12. Telemonitoring for patients with advanced heart failure, Czech Republic

Heart failure (HF), also known as congestive heart failure, is when the heart muscle stops pumping blood the way they should. Consequently, fluid can build up in the lungs leading to shortness of breath. There are several common causes of HF including coronary artery disease (caused by a build-up fatty material in the arteries, also known as plaque), high blood pressure and diabetes. For these reasons, HF is more common among people living with overweight and those aged 65 years and over. It is also more common among men than women (Mayo Clinic, 2022[]).

An ageing population combined with rising rates of overweight (including obesity) have led to an increase in the number of people experiencing HF in OECD and EU countries. For example, between 2000 and 2019, the rate of cardiovascular diseases (CVDs) among OECD countries increased by 18%. However, mortality from major types of HF such as cardiac arrests has been falling over the past two decades (e.g. across the OECD, mortality from cardiac arrests and other ischemic heart diseases fell by 46% between 2000 and 2019) (OECD, 2021[]). Trends in HF specific to the Czech Republic are in Box 12.1.

Increased rates of people with HF is not only a health problem, but also an economic one given it is associated with a high number of hospital visits, premature mortality and productivity losses. For example, approximately 2% of a country’s healthcare budget is spent on HF in European and North American countries (Soundarraj et al., 2017[]). In the Czech Republic, this equates to approximately EUR 21.2 million per year (OECD, 2021[]).

In an effort to improve care for patients with HF while simultaneously reducing costs, countries across the OECD are increasingly looking to digital solutions, including telemonitoring. Telemonitoring refers to the use of “mobile devices and platforms to conduct routine medical tests, communicate the results to healthcare workers in real-time, and potentially launch pre-programmed automated responses” (Oliveira Hashiguchi, 2020[]).

In the Czech Republic, in 2013, the University Hospital Olomouc introduced telemonitoring for patients with advanced HF – specifically, congestive heart failure, structural damage of the myocardium or left chamber dysfunction.1 As part of this intervention, a patient’s vital signs are shared daily with health professionals, using both automatic and manual means (see Box 12.2 for a list of vital signs). Patient information is primarily collected using invasive means – i.e. an implanted defibrillator or pacemaker.

Each patient receives the necessary equipment and devices to transmit data, which are property of the hospital to ensure they meet regulatory standards. To participate, patients must also have access to a smart phone or tablet with Android iOS in order to upload the application necessary for transferring data (a smart phone or tablet can be supplied by the patient or provided by the University Hospital Olomouc).

The objectives of this intervention are three-fold, namely:

  • Treatment quality: deliver patients high-quality, standardised care in line with national and European medical society standards

  • Patient outcomes: improve morbidity, mortality and patient quality of life by detecting signs of deterioration at an early stage, thereby allowing patients to receive treatment promptly

  • Cost savings: reduce hospitalisations, emergency admissions and other healthcare services thereby cutting expenses.

The intervention currently operates out of one hospital in the Czech Republic – the University Hospital of Olomouc – and therefore only covers patients living within this city.

This section analyses telemonitoring for advanced HF patients in the Czech city of Olomouc against five criteria within OECD’s Best Practice Identification Framework – Effectiveness, Efficiency, Equity, Evidence-base and Extent of coverage (see Box 12.3 for a high-level assessment). Further details on the OECD Framework can be found in Annex A.

Evidence to assess whether telemonitoring for patients with advanced HF in the Czech city of Olomouc is meeting its three objectives2 is limited. According to a 2017 European Commission report, the intervention was found to improve medication adherence and access to healthcare professionals (specific indicators for the latter two measures were not provided) (Gutter, 2017[]). Details on the methodological study design associated with these results are not available meaning the effectiveness of this specific intervention cannot be verified.

Evidence of similar interventions operating in other countries, however, is well established (see Table 12.1). Specifically, recent systematic reviews and meta-analyses reveal this type of intervention is effective at reducing all-cause and HF mortality.

