WHF ROADMAP

CORRESPONDING AND

CO-FIRST AUTHORS:

Jasper Tromp

National University of

Singapore, SG

jasper_tromp@nus.edu.sg

Devraj Jindal

Centre for Chronic Disease

Control, New Delhi, IN

djindal@ccdcindia.org

KEYWORDS:

digital health interventions for

CVD; e-health; health system

governance

TO CITE THIS ARTICLE:

Tromp J, Jindal D, Redfern J,

Bhatt A, Séverin T, Banerjee A,

Ge J, Itchhaporia D, Jaarsma

T, Lanas F, Lopez-Jimenez F,

Mohamed A, Perel P, Perez

GE, Pinto F, Vedanthan R,

Verstrael A, Yeo KK, Zulﬁya

K, Prabhakaran D, Lam CSP,

Cowie MR. World Heart

Federation Roadmap for

Digital Health in Cardiology.

Global Heart. 2022; 17(1): 61.

DOI: https://doi.org/10.5334/

gh.1141

World Heart Federation

Roadmap for Digital Health

in Cardiology

JASPER TROMP*

DEVRAJ JINDAL*

JULIE REDFERN

AMI BHATT

TANIA SÉVERIN

AMITAVA BANERJEE

JUNBO GE

DIPTI ITCHHAPORIA

TINY JAARSMA

FERNANDO LANAS

FRANCISCO LOPEZ-JIMENEZ

AWAD MOHAMED

PABLO PEREL

GONZALO EMANUEL PEREZ

FAUSTO PINTO

RAJESH VEDANTHAN

AXEL VERSTRAEL

KHUNG KEONG YEO

KIM ZULFIYA

DORAIRAJ PRABHAKARAN

CAROLYN S. P. LAM

MARTIN R. COWIE

ABSTRACT

More than 500 million people worldwide live with cardiovascular disease (CVD). Health

systems today face fundamental challenges in delivering optimal care due to ageing

populations, healthcare workforce constraints, ﬁnancing, availability and affordability

of CVD medicine, and service delivery.

Digital health technologies can help address these challenges. They may be a tool

to reach Sustainable Development Goal 3.4 and reduce premature mortality from

non-communicable diseases (NCDs) by a third by 2030. Yet, a range of fundamental

barriers prevents implementation and access to such technologies. Health system

governance, health provider, patient and technological factors can prevent or distort

their implementation.

World Heart Federation (WHF) roadmaps aim to identify essential roadblocks on the

pathway to effective prevention, detection, and treatment of CVD. Further, they aim

to provide actionable solutions and implementation frameworks for local adaptation.

This WHF Roadmap for digital health in cardiology identiﬁes barriers to implementing

digital health technologies for CVD and provides recommendations for overcoming

them.

Author afﬁliations can be found in the back matter of this article

*Jasper Tromp and Devraj Jindal are co-ﬁrst authors.

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DOI: 10.5334/gh.1141

BACKGROUND

Cardiovascular disease (CVD) affects more than 500 million people worldwide [1]. Global

lifestyle changes, including worsening diets, reduced physical activity and an increasing

smoking prevalence, have led to a growing burden of non-communicable diseases (NCDs) and

risk factors for CVD [2, 3]. Health systems today face fundamental challenges in delivering

optimal care due to ageing populations, constraints in their healthcare workforce, ﬁnancing,

availability and affordability of CVD medicine, and service delivery [4–6]. Therefore, patient self-

care and empowerment is becoming increasingly important.

Digital health technologies, such as electronic decision support tools, telemonitoring, remote

monitoring, or mobile health (mHealth) apps, have the potential to help address health

system challenges which limit the achievement of optimal and universal health coverage

(UHC). These technologies can contribute to UHC by empowering patients [7] and providers

[8], promoting universal health services coverage [9], improving long-term patient outcomes

and care experience, and reducing healthcare costs (Figure 1) [10]. Therefore, Digital Health

Interventions (DHIs) may be a tool to reach Sustainable Development Goal 3.4 and reduce

premature mortality from NCDs by a third by 2030 [11].

A range of fundamental barriers prevent implementation and access to digital health

technologies globally [12]. Health system governance (e.g., national privacy regulations and

internet access), health provider (e.g., digital literacy, perceived effectiveness), patient (e.g., age

[13], local sex/gender norms [14], socioeconomic factors [15], digital and health literacy [16]),

and technological factors (e.g., a context-speciﬁc adaptation of technology, interoperability

[16]) can prevent or distort the implementation of new digital health technologies. Digital

determinants of health and socioeconomic factors determining access and adoption of digital

technologies can create a ‘digital divide’: a chasm between those with and without access

to digital technologies due to economic factors, (digital and health) literacy, age, or sex. This

can cause inequity and inequality in access to digital technology and its potential beneﬁts.

Unfortunately, similar inequalities often permeate across diseases and beyond health [17].

Furthermore, it is essential to acknowledge that not all DHIs to date have positively impacted

outcomes [18, 19]. Process evaluations have demonstrated that common barriers, such as

(poor) context-speciﬁc design of interventions or poor implementation, are often at the root of

an intervention’s effectiveness [20, 21]. Yet proper process evaluations for complex DHI are not

commonly performed, leaving many questions at the end of effectiveness studies about why

Figure 1 The potential of

digital health interventions for

CVD. © World Heart Federation.

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DHI were (not) effective. The World Heart Federation (WHF) Roadmaps have been published

since 2014 to identify essential roadblocks on the pathway to effective prevention, detection,

and treatment of cardiovascular disease [22–28]. The ultimate aim of the WHF Roadmap is

to provide implementation frameworks for local adaptation for prevention, detection and

treatment strategies for CVD. This WHF roadmap for digital health in cardiology aims to identify

barriers to implementing digital health technologies for CVD and provide recommendations for

overcoming them.

