2025 ERS临床实践指南：家庭机械通气中的远程医疗
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The level and certainty of evidence for use of telemedicine in the initiation and follow-up of patients on home mechanical ventilation is currently very limited. However, technological advances are expected to drive further research and telemedicine use. https://bit.ly/45wkk4u
Cite this article as: Duiverman ML, Ribeiro C, Tonia T, et al. European Respiratory Society clinical practice guideline on telemedicine in home mechanical ventilation. Eur Respir J 2025; 66: 2500094 [DOI: 10.1183/13993003.00094-2025].
Copyright © The authors 2025. For reproduction rights and permissions contact permissions@ersnet.org
This article has an editorial commentary: https://doi.org/10.1183/13993003.01636-2025
Received: 24 Jan 2025 Accepted: 27 April 2025
Abstract
Background With the increasing prevalence of patients on home mechanical ventilation (HMV), changing indications, shortage of hospital resources and rapidly evolving technology, there is an urgent need for evaluating the added value of telemedicine in initiation and follow-up of HMV. This European Respiratory Society (ERS) clinical practice guideline provides evidence-based recommendations on the use of telemedicine in HMV.
Methods The ERS Task Force consisted of 20 members, including a patient representative and her caregiver. The Task Force addressed five PICO (Population, Intervention, Comparison, Outcome) questions and three narrative questions. Systematic searches were performed in MEDLINE, Embase, Cochrane and CINAHL. Evidence was synthesised by conducting meta-analyses, when possible, or when not, narratively. Certainty of evidence was rated with GRADE (Grading of Recommendations Assessment, Development and Evaluation) guidance. The Evidence-to-Decision framework was used to decide on the direction and formulate strengths of recommendations.
Results The panel makes a conditional recommendation for the initiation of HMV with telemedicine in patients with neuromuscular diseases or restrictive thoracic diseases and in patients with COPD. No recommendation could be made for obesity hypoventilation syndrome. The panel conditionally recommends the use of telemedicine for the follow-up of patients on HMV, although could not make
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recommendations on parameters to be monitored. Suggestions were mainly based on theoretical benefits and patient preferences, as our confidence in the evidence was low.
Conclusions With these guidelines, clinical practice recommendations are provided for the use of telemedicine in HMV. Technological advances and the use of advanced data processing algorithms and artificial intelligence were identified as drivers for future research and telemedicine use.
Introduction
The use of home mechanical ventilation (HMV) is increasing worldwide. According to the Eurovent study published in 2005, HMV prevalence in Europe ranged from 0.1 to 6.6 per 100 000 people [1]. More recent data showed a prevalence of 3.9 per 100 000 in Hungary [2] and up to 38 per 100 000 inhabitants in the Cantons of Geneva and Vaud in Switzerland [3], reflecting a 2.5-fold increase in HMV prescriptions since 2000 in this area.
Furthermore, the population of patients being initiated on HMV has changed over time with differences in the proportions of diagnostic indication for HMV. While HMV was initially used mainly in patients with neuromuscular diseases (NMDs) and restrictive thoracic diseases (RTDs), more recently, its use in patients with obesity hypoventilation syndrome (OHS) and COPD has grown substantially in many centres [4, 5]. Moreover, the prevalence of paediatric HMV has also increased, with more ventilator-dependent children transitioning to adult care [6].
To ensure successful long-term HMV, patients need careful and close monitoring, training, and support by a multidisciplinary healthcare team. Furthermore, robust data collection is essential to drive research and improve future care. Despite its complexity, there are several compelling reasons to provide home-based monitoring and support for patients on HMV. First, patients may prefer receiving assistance and support for their HMV therapy in the familiarity and comfort of their own homes, where the therapy is usually carried out [7]. Additionally, as inpatient resources for elective chronic care are decreasing, home support emerges as an essential alternative for ensuring the delivery of patient care. During the COVID-19 pandemic, many HMV centres experienced severe problems initiating HMV promptly and delivering regular follow-up [8, 9]. To overcome these challenges, the use of information and communication technologies (ICTs) for remote health service delivery, otherwise known as telemedicine (supplementary material S1), was widespread during the pandemic and it has great potential to contribute to the future delivery of HMV [10]. The European Commission has presented the "Europe's Digital Decade" project, aiming to digitally transform Europe by 2030 [11]. Also, there is increasing interest in home monitoring of chronic lung diseases in general [12]. In the field of HMV, digital health might improve access to this treatment also in areas with limited hospital resources, and improve the quality of ventilatory support and care. Ideally, telemedicine could reduce inpatient hospital care, decrease healthcare consumption, lower costs and foster a more patient-centred approach.
In 2016, a European Respiratory Society (ERS) Task Force published a statement on telemonitoring of ventilator-dependent patients aiming to describe commonly accepted indications, follow-up schedules, equipment and facilities, and legal issues [13]. Since then, well-designed studies have been conducted to explore various applications of telemedicine in the adaptation and follow-up of patients receiving long-term HMV, leading to significant advancements in this field [14–19].
To remain contemporary in this rapidly evolving field, there is an urgent need for evidence-based guidelines to address the use, effectiveness, outcomes and challenges of different telemedicine solutions in HMV. Technology is advancing rapidly, with most ventilator companies nowadays providing online platforms for continuous monitoring of ventilator data, although for most platforms clinicians can only obtain daily trends and no raw data. Connectivity is also being expanded to include gas exchange and polygraphic monitoring, which can be displayed synchronously alongside more traditional ventilator-derived data [20]. Independent platforms have also been developed that enable connection of data from different resources, ranging from video-consultations to digital questionnaires, vital signs monitoring, gas exchange and ventilator data. This opens opportunities for a comprehensive “overall care package” using telemedicine and studies are currently underway to assess its value during follow-up care [21, 22].
However, regulatory and privacy issues have become more stringent, particularly since the implementation of the European Union's General Data Protection Regulation in 2018 [23]. Furthermore, patient and family preferences have changed over time. Many patients may be reluctant to use telemedicine due to privacy concerns (it may feel like “big brother is watching you”) and to the perceived loss of personal contact with healthcare teams [24]. However, telemedicine may also allow patients to feel more secure and confident about being in their own home while undertaking a complex medical intervention such as HMV. Although
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age has been identified as a barrier to accessing health technology, older patients are now more willing to use ICT solutions [25].
The aim of this clinical practice guideline (CPG) is to provide recommendations for the use of telemedicine in initiation and follow-up of HMV in patients with chronic respiratory failure, focusing on its effectiveness, patient preference and adherence to therapy. Furthermore, we will address advances in telemedicine solutions, considering its facilitators and barriers, regional differences in internet connectivity, reimbursement policies, legal regulations, organisation of care, regulatory issues, and patient perspectives, offering a roadmap for implementation in care.
Methods
The ERS Task Force (TF-2022-03), co-chaired by M.L. Duiverman, C. Crimi and C. Ribeiro (early-career co-chair), consisted of 20 members of different backgrounds (physicians, nurse specialists, respiratory therapist, physiotherapist, methodologist, epidemiologist and engineer) and from different countries. The panel included a representative from the European Lung Foundation (ELF), a patient representative actively using HMV and her partner/caregiver. The patient representative and her partner were actively engaged in the discussions. One of the Task Force members (A. Hazenberg), together with the ELF representative (C. Williams), held three separate meetings with the patient representative: one at the start of the process to discuss the aims of the Task Force and expectations, another to discuss their input for formulating recommendations, and the last one to review recommendations and provide final input. The lead ERS methodologist (T. Tonia) overviewed the guideline development and ensured adherence to ERS methodological standards but did not participate in the formulation of questions or recommendations. An information specialist (S. van der Werf) performed the literature searches for all questions. An epidemiologist (M. de Boer) performed the meta-analyses. Subgroups of four panellists were formed to work on each question. Three face-to-face and two virtual meetings were held between November 2022 and September 2024. Conflicts of interest were declared and managed according to ERS policies.
Formulation of questions and selection of outcomes
The ERS guideline was developed according to the ERS standards and methodology for CPG development [26, 27]. During the first meeting, panelists discussed and agreed upon the following main topics to address: the value of telemedicine in HMV initiation (PICO (Population, Intervention, Comparison, Outcome) 1–3), telemedicine in the follow-up of patients on HMV (PICO 4 and 5), and patient and caregiver views on facilitators, barriers, logistical and regulatory aspects, and future perspectives (Narrative Questions 1–3), resulting in five PICO questions and three narrative questions (tables 1 and 2 and supplementary material S3).
