informatics - Taipei, Taiwan
Kesto: 9 elok. 202513 elok. 2025

Julkaisusarja

NimiStudies in health technology and informatics
ISSN (painettu)0926-9630

Conference

ConferenceWorld Congress on Medical and Health Informatics
Maa/AlueTaiwan
KaupunkiTaipei
Ajanjakso9/08/2513/08/25

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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