Reports from a previous European Commission report noted that telemonitoring for HF patients in Olomouc resulted in a 40% reduction in hospitalisations (Gutter, 2017[]). However, similar to the findings reported under “Effectiveness”, these results cannot be verified. No further studies evaluating the economic impact of the intervention are available, for this reason, the remainder of this section focuses on investment costs for telemonitoring facilities in the Czech Republic as well as summarising economic studies from similar interventions operating in other countries.

The Czech national health service does not reimburse telemonitoring services for advanced HF patients. For this reason, the intervention is reliant on funds from projects undertaken by the Czech National eHealth Centre, operated by the Ministry of Health, as well as funds from project partners. It is estimated that an investment between EUR 1 000 – 5 000 per eligible patient is needed to operate the intervention (however, information on the timeline for investment was not provided) (Gutter, 2017[]). Given the average hospitalisation cost for chronic HF patients in the Czech Republic is approximately EUR 3 500 (or CZK 84 900), such an intervention has the potential to be not only cost-effective, but even cost-saving (Pavlušová et al., 2018[]).

Telemonitoring can reduce costs by performing routine status checks remotely, detecting patient deterioration at an early stage thereby limiting the potential for health problems to escalate as well as reducing patient travel time. Several studies from the academic literature support this argument while others report opposing results. For example, regarding telemonitoring’s impact on utilisation, some studies show a decrease in hospitalisations but an increase in emergency department visits, while the most recent systematic review found most studies recorded no change in utilisation (see Table 12.2). The impact of telemonitoring on total costs was also assessed, which reported mixed, inconclusive results (see Table 12.3).

Given there are no studies evaluating the impact this intervention, it is not possible to assess its impact on equity. Drawing upon the broader literature regarding digital health technologies and equity, there is evidence to suggest telemonitoring can both widen as well as narrow existing health inequalities (e.g. between socio-economic groups) (Table 12.4).

Evidence supporting the impact of the Czech Republic’s telemonitoring for advanced HF patients is limited. Further, findings that are available do not detail the design of the study’s methodology. For this reason, an evaluation of the quality of evidence supporting this specific intervention is not possible. Instead, this section (i.e. Box 12.4) details the quality of studies used in systematic reviews and meta-analyses that support the effectiveness and efficiency of telemonitoring for HF patients.

Overall, the evidence supporting the effectiveness of telemonitoring for HF patients is strong given there are a large number of systematic reviews and meta-analysis based on randomised controlled trials (RCTs), which are considered high quality evidence. The evidence supporting efficiency is less developed.

At present, telemonitoring for advanced HF patients is only available to eligible patients living within the city of Olomouc. This equates to between 100 and 249 people. However, there is only enough equipment for 40 patients. Since 285 745 people in the Czech Republic live with HF (as of 20183), it is clear there is significant potential to extend the coverage of this intervention (Táborský et al., 2021[]).

This section outlines policies to enhance the performance of Olomouc’s telemonitoring programme for HF patients against each of the five best practice criteria.

Table 12.5 compares best practices related to telemonitoring for HF patients from the literature with characteristics of the model in the Czech Republic. The analysis reveals the current model in the Czech Republic aligns with international recommendations; therefore, no specific policies to enhance effectiveness are included in this section. This does not mean, however, there is not room for improvement; instead, it highlights the importance of undertaking a rigorous evaluation to identify policy enhancement options (see “Enhancing the evidence base”).

As outlined under “Efficiency”, telemonitoring for HF patients has the potential to improve efficiency within the healthcare system. However, at present it is unlikely to be cost-effective in the Czech Republic given the small number of participating patients. For this reason, once an evaluation of the pilot in Olomouc is complete (see “Enhancing the evidence-base”), and assuming positive results, policy makers should prioritise expanding the intervention’s reach across the country. By doing so, the average cost per patient will markedly fall (Auener et al., 2021[]).

