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A. Piau1,2, Z. Steinmeyer1, M. Cesari3, J. Kornfeld4, Z. Beattie4, J. Kaye4, B. Vellas1,2, F. Nourhashemi1,2

1. Gerontopole, Toulouse University Hospital, 31059 Toulouse, France; 2. UPS/INSERM, UMR1027, F-31073 Toulouse, France; 3. Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy; 4. Oregon Center for Aging & Technology (ORCATECH), Oregon Health & Science University, Portland, USA.
Corresponding author: Antoine Piau, La Cité de la Santé, Bâtiment Ex-Biochimie, Hôpital La Grave, Place Lange, TSA 60033, 31059 Toulouse Cedex 9, France, E-mail address: piau.a@chu-toulouse.fr, Phone number: +335 61 32 30 10, Fax number: +335 61 77 64 75

J Frailty Aging 2020;in press
Published online October 5, 2020, http://dx.doi.org/10.14283/jfa.2020.51



The WHO action plan on aging expects to change current clinical practices by promoting a more personalized model of medicine. To widely promote this initiative and achieve this goal, healthcare professionals need innovative monitoring tools. Use of conventional biomarkers (clinical, biological or imaging) provides a health status assessment at a given time once a capacity has declined. As a complement, continuous monitoring thanks to digital biomarkers makes it possible to remotely collect and analyze real life, ecologically valid, and continuous health related data. A seamless assessment of the patient’s health status potentially enables early diagnosis of IC decline (e.g. sub-clinical or transient events not detectable by episodic evaluations) and investigation of its probable causes. This narrative review aims to develop the concept of digital biomarkers and its implementation in IC monitoring.

Key words: ICOPE program, digital biomarkers, technology, remote monitoring, intrinsic capacity.


The ICOPE program and the necessary but difficult monitoring of intrinsic capacity over time

The WHO defines Intrinsic Capacity (IC) as a “composite of all physical and mental capacities that an individual can draw on”, and functional ability as “health-related attributes that enable people to be and to do what they have reason to value” determined by the interaction of a person’s IC with their environment (1). The ‘Integrated care for older people’ (ICOPE) report translates this strategy into clinical recommendations (WHO ICOPE), from assessment of individual needs and preferences to the development of a comprehensive care plan and coordinated services. ICOPE defines older adult’s health status with five domains of intrinsic capacity: locomotor, vitality, sensory, cognition and psychological capacity. WHO ICOPE recommended an overall clinical approach from large-scale screening to the proposal of an individualized intervention if IC declines.
IC evaluation should be based on longitudinal multiple observations of an individual’s trajectory over time (1), but real-life implementation raises serious issues. Previous primary care initiatives have shown the possibility to screen and assess older people presenting a high risk of IC impairment and to implement a personalized care plan as necessary (2, 3). Ideally, this close follow-up would occur in a person’s home and community setting with minimal intrusion. However, promotion of this outpatient care follow-up remains sparse. Despite being challenging, continuous monitoring of health-related real-life data (not reliant on clinician-mediation), persists as among the most critical issues faced by modern medicine (4, 5) for a number of reasons:
(i) Increasing numbers of patients with limited health resources, constrains the possibility of in-person assessment (self-management is increasingly necessary);
(ii) For implementation of proactive or preventive personalized interventions, early negative trends in IC must be detected in order to investigate underlying causes;
(iii) Continuous monitoring of IC dimensions is needed to measure an individual’s longitudinal trajectories over time after an intervention;
(iv) Functional abilities assessment – explained by the interaction of a person’s IC with its environment – must be unobtrusively measured in one’s own environment (achieving ecological validity).

In this narrative review, we propose to illustrate, through examples from basic research and clinical initiatives, the potential contribution of the so-called «digital biomarker» to this need for intrinsic capacity monitoring.

Why Digital Medicine can be useful for ICOPE implementation

How is a digital biomarker different from a ‘conventional’ biomarker?

Early detection of health transitions by physicians is often difficult (4, 5). Thus, identifying sensitive and clinically relevant biomarkers to detect subtle but meaningful changes is a challenge. Most conventional biomarkers (6) do not fit a long-term monitoring strategy. Indeed, clinical biomarkers such as questionnaires are time consuming, performed at a given point in time, which affects sensitivity, and are based on patients’ recall of prior events (7). Biological biomarkers are often invasive and do not lend themselves to high throughput collection. Finally, imaging biomarkers are costly, require specialized facilities and personnel, and inappropriate for a continuous data collection model (5).
Relatively new terms and concepts have been developed in Information and Communication Technologies (ICT) in particular with regard to innovative clinical endpoints emerging from digital medicine (8-12). We have chosen to use the widespread term ‘digital biomarkers’ (DB). The proposed definition of ‘digital biomarkers’ is : objective, quantifiable, physiological and behavioral data that are collected and measured by means of digital devices such as embedded environmental sensors or wearables, which opens up opportunities for remote data collection and processing of large amounts of ecologically valid, real-life, continuous and long-term health-related data. Table 1. illustrates the difference between conventional compared to digital biomarkers.