Members, anonymously, rated the importance of outcomes for clinical decision for each PICO question, through online voting, using a scoring system of 0–9 (1–3: not important; 4–6: important; 7–9: critical) following GRADE (Grading of Recommendations Assessment, Development and Evaluation) [28]. Outcome ratings were further discussed during a meeting to reach consensus. Only outcomes rated as critical or important were included.
Literature searches
An information specialist of the Central Library of the University Medical Center Groningen (Groningen, The Netherlands) conducted the literature searches: a combined search strategy based on three concepts (search blocks) was performed: 1) mechanical ventilation, 2) home and 3) telemonitoring. This revealed a total of 1823 papers. Databases searched were MEDLINE (OVID), Embase (OVID), Cochrane Database of Systematic Reviews and Cochrane Central Register of Controlled Trials (Cochrane Library), and CINAHL (EBSCOhost). Initial searches were performed between January and February 2023, and updated in October 2024. The search process and full search strategies are summarised in the supplementary material.
Search results were imported in the Rayyan web application and screened in two phases (title/abstract and full-text) independently by two panellists from each subgroup for eligibility. Articles for which no agreement was reached were discussed with one of the co-chairs. Whenever randomised controlled trials (RCTs) were available, those were used as the main body of evidence. Also, relevant (systematic) reviews were searched for additional references. Relevant articles not identified in the initial search could be added by the Task Force members (supplementary material S5).
Evidence syntheses, assessment of quality of evidence and strength of recommendations
Data extraction for each PICO was performed by one panel member and reviewed by other panellists. For PICO 1 and 3, the main evidence was provided by two similar RCTs, including patients with NMD or
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|Questions|Recommendation| |---|---| |Telemedicine during initiation of HMV|| |PICO 1|In patients with NMD or RTD, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine?| |PICO 2|In patients with COPD, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine?| |PICO 3|In patients with OHS, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine?| |Teilemedicine during HMV follow-up|| |PICO 4|Should telemedicine be used to follow-up patients on long-term HMV compared to follow-up without telemedicine?| |PICO 5|Should extensive remote monitoring (e.g. remote gas exchange, sleep quality/apnoea, patient-ventilator synchrony) be used compared to limited remote monitoring only using ventilator data in patients on long-term HMV?| |NMD: neuromuscular disease; RTD: restrictive thoracic disease; OHS: obesity hypoventilation syndrome; HMV: home mechanical ventilation.||
RTD (population of PICO 1) and patients with OHS (population of PICO 3). Therefore, we requested the authors of these studies to provide separate data for these patient groups to perform a meta-analysis and create a summary table. Evidence synthesis using meta-analysis was only possible for PICO 1 and 4, because of the limited evidence available.
RCTs were assessed for risk of bias using the Cochrane Risk of Bias tool (version 1) [29] by one panellist, discussed and agreed upon by another, and, if disagreement, by two other panellists. GRADE evidence profiles were created for each PICO question using the GRADEpro guideline development tool (www. gradepro.org), and the certainty of evidence was assessed with GRADE considering risk of bias, indirectness, inconsistency, imprecision and publication bias/other bias [30]. The GRADE evidence profiles were based on RCTs only. The overall quality of evidence is a combined rating of the quality of evidence across all critical outcomes, and it is determined by the lowest quality of evidence for any of the critical outcomes [31]. Narrative questions were assessed via narrative review only, with no risk of bias assessment and GRADEing, following ERS rules [26].
|Questions|Key considerations| |---|---| |NQ 1|What are the patients' and caregivers' views, experiences and challenges with telemedicine in HMV?| |NQ 2|What are the barriers and facilitators including regional differences which influence the implementation of telemedicine in the initiation and follow-up of HMV?| |NQ 3|What are recent and expected technological advances and how might these influence the implementation and effectiveness of initiation and follow-up of HMV with telemedicine?| |HMV: home mechanical ventilation.||
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Formulating recommendations
GRADE Evidence-to-Decision (EtD) frameworks were generated for each PICO and used to structure the discussions and to document the different factors considered for the strength of recommendations [32]. Evidence summary tables were generated for narrative questions (supplementary material S7 and S8) The EtD frameworks incorporated the evidence and its level of certainty and other factors such as values and preferences of people with illness, resources, feasibility, health equity and acceptability, as well as clinical experience and additional considerations stemming from other evidence that were not part of the main body of evidence. Prior to and after the dedicated recommendations meetings, the EtD frameworks were discussed with the patient representative and her partner to include additional considerations regarding patient preferences. The strength of the recommendations was rated as either strong (phrased as “we recommend”) or conditional (phrased as “we suggest”) [33].
For narrative questions, evidence was reviewed narratively to develop recommendations. Findings were grouped into key themes and synthesised in a summary text. For all the questions, recommendations for research were drafted by the subgroup and discussed within the Task Force until consensus was reached. The final recommendations proposed were discussed, edited, voted and approved by all Task Force members in a recommendations hybrid meeting.
Results
The number of studies identified and selected for each question is shown in a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram in supplementary material S5. The GRADE evidence profiles and EtD frameworks are shown in supplementary material S7. The recommendations for the PICO questions are listed in table 1.
Initiation of long-term HMV with the use of telemedicine (PICO 1–3)
PICO 1: In patients with NMD or RTD, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine?
Recommendation
In patients with NMD or RTD we suggest the initiation of HMV with telemedicine versus initiation of HMV without telemedicine. (Conditional recommendation for the intervention; very low certainty of evidence.)
Justification
A conditional recommendation was chosen based on the non-inferiority of this intervention versus standard in-hospital initiation in our meta-analysis regarding adherence to HMV, efficacy (measured by arterial partial pressure of carbon dioxide ($P_{\text{acCO}_2}$)), health-related quality of life (HRQoL) and considering patient preferences.
Summary of main findings
From the screening of titles and abstracts, 26 papers were retrieved for full-text screening and two RCTs fulfilled the inclusion/exclusion criteria. The meta-analysis of the two RCTs (supplementary material S7) showed similar results in the telemedicine group compared to the standard in-hospital initiation group regarding adherence to HMV (mean difference (MD) -0.02 (95% CI -1.93-1.88) h), reduction in daytime PaCO₂ (MD -0.04 (95% CI -0.41-0.31) kPa), change in HRQoL measured with the Severe Respiratory Insufficiency (SRI) questionnaire (MD 0.33 (95% CI -3.42-4.07) points), the Medical Outcome Study Short Form Survey (SF-36) mental health component (MD 0.74 (95% CI -4.77-6.24) points) and the SF-36 physical function component (MD -2.73 (95% CI -8.98-3.52) points), and a tendency towards a greater improvement in HRQoL measured with the Maugeri Respiratory Failure (MRF) questionnaire (MD -6.52 (95% CI -13.83-0.78) points) [14, 19]. However, it seemed that home initiation with telemedicine showed less reduction in night-time transcutaneous partial pressure of carbon dioxide (PtcCO₂) (MD 0.89 (95% CI 0.19-1.6) kPa) at 6 months. Of note, technical problems did occur in 11 out of the 38 patients included in one study [14]. Despite these problems, it appeared that clinical outcomes and safety were not compromised, although technical problems may impact costs or resource time allocation due to unplanned home visits. Still, both studies showed significant cost savings in the telemonitoring arm. None of the studies addressed caregiver-related costs or burden.
Additional considerations
One additional conference abstract was found showing that in 21 patients with amyotrophic lateral sclerosis (ALS) using telemonitoring through a software ventilator platform was acceptable and feasible to support initiation and sustained use of HMV [34]. A recent French retrospective study in 265 patients with ALS found that home initiation supported by remote monitoring of ventilator data, performed in the 184 out of
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265 ALS patients that were normocapnic at baseline and had a caregiver at home, was effective and decreased the mean delay to initiation [35]. Furthermore, ventilator usage was better compared to the patients initiated in the hospital (at 1 month, 70% of the home-initiated and 52% of the in-hospital-initiated patients used their ventilator >4 h). However, comparisons between these two groups may be biased, as the decision to start treatment at home was based on having less severe respiratory compromise in the home group. Additionally, after the search of 30 September 2024, an additional randomised controlled pilot trial was detected comparing in-hospital initiation during a day admission with at-home initiation with intensive follow-up using remote monitoring of ventilator data (NIV@Home) in clinically stable patients (20 with motor neuron disease and three with other NMDs) [36]. Unfortunately, the study reported several protocol deviations, including missing interventions in patients with low adherence due to COVID-19-related workloads and deviations from the usual care protocol. Therefore, we decided not to include the paper in the meta-analysis. In short, although NIV@Home was found to be feasible and safe (no adverse events), it required additional work from the healthcare professionals involved. There were no statistically significant differences in adherence or symptom scores between the groups. Interestingly, the study also investigated patients' and caregivers' opinions: participants in the NIV@Home group reported substantial advantages to receiving care at home, particularly in terms of reduced travel and a more trustworthy environment [36].