There is paucity of studies of telemonitoring studies that stratify data by different patient characteristics. Such information is necessary for evaluating the impact of an intervention on existing health inequalities. Policies to ensure telemonitoring for HF patients in the Czech Republic lessens existing inequalities should be derived from future programme evaluations (as discussed under “Enhancing the evidence-base”). Nevertheless, given it is known that vulnerable populations such as the elderly and those with a low socio-economic status (SES) are at greater risk of being digitally excluded, it is important that specific efforts are made to ensure participation by these population groups. For example, including representatives of disadvantaged groups in the design of the intervention, and providing targeted training and support.

There has not been a robust outcome or economic evaluation of telemonitoring for HF patients in Olomouc. An evaluation should therefore be of top priority to policy makers. Tips on how to undertake a thorough evaluation are summarised in this section with a focus on what indicators to collect (see Box 12.5).

The indicators listed are useful for undertaking an outcome evaluation (i.e. whether the intervention achieved its desired objectives). For greater insight, outcomes evaluations can be paired with a process evaluation which assesses whether the intervention was implemented as planned. For example, if an outcome evaluation reveals no major change in key outcome indicators, a process evaluation will inform researchers whether this is due to poor implementation or not. For further details on undertaking an evaluation, see OECD’s Guidebook on Best Practices in Public Health (OECD, 2022[]).

As outlined under “Extent of coverage”, to date, very few patients with advanced heart failure have access to this intervention in the Czech Republic. Following an evaluation of the pilot in Olomouc, assuming positive results and no major negative side effects, this intervention should be expanded to reach the thousands of people in the country experiencing HF.

Based on feedback from intervention administrators in Olomouc, there are no major barriers to scaling-up this intervention in the region (Gutter, 2017[]). However, as discussed under the section on “Transferability”, it is important to take into the local context of where an intervention is being transferred and to adapt the intervention accordingly.

“This good practice can be replicated in other hospitals providing medical services for patients with heart failure.” (Gutter, 2017[])

This section explores the transferability of telemonitoring for HF patients and is broken into three components: 1) an examination of previous transfers; 2) a transferability assessment using publicly available data; and 3) additional considerations for policy makers interested in transferring this intervention.

Telemonitoring for patients with HF in the city of Olomouc has neither been transferred to another country nor scaled-up across the Czech Republic. However, several countries across the OECD have already implemented similar if not near identical interventions indicating telemonitoring for HF patients is highly transferable (see Box 12.6).

The transferability potential of this intervention is supported by administrators from the University Hospital Olomouc, which operate this intervention. Specifically, intervention administrators state that the target population in Olomouc reflects the “standard [EU] population” as it has a medium developed economy and a population with average rates of chronic disease. For this reason, it is suitable for transferral across the EU.

“The good practice is, thanks to use EBM [evidence-based medicine] methods, highly transferable to other hospitals in the region, the whole country and, with possible adjustments to other medical systems, also to further EU countries.” (Gutter, 2017[])

In order to be prepared to implement telemedicine interventions (such as telemonitoring) successfully, policy makers can draw upon the validated Telemedicine Community Readiness Model (TCRM) tool. The tool is free and available online, http://care4saxony.de/?page_id=3837.

The following section outlines the methodological framework to assess transferability and results from the assessment.

A few indicators to assess the transferability of telemonitoring for HF were identified (see Table 12.6). Indicators were drawn from international databases and surveys to maximise coverage across OECD and non-OECD European countries. Please note, the assessment is intentionally high level given the availability of public data covering OECD and non-OECD European countries.

Table 12.7 provides a summary of transferability indicator values among OECD and EU countries compared to the Czech Republic. Key findings from the analysis according to each transferability context is below:

  • Population context: relative to the Czech Republic, populations in OECD and EU countries have a higher ICT index indicating greater confidence using digital tools (7.20 versus 7.34 average). Further, the use of home healthcare services is markedly higher on average across the OECD/EU when compared to the Czech Republic (23% versus 29%).