Table 1
Key points underling the uniqueness of digital biomarkers and opportunities for ICOPE

*IC, Intrinsic Capacity.


What do digital biomarkers have to offer for ICOPE?

The use of conventional biomarkers proposes an in-depth clinical, biological or imaging assessment when a decline in capacity is diagnosed. Conversely, continuous monitoring with digital biomarkers make it possible to prospectively detect transitory or short-term variation over time or sub-clinical decline in IC (see Figure 1 for practical examples). For example, the evolution of ultradian (e.g. variation in body temperature) or circadian (e.g. sleep-wake cycle) rhythms is poorly explored and exploited in clinical practice due to the lack of simple and acceptable measurement tools. DB can capture short-term intra-individual fluctuations in IC and functional abilities. Intra-individual variability in performance (e.g. day-to-day gait speed variability) may also be among the earliest indicators of a negative trend in one’s IC (13-18) (figure 2). DBs enable the differentiation of short-term fluctuations (i.e. a good day vs. a bad day) from more persistent, long-term changes and provides a means to objectify the speed of recovery of an individual after an acute event (e.g. fall). Lastly, DB could measure subclinical events, which are associated with poor prognosis that are not detectable by episodic assessments. For example, ‘silent falls’ are falls which are unnoticed by healthcare professionals but lead nevertheless to impaired walking ability and an increased the risk of loss of autonomy in the future (19).
DB can thus provide health care professionals with information about negative trends in IC by timely checking the patient’s status and investigating the underlying causes. This measurement of variations in IC gives us access to information that was previously inaccessible and allows us to understand why and when a person remains stable, recovers quickly after an event or continues to lose autonomy despite interventions.

Figure 1
Monitoring the activity dimension of intrinsic capacity through digital biomarkers

Note: The monitoring of physical activity through digital biomarkers (e.g. gait speed as measured by wearables or embedded sensors) could detect: (i) early negative trends or subclinical declines not detected by episodic clinical assessments due to lack of sensitivity ( scenario A); (ii) a transient decline between two face-to-face visits ( scenario B); (iii) a change in intra-individual variability that may precede a decline or herald recovery ( scenario C).


Figure 2
Intra-individual variability in performance over time

Note: one hypothesis, supported by several authors (15, 40), is an increased variability of health-related parameter in a situation of early pre-symptomatic impairment followed by a decreased variability before a clinically perceptible impairment occur (scenario A). If we stick to that hypothesis, an increased variability in performance (physiological reaction) and then a return to a normal variability could announce an early recovery in IC and thus a favorable prognosis (scenario B).


How can we design a digital health program for ICOPE

The implementation of ICOPE is divided into several steps: a remote first line screening of the domains of intrinsic capacity as defined by WHO (STEP 1); follow-up over time and, if necessary, an in-depth assessment carried out at home or in a health care facility (STEP 2). The latter would occur if a decline is detected. Once the underlying causes are investigated, an individualized intervention program can be proposed (STEPS 3-5). Digital biomarkers can be implemented in the first step (STEP 1) and carried through to later steps for long-term patient monitoring.

First-line Screening (STEP 1)

It is possible to propose different digital tools depending on the healthcare context, specific use case and end-users. Large-scale evaluation (e.g. text messaging) may be implemented by the use of existing technologies such as smartphones which are low-cost and widely available tools. For specific scenarios, other tools may be developed and integrated (e. g. dedicated smartphone apps, embedded sensors). Examples of tools are proposed in Table 2: from the simplest use of online surveys to complex multi-domain, sensor-based measurements. A personalized and increasing level of digital assistance can be offered to the user. The level of assistance required and its evolution over time may by itself indicate the user’s capabilities.
Digital technologies offer us numerous possibilities of remote screening and assessment, as shown in Table 2, However, by definition, digital biomarkers are more related to continuous monitoring or high frequency collection, and not to the occasional use of a digital tool for one-time screening.. Ideally, DBs allow us to uncover (figure 1):
– a transient decline in an IC during a minor clinical event;
– a negative and sustained subclinical trend in one or several IC subdomains;
– an abnormal intra-individual fluctuation in IC and/or in functional abilities.

This will also be used to objectify the recovery rate during the proposed intervention.