In patients with NMD, studies with home [37] or outpatient adaptation [38–45] without telemedicine have also shown satisfactory results with similar adherence [37–42, 44, 45], similar improvements in gas exchange [37, 38, 40–42, 44, 45], reduced waiting time to HMV initiation [40], similar or even better HRQoL and symptoms [37, 41], and similar number of unscheduled visits and equal side-effects compared to hospital-based setup strategies [39, 44]. However, the studies were small, the organisation of the setup variable (with very different interventions ranging from a single daytime session to up to eight daytime supervised sessions at home), the patients included were in general stable, having a slowly progressive NMD or NMD in earlier stages, and were living close to the HMV centre. Also, these studies describe technical difficulties related to the use of the ventilator that may require significant sessions in the hospital or sessions at home that can burden the patient or healthcare system [37–39, 45]. Finally, sophisticated nocturnal monitoring to detect (additional) sleep-related breathing disturbances was not performed.
Regarding patient perspectives, the patient and her caregiver and ELF representative that are part of this Task Force stated that most patients reported positive experiences and expectations with telemedicine, such as fewer hospital visits, lower infection risks, less travelling, better remote communication with their physician and easier getting in touch with physicians to get an appointment. The patient representatives also mentioned positive expectations from real-time monitoring in the future, including self-monitoring and real-time adjustments of ventilator settings. However, it has to be considered that telemedicine may not be the ideal option for every patient. Some patients may prefer a closer in-person follow-up or might struggle with technology, e.g. patients with low technical or e-health literacy may have difficulties setting up all the requirements for the telemedicine approach. It was mentioned that education and online learning should always be available to support patients and caregivers. Furthermore, the severity of patients' illness may be a factor to consider, and studies have not included marginalised or minority groups [46]. Also, the acceptability of the intervention might depend on the physicians/healthcare professionals/organisations availability, time, digital proficiency, willingness to adopt new technologies and openness to adapt to a new work process, as well as costs for the healthcare system.
PICO 2: In patients with COPD, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine?
Recommendation
In patients with COPD, we suggest the initiation of HMV with telemedicine versus initiation of HMV without telemedicine. (Conditional recommendation for the intervention; very low certainty of evidence.)
Justification
A conditional recommendation was chosen based on the non-inferiority of this intervention versus standard in-hospital initiation (in the only RCT that fulfilled the inclusion criteria) regarding adherence to HMV, exacerbation frequency, efficacy (measured by $P_{\text{ACO}_2}$), side-effects and HRQoL, and considering patient preferences [15].
Summary of main findings
From the screening of titles and abstracts, 20 papers were retrieved for full-text screening and one study fulfilled the inclusion/exclusion criteria. One RCT was identified, showing similar results regarding adherence to HMV (MD 0.66 (95% CI -1.76-0.42) h), exacerbation frequency (MD -0.9 (95% CI -0.9-0.7) exacerbations per 6 months), change in daytime $P_{\text{acO}_2}$ (MD 0.04 (95% CI -0.31-0.38) kPa), change in
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night-time $P_{tcCO_2}$ (MD -0.01 kPa (95% CI -0.42-0.41) kPa), change in HRQoL measured with the SRI (MD -1.5 (95% CI -12-9) points), and a similar number of dropouts and therapy side-effects [15]. However, the study stated that technical problems with nocturnal measurements and transcutaneous gas exchange data transfer occurred frequently, necessitating additional home visits or daytime measurements. Despite these additional visits in the telemonitoring group, the study showed significant cost savings for the addition of telemonitoring compared with ward-based inpatient HMV setups. Caregiver-related costs or burden were not assessed.
Additional considerations
Patient perspectives were similar for all diseases and are described in PICO 1. Feasibility depends on the possibility of organising remote monitoring and initiation within a healthcare system (availability of hardware, software, and the organisation to visit patients at home and monitor remotely) on a large scale due to the high prevalence of COPD patients. A certain percentage of patients will start HMV at the hospital, such as COPD patients during an exacerbation [47], patients in unstable condition or with unstable comorbidities, or patients living in a situation where home initiation is not desirable or feasible.
No formal cost-effectiveness analysis was performed, and costs related to adaptation with telemedicine in routine clinical practice may be higher due to resource allocation, travel costs, equipment costs and availability. Cost savings are associated with the different national and regional healthcare organisation practices, such as the standardised approach adopted in various countries for initiating HMV in COPD patients. Recently, an uncontrolled study showed that in patients with COPD, outpatient adaptation without telemedicine resulted in good compliance, significant improvement in blood gas analysis and a positive impact in short-term HRQoL [43], and patients perceived this approach as a positive experience [42].
PICO 3: In patients with OHS, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine?
Recommendation
In patients with OHS, due to the lack of evidence, we were unable to make any recommendation for or against the initiation of HMV with the use of telemedicine versus initiation of HMV without the use of telemedicine. (No recommendation for or against the intervention; very low certainty of evidence.)
Justification
No recommendation can be made for or against the intervention, as no RCT or non-controlled trial met the inclusion criteria in this patient population, and only individual patient data from a very limited sample of patients from two RCTs with mainly patients with NMDs or RTDs were available. This sample included four patients with OHS initiated at home with telemonitoring and four patients with OHS who initiated HMV in the inpatient setting [14].
Summary of main findings
From the screening of titles and abstracts, eight papers were retrieved for full-text screening and two papers partially fulfilled the inclusion/exclusion criteria, as the studies represented a mixed population and individual patient data for patients with OHS were available for the Task Force. This individual patient data extracted from two RCTs showed similar results in terms of adherence, change in daytime $P_{\text{ACO}_2}$, and improvement in HRQoL assessed by the SRI and SF-36 (mental health), but a reduction in HRQoL assessed by the MRF and SF-36 (physical function), although there were substantial interindividual differences in outcomes.
Additional considerations
Patients with OHS typically experience a more favourable prognosis when initiated on HMV compared to those with COPD and other RTDs such as rapidly progressive NMDs, especially when HMV is initiated electively [48]. Since most patients with OHS also have obstructive sleep apnoea [49, 50], implementing HMV at home with telemedicine is considered a safe option for this population, as recommended by the American Academy of Sleep Medicine [51]. As one of the main aims of positive pressure support in OHS is to reduce obstructive events and respiratory-related arousal, the need for overnight monitoring, which might especially be provided through telemonitoring, is usually evident.
While the initiation of HMV with the use of telemedicine has many theoretical advantages, including feasibility, effectiveness and a personalised approach, there remain areas of uncertainty, requiring further investigation. There are limited data on alternatives to inpatient adaptation without the use of telemedicine, such as outpatient day acclimatisation [44] or at-home titration of HMV with autotitration modes [52], showing that this strategy might also be feasible and effective. However, complete unsupervised titration,
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which is possible with autotitration modes, may lead to an increase in the number of (unscheduled) healthcare contacts after the initiation phase [52].
Patient perspectives were similar for all diseases and are described in PICO 1. Additionally, the advantage of being able to maintain daily activities including work was especially stressed for OHS patients, who are typically younger and less disabled compared to NMD or COPD patients. Home initiation might not be feasible for every patient as a significant proportion of patients with OHS are initiated after an acute exacerbation, and this might be the reason that the RCTs included only a few patients with OHS that were eligible for elective initiation.
Telemedicine during HMV follow-up (PICO 4 and 5)
PICO 4: Should telemedicine be used to follow-up patients on long-term HMV compared to follow-up without telemedicine?
Recommendation
In patients on long-term HMV, we suggest using either telemedicine-guided follow-up or treatment follow-up without telemedicine. (Conditional recommendation for either the intervention or the comparison; very low certainty of evidence.)
Justification
A conditional recommendation was chosen as the meta-analysis of the included studies showed that both interventions were equally effective for the outcomes analysed, and telemedicine was not related to telemedicine-related harmful or adverse events.
Only five RCTs fulfilled the inclusion criteria and these were very heterogeneous, often applied to mixed populations (including patients without HMV) and with different durations (3, 6 and 12 months), resulting in a very low certainty of evidence regarding the use of telemedicine-guided follow-up [18, 53–56].
