REsponsible roLl-out of E-heAlth Through Systematic Evaluation - Heart Failure Study

REsponsible roLl-out of E-heAlth Through Systematic Evaluation - Heart Failure Study

Telemedicine is gradually becoming accepted in heart failure (HF) management. Meta-analyses show a positive effect of telemedicine on hospital admission, length of stay, mortality, and costs. However, the magnitude of the effect is heterogeneous because of the variety in the HF population using telemedicine, components of telemedicine, and variety in considered costs. Despite the lack of clear guidance how to implement telemedicine within routine HF management, implementation of telemedicine is advocated by payers, private companies, and patient organizations.

In this nationwide study the investigators aim to identify in which subgroup of HF patients telemedicine is (cost-)effective, and which intervention components of telemedicine are most (cost-)effective.

The objectives of the study are to examine:

1. which HF patient characteristics are related to an increase in number of days spent outside the hospital within one year of follow-up, when telemedicine is part of regular HF care compared to regular HF care alone?
2. which HF patient characteristics are related to cost-effectiveness when telemedicine is part of regular care compared to regular HF care alone?
3. which components of telemedicine as part of regular HF care lead to an increase in number of days spent outside the hospital within one year of follow-up?
4. which components of telemedicine as part of regular HF care are cost-effective?

The main focus of this study is on patient-related subgroup analyses with telemedicine. The patient-related subgroups are identified by a systematic literature review of randomized-controlled trials of telemedicine: (1) age, (2) severity of HF (NYHA class at baseline), (3) sex (female compared to male), (4) socio-economic status (SES) (HF patients with higher SES compared to lower SES), (5) presence of depression, (6) Type of heart failure (LVEF: HFrEF, HFmrEF, HFpEF), (7) presence of atrial fibrillation (AF). In an additional analysis, (8) heterogeneity across time of diagnosis will be explored (recently diagnosed compared to not recently diagnosed).

To answer the four research questions a RELEASE-HF database will be set up. The RELEASE-HF database will be composed from various data sources:

1. National Heart Failure Registry (abbreviated as Registry; a patient registry),
2. Interviews with clinicians about telemedicine features on hospital level,
3. Interviews with finance department staff about costs in HF care (including telemedicine use),
4. Electronic Health Record (EHR) data about telemedicine (including supplier system data)
5. External national registries and/or databases as Statistics Netherlands (CBS), declaration data (Vektis), Dutch Hospital Data (DHD) or PHARMO.

Inclusion Criteria:

• All heart failure patients newly admitted to a hospital outpatient clinic for HF
• All phenotypes of heart failure that meet the ESC 2021 guideline
• Patient who has been diagnosed with heart failure in a setting other than the one where the patient currently presents (primary, secondary or tertiary care)