Table 2
Examples of digital solution for STEP 1 implementation

*Abbreviations: SPPB, Short Physical Performance Battery; GP, General Practitioner; MOCA, Montreal Cognitive Assessment; GDS, Geriatric depression Scale; MNA-SF, Mini Nutritional Assessment Short-Form; § Note. Most of the examples of simple digital solutions (STEP 1, column 3) are already implemented in the ICOPE-CARE program, whereas the example of advanced digital solutions (STEP 1, column 4) are ideas for future improvements.


DB for remote continuous follow-up of IC

Several research teams have confirmed both the relationship between real life sensor-based DB and IC dimensions (5, 10, 11, 20, 21) and the possibility of tracking subclinical events (19). Sensor-based real life in-home walking speeds (15), activity patterns (18), routine driving (22), variability in medication taking (17), sleep activity (23), and daily computer use (14) have been correlated to functional autonomy and cognitive status. Continuous monitoring of IC-related parameters provides relevant information under free-living conditions. Given the importance of acceptability and adherence issues in this population, use of passive unobtrusive solutions are preferred (e.g. smart home environments) rather than wearables that require more active engagement (24). However, wearables (and their related apps) rely on self-management and thus can actively involve patients in their care.
Remote follow-up may be performed in different ways:
– End-user centered active solutions (self-assessment) providing feedback to the patient in order to drive him/her to a healthier lifestyle without any professional support.
– A solution focused on healthcare professionals through regular teleconsultations with connected objects (e.g. actimeter) to provide continuous objective data.

In between, the intervention of a third party, will be required in many cases. The range of solutions is wide, from a family care partner to a health professional’s support (e.g. nurse), at home or in a dedicated place (e.g. pharmacy, public office). The tool chosen and the complexity of the assessment must obviously be adapted to the patient’s socio-economic context (e.g. highly educated urban dwellers vs low income, rural, socially isolated). Many variables must be taken into account before designing a monitoring solution (Table 3). Using tools that are familiar to the target audience (e.g. email, text messaging) allows a better implementation at a lower cost. One simple solution for continuous follow-up of IC is to repeat ‘STEP 1’ over time through a text-messaging questionnaire coupled to connected objects or sensors.

Table 3
Different variables illustrating the possible monitoring modalities depending on available resources


Moving forward, the digital part of the INSPIRE project

To better illustrate how DB could be implemented in daily clinical practice, here is the practical example of the Inspire project, which includes a digital part focusing on IC monitoring.

The INSPIRE-T cohort

A vast research program dedicated to healthy aging was launched in the Occitania region (France), called the INSPIRE initiative (25-27). The INSPIRE Human Research Translational cohort (called INSPIRE-T) is part of this program. The specific aim is to explore and identify biomarkers of aging and IC evolution through annual biological, clinical, and digital data over 10 years, and therefore through both so-called conventional biomarkers and digital biomarkers. 1000 subjects ages 20 to 100+ years old are being enrolled. An important part of the project is to better understand the evolution of IC over time, followed by a web-application for IC self-monitoring, the ICOPE MONITOR Smartphone-app. This application can be easily used by the population and, beyond this research initiative, will be implemented on a large scale through the INSPIRE ICOPE-CARE program (28-34).
This free, open-access application allows the patient to self-assess quickly every 4 months (Step 1, about 6 minutes) through simple, validated tests. For example, he is asked to perform a self-timed chair-raising test. A team of nurses receives the results remotely on a dashboard. When a decline is detected between two self-assessments, the patient is offered a face-to-face evaluation (Step 2). If the time gap between two self-assessments is relatively long (4 months) and if the measurement is not yet sensor-mediated, this type of organization paves the way for the wider use of digital biomarkers for IC monitoring (e.g. automatic and unobtrusive measurement of transfers from sitting to standing by an accelerometer throughout the day). It is with this in mind that we launched the ancillary study CART France to anticipate this transition.

The CART-France digital biomarkers cohort

To further explore the field of IC digital biomarkers, we launched the CART-France cohort (an ancillary study of INSPIRE-T). It consists of a subgroup of 100 INSPIRE-T participants monitored by ambient and wearable sensors at home (e.g. infrared sensors on the ceiling, bed mat) over a long period of time. This will allow remote and continuous monitoring of IC trajectories and detect subtle changes that are not readily detected with conventional methods. For this purpose, INSPIRE has initiated a partnership with the ORCATECH team at Oregon Health & Science University in Portland (OHSU, OR, USA), a leading center in the field of smart homes and digital biomarkers in the field of advanced age and the coordinating center of the Collaborative Aging (in Place) Research Using Technology (CART) research project. The ORCATECH CART program supports an infrastructure for rapid and effective conduct of research utilizing technology (35). As such, we will be the first center outside the USA and Canada to join this research network. The collaboration between INSPIRE and CART is an important step in facilitating a more global view of digital health technology methodology and data sharing. These digital biomarkers will be correlated with clinical data but also biological and imaging -hallmarks of aging gathered through the INSPIRE-T cohort (36). This will be the most original part of the project, which will allow a better understanding of the complementary aspects of each type of biomarker. If we take the example of the ‘locomotion’ domain of intrinsic capacity (figure 1 and 2), continuous real-life measurements such as: room transitions, walking speed and its variability over time, number of steps, activity time and sleep time, etc. will be correlated with the annual biological, imaging and clinical evaluations. They are all digital biomarker candidates to be confirmed or discovered.