Summary of main findings
From the screening of titles and abstracts, 97 papers were retrieved for full-text screening and five eventually fulfilled the inclusion/exclusion criteria. Meta-analysis of the results (supplementary material S7) showed that telemedicine-guided follow-up interventions showed similar results as current standard of care in adherence to HMV (MD 0.30 (95% CI -0.47-1.07 h), hospitalisations (MD -0.03 (95% CI -0.10-0.03) admissions per patient), HRQoL measured with the EuroQol 5D visual analogue scale (MD 0.89 (95% CI -7.24-9.01)), mortality (rate ratio 0.82 (95% CI 0.50-1.34)), $P_{ACO₂}$ (MD 0.47 (95% CI -3.47-4.41) kPa), emergency department visits (MD -0.02 (95% CI -0.11-0.08) visits per month) and contacts with general practitioners (MD -0.04 (95% CI -0.12-0.03) contacts per month). There was an increase in the number of unscheduled outpatient visits in the intervention group (p=0.045) in one study [54]. No harmful or adverse events were reported for any intervention.
Additional considerations
Patient perspectives were similar for initiation and follow-up and are described in PICO 1. Patient representatives mentioned that they expect future developments in real-time monitoring (how should this be organised, is this feasible, who is responsible, is there a role for patient self-monitoring?) and real-time adjustments. Also, they mentioned that they expect a role for artificial intelligence (AI).
Observational studies, either retrospective or pilot studies, demonstrate that telemedicine-guided follow-up increased family confidence in clinical care, supported clinical decision making, especially in patients with active clinical problems or acutely ill patients, and reduced the number of needed healthcare contacts and costs [57–59]. A large multicentric cohort study demonstrated the potential to identify non-adherent patients or patients who do not tolerate HMV early on, allowing targeted interventions to be implemented [60]. Evidence from non-RCT and qualitative studies shows that telemedicine follow-up is valued by people with chronic hypercapnic respiratory failure on long-term HMV [7, 58, 61, 62]. However, a small proportion of patients and caregivers may also be concerned that they might become overly dependent on the telemedicine system. Indeed, patients' self-efficacy decreased during one trial [54].
PICO 5: Should extensive remote monitoring (e.g. remote gas exchange, sleep quality/apnoea, patient-ventilator synchrony) be used compared to limited remote monitoring only using ventilator data in patients on long-term HMV? Recommendation Due to lack of studies addressing this issue, we were unable to make any recommendation. (No recommendation.)
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Justification
We did not identify any studies comparing extensive with limited remote monitoring.
Summary of main findings
From the screening of titles and abstracts, 82 papers were retrieved for full-text screening. As none of the studies compared limited with extensive remote monitoring during follow-up, the evidence is only indirect and obtained from 13 uncontrolled studies showing that remote monitoring of only ventilator data (limited monitoring) during follow-up of patients on HMV is feasible [18, 20, 57, 60, 61, 63–68], and might have a value in predicting exacerbations in COPD [16, 17], reducing hospitalisations [61], reducing hospital visits [57] and predicting or even improving survival [68]. Also, it has been shown that changes in ventilatory characteristics detected by the ventilator (e.g. tidal volume over time, breathing patterns and pressure support changes) differ between diseases [66].
Additional considerations
Unfortunately, sensitivity and specificity of ventilator data and derived algorithms in predicting relevant outcomes has been found to be suboptimal [17]. Nevertheless, in a recent survey study, clinicians pointed out that they rely heavily on data from the ventilator during titration and follow-up; although adding peripheral oxygen saturation monitoring was also considered important, $P_{IccO_2}$ monitoring was only considered by 30% of the respondents in every patient and polygraphic monitoring almost specifically reserved for specific diagnoses or not done at all [69]. Although many respondents considered lots of parameters important, including ones that are not derived directly from the ventilator, practical issues and a lack of data regarding outcomes of additional in-depth monitoring probably drives less frequent use in clinical practice [69]. Furthermore, even limited monitoring might be considered complicated; satisfaction scores with the systems used were variable and no studies have been performed looking at costs, required resources, and patient and caregiver burden.
Patients highly value a reduction in exacerbations/hospitalisations, an important outcome that might be improved with more sophisticated monitoring [70]. However, it was also acknowledged that more extensive monitoring might complicate the setup and increase the burden for patients and caregivers. Also, extending monitoring will increase costs, require more data download and storage capacity, and will probably be difficult to organise in less developed countries. There is currently no way to combine (and synchronise) different monitoring data easily, and further developments in this area are needed but potential problems with combining data from different devices and sources are foreseen, including a safe and secure transfer of the data to electronic medical records systems.
Narrative questions (NQ 1-3)
Evidence summary tables for narrative questions are provided in supplementary material S8. Key considerations regarding the narrative questions are listed in table 2.
NQ 1: What are the patients' and caregivers' views, experiences and challenges with telemedicine in HMV?
Summary of main findings
Overall, the examined studies reported high satisfaction of patients and caregivers with telemedicine, particularly those who were adherent to the telemedicine protocol. 13 studies [7, 24, 58, 61, 71–79] were selected and the evidence was narratively reviewed (supplementary material S8). Overall, these studies included 338 subjects among patients and caregivers, which expressed overall positive feedback on telemedicine and highlighted that patients and caregivers may desire to be informed about and directed to telemedicine programmes.
In qualitative studies, patients and caregivers who experienced telemedicine endorsed its importance in improving their health, wellbeing and confidence, expressing a positive attitude towards the use of telemedicine, considering it acceptable and desirable. When exploring patients’ views, telemedicine was considered an opportunity to reduce unnecessary interventions and receive timely care. No major concerns or harms were reported. Some studies also emphasised the importance of ensuring that monitored data are notified and taken action upon. A patient survey from 2017 showed that 47% of patients and 62% of caregivers were satisfied with healthcare professionals remotely monitoring their ventilator to make sure the settings are always correct and comfortable [24]. With the increasing integration of technology in society and daily life, expectations and satisfaction might be expected to become more positive.
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Additional considerations
Multiple factors can influence the perspectives and values of telemedicine for patients and caregivers (table 3). Through telemedicine, all patients needing HMV may have timely and convenient access to expert opinions, including those living in rural areas. However, it is important to consider findings from the OPIP study [52], which suggests that reducing contact time nurses/conlicumnas may shorten the duration of caregiver-led non-invasive ventilation titration and education during the outpatient non-invasive ventilation setup. This could potentially result in patients and caregivers feeling as well as the result of the post-� and troubleshooting during subsequent follow-up. Similarly, the drawbacks of less caregiver time and attention should be considered when planning implementation of HMV telemonitoring for patients. However, most patients' needs on HMV can be addressed without a medical respiratory specialist consultation, and common issues can be identified and managed by other healthcare professionals at the HMV facility (nurses and respiratory therapists). Furthermore, evidence indicates that patients undergoing outpatient HMV setup may require longer periods to acclimatise to ventilation [38, 52]. Telemedicine can mitigate these challenges by enabling healthcare providers to remotely supervise titration while also providing education to both patients and caregivers [15, 19].
Additionally, feasibility issues related to telemedicine should also be considered. Data from the Dutch Homer trial showed that 24 out of 608 patients (3.9%) declined to participate [19, 80]. For a further 39 patients (6.4%), the Wi-Fi network was not sufficient for home initiation [80]. It therefore appears important to consider the availability of physicians/healthcare workers if these issues are to be surmounted. The resources needed varied, and include, but are not limited. time for patient and caregiver training, time for reviewing telemonitored data, digital proficiency, willingness to adopt new technologies, and absence of clinician barriers to novel methods and activities.
NQ 2: What are the barriers and facilitators including regional differences which influence the implementation of telemedicine in the initiation and follow-up of HMV?
Summary of main findings
18 original studies were selected based on a narrative review of the evidence [7, 20, 34, 53, 58, 59, 61, 64, 68, 71–73, 76–78, 81–83], with four studies discussing internet connectivity issues, seven studies evaluating remunisements/costations, the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the development of the
||Patients|Patients|Caregivers|Caregivers| |---|---|---|---|---| ||Advantages|Disadvantages|Advantages|Disadvantages| |Timely intervention|Early detection of health issues||Timely problem solving|| |Timely intervention|Faster interventions|||| |Convenience|Time saving||Supports remote care|| |Convenience|Remote data transmission||Better clinician communication|| |Access to care|Improved access in rural areas|Less personal interaction with clinicians|Less travel|| |Access to care|Reduced travel and infection risk||Faster feedback|| |Psychological wellbeing|Reassurance from being monitored|Fear data is not being monitored|Lessuced mental burden|Responsibility for device function| |Psychological wellbeing|Feeling connected with care|Stress from device management|Reassurance|Fear data is not monitored| |Peace of mind|Security through monitoring|Anxiety about data oversight|Reassurance about loved one's monitoring|Long-term care consistency concerns| |Peace of mind|Familiar clinical team|Less personal care||| |Burden|Fewer hospital visits||Less organisational load|Tech management anxiety More caregiver responsibility| |Personalised care|Tailored treatment End-of-life reassurance|Highlights end-stage disease perception||| |Autonomy|Encourages self-management|May reduce self-efficacy Requires education|||
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regulatory issues. Despite the limited available evidence, the Task Force identified regional differences with respect to travel distances (patient living far away or close to the referral HMV centre), disease categories indicated for HMV [3, 84, 85], living situation and family support, organisation and availability of formal home care, and differences in existing organisations (from HMV centres already providing almost full care at home to centres now only being able to provide care at the hospital) and reimbursement. Also, regional differences in internet connectivity, legal frameworks and regulatory issues play a crucial role in shaping the implementation of telemedicine-based HMV.