METHODOLOGY AND SELECTION OF THE EXPERT WRITING GROUP

In 2020, the WHF commissioned a writing group to develop a roadmap on digital health for

cardiology. WHF regional Members were invited to nominate an expert to the writing group

to ensure that the content of the roadmap has accurate global representation. In addition,

experts in digital health with clinical, public health or research backgrounds were selected. The

writing group also included representatives from allied health professions and people living

with CVD to ensure an inclusive perspective.

The roadmap is derived from a synthesis of peer-reviewed evidence on the barriers to and

beneﬁts of using digital technologies, an online survey among WHF members and the public

and an iterative process of expert consultation involving eight writing committee members

and 12 reviewing committee members drawn from the global WHF membership network.

The Supplementary Appendix details the methodology of the survey. Inputs from surveys

and (patient) experts were supplemented with a narrative evidence synthesis on barriers and

solutions for implementing digital health solutions. The Writing Committee identiﬁed and

selected case studies based on their experience and relevance to the identiﬁed barriers and

solutions.

TARGET AUDIENCE

The primary focus of this roadmap is to identify and provide solutions and tools for commonly

faced barriers in the development, implementation and scaling of DHIs for CVDs and their risk

factors. Solutions in this roadmap are intended to be practical and are directed at different

stakeholders within health systems, including people living with CVD and who might be active

in-patient organisations, health care practitioners and policy makers, helping them to come

together and drive meaningful change.

DEFINITION AND TYPE OF DIGITAL HEALTH INTERVENTIONS

In 2018, the World Health Organization (WHO) presented a classiﬁcation of digital health

interventions (DHIs) [29]. This taxonomy classiﬁes digital health solutions according to the

health system challenges they seek to address. In contrast, the United States Federal Drug

Administration (FDA) deﬁned a digital health taxonomy based on the product or service to guide

legal regulations for each product [30]. Other existing classiﬁcations use the target group (e.g.

clients, healthcare providers, health system managers or data services) [31] for the purpose

of the intervention [32]. In the context of this roadmap, we used the WHO classiﬁcation and

focused on client or provider-facing technologies and data services.

POTENTIAL OF DIGITAL HEALTH IN PREVENTING AND MANAGING

CARDIOVASCULAR DISEASE

Several DHIs have shown potential for CVD management [18, 33, 34–41, 42–44], including

text message programmes [34, 38–43], mobile (mHealth) apps [18, 33, 35, 36, 44], telehealth

consultations [45–47], wearable devices [48–50], and electronic decision support tools [37,

51, 52]. This section provides several non-exhaustive examples of DHIs to illustrate their

potential impact. Text message programmes can improve the management of single risk

factors, including tobacco smoking [33], high blood pressure [34], physical activity [38], weight

management

[39], and medication adherence [40, 41]. For example, the TEXTME randomised

controlled trial (RCT) showed that four semi-personalised messages sent automatically on

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random times and days of the week signiﬁcantly improved blood pressure, body mass index,

smoking rates, physical activity and adherence to dietary guidelines [42]. A signiﬁcant part of

its success was the co-design of text content with patients and clinicians, using techniques

from behavioural psychology [43].

A 2018 systematic review found that mobile (mhealth) apps can reduce rehospitalisation, improve

patient knowledge, quality of life, and psychosocial well-being, and help manage CVD risk factors

[44]. Importantly, the success of mHealth interventions depended on simplicity, credible and

evidence-based information relying on behaviour change concepts, real-time data tracking,

virtual positive reinforcement, app personalisation, social elements, and ensuring privacy [53]. The

HERB Digital Hypertension 1 (HERB-DH1) RCT (390 patients from 12 sites in Japan) showed that

an interactive smartphone app retrieving home BP monitoring data to generate a personalised

programme of lifestyle modiﬁcations improved ambulatory, home and ofﬁce SBP [35].

Physical activity trackers are an example of wearable devices that may be used to support

CVD management. A 2019 systematic review (28 RCTs including 3646 participants across nine

countries) investigated the effects of wearable activity trackers and found an average increase

of 627 daily steps (95% CI 417 to 862 steps) and energy expenditure among the intervention

groups compared to controls [50]. The mSToPS RCT demonstrated that a home-based wearable

continuous ECG monitoring patch could successfully identify patients with atrial ﬁbrillation

[54]. The Apple Heart Study demonstrated moderate effectiveness of the Apple Watch in

identifying people with atrial ﬁbrillation [55]. However, this study was not without criticism [56]:

An essential issue was the absence of a response by individuals notiﬁed by the Apple Watch of

possible health issues, highlighting the importance of considering how users interact with DHIs

to ensure effectiveness.

The EXPERT (Exercise Prescription in Everyday Practice & Rehabilitation Training) Tool is an

example of a clinical electronic decision support tool. The European Association for Preventive

Cardiology (EAPC) introduced EXPERT as an interactive decision aid enabling healthcare

professionals to compare their exercise prescriptions to predetermined patient cases using

an algorithm [57]. The recent PROMPT-HF trial showed that a tailored EHR-based alerting

system could improve the use of guideline-directed medication in heart failure [52]. Lastly,

artiﬁcial intelligence (AI) decision support tools can aid in interpreting medical imaging data

automatically [51, 58, 59].

REQUIREMENTS FOR SUCCESSFUL IMPLEMENTATION OF DIGITAL

HEALTH SOLUTIONS

The WHO recommendations on DHIs for health system strengthening laid out several conditions

necessary to implement digital health technologies successfully [60]. These include (1) The

health content, referring to the disease domain and associated treatment recommendations,

(2) a DHI that is technically aligned to achieve the proposed goal (3) digital applications such

as information and communications technology (ICT) systems and communication channels

to deliver the digital intervention — these include the ICT and software systems optimised

for its intended goal — and (4) an enabling environment consisting of a national strategy,

reimbursement policies, and a digital infrastructure. A recent European Society of Cardiology

(ESC) working paper emphasises the importance of DHIs for managing CVDs and provides

various practical recommendations [12].

