Usefulness of telemedicine-based heart failure monitoring according to “eHealth literacy” domains: insights from the iCOR randomised controlled trial
Authors: Yun Viladomat S , Enjuanes C , Calero-Molina E , Hidalgo E , Jose-Bazan N , Ruiz M , Jimenez-Marrero S , Garay A , Alcoberro L , Ras M , Ramos R , Pons-Riverola A , Moliner P , Comin-Colet J 
Published: October 2022

Abstract

Background/Introduction
The potential positive effect of electronic health (eHealth)-based heart failure (HF) monitoring remains uncertain, largely due to the heterogeneity of the studies published to date. A subgroup of patients in which its key role is particularly uncertain is in the “low literacy” or “computer or digital illiterate” patients mainly due to telemedicine (TM)-based strategies have been often discouraged on the basis of a foreseeable limited benefit in them.

Purpose
The aim of this study was to determine the effectiveness of a TM-based managed care solution across literacy levels and information and communications technology (ICT) skills.

Methods
We performed a sub-analysis on the basis of two literacy domains (traditional and computer literacy) encompassed in the definition of “eHealth literacy” to the HF-patients included in the “insuficiència Cardíaca Optimitzaciό Remota” (iCOR) randomised study comparing TM vs. usual care (UC) in HF-patients. The primary study endpoint was the incidence of a non-fatal HF event after 6 months of inclusion. The event rates of primary (the occurrence of non-fatal HF event) and secondary (all-cause hospitalization, all cause death and the composite endpoint combining of allcause death or non-fatal HF events) study endpoints were calculated for each literacy domains and its combination. Cox proportional-hazards regression models were used to evaluate the effect of “eHealth literacy” dimensions, treatment group and the interaction term “eHealth literacy” domains by treatment group on study endpoints, and p-value was used to compare the different curves.

Results
178 patients were analysed (81 TM vs 90 UC). As far as the “traditional literacy” analyses, 65% of patients had only elementary education and the 6% had no literacy qualifications, defining the low-educated subgroup as “lower literacy” (126 patients, 71%). All the other patients were classified in the “middle or higher literacy” (52 patients, 29%) subgroup. Moreover, concerning new technological management, 128 patients (72%) referred presenting moderate to high difficulties in its handling, constituting the “lower ICT skills” subgroup. The remaining 28% (50 patients) were allocated into the “middle or higher ICT skills” subgroup due to their minor handicap in their ICT use.
The beneficial effect of TM compared to UC strategy was consistent across all literacy domains (pvalue for interaction 0.207 and 0.117 respectively). The risk of experiencing a primary event was significantly lower in patients that underwent allocation to the TM arm compared to UC in both clustered in the “lower literacy” (p-value=0.001) (Picture 1) and those allocated to the “lower ICT skills” (p-value=0.001) (Picture 2) subgroup.

Conclusions
Non-invasive eHealth-based HF monitoring tools are effective compared to UC in preventing HF events in the early post-discharge period, regardless of two “eHealth literacy” domains (“traditional and computer literacy”).

Funding Acknowledgement
Type of funding sources: None.