Additional considerations
Telemedicine has the potential to improve healthcare access, particularly in rural areas. However, its successful implementation and adoption require substantial infrastructure investment, and it faces challenges posed by poor internet connectivity. Overcoming these obstacles will involve a long and comprehensive overhaul of established practices and integration of national and regional information networks, along with the implementation of e-referrals and e-prescribing. Global and European policies promoting innovation and establishing legal frameworks are crucial to encourage the institution of telemedicine. Figure 1 illustrates the barriers and facilitators of telemedicine in HMV.
Results from a recent European survey on HMV practices indicate that telemedicine programmes were only an option for 5% of clinician respondents, suggesting possible resistance to change within healthcare systems, financial or organisational issues and/or regulatory hurdles [86]. Moreover, the introduction of telemedicine poses several complex regulatory and legal responsibilities on stakeholders, potentially
Barriers
Requirement for a fixed telephone line Communication issues (video/audio lag) Data extraction speed Manual data transmission Insufficient interoperability between e-health solutions
 Technology
Increased access Opportunities for rural areas User-friendly devices and platforms Improved audio and video quality No increase in internet costs Compatibility between monitoring devices and telemonitoring platforms
Patient costs (electricity) Limited access to broadband internet Patient's physical limitations Patient's decreased working memory Low socioeconomic status Low digital literacy Regional disparities in accessing ICT services Economic disadvantages
 Enhanced self-awareness Access to urgent calls Improved adherence and duration for NIV Active engagement in care Reduced travel distance Decreased visits to specialty physicians Decreased hospitalisations Flexibility in therapy adjustments Cost savings
High start-up costs Limited large-scale cost-effectiveness evidence Lack of transparency in the utilisation of collected data
 Institute
Care efficiency Cost savings Effective education and communication with patients Training healthcare providers Evidence-based clinical protocols and guidelines
Inadequate or fragmented legal frameworks Lack of reimbursement schemes Absence of reimbursement mechanisms
 Collaboration with regulatory agencies Simplification of privacy/security issues Adequate reimbursement Clear regulatory frameworks
FIGURE 1 Barriers and facilitators that may influence the implementation of telemedicine in home mechanical ventilation. ICT: information and communication technology; NIV: non-invasive ventilation.
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affecting its adoption. Physicians may feel overwhelmed by the increased responsibility of remotely monitoring patients' data and worry about ensuring timely intervention and missing or delaying prompt responses to deteriorating patients' conditions. They may also have concerns with data confidentiality and worries that telemonitoring may disrupt patient-doctor interactions [87]. Device manufacturers need to provide sustainable production and distribution of remote health technology and manage increasing regulatory complexities to ensure that the devices comply with monitoring requirements. Furthermore, the transmission of data and remote adjustments pose relevant risks to privacy and software security that must be addressed by physicians and home care providers. Governments should provide reimbursement policies for payment parity between telemedicine and in-person care, and guarantee quality, legal and regulatory compliance.
Telemedicine can be helpful to start and titrate HMV at home in all patient groups [15, 19]. Most studies have focused on patients with COPD and NMDs, particularly ALS. However, different underlying diseases might affect how telemedicine is used, perceived and accepted. Telemedicine might provide the added advantage of early detection of acute exacerbations and monitoring of HMV adherence for COPD patients [16, 17]. While cost-effectiveness of telemedicine has been demonstrated, particularly for frail patients with chronic respiratory failure with and without HMV, these benefits are dependent on the specific organisation of the healthcare systems [88]. Further robust evidence is urgently needed as it could potentially enhance the benefits of telemedicine across different patient groups and healthcare systems. However, it has been reported that many rural households lack access to computers and digital technology, leading to issues with sustaining telemedicine services including retaining clinicians and maintaining equipment. These factors must be considered when commissioning services and allocating resources [83].
The use of telemedicine carries several risks: teleconsultation may fail to reach the standard of care because it lacks physical examination of the patient; equipment or software may fail; electronic data can be manipulated; the network may suffer from poor data protection (poor confidentiality, authenticity, data report, procedure certification, security and privacy). Additionally, there might be difficulties in ascertaining the responsibilities and potential obligations of health professionals. Therefore, it is important for telemedicine users to take necessary precautions [89].
NQ 3: What are recent and expected technological advances and how might these influence the implementation and effectiveness of initiation and follow-up of HMV with telemedicine?
Summary of main findings
10 studies were included [53, 58, 61, 64, 73, 76–79, 82], involving 402 subjects on HMV (132 patients with NMDs, 240 patients with COPD and 30 patients with no specified underlying disease), and the evidence was narratively reviewed (supplementary material S8). The studies reviewed the telemedicine solutions currently in use, along with clinical parameters and indicators to measure. Overall, the studies revealed a high variability in the technology used for telemedicine protocols, mainly adapting existing devices and incorporating telemedicine functionalities by connecting additional components. The studies also described the clinical parameters measured, and different telemonitoring solutions currently and historically available. A qualitative study emphasised that confidence with telemonitoring can be improved through technology itself. However, studies identifying the most effective models for this application have been limited so far and only focused on patients with ALS [64, 75, 76].
The recent technical advances in sensors, data processing and AI that are expected to significantly influence tele-titrated home initiation and follow-up of HMV are described in table 4.
Technologies such as electrical impedance tomography, oscillometry and wearable electromyography devices are possible candidates for gathering information on lung ventilation, lung mechanics, and respiratory muscle effort and drive in telemedicine settings. Such additional variables can be processed, filtered and combined with other data using advanced data processing algorithms leading to a better characterisation of patients' conditions and patient-ventilator interaction, ultimately producing comprehensive, more accurate, clean datasets that clinicians can readily interpret and that AI algorithms can use to predict future trajectories. Advanced monitoring can enhance ventilatory quality, but accessible solutions are essential to ensure successful home use. Additionally, technical advancements offer the possibility of simulating therapy outcomes, determining personalised and optimised treatment decisions, and improving patient and caregiver education and self-efficacy. Technology may also contribute to providing easier and more effective tools for education and empowerment, improving acceptance, adherence and effectiveness of HMV. From the technological standpoint, potential harms may arise from the lack of supervision of devices by properly trained personnel. Devices used at home are not evaluated by experts who might identify erroneous system behaviours, and their reliability depends solely on
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|TABLE 4 Technical advances in telemedicine solutions|| |---|---| |Novel sensor technologies|Emerging sensor technologies hold the potential to revolutionise the future of patient monitoring by enabling the collection of detailed information regarding the patient's conditions. These advanced sensors can measure critical physiological parameters (i.e. blood gases, lung aeration, etc.), lung volumes (i.e. accurate tidal volumes, functional residual capacity) and respiratory drive. By accurately capturing these variables, physicians can gain a more comprehensive and precise understanding of the patient's health status remotely, thereby facilitating more informed and effective interventions.| |Advanced data processing algorithms|Advanced data processing can significantly enhance the quality control of data by identifying and correcting typical artefacts that are particularly prevalent during the unsupervised use of ventilators, such as leaks and asynchronies. This results in more reliable information for interpretation. Data processing can also improve the informative content of the data by extracting physiological parameters of interest from measured variables during patient monitoring (i.e. flow and pressure data may be properly combined to estimate indices of lung mechanics, respiratory drive or asynchronies).| |Cloud-based data collection, data fusion, Al and machine learning algorithms|Cloud-based data collection allows gathering information from diverse sources and needs vast storage capacities. It allows integrated care coordination and interoperability with electronic health records, while ensuring compliance with stringent health data regulations. For this structured data need to be converted into a standardised and interoperable data format. Cloud-based platforms allow storing huge amounts of data and creating long time series of several parameters. These datasets enable the development and adoption of data fusion and AI/machine learning approaches to drive the automatic interpretation of the recorded time series. As part of a clinical decision support system, they can identify and prioritise conditions that require physician attention by filtering out less relevant data and alerting clinicians when a patient is at risk of non-optimised treatment with HMV or HMV failure (i.e. unintentional leaks, asynchronies, low treatment adherence) or exacerbation of the underlying disease. By combining information and signals from multiple sources (i.e. clinical records, other devices, questionnaires of symptoms and/or quality of life), these algorithms can simplify basic tasks by reducing the clinician's workload, significantly enhancing their effectiveness in managing patients remotely, delivering personalised care and increasing job satisfaction.| |Technologies for improving education and empowerment|Digital twin technology is a sophisticated model designed to faithfully mirror a real-world patient system. The model can digitally acquire real-time patient data and insights using advanced simulation. These data can be used to benchmark, validate and improve the digital twin model. Digital twin data can provide additional insights into individuals' lifestyles, psychological states and sociodemographics, and the environment of an individual, which can affect the personalised implementation, titration, success and failure of HMV. Virtual reality allows learners to interact with virtual objects and observe their effects in real-time. A virtual reality programme for HMV management can offer virtual support and basic troubleshooting to patients and caregivers initiating/titrating HMV through telemedicine, promoting self-efficacy while also providing the opportunity to refresh their knowledge and skills as needed.| |AI: artificial intelligence; HMV: home mechanical ventilation.||
self-tests and a comprehensive maintenance plan. Moreover, training and especially the validation of AI systems is difficult as they require very large and comprehensive datasets. Medical information interoperability and integration with electronic health records and other healthcare providers are essential to reduce redundancy, facilitate efficient data exchange, promote patient engagement and support clinicians' decisions. Considerations on such disparities in access, familiarity with the technology, healthcare infrastructure and health literacy are essential to ensure equitable access to telemedicine services. Furthermore, the establishment of a standard taxonomy with technical specifications and quality is desirable. This would serve as an information management strategy to improve knowledge sharing, facilitate research and policy initiatives, increase accountability, and provide guidance for the regular development of telemedicine.