ROADBLOCKS AND SOLUTIONS TO IMPLEMENT DIGITAL HEALTH

INTERVENTIONS

Unfortunately, in reality, many of the ideal conditions for implementing digital health

technologies are often not met. The WHO/ITU framework suggests that a national eHealth

environment requires good leadership and governance, high-quality legislation and policies,

a clear investment and reimbursement strategy, high-quality services and applications, a

supporting digital health infrastructure, clear interoperability and data standards and a tech-

savvy workforce [61]. Barriers and solutions were classiﬁed according to these components. In

addition, a category of patient-level barriers was added as it was not included in the WHO/ITU

framework (Figure 2).

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Table 1 outlines common barriers to implementing digital health solutions based on a narrative

synthesis of existing literature and the online survey. The online survey was shared with WHF

membership organisations and social media channels between September 2, 2021 and

October 14, 2021. In total, 227 participants from 71 countries completed the survey. The survey

achieved global representation: 28.4% of the responses were collected in the WHO European

region; 25.3% in the Americas, 21.3% in South-East Asia, followed by 12% in the African Region,

9.8% in the western Paciﬁc and 3.1% in the Eastern Mediterranean regions. Furthermore, 35%

were from high-income countries, 60% from middle-income countries and 15% from low-

income countries, according to 2019 World Bank Criteria. Solutions were identiﬁed based on

expert consensus and existing literature. In the next section, we discuss some of the most

reported barriers to implementing digital health solutions and provide solutions that might be

relevant to the local context.

LEADERSHIP AND GOVERNANCE

Roadblock: Lack of national guidelines

National governments and policymakers are uniquely responsible for setting universally

applicable strategies and standards [61]. More than 70% of respondents to the survey noted

that a lack of national data privacy and sharing guidelines was a critical roadblock. The lack of

national guidelines was an essential barrier in a recent systematic scoping review [16], as it

can lead to the reluctance of providers to use DHIs. For example, the absence of clear national

guidelines on telehealth solutions in Bangladesh was a signiﬁcant barrier for local healthcare

practitioners to adopt this technology [62].

Suggested solutions

The ITU/WHO national eHealth strategy toolkit guides the development of national eHealth

strategies [61]. National professional medical societies are uniquely positioned to advocate for

national guidelines on data sharing and universal data standards. Increasingly, digital health

data governance standards are emerging, involving regulations for ethics, data security, and

regulatory policies [63]. The development and deployment of digital health technologies are

dependent on the ability to collect, store, access and share medical data. Clear guidelines for

accessing these data can ensure their quality and availability [64]. A key aspect of development

includes rigorous stakeholder management with an emphasis on inclusive development [61].

Figure 2 Selected roadblocks

and solutions to implement

digital health interventions,

based on the WHO/ITU

framework. © World Heart

Federation.

DESCRIPTION OF ROADBLOCK SOLUTION

Leadership and governance

National guidelines and

strategies

Lack of national guidelines and eHealth

strategy.

Establish national or regional eHealth guidelines and strategy.

Stakeholder engagement Poor involvement of critical national

stakeholders.

Inclusive engagement with stakeholders by policymakers,

including representatives of patients, practitioners, payers,

industry and civil society.

Monitoring and evaluation

standards.

Lack of clear monitoring and evaluation

standards. No repeated monitoring

of effectiveness, reach and impact of

interventions.

Clear national standards for monitoring and evaluation of DHIs.

Long-term monitoring of effectiveness and implications of digital

health interventions. ‘unexpected effects’ registry.

Legislation, policy and compliance

National legislation on data

security and access

Lack of national guidelines on data security

and access. Local institutional guidelines are

not harmonized.

Explicit national guidelines on data access and security. Promote

harmonization of policies between institutions.

Lack of regulatory approval or

guidance

Lack of regulatory standards; poor health

technology assessment (HTA) standards.

Improve HTA and regulatory standards.

Strategy and investment

Reimbursement Unclear reimbursement pathways for digital

technologies.

Clear reimbursement strategy for DHI. Include economic

evaluations in the design phase.

Long-term investment

strategy

Lack of long-term investment strategy for

sustainability of digital technologies.

Include long-term investment strategy as part of national

guidelines.

Services and applications

Contextualisation Intervention not adapted to the local context. Perform a structured and holistic needs and context assessment

before designing and implementing interventions. Health system

assessment frameworks might be helpful tools.

Poor usability and design Non-user focused design. Employ user-centred and co-design principles. Include end-users

(practitioners/patients) early in the design phase.

Infrastructure

National or regional digital

infrastructure

No clear investment in national or regional

digital infrastructure.

Investing in digital health infrastructure should be included as a

national policy priority.

Healthcare provider systems Local infrastructure does not allow the

integration of new DHI.

Applications should be ﬂexible and available in on- and ofﬂine

modes.

Standards and interoperability

Data structure standards National and international differences in data

collection, storage and deﬁnitions standards.

Promote collective deﬁnitions and data storage formats.

Emphasise implementation of open data platforms.

Health workforce

Poor needs assessment Poor understanding of the health workforce

needs.

Include clear health system and needs assessment in the design

phase of DHIs.

Data literacy Lack of understanding of DHI. Provider education on the use of digital technology.

Low acceptability Lack of perceived effectiveness and use of

DHIs.

Inclusive technology design and education of use.

Patients

Poor digital literacy and skills Lack of understanding of DHI (literacy), or not

having physical capabilities to interact with

DHI.

Patient education on the use of digital technology, context

speciﬁc adaptations of technology to match patients’ physical

abilities.

Low acceptability Lack of perceived effectiveness and use of

DHIs.

Inclusive technology design, education of use and user

acceptance, usefulness and engagement evaluation alongside

clinical trials and related research.

