OC31 Adherence to electronic monitoring of PROs according with multidimensional biophenotypes (MBP)
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Le résumé fourni par la source
Background The electronic monitoring of PROMs (ePROMs) has been suggested as a gold standard for QoL assessment in PWH. Adherence to ePROMs is a challenging aspect, frequently limiting the wide use of ePROMs in clinical practice. To implement these outcomes we applied a multidimensional profiling of PWH to identify clusters with different adherence to ePROMs. Materials and Methods A cohort of adult PWH on cART—diagnosed with HIV for more than 3 months, having provided informed consent, and capable of using smart devices—was enrolled in the Multiface study across three Italian centers. Comprehensive remote assessments were conducted using the Healthentia SaMD (Software-as-Medical-Device), which enabled the submission of a battery of questionnaires (HIVSRQ, ADH5Q, GAD-7, PHQ-9, HSS) through a mobile App. An algorithm-based pathway, initiated by the screening questionnaire (EQ5D3L), tailored the assessment battery to individual needs and generated real-time alerts for altered responses. Self-reported data (demographics, questionnaire answers, tags and alerts) was extracted from the Healthentia database. Weekly EQ5D3L answers were used to calculate response rates, further analyzed to harmonize follow-up time to a maximum of 1 year for all patients across all three pilot sites. Correlation analysis was performed using the Pearson correlation coefficient to identify the most important variables and their potential associations among demographics, symptoms, quality of life aspects and app usage metrics. K-means algorithm was fitted on selected variables and optimized in terms of cluster number to classify patients in different groups (MBP) with certain adherence and symptomatology. Results 228 PWH responded at least once (female 18.4%, mean age 50.0 [SD +11.1]). The mean EQ5D3L response rate was 29.8 (SD+15.9). The cluster analysis yielded five MBP based on the means in demographics, health status, mental health and symptoms (figure 1A): MBP 1 (N=91; 40%) (woman, good general health status, without identified specific needs); MBP2 (N=7, 3%) (older, relatively low general health status, high burden of mental health needs); MBP3 (N=5; 2%) (low general health status, high burden of MH needs); MBP4 (N=28; 12%) (quite old, relatively low general health status, without identified specific needs); MBP5 (N=47; 21%) (young, good health, without specific needs). The mean response rate to EQ5D, identified as proxy of app response, according with different phenotypes was shown in figure 1B, with highest response in MBP1 (46.1, SD+10.6) and lowest in MBP5 (17.9, +7.3). Conclusions Adherence to ePROMs was found to be relatively low. Cluster analysis identified MBP of PWHs with different adherence to ePROMs: low adherence was found in MBP with more complex MH and symptoms needs (MBP3 and MBP4). A further in-depth multidimensional approach could better identify PWH profiles for tailored systems to enhance ePROM use and engage less responsive PWH.
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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- OC31 Adherence to electronic monitoring of PROs according with multidimensional biophenotypes (MBP)
- Date Crossref
- 01/06/2025
- Éditeur
- BMJ Publishing Group Ltd
- Type
- proceedings-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
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Università Cattolica del Sacro Cuore, Agostino Gemelli University Polyclinic et Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia, avec 9 autres affiliations.
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