Discussion
The ERS Task Force on telemedicine in HMV evaluated eight questions, including five PICO questions and three narrative questions, related to telemedicine's role in the initiation and follow-up of patients with long-term HMV. We addressed patients' and caregivers' perspectives, regional healthcare differences, and discussed how recent and emerging advances in telemedicine solutions may influence the implementation and effectiveness of telemedicine-guided initiation and follow-up of HMV. Despite a growing body of research published since the last ERS statement on telemedicine of ventilator-dependent patients, the added value of telemedicine in managing patients with chronic respiratory failure on HMV remains
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controversial as the evidence was still very low. Building upon the 2016 ERS statement, new RCTs comparing telemedicine-guided titration and follow-up with standard care (without telemedicine) were included, providing evidence on tele-titration and tele-follow-up of patients on HMV.
With regard to initiation of HMV, three RCTs all conducted within a single country (the Netherlands) have shown that telemedicine for home-based initiation is non-inferior to standard in-hospital initiation, while also being feasible, safe and cost-effective [14, 15]. Based on these findings, we made a conditional recommendation for telemedicine-guided initiation of HMV for patients with NMD, RTD and COPD, supported by both the non-inferiority of this approach versus standard in-hospital initiation and considering patients' preferences for home-based care, but with very low certainty of evidence. However, no recommendation was made for patients with OHS (PICO 3), due to the limited number of OHS patients included in the studies. Of note, these trials were performed in a single country/healthcare system and rely on a highly sophisticated setup that allows the provision of outpatient nocturnal monitoring by well-trained specialised staff [14, 15, 19], and therefore may not fully represent the challenges other healthcare systems could face when implementing similar telemedicine models. Indeed, substantial regional differences exist across Europe in the healthcare organisations, disease prevalence, patient selection, HMV adaptation setting, organisational structures, treatment costs and reimbursement policies (as acknowledged in Narrative of Narrative studies and hinder the implementation of homogeneous telemedicine programmes across different countries and regions. Consequently, the generalisability of these findings may be limited outside the specific context in which the trials were conducted. Other models of outpatient non-invasive ventilation titration, even without the use of telemedicine, have shown satisfactory outcomes, in stable, less complex patients [38, 42, 43]. Autotitrating devices also provide the opportunity for automated at-home non-invasive ventilation titration, as shown in the OPIP trial, where this strategy was non-inferior in patients with OHS, although it required frequent follow-up contacts, limiting cost savings [52]. To date, no comparative studies have directly compared home or outpatient adaptation without telemedicine with at-home telemedicine-based adaptation. We hypothesise that telemedicine-guided initiation might not be needed for all patients; it could be particularly beneficial for patients who are more challenging to ventilate effectively. For example, in patients with ALS with more severely compromised lung function and bulbar dysfunction, telemonitoring might specifically be needed to titrate them adequately at home (the included RCTs in general included ALS patients with lower vital capacity [14] and/or more frequent bulbar symptoms [19] compared to outpatient setup trials without the use of telemedicine). However, there is limited evidence on specific patient characteristics that can predict telemedicine success, except for the underlying disease. As a result, identifying which patients might benefit the most from telemedicine-guided adaptation beforehand remains difficult. Since our guideline focuses on the use of telemedicine, studies not involving telemedicine were excluded for evidence assessment and referred to only as additional considerations.
Regarding HMV follow-up, we defined two questions, related to the efficacy of telemedicine follow-up and the way this should be performed. Theoretically, telemonitoring during the follow-up of patients on HMV might enable early detection of potential problems related to the ventilator, such as adherence, leakage and ineffective ventilation. It might also help detect disease deterioration or exacerbations, thus potentially preventing unnecessary and burdensome hospital visits. However, the parameters to be obtained and the optimal protocol for follow-up monitoring is unknown. Currently, several commercial platforms allow for the monitoring of ventilator data, but most of these provide only summary data, such as usage data and median leakage per night. More sophisticated monitoring of both ventilator data (i.e. detailed flow and pressure curves) as well as parameters related to ventilatory efficacy might optimise chronic HMV management. However, no studies were found comparing ventilator data monitoring only with add-on monitoring of data on ventilatory efficacy (PICO 5). Overall, we found that telemedicine-guided follow-up of HMV using ventilator data did not result in significant differences in clinical outcomes compared to standard of care (without telemedicine) nor was it associated with harmful or adverse events [18, 53–56]. However, the studies included heterogeneous populations (not exclusively patients on HMV) and were mostly short term, and the telemedicine interventions were very diverse. This resulted in a conditional recommendation for either the intervention or the comparison, with very low certainty of evidence.
A major challenge is that there is very limited evidence linking specific telemonitored parameters to clinically relevant outcomes. Although a combination of data over time may be promising, there is currently no consensus or clear evidence of a reliable predictive algorithm with sufficient specificity and sensitivity to detect clinically meaningful deterioration [17]. Future research should prioritise collaborative efforts among HMV centres and ventilator manufacturers to develop larger datasets and combined telemonitored ventilator data to relevant outcomes such as exacerbations, hospitalisations and survival.
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From the perspective of patients and caregivers, telemedicine-guided follow-up is generally considered as a feasible and safe alternative to standard care. Patients consistently emphasised the advantage of telemedicine in avoiding unnecessary interventions and enabling timely personalised care for every patient, especially valuable for those with limited access to their healthcare centre. Telemedicine thereby holds promise for expanding care to more remote areas, although differences in infrastructures (reimbursement, access to internet) may impact equitable access to these services. Also, with telemedicine, adding extensive therapeutic education for patients and caregivers at a distance will be far more easy. Finally, evidence from larger cohorts in patients with obstructive sleep apnoea treated with continuous positive airway pressure indicates that careful monitoring and targeted intervention can improve suboptimal adherence and, thereby enhance treatment efficacy [91]. Given this positive reception and the absence of adverse effects, telemonitoring might be considered when planning HMV follow-up care.
Challenges of telemedicine are, however, multiple. First, the cost-effectiveness of this approach remains uncertain, and further studies are needed to determine the additional technological cost related to the potential clinical benefits. Additionally, economic evaluations across different healthcare systems are required, considering different organisational structures and reimbursement policies. Second, implementation might be constrained by organisational issues, as adopting telemedicine requires new workflows, rules for data monitoring and alert responses, and suitable reimbursement structures, all requiring investments. Technology advances need to progress in order to reach an easier-to-use straightforward continuous real-time monitoring of HMV suitable for all patients. Of note, currently, most telemonitoring options are incorporated in non-life-support ventilators, while patients that are likely to benefit the most from telemonitoring are those with high ventilatory dependency (level 3) using life-support/level 3 ventilators. It is a huge challenge for those in the HMV field to keep track of these challenges and conduct additional research, potentially using adaptive trial designs, investigating the optimal way of delivering telemedicine for feasible, sustainable and accessible care for all patient groups. Our proposed research priorities for telemedicine in HMV are described in table 5.