Table 1 Barriers and possible solutions.

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Roadblock: Lack of monitoring and evaluation standards

In the WHF digital health roadmap survey, low (perceived) quality was a moderate to

signiﬁcant barrier to more than 70% of respondents. The WHO reported that only 7% of DHIs

in LMICs are properly evaluated [65]. A systematic review conﬁrmed these results and found

only the minority of DHIs are properly evaluated [66]. Similarly, few AI decision support tools

are evaluated prospectively [67]. On a policy level, few countries have dedicated frameworks

for evaluating DHIs [51]. The lack of perceived or proven effectiveness is a critical barrier to

the use of DHI by patients and clinicians [16]. The lack of proper evaluation standards has

prevented the uptake of DHIs in clinical guidelines, which has negatively inﬂuenced adoption.

Because they imply multiple interacting components that can target various behaviours and

require signiﬁcant expertise to deliver or target numerous groups of people, many DHIs can be

considered complex interventions as deﬁned by the British Medical Research Council [68]. This

means that the evaluation of DHIs in RCT settings is complex and not always possible when

deployed in a ‘real-world’ setting. Software-driven by AI algorithms poses a unique challenge.

These algorithms often undergo continuous training to improve their predictive capabilities.

However, there is a signiﬁcant risk that ongoing training reinforces existing structural biases in

the data [69].

Suggested solutions

The WHO has highlighted the importance of robust evaluation and recommends using the

mHealth Evidence Reporting and Assessment (mERA) checklist, emphasising quantitative,

qualitative, and economic evaluation [70, 71]. The United Kingdom National Institute for Health

and Care Excellence (NICE) provides an Evidence Standards Framework for DHIs [72]. Cardiology

guidelines have a hierarchy of evidence that puts RCT at the top. Rarely are digital technologies

assessed this way – partly because of the small nature of many companies developing tech,

and the complex and rapid nature of DHIs. This requires a shift in the mindset of appreciating

DHI’s effectiveness. Many DHIs are considered complex interventions with multiple interacting

components. For example, the mWellcare Cluster-Randomized Controlled Trial randomised

community health centres and compared the use of electronic decision support tools versus

care as usual [73]. The nature of the intervention required healthcare practitioners (doctors,

nurses) to engage with the software effectively. A process evaluation can evaluate whether

the lack of beneﬁt of mWellcare was due to poor staff engagement with the software or to

the software’s intrinsic capabilities. Frameworks for evaluating complex interventions, such

as the RE-AIM framework [74] can be used to assess complex DHIs with multiple interacting

components. Evaluation of AI-drive software requires speciﬁc frameworks [75]. The United

States Food and Drug Administration (FDA) outlined a framework in their AI action plan [76]. This

framework requires a predetermined change control plan with anticipated algorithm changes

by the developers and how this would impact safety and performance [76]. Subsequent

post-market access periodic updates are necessary to monitor real-world performance [76].

Professional medical associations play a role in advocating for the necessity for continuous

monitoring of AI-drive algorithms. In the same way that post-market monitoring of drug safety

and effectiveness is performed in phase IV trials, we require continuous monitoring of software

performance and safety when using rapidly changing algorithms.

LEGISLATION, POLICY AND COMPLIANCE

Roadblock: Lack of guidance on data security of digital health technologies

Privacy concerns and individuals’ willingness to disclose personal medical information

are essential barriers to adopting technologies [77]. The lack of national regulations and

inadequacy of legal requirements of DHIs was considered a signiﬁcant barrier by more than

60% of respondents of the WHF survey. Multiple studies have shown that this is particularly

true for older individuals [78] and is essential in creating a ‘digital divide’. A study in Ireland

suggested that perceived trust and safety of digital (mHealth) technologies were important

adoption determinants, particularly in older individuals [79]. Similar studies performed in India

and China indicate that trust in the data security of digital health technologies contributes

to digital health adoption by patients across cultures and geographies [80, 81]. A recent

systematic review highlighted the importance of the lack of clarity of digital health regulations

as a signiﬁcant barrier in LMICs [82]. Results of the online survey support these ﬁndings: lack of

national rules and issues surrounding data privacy for clients (patients) were among the most

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signiﬁcant barriers to implementing digital technologies. A recent scoping review highlighted

a lack of trust and issues with data privacy and security as a vital clinician-level barrier in

7% of studies on barriers and enablers for digital health in CVD [16]. A recent study from the

United Kingdom suggested that a National Health Service (NHS) stamp of approval served as a

signiﬁcant facilitator for digital health implementation [83].

Suggested solutions

Rigorous and transparent regulatory mechanisms and guidance on data security and privacy

are essential conduits to enhance trust by patients and clinicians in using digital health

technologies [61, 64]. An article by Tifﬁn and colleagues summarises components of data

governance. It includes guidelines on ethics and consent, data access, sustainability, and

legal frameworks on data security, third party access and a right to privacy [84]. The European

Union’s General Data Protection Regulation (GDPR) outlines vital data protection principles as

a global gold standard [85]. Importantly, patients are increasingly asking to be the owners of

their data. In this situation, the patient determines with whom their data is shared and in what

context, even after informed consent. While this is not commonplace, new technologies such

as blockchain might facilitate individual patient data ownership for research and development

purposes [86].

STRATEGY AND INVESTMENT

Roadblock: No strategy for reimbursement and long-term investment

Current policy guidelines in many countries require face-to-face consultation for reimbursement.

Therefore, the lack of proper reimbursement of DHIs is a signiﬁcant barrier to adoption by

patients and providers. More than half of survey respondents considered limited reimbursement,

prohibitive costs of training staff and patients, and high out-of-pocket patient costs signiﬁcant

barriers. Separate scoping and systematic reviews [16, 87, 88] on barriers and facilitators

highlighted that ﬁnancial concerns were essential barriers for both patients and health care

providers. Unfortunately, many countries’ care facilities or suppliers’ costs are not reimbursed

[12]. Furthermore, the ﬁnancing of DHIs often does not consider long-term sustainability. In

Africa, 85% of the funding for DHIs is targeted at research and early pilot programmes [89, 90].