  • Digital health sector context: based on available indicators, the digital health sector among OECD/EU countries is just as advanced or more advanced than the Czech Republic. For example, all countries with available data have some form of telemonitoring programme in place and have legislation in place to protect patient data collected digitally (therefore patients are more likely to feel comfortable sharing information on their vital signs remotely).

  • Political context: unlike Czech Republic, 74% of OECD/EU countries with available data have a national eHealth policy or strategy in place to support telemonitoring programs. Conversely, a large proportion of countries (44%) do not have a plan or strategy specific to telehealth interventions, which may hinder implementation efforts.

  • Economic context: compared to the Czech Republic most OECD/EU governments contribute a large amount to eHealth programs thereby supporting the financial sustainability of telemonitoring programs. Further, unlike the Czech Republic, the majority of OECD/EU governments (86% with available data) provide additional “special funding” for their eHealth strategy, which again contributes to financial sustainability.

To help consolidate findings from the transferability assessment above, countries have been clustered into one of three groups, based on indicators reported in Table 12.6. Countries in clusters with more positive values have the greatest transfer potential. For further details on the methodological approach used, please refer to Annex A.

Key findings from each of the clusters are below with further details in Figure 12.1 and Table 12.8:

  • Based on chosen indicators, countries in cluster one will likely receive political and economic support for telemonitoring interventions. However, prior to implementation the digital sector’s readiness to implement such an intervention should be assessed (e.g. using the TCRM tool). Czech Republic, which is the owner of this intervention, falls under this cluster.

  • Countries in cluster two have a population and digital health sector ready to implement telemonitoring interventions. Nevertheless, the financial sustainability of telemonitoring interventions should be confirmed given governments in these countries typically contribute less to eHealth programs (as a proportion of total spending on eHealth).

  • Although most countries in cluster three have telemonitoring interventions in place already, policy makers are encouraged to thoroughly assess the potential to transfer this intervention – e.g. to assess workforce readiness and ensure telemonitoring aligns with overall political objectives.

Data from publicly available datasets alone is not sufficient to assess the transferability of public health interventions. Box 12.7 outlines several new indicators policy makers could consider before transferring telemonitoring for HF patients.

In addition to the indicators below, policy makers can refer to the TCRM (Telemedicine Community Readiness Model) tool as previously detailed.

In 2013, the University Hospital Olomouc in the Czech Republic introduced a telemonitoring intervention for HF patients. The intervention shares patient vital signs with health professionals on a daily basis including blood pressure, medication adherence and weight. The majority of indicators shared with health professionals is collected automatically through either an implanted defibrillator or pacemaker.

No evaluation of this pilot intervention is currently available therefore it is not possible to determine its impact on patient outcomes, experiences as well as costs. A review of similar interventions in the literature indicate telemonitoring for HF patients is effective at reducing all-cause and HF-related mortality, however, its impact on costs is less clear.

The design of Olomouc’s telemonitoring intervention aligns with international best practice given it involves frequent transmission of biological parameters including medication adherence, weight and blood pressure. However, prior to scaling-up this intervention across the Czech Republic, a robust outcome and process evaluation is recommended. The types of indicators to measure the intervention’s impact are outlined in this case study and include data routinely collected by hospitals.

Several OECD and EU countries have telemonitoring programs for patients with HF including Sweden and Japan highlighting the intervention’s transferability potential. In the Czech Republic, administrators in Olomouc believe the intervention is “highly transferable to other hospitals in the region”.

Box 12.8 outlines next steps for policy makers and funding agencies in regards to telemonitoring for advanced HF patients.


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← 1. New York Heart Association classification III (marked limitation in activity due to symptoms, even during less-than-ordinary activity such as walking short distances) or IV (severe heart limitations – experience symptoms even when resting).

← 2. Improve treatment quality, improve patient outcomes and reduce costs (see “Intervention description”).

← 3. The proportion of these patients who have advanced HF is not known.

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