Overall, although some RCTs have been published, the evidence on the benefits of telemedicine-guided HMV titration and follow-up remains limited. Healthcare systems are actively seeking alternative and
TABLE 5 Recommendations for future research directions
||Research priorities| |---|---| |Initiation of HMV|1) Compare outpatient adaptation with and without the use of telemedicine, addressing adherence, blood gas disturbance correction, patient comfort, symptom burden, HRQoL, patient experience, caregiver burden and cost-effectiveness. 2) Investigate different protocols for telemonitoring (limited to ventilator software analysis or more extended, including gas exchange analysis) addressing adherence, blood gas disturbance correction, comfort, symptom burden, HRQoL, patient experience, caregiver burden and cost-effectiveness. 3) Compare automatic ventilator modes versus standard in-person titration, addressing adherence, blood gas disturbance correction, patient comfort, symptom burden, HRQoL, patient experience, caregiver burden and cost-effectiveness. 4) Use at the effectiveness of telemedicine-guided follow-up versus standard in-person follow-up for patients on HMV on caregivers' outcomes (burden, self-efficacy, experience, etc.). 3) Investigate which parameters should be monitored to predict outcomes in patients on HMV, also including parameters beyond ventilator data monitoring, such as monitoring of gas exchange, patient effort and patient-ventilator asynchrony. 4) Determine the cost-effectiveness of telemedicine-guided versus standard in-person follow-up for patients undergoing long-term HMV. Others| |Others|1) Develop an overview of common practices, values and needs, feasibility and acceptability in different countries among clinicians, patients, caregivers, clinicians and other stakeholders to enhance shared decision making. 2) Define strategies to promote equitable access to telemedicine-guided initiation and follow-up of HMV. 3) Research dedicated to the development of a tailored telemedicine-based HMV approach focusing on designing specific models of interactions between the different users (patients, clinicians, nurses, respiratory therapists and caregivers) along with input from engineering departments and medical forensic services to improve the machine-human interface. 4) Use innovative technologies to create a centralised, user-friendly data hub that may promote interactions and adherence while enhancing different users' perceptions of the effectiveness and value of the telemedicine approach while allowing for cost-benefit evaluations. 5) Assess the role of AI or other cutting-edge technologies in reducing clinician supervision and workload while ensuring safety standards.| |HomME: home mechanical ventilation; HRQoL: health-related quality of life; AI: artificial intelligence.||
HMV: home mechanical ventilation; HRQoL: health-related quality of life; AI: artificial intelligence.
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sustainable ways to the traditional in-hospital care model opting for transition of care from hospital to patients' homes. Telemedicine offers potential advantages enabling closer monitoring of patients and timely detection of their clinical deterioration or technical issues, which might prevent unnecessary hospital visits and can also have an environmental benefit, as it reduces the use of hospital supplies and minimises travel for visitors. However, further research is needed to compare telemedicine-guided care with other out-of-hospital approaches, investigate different monitoring strategies and explore the role of automatic modes. Moreover, the use and implementation of telemedicine is strongly influenced by country-specific and regional differences, highlighting the need for a collaborative approach to get more insight into unmet needs, challenges and opportunities, including the development of big data research and useful algorithms that leverage telemonitored data to predict outcomes. Until more robust evidence is available, providing clear guidance on implementation of telemedicine in HMV care will largely depend on regional and local circumstances, including administrative aspects, reimbursement policies, incentives and healthcare organisation.
Conclusions
With this international guideline, the ERS provides evidence-based clinical practice recommendations for the use of telemedicine for the initiation and follow-up of HMV, highlights evidence gaps, and provides future research recommendations.
Acknowledgements: We would like to thank Stien and Hans van Meerloo, patient expert and her caregiver, for providing us with their experiences and suggestions during the meeting and on the eventual manuscript. We would like to thank Michiel de Boer, statistician of the University Medical Center Groningen (Groningen, The Netherlands), for performing the meta-analyses and providing us with statistical advice, and Sjoukje van der Werf, information specialist at the University of Groningen (Groningen, The Netherlands), for performing the literature searches. We thank Annemijn Jonkman, illustrator of technical physician at the Erasmus University Hospital (Rotterdam, The Netherlands), for her illustrative work on figure 1, and Will Stahl, designer and illustrator (London, UK), for his work on the infographics in the supplementary material.
This document was endorsed by the ERS executive committee on 10 June 2025.
The guidelines published by the European Respiratory Society (ERS) incorporate data obtained from a comprehensive and systematic literature review of the most recent studies available at the time. Health professionals are encouraged to take the guidelines into account in their clinical practice. However, the recommendations issued by this guideline may not be appropriate for use in all situations. It is the individual responsibility of health professionals to consult other sources of relevant information, to make appropriate and accurate decisions in consideration of each patient's health condition and in consultation with that patient and the patient's caregiver where appropriate and/or necessary, and to verify rules and regulations applicable to drugs and devices at the time of prescription.
A plain language summary of this guideline is available at https://europeanlung.org/en/information-hub/guidelines/the-use-of-telemedicine-in-home-mechanical-ventilation. Visual infographics aimed at patients and researchers and a pocket guideline can be found in the supplementary material.
Conflicts of interest: M.L. Duiverman reports support for the present study from the European Respiratory Society, grants from ResMed, Löwenstein, Vivisol, Sencure and Fisher & Paykel, payment or honoraria for lectures, presentations, manuscript writing or educational events from Chiesi, Breas and AstraZeneca, receipt of equipment, materials, drugs, medical writing, gifts or other services from ResMed, Sencure and Fisher & Paykel, and is Chair of Group 2.2 of ERS Assembly 2. C. Ribeiro reports a speaking fee from Vitalair, and support for attending meetings from Vitalair, Nippon, Vivisol, Linde and Novartis. T. Tonia acted as an ERS methodologist and reports no further conflicts of interest. C. Schöbel reports research grants from the German Joint Federal Committee, German Federal Ministry of Health, and German Federal Ministry of Education and Research, consulting fees from AstraZeneca, Chiesi, Idorsia, Insdiares, Inspire, Lilly, ResMed, ZOLL and Bioprojet, payment for lectures from AstraZeneca, Chiesi, Inspire, MSD, ResMed, BMS, Idorsia, Memetor, Lilly and ZOLL, and is board member of the German Sleep Society and German Society for Telemedicine, and working group member of the German Society for Internal Medicine, German Respiratory Society and the working group Cardiovascular Sleep Medicine of the German Cardiac Society. A. Özsancak Uğurlu reports a fee for attending a meeting from AstraZeneca (ERS 2024 online), and reports being National Representative for IRC and coordinator of the Turkish Respiratory Coalition (unpaid). J-C. Borel reports consulting fees from AGIR à dom, French Homecare provider, and ICADOM, a contract research organisation. M. Patout reports research grants from Fisher & Paykel, ResMed and Asten Santé, consulting fees from Philips, ResMed, Asten Santé, GSK, Air Liquide Medical and Isis, honoraria for lectures from Philips, ResMed, SOS Oxygene, Chiesi, Löwenstein, Bastide Medical, Elivie, Asten
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Santé, Air Liquide Medical, Antadir, Jazz Pharmaceutical, Fisher & Paykel, Orkyn and Sanofi, support for meeting attendance from Asten Santé, Vitalair and Sonofi, participation in advisory boards for ResMed, Sanofi, Philips and Asten Santé, stock from Kernel Biomedical, and receipt of equipment from Philips, ResMed and Fisher & Paykel. B. Ergan reports a consulting fee from Breas, and support for attending a meeting from Fisher & Paykel. C. Carlin reports an unrestricted investigator initiated research award (to institution) from ResMed, advisory board and speaker fees from ResMed, and meeting support and speaker fees from Fisher & Paykel. P. Murphy reports grants to institution from Breas, Philips, ResMed, GSK and Fisher & Paykel, payment for lectures from Philips, ResMed, Fisher & Paykel, Breas, Löwenstein, Santhera, GSK and Chiesi, support for attending meetings from Philips, ResMed, Fisher & Paykel, Breas and Löwenstein, and participation on an advisory board for ResMed. R. Dellacà reports a patent on the automatic detection of tidal expiratory flow limitation, owned by his institution, which was licensed to Philips for the automatic tailoring of PEEP in non-invasive ventilation. The patent (and license) expired in 2023. The licensed technology was unrelated to the manuscript's content. M. Vitacca reports payment for lectures from AstraZeneca, GSK, Menarini, Vivisol and Chiesi. C. Crimi reports speaking fees from Fisher & Paykel, Vitalair, Philips, ResMed, Sanofi, GSK, Aerogen and AstraZeneca, a patent pending (number 102023000013077) not discussed in the present work, and participation on advisory boards for Vitalair and Aerogen (occasional). The remaining authors have no potential conflicts of interest to disclose.