For example, a national survey in Uganda found that most DHIs were pilot studies, operated

in silos, donor-funded, and lacked sustainability [91]. Unfortunately, donor-based funding in

LMICs often does not consider ﬁnancial sustainability [92], and long-term public ﬁnancing by

public healthcare systems in LMICs is often challenging [89].

Suggested solutions

Implementation of DHIs should consider funding mechanisms because they will impact the

(cost) evaluation and long-term sustainability. The COVID-19 pandemic has accelerated the

need for new funding mechanisms for telehealth solutions, for example, in the United States

[93] and Singapore [94]. Unfortunately, these funding mechanisms have primarily been ad-

hoc. Some of these funding mechanisms have been made permanent, as in Australia for

example [95]. Governments play a crucial role as conveners to guide the long-term ﬁnancing

strategy, recognised by the WHO/ITU framework for developing a national eHealth strategy

[61]. National ﬁnancing strategies should consider the national and local IT infrastructure as

fundamental perquisites for implementing individual DHIs. While many governments have

funded telehealth services with health professionals and electronic pharmacy scripts, this

does not extend to using DHIs such as apps and wearable devices [51]. Speciﬁc ﬁnancing

instruments are beyond the scope of this roadmap. Examples relevant to the local context

can be found in the Broadband Commission for Sustainable Development Working Group on

Digital Health report [89]. Therefore, researchers/developers should consider the long-term

ﬁnancial sustainability of DHIs during the design phase and cost-effectiveness analyses during

the testing phase [68].

SERVICES AND APPLICATIONS

Roadblock: No user- and context-speciﬁc adaptations

Common issues with DHIs are insufﬁcient assessment of the patients’ and healthcare

providers’ actual needs, developing ‘one-off’ interventions without contextualisation within

national health systems, and lacking cultural and social adaptations [96]. Lack of contextual

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adaptation was considered a barrier to DHIs among more than 60% of survey respondents

for this roadmap. The effectiveness of DHIs is dependent on the local context, which can also

include the wider socioeconomic context. For example, a recent evaluation of a mobile text-

based support programme for people living with diabetes or hypertension in Cambodia found

that the intervention added little to an already effective peer-support network. Notably, the

intervention did not address the structural barriers determining access to care, such as patient

reimbursement and patient health literacy [20]. DHIs should also be designed with the user

in mind. The introduction of electronic medical records designed without considering the

clinician’s workﬂow is one of the prime examples of poor design standards [97]. Increased work

and responsibilities for clinicians were the most signiﬁcant barrier to the uptake of digital health

technology by cardiovascular clinicians in a recent scoping review [16]. Similar to patients, poor

design and ability to interact with DHIs were signiﬁcant barriers to adoption among healthcare

workers [16, 98].

Suggested solutions

User-focused design and a solid evidence base regarding effectiveness are vital in enabling

clinicians to use digital health technologies [60]. As a rule, digital technologies should reduce

the burden on clinicians or signiﬁcantly improve patient outcomes to be acceptable. Involving

healthcare workers in the design phase of DHIs can prevent poor usability and integration with

existing clinical workﬂows. Most DHIs are not evaluated in randomised controlled trials [66].

Therefore, the design of DHIs should be accompanied by rigorous testing in randomised clinical

trials. Digital literacy of health workers is vital. Therefore, targeted health worker education on

using digital health technologies is essential. Notably, costs of (continued) training of healthcare

workers in digital technologies should be considered when estimating cost-effectiveness.

Professional medical organisations, such as ESC, AHA or the Asia Paciﬁc Society of Cardiology,

have a unique opportunity to educate their members on the beneﬁts and limitations of DHIs

and their evaluation. Speciﬁcally, they could offer training during professional meetings on

digital solutions and develop speciﬁc eLearnings for their members.

PATIENTS

Roadblock: Acceptability and feasibility for patients

Similar to providers, DHIs have the potential to empower and educate patients, reduce their

workload and save travelling time. Various patient-level barriers impact DHI adoption and

acceptability. Patients with CVD are commonly older and have several comorbidities leading

to impaired physical and mental functioning [82]. The disease progression of various subtypes

of CVD, such as heart failure, can lead to progressive cognitive impairment, which can reduce

patients’ ability to engage with DHIs. This barrier is shared across countries of different economic

levels [16, 82, 88, 91]. Cultural, and socioeconomic factors might inﬂuence the acceptability

of digital health technologies. Well-known user characteristics associated with lower digital

health use are sex [62], older age, low (health) literacy [62] and low socioeconomic status

[123–125]. These characteristics, in part, are related to lower digital literacy, especially in

the use of mobile apps and telehealth solutions [123–125]. For example, patients might feel

uncomfortable with home visits or telemedicine visits with video calls in some cultures due

to privacy concerns regarding their home situation. Economic barriers remain a signiﬁcant

challenge for patients but have been extensively discussed in previous sections. Finally, a lack

of perceived effectiveness experienced by patients and a potential overload of DHIs might

hinder adoption. Because patients with CVD often have multiple comorbidities, there is an

inherent risk of being confronted with different unrelated DHIs for individual comorbidities (e.g.,

hyperlipidaemia, hypertension). Patients with a lower education level are at a higher risk of not

being able to engage with digital health technologies, especially at an older age [126].

Suggested solutions

As is the case for health care workers, digital health technologies require signiﬁcant investments

in patient education. Active involvement of caregivers and assisting patients in using DHIs might

improve utilisation [82]. Deployment of DHIs requires a rigorous context and needs assessment.