Challenges and opportunities

Integration of digital health in a pre-existing care network and a given socio-economic context is challenging. Beyond technical and regulatory requirements (e.g. health data security, interoperability with the existing IT ecosystem), raw collected data needs to be analyzed before it can be used in decision-making in clinical practice (e.g. establishing thresholds, critical scores). A clinician’s involvement in technical solutions specification is necessary to develop tools which are easily implemented in routine clinical practice. Up until now, most of the literature dealing with digital monitoring has been limited to small samples assessed in specially designed test-homes or bioengineering laboratories (21). These latter results are difficult to extrapolate to real life settings, and less selected, wider populations. Furthermore, as with any change in clinical practice, we need a combination of specific initial and continuing training in addition to political and public awareness to achieve widespread implementation of digital innovations in this area.
As fully discussed elsewhere, technological tools, as a medical intervention, comprises potential risks and thus security, ethical and regulatory concerns (37). As an example, both health data security and regulatory policy issues (e.g. medical device regulation) remain unsettled areas, highly dependent on national regulations despite the effort to develop international health data security standards (e.g. HIPAA, GDPR). Another point of concern is access to care. Paradoxically, new technologies have the potential to both increase and decrease health inequalities. On one hand, digital devices may increase social inequalities due to limited access. For example, an older age, lower income, lower education, living alone, and living in rural areas were found to be associated with lower eHealth use (38); On the other hand, certain studies suggest that digital technologies may reduce disparity in healthcare access regardless of social or economic status and geographical considerations (39, 40).
The clinical validation of DBs also remains a fundamental issue (8-15). It can be done through comparison to clinical gold standard. For example, walking speed as measured by infrared sensors versus walking speed as measured by a stopwatch. However, this example illustrates the paradoxical aspect of such an approach since the precision of these measurements are in no way comparable. The use of a handheld chronometer only gives a measurement that is far from the desired accuracy, which can approach 0.1cm/sec (41). It is also possible to validate these measurements by direct correlations with clinical events (41), when possible and appropriate. Finally, although the first large-scale continuous monitoring initiatives are now more than 10 years old, and have demonstrated valid associations with clinical evaluations using gold standards, there is little cross-reference of these DB with biological or imaging biomarkers. The INSPIRE-T cohort aligns with this need (26, 28).


Conclusion and perspectives

Digital technologies offer opportunities to support new models of healthcare through telehealth initiatives enriched by digital biomarkers data. The ICOPE initiative provides a framework to capture the potential contribution of these technologies to the field of aging. DB provide the opportunity to enhance ‘conventional’ biomarkers by adding continuous data flow to discrete and focused in depth analysis. They do not substitute but complement each other. Moreover, DBs uniquely assess a person’s IC interaction with their own environment and thus their functional abilities. Implementing digital medicine in routine clinical practice has the great advantage of integrating overall medical care from screening to treatment. ICTs may also promote other recommendations such as self-management encouragement and remote support for a healthy lifestyle. (http://www.who.int/ageing/health-systems/mAgeing/en/).


Funding: The Inspire Program was supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175), the European Regional Development Fund (ERDF) (Project number: MP0022856), and the Inspire Chairs of Excellence funded by: Alzheimer Prevention in Occitania and Catalonia (APOC), EDENIS, KORIAN, Pfizer, Pierre-Fabre, Fondation Avenir Cogfrail Grant.
Acknowledgements: The authors thank all the health professionals participating in the INSPIRE ICOPE CARE Program. We would also like to thank Zachary Beattie and Judith Kornfeld (OHSU, OR, Portland) for their careful rereading of the first drafts of the article.
Potential Conflicts of Interest: All authors declare to have no support from any organization for the submitted work (except the French Ministry of Health which supported the study by a grant), no financial relationships with any organisations that might have an interest in the submitted work, no other relationships or activities that could appear to have influenced the submitted work.
Ethical Standards: There were no patients included in this study, therefore we did not obtain consent and were not reviewed by an ethics committee.



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