Support statement: This Task Force was funded by the European Respiratory Society (TF 2022-03). Funding information for this article has been deposited with the Open Funder Registry.
References
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| Questions | Recommendation |
|---|---|
| Telemedicine during initiation of HMV | |
| PICO 1 | In patients with NMD or RTD, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine? |
| PICO 2 | In patients with COPD, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine? |
| PICO 3 | In patients with OHS, should initiation of long-term HMV with telemedicine be used compared to initiation of HMV without the use of telemedicine? |
| Teilemedicine during HMV follow-up | |
| PICO 4 | Should telemedicine be used to follow-up patients on long-term HMV compared to follow-up without telemedicine? |
| PICO 5 | Should extensive remote monitoring (e.g. remote gas exchange, sleep quality/apnoea, patient-ventilator synchrony) be used compared to limited remote monitoring only using ventilator data in patients on long-term HMV? |
| NMD: neuromuscular disease; RTD: restrictive thoracic disease; OHS: obesity hypoventilation syndrome; HMV: home mechanical ventilation. |
| Questions | Key considerations |
|---|---|
| NQ 1 | What are the patients' and caregivers' views, experiences and challenges with telemedicine in HMV? |
| NQ 2 | What are the barriers and facilitators including regional differences which influence the implementation of telemedicine in the initiation and follow-up of HMV? |
| NQ 3 | What are recent and expected technological advances and how might these influence the implementation and effectiveness of initiation and follow-up of HMV with telemedicine? |
| HMV: home mechanical ventilation. |
| Patients | Patients | Caregivers | Caregivers | |
|---|---|---|---|---|
| Advantages | Disadvantages | Advantages | Disadvantages | |
| Timely intervention | Early detection of health issues | Timely problem solving | ||
| Timely intervention | Faster interventions | |||
| Convenience | Time saving | Supports remote care | ||
| Convenience | Remote data transmission | Better clinician communication | ||
| Access to care | Improved access in rural areas | Less personal interaction with clinicians | Less travel | |
| Access to care | Reduced travel and infection risk | Faster feedback | ||
| Psychological wellbeing | Reassurance from being monitored | Fear data is not being monitored | Lessuced mental burden | Responsibility for device function |
| Psychological wellbeing | Feeling connected with care | Stress from device management | Reassurance | Fear data is not monitored |
| Peace of mind | Security through monitoring | Anxiety about data oversight | Reassurance about loved one's monitoring | Long-term care consistency concerns |
| Peace of mind | Familiar clinical team | Less personal care | ||
| Burden | Fewer hospital visits | Less organisational load | Tech management anxiety More caregiver responsibility | |
| Personalised care | Tailored treatment End-of-life reassurance | Highlights end-stage disease perception | ||
| Autonomy | Encourages self-management | May reduce self-efficacy Requires education |
| TABLE 4 Technical advances in telemedicine solutions | |
|---|---|
| Novel sensor technologies | Emerging sensor technologies hold the potential to revolutionise the future of patient monitoring by enabling the collection of detailed information regarding the patient's conditions. These advanced sensors can measure critical physiological parameters (i.e. blood gases, lung aeration, etc.), lung volumes (i.e. accurate tidal volumes, functional residual capacity) and respiratory drive. By accurately capturing these variables, physicians can gain a more comprehensive and precise understanding of the patient's health status remotely, thereby facilitating more informed and effective interventions. |
| Advanced data processing algorithms | Advanced data processing can significantly enhance the quality control of data by identifying and correcting typical artefacts that are particularly prevalent during the unsupervised use of ventilators, such as leaks and asynchronies. This results in more reliable information for interpretation. Data processing can also improve the informative content of the data by extracting physiological parameters of interest from measured variables during patient monitoring (i.e. flow and pressure data may be properly combined to estimate indices of lung mechanics, respiratory drive or asynchronies). |
| Cloud-based data collection, data fusion, Al and machine learning algorithms | Cloud-based data collection allows gathering information from diverse sources and needs vast storage capacities. It allows integrated care coordination and interoperability with electronic health records, while ensuring compliance with stringent health data regulations. For this structured data need to be converted into a standardised and interoperable data format. Cloud-based platforms allow storing huge amounts of data and creating long time series of several parameters. These datasets enable the development and adoption of data fusion and AI/machine learning approaches to drive the automatic interpretation of the recorded time series. As part of a clinical decision support system, they can identify and prioritise conditions that require physician attention by filtering out less relevant data and alerting clinicians when a patient is at risk of non-optimised treatment with HMV or HMV failure (i.e. unintentional leaks, asynchronies, low treatment adherence) or exacerbation of the underlying disease. By combining information and signals from multiple sources (i.e. clinical records, other devices, questionnaires of symptoms and/or quality of life), these algorithms can simplify basic tasks by reducing the clinician's workload, significantly enhancing their effectiveness in managing patients remotely, delivering personalised care and increasing job satisfaction. |
| Technologies for improving education and empowerment | Digital twin technology is a sophisticated model designed to faithfully mirror a real-world patient system. The model can digitally acquire real-time patient data and insights using advanced simulation. These data can be used to benchmark, validate and improve the digital twin model. Digital twin data can provide additional insights into individuals' lifestyles, psychological states and sociodemographics, and the environment of an individual, which can affect the personalised implementation, titration, success and failure of HMV. Virtual reality allows learners to interact with virtual objects and observe their effects in real-time. A virtual reality programme for HMV management can offer virtual support and basic troubleshooting to patients and caregivers initiating/titrating HMV through telemedicine, promoting self-efficacy while also providing the opportunity to refresh their knowledge and skills as needed. |
| AI: artificial intelligence; HMV: home mechanical ventilation. |
| Research priorities | |
|---|---|
| Initiation of HMV | 1) Compare outpatient adaptation with and without the use of telemedicine, addressing adherence, blood gas disturbance correction, patient comfort, symptom burden, HRQoL, patient experience, caregiver burden and cost-effectiveness. 2) Investigate different protocols for telemonitoring (limited to ventilator software analysis or more extended, including gas exchange analysis) addressing adherence, blood gas disturbance correction, comfort, symptom burden, HRQoL, patient experience, caregiver burden and cost-effectiveness. 3) Compare automatic ventilator modes versus standard in-person titration, addressing adherence, blood gas disturbance correction, patient comfort, symptom burden, HRQoL, patient experience, caregiver burden and cost-effectiveness. 4) Use at the effectiveness of telemedicine-guided follow-up versus standard in-person follow-up for patients on HMV on caregivers' outcomes (burden, self-efficacy, experience, etc.). 3) Investigate which parameters should be monitored to predict outcomes in patients on HMV, also including parameters beyond ventilator data monitoring, such as monitoring of gas exchange, patient effort and patient-ventilator asynchrony. 4) Determine the cost-effectiveness of telemedicine-guided versus standard in-person follow-up for patients undergoing long-term HMV. Others |
| Others | 1) Develop an overview of common practices, values and needs, feasibility and acceptability in different countries among clinicians, patients, caregivers, clinicians and other stakeholders to enhance shared decision making. 2) Define strategies to promote equitable access to telemedicine-guided initiation and follow-up of HMV. 3) Research dedicated to the development of a tailored telemedicine-based HMV approach focusing on designing specific models of interactions between the different users (patients, clinicians, nurses, respiratory therapists and caregivers) along with input from engineering departments and medical forensic services to improve the machine-human interface. 4) Use innovative technologies to create a centralised, user-friendly data hub that may promote interactions and adherence while enhancing different users' perceptions of the effectiveness and value of the telemedicine approach while allowing for cost-benefit evaluations. 5) Assess the role of AI or other cutting-edge technologies in reducing clinician supervision and workload while ensuring safety standards. |
| HomME: home mechanical ventilation; HRQoL: health-related quality of life; AI: artificial intelligence. |
引用 / 出处
2025 ERS临床实践指南：家庭机械通气中的远程医疗. 2025.