Patient factors such as socioeconomic status, gender role inﬂuencing access to technology,

cultural factors, practical ability, and digital literacy should be considered. Involving patients

in co-designing DHIs is necessary to mitigate these risks and has been demonstrated to be

impactful [43]. Further, it is essential to evaluate user perspectives and engagement alongside

clinical trials to fully understand how to optimise usefulness and engagement beyond the trial

[36].

CONCLUSIONS AND RECOMMENDATIONS

DHIs can ﬁll critical health system gaps in CVD management and prevention, empower patients,

and enable healthcare practitioners to provide higher quality and more efﬁcient care. There is

a substantial unmet need for collective action involving patients, healthcare providers, industry

members, regulators and reimbursement authorities, and policy makers to identify and

help solve context-speciﬁc barriers. This roadmap provided potential solutions for frequently

encountered obstacles to scaling up digital health solutions to improve the management and

prevention of CVD and the support and experience of care for those living with those conditions

globally.

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CASE STUDIES

MPOWER HEALTH A CLINICAL DECISION SUPPORT SYSTEM FOR EVIDENCE-

BASED CARE

Health system challenge

Empower non-physician healthcare workers through the use of a digital platform (evidence-

based Clinical Decision Support System).

Intervention

mPower Health is a digital platform designed to deliver integrated, comprehensive, and

continuous care to patients through innovative technology-driven tools that support healthcare

professionals.

In 2010, the Government of India initiated the National Programme for Prevention and Control

of Cancer, Diabetes, Cardiovascular Diseases and Stroke (NPCDCS) to respond to the challenges

related to the high burden of NCDs in India. The mPower Health platform was designed to

complement the NPCDCS programme.

The mPower Heart works on two core principles: Technology (a knowledge-based Clinical

Decision Support System-CDSS) and task-shifting (empowering non-physician healthcare

providers) (Figure 3).

mPower Health’s major capabilities/features are:

• A mobile app for healthcare providers and a web-based dashboard/server for healthcare

administration.

• Clinical Decision Support System generates ersonalized management plans for patients

with hypertension and diabetes by computing complex clinical management algorithms

and suggesting the diagnosis, optimal drugs, dosage, warning contra-indications, etc.

• Computing clinical risk scores to identify high-risk individuals and initiate preventive

measures.

• Maintaining longitudinal health records of the patient and assisting in scheduling follow-

up visits based on clinical parameters (avoid unnecessary travel and visits of the patients).

• Task Shifting: empowering the non-physician workforce to deliver quality care by using

technology.

• Generating lifestyle recommendations tailored to individual patients.

• Ability to work in ofﬂine mode (without internet connectivity).

• Real-time monitoring and proﬁle visualiser for trending and quick decision making.

Link with barriers and solutions

Acceptability and feasibility for health workers, ICT infrastructure

Piloting of the mPower platform has shown impressive results and signiﬁcantly impacted clinical

outcomes of patients with hypertension and diabetes [127]. Two states (Tripura and Mizoram)

governments in India adopted the mPower Health system for state-wide implementation.

Figure 3 NCD nurse using

mPower Health CDSS in a

government health facility,

reproduced with permission

from the Centre for Chronic

Disease Control (CCDC), New

Delhi, India.

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It was successfully implemented in forty health facilities in the state of Tripura [128] and

sixteen health facilities in Mizoram in India with the support of key stakeholders by providing an

enabling environment (healthcare workforce, digital infrastructure, change management, etc.).

The mPower Health met all the important conditions recommended by WHO for a successful

DHI such as health content (mPower Health provided standardised evidence-based care for

NCDs), alignment of the intervention with the national goal, digital infrastructure (support

provided the state health department) and enabling environment. In Tripura and Mizoram,

around 207, 000 people have beneﬁted from this technology-enabled NCD care.

National guidelines and clear strategy for long-term investment

The lack of national guidelines and strategies for the DHI at the time of implementation of

the mPower Health and no strategies for long-term investment impacted the uptake and

sustainability of mPower Health. As a result, the Government of India recently initiated the

Ayushman Bharat Digital Mission (ABDM) which aims to provide the necessary framework and

infrastructure [129]. The learnings from the states of Tripura and Mizoram and the support

provided by national agencies led to integrating the CDSS module of the mPower Health with

the Government of India’s Comprehensive Primary Health Care -NCD system under the I-TREC

[130]. Furthermore, the World Health Organization (WHO) adopted the mPower platform

to develop the mPEN App for promoting the use of the WHO PEN Package in the clinical

management of non-communicable diseases.

CONNECT: A CONSUMER-FOCUSED, RESPONSIVE AND PRIMARY CARE-

INTEGRATED WEB-APPLICATION

Health system challenge

To integrate data and communication directly between patients and their health care providers.

Intervention

Consumer Navigation of Electronic Cardiovascular Tools (CONNECT) is a consumer-focused,

responsive web application that is interactive and integrated with data from the patient’s

primary care electronic health record. It was co-designed with consumers, clinicians and

software developers and supported CVD risk management and decision-making. CONNECT

(Figure 4) includes digital reminders and access to (1) medical conditions, medicines and

interactive absolute risk awareness (red tiles); (2) goal-setting, progress tracking and virtual

rewards (green tiles); polling for interactivity and social interaction (blue tiles). In the words of

a patient, ‘It was a nice way of seeing the graph of the cholesterol thing coming down, so that

was great–that’s a bonus…visual feedback…I better keep walking, riding, whatever because it’s

working.’ [131].

Figure 4 CONNECT

smartphone application.

Reproduced from NPJ Digit

Med. 2020; 3. Redfern J,

Coorey G, Mulley J, et al., A

digital health intervention

for cardiovascular disease

management in primary

care (CONNECT) randomized

controlled trial.

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Links with barriers and solutions

User- and context-speciﬁc adaptations

Patients have electronic access to auto-populated information about their medical conditions

and prescribed medicines with links to more detailed information to enhance knowledge.

CONNECT also has smartphone and website access to an interactive and personalised CVD

risk system where individual patients can use interactive functions and receive visual feedback

about the relationships between their risk factors and absolute cardiovascular risk. Interactive

goal-setting (including virtual rewards) based on healthier eating, physical activity, smoking

cessation and emotional well-being, and goal achievement tracking with virtual rewards to

facilitate and motivate lifestyle changes.

Interoperability of digital health interventions

CONNECT is integrated with each patient’s primary care electronic record. Progress tracking

combines data imported from electronic medical records with patient logs such as blood

pressure control and weight management with calendar links for tests such as cholesterol

measurement requirements.

Acceptability and feasibility for healthcare works and patients

The intervention was co-designed, validated and beta-tested via a four-phase iterative

process that involved consumers, multidisciplinary clinicians, software developers and graphic

designers [132]. Through this process, researchers understood the complexity of end-user

needs and preferences, thereby improving and enriching the increasingly detailed system

designs and prototypes for a mobile responsive web application. The CONNECT intervention was

subsequently tested in a randomised clinical trial (n=934 patients with or at high risk of CVD) in

the Australian primary care environment with an average follow-up of 12. The study found no

signiﬁcant difference between groups for medication adherence, modest (but not signiﬁcant)

improvements in risk but signiﬁcant improvements in attainment of physical activity targets and

e-health literacy [18]. However, in qualitative analysis, patients, reported beneﬁting from the

cardiovascular risk score, goal tracking, risk factor self-monitoring and receipt of motivational

health tips. In contrast, general practitioners reported increased patient attendance and

engagement with care [131]. CONNECT has also been found to be accessible, well utilised, and

supported [121, 123]. It includes social interaction and an optional messaging service (email

or text). Patients can receive semi-personalised cardiovascular disease prevention tips and

motivational messages related to diet, medications and lifestyle. Further work is underway to

be iterative in implementation and revision of CONNECT and related DHIs that enable delivery

of tools that are useful for patients and beneﬁcial for health outcomes.

RURAL EMERGENCY TELEMEDICINE SUPPORT

Health system challenge

Deliver emergency care in underserved areas and remote settings.

Intervention

Providing emergency care in rural areas continues to be a global challenge. The pandemic

ampliﬁed the disparity in the care of underserved populations in the United States, notably the

20% of the people living in rural areas. With the closure of many rural hospitals, the emergency

medical response system faced longer response and transport times, delaying hospital-level

medical care. The Emory rural Tele-Emergency Medical Services (Tele-EMS) network underwent

a signiﬁcant innovative change with the work of Drs. Monique Smith and Michael Carr and their

team bring the clinical understanding of the hospital to the point of emergency contact and

automate data communication, allowing earlier patient-focused clinical care in the community

[133]. The digital strategy needed to accomplish this network in a rural area was an impressive

and globally relevant challenge to overcome. It involved three key pillars: clinical expertise,

the coordinated transmission of medical information and investment in communication

infrastructure.

In this programme, an emergency physician provides a video televisit to rural Grady Hospital

EMS crews to evaluate and suggest management of initial patient care. Patient data is

uploaded to a streaming cloud if specialised care is needed. The receiving facility is notiﬁed of

the patient’s arrival and the treatment plans that have been started. This allows emergency

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medical personnel to focus their attention on the patient’s care while the communication is

automated.

Links with barriers and solutions

User- and context-speciﬁc adaptations, ICT infrastructure

In contrast to usual telemedicine programmes, rural platforms require the ability to work in low

bandwidth settings and inside and outside the hospital. After evaluating solutions from multiple

companies, Emory chose SWYMED [134], which allows telemedicine visits to be conducted with

transmission as low as 60 kb per second. This signiﬁcantly increased the geographic reach of

telemedicine utilisation for emergency services. In addition, Emory worked with the primary

cellular provider for their region, Verizon, to identify the Airlink MG 90 router (Sierra wireless[R]

Vancouver Canada [135]) and installed it in their hospital system and afﬁliated ambulances.

This allowed rapid downlink and uplink speeds, Wi-Fi and ethernet access.

Interoperability of digital health interventions

Notably, the platform can integrate into EMS and hospital technology to enable rapid

cardiovascular data transmission. In this instance, the product integrated explicitly with Zoll,

the X series monitor deﬁbrillator used on Grady ambulances and the Emory electronic medical

record.

In conclusion, this case underscores the complex human capital, data standardisation,

integration, transmission and communications infrastructure needed to achieve scalable and

sustainable rural telemedicine. It also highlights the importance of multi-industry collaboration

to create meaningful change in rural health by creating new systems for high-quality access to

high-quality care.

ACKNOWLEDGEMENTS

We would like to thank World Heart Federation members and partners who provided feedback

through the roadmap development.

We also thank Astra Zeneca for their sponsorship of the WHF Digital Health Roadmap, as well

as Aktiia for their support of the initiative.

PUBLISHER’S NOTE

In February 2023, a typo in the ﬁrst sentence was brought to the attention of the publisher and

was amended.

COMPETING INTERESTS

Dr Jasper Tromp is supported by the National University of Singapore Start-up grant, the tier 1

grant from the ministry of education and the CS-IRG New Investigator Grant from the National

Medical Research Council; has received consulting or speaker fees from Daiichi-Sankyo,

Boehringer Ingelheim, Roche diagnostics and Us2.ai, owns patent US-10702247-B2 related to

artiﬁcial intelligence and echocardiography.

Dr Devraj Jindal holds a copyright for the CARDIOMETCARE-M software which is a clinical

decision support system.

Dr Julie Redfern owns a portion of the IP for the TEXTCARE software that was developed

following the TEXTME study. She is also funded by a NHMRC Investigator Grant Leadership Level

2 [GNT2007946].

Dr Khung Keong Yeo has received research funding from Amgen, Astra Zeneca, Abbott Vascular,

Bayer, Boston Scientiﬁc, Shockwave Medical, Nestle, Novartis (all signiﬁcant, via institution);

Consulting or honoraria feeds (all modest) from Abbott Vascular, Boston Scientiﬁc, Medtronic,

Amgen, Bayer, Novartis, Astra Zeneca, Peijia Medical; Speaker or Proctor fees from Shockwave

Medical, Abbott Vascular, Boston Scientiﬁc, Medtronic, Philips, Alvimedica, Bayer, Biotronik,

Orbus Neich, Shockwave Medical, Amgen, Novartis, Astra Zeneca, Microport, Terumo.

16Tromp et al.

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DOI: 10.5334/gh.1141

Dr. Lopez-Jimenez is co-inventor of several AI algorithms that have been licensed to digital

health companies and may receive ﬁnancial compensation in the future. He is member of the

advisory board for Anumana, an AI-based technology company. He has co-developed digital

health technology to use 3D volumes to assess cardiometabolic risk with Selected Research

Inc, and may receive ﬁnancial beneﬁt in the future.

Dr Dorairaj Prabhakaran holds a copyright for the CARDIOMETCARE-M software which is a

clinical decision support system.

Prof Carolyn SP Lam is supported by a Clinician Scientist Award from the National Medical

Research Council of Singapore; has received research support from Bayer and Roche Diagnostics;

has served as consultant or on the Advisory Board/Steering Committee/ Executive Committee

for Abbott, Actelion, Alleviant Medical, Allysta Pharma, Amgen, AnaCardio AB, Applied

Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientiﬁc, Cytokinetics, Darma

Inc., EchoNous Inc, Impulse Dynamics, Ionis Pharmaceutical, Janssen Research & Development

LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Radcliffe

Group Ltd., Roche Diagnostics, Sanoﬁ, Siemens Healthcare Diagnostics and Us2.ai; and serves

as co-founder & non-executive director of Us2.ai.

Dr Martin R Cowie has provided consultancy advice to Medtronic, Boston Scientiﬁc, Abbott and

AstraZeneca, related to aspects of digital health. As from 1 August 2022 he has been employed

by AstraZeneca as Clinical Vice-President in Late Stage Research (Biopharmaceuticals).

AUTHOR CONTRIBUTIONS

Dorairaj Prabhakaran, Carolyn S.P. Lam and Martin R. Cowie are co-Chairs of the Roadmap

and contributed equally to this manuscript.

AUTHOR AFFILIATIONS

Jasper Tromp orcid.org/0000-0001-6043-0713

Saw Swee Hock School of Public Health, National University of Singapore, The National University Health

System Singapore, and Duke-NUS Medical school, Singapore

Devraj Jindal

orcid.org/0000-0003-2384-7354

Centre for Chronic Disease Control, New Delhi, IN

Julie Redfern

School of Health Sciences, Faculty of Medicine and Health, University of Sydney, AU

Ami B. Bhatt

Massachusetts General Hospital, Boston, US

Tania Séverin

World Heart Federation, Geneva, CH

Amitava Banerjee

Institute of Health Informatics, University College London, London, GB

Junbo Ge

Fudan University Zhongshan Hospital, CN

Dipti Itchhaporia

Hoag Hospital, University of California, Irvine, Newport Beach, US

Tiny Jaarsma

Dpt of Medicine, Health and Caring Sciences, Linköping University, Linköping, SE

Fernando Lanas

Universidad de La Frontera, Temuco, CL

Francisco Lopez-Jimenez

Dpt of cardiovascular medicine, Mayo Clinic, Rochester, US

Awad Mohamed

Dpt of Medicine, University of Khartoum, Khartoum, SD

Pablo Perel

London School of Hygiene & Tropical Medicine, London, UK; World Heart Federation, Geneva, CH

Gonzalo Emanuel Perez

Dpt of Cardiology, Clínica Olivos, Buenos Aires, AR

Fausto J. Pinto

University Hospital CHULN, CAML, CCUL@RISE, Faculty of Medicine of the University of Lisbon, Lisbon, PT

17Tromp et al.

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DOI: 10.5334/gh.1141

Rajesh Vedanthan

Department of Population Health/Institute for Excellence in Health Equity, New York University Grossman

School of Medicine, New York, US

Axel Verstrael

Hasselt University, Antwerp, BE

Khung Keong Yeo

Dpt of cardiology, National Heart Centre Singapore, SG

Kim Zulﬁya

Dpt of internal medicine, City Clinical Hospital No. 7, Kazan medical state university, Kazan, RU

Dorairaj Prabhakaran

orcid.org/0000-0002-3172-834X

Centre for Chronic Disease Control, New Delhi, IN; Public Health Foundation of India, Gurugram, IN;

London School of Hygiene & Tropical Medicine, London, UK

Carolyn S.P. Lam

National Heart Centre Singapore, Duke-National University of Singapore, SG

Martin R. Cowie

orcid.org/0000-0001-7457-2552

Royal Brompton Hospital & School of Cardiovascular Medicine, Faculty of Life-sciences and Medicine,

King’s College London, London, GB

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TO CITE THIS ARTICLE:

Tromp J, Jindal D, Redfern J,

Bhatt A, Séverin T, Banerjee A,

Ge J, Itchhaporia D, Jaarsma

T, Lanas F, Lopez-Jimenez F,

Mohamed A, Perel P, Perez

GE, Pinto F, Vedanthan R,

Verstrael A, Yeo KK, Zulﬁya

K, Prabhakaran D, Lam CSP,

Cowie MR. World Heart

Federation Roadmap for

Digital Health in Cardiology.

Global Heart. 2022; 17(1): 61.

DOI: https://doi.org/10.5334/

gh.1141

Submitted: 14 July 2022

Accepted: 20 July 2022

Published: 26 August 2022

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Global Heart is a peer-reviewed

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