Are Conversational Agents Used at Scale by Companies Offering

Digital Health Services for the Management and Prevention of

Diabetes?

Roman Keller

, Jiali Yao

, Gisbert Wilhelm Teepe

, Sven Hartmann

Kim-Morgaine Lohse

, Florian von Wangenheim

1,2 e

, Falk Müller-Riemenschneider

1,3,4 f

Jacqueline Louise Mair

1,2,

and Tobias Kowatsch

1,2,5,

Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise

(CREATE), Singapore

Center for Digital Health Interventions, Department of Management, Technology, and Economics, ETH Zurich,

Zurich, Switzerland

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

Yong Loo Lin School of Medicine, National University of Singapore, Singapore

Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen,

St. Gallen, Switzerland

Keywords: Digital Health Companies, Healthcare, Type 2 Diabetes, Prevention, Management, Funding, Conversational

Agents.

Abstract: Successful interventions to prevent and manage type 2 diabetes rely on long-term, day-to-day decisions which

take place outside of clinical settings. In this context, human resources are difficult to scale up, and leveraging

Conversational agents (CAs) could be one way to scale up healthcare to tackle the emerging epidemic of type

2 diabetes. The objective of this paper is to assess the degree to which CAs are employed by top-funded digital

health companies that target the prevention and management of type 2 diabetes. Companies were identified

via two venture capital databases, i.e. Crunchbase Pro and Pitchbook. Two independent reviewers screened

results and the final list of companies was validated and revised by three independent digital health experts.

The companies’ digital services (usually mobile applications) were accessed and reviewed for the utilisation

of CAs. To better understand the purpose of identified CAs, relevant publications were identified via PubMed,

Google Scholar, ACM Digital Library and on the companies’ website. Nine out of 15 companies’ digital

services were accessible to the authors and only in one case a CA was employed. The uptake of CAs by top-

funded digital health companies targeting type-2 diabetes is still low.

1 INTRODUCTION

Diabetes is a chronic condition characterized by

elevated levels of blood glucose. It occurs when the

pancreas cannot produce sufficient hormone insulin

https://orcid.org/0000-0003-4810-4944

https://orcid.org/0000-0001-7269-4679

https://orcid.org/0000-0002-2264-9797

https://orcid.org/0000-0002-0256-6687

https://orcid.org/0000-0003-3964-2353

https://orcid.org/0000-0003-1402-7477

https://orcid.org/0000-0002-1466-8680

https://orcid.org/0000-0001-5939-4145

Shared last authorship

or the body cannot use the insulin effectively (WHO,

2016). If not managed appropriately, diabetes can

lead to a series of life-threatening microvascular and

macrovascular complications including blindness,

Keller, R., Yao, J., Teepe, G., Hartmann, S., Lohse, K., von Wangenheim, F., Müller-Riemenschneider, F., Mair, J. and Kowatsch, T.

Are Conversational Agents Used at Scale by Companies Offering Digital Health Services for the Management and Prevention of Diabetes?.

DOI: 10.5220/0010412708110816

In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF, pages 811-816

ISBN: 978-989-758-490-9

811

kidney failure, heart attacks, stroke and lower limb

amputation (WHO, 2016).

Type 2 diabetes (T2D) is the most common form

of diabetes and accounts for about 90% of diabetes

cases worldwide (International Diabetes Federation,

2019; WHO, 2016). Despite its links to non-

modifiable factors such as family history, ethnicity,

and increasing age, T2D is strongly tied to key

modifiable lifestyle risk factors including overweight

or obesity, poor diet, physical inactivity, and smoking

(International Diabetes Federation, 2019; WHO,

2016). Numerous landmark studies in the past have

demonstrated that over 50% of T2D can be prevented

or delayed through cornerstone interventions

targeting lifestyle modification and through

pharmacological interventions (International

Diabetes Federation, 2019). Likewise, strong

evidence also shows that T2D can be effectively

managed, or even reversed, in T2D patients via

similar intervention strategies (International Diabetes

Federation, 2019). Despite firm and encouraging

evidence, many key challenges persist with respect to

real-world implementation of T2D prevention and

management interventions at scale. One key

challenge is that conventional approaches of

delivering these T2D interventions are financially

expensive and human-resource intensive (Wu et al.,

2019). Another is that these interventions on T2D,

similar to those on other non-communicable diseases,

rely heavily on individual’s long-term and day-to-day

decisions, which mostly occur outside clinics and

hospitals and are difficult to monitor and intervene in

traditional manners (Rui et al., 2014; Wu et al., 2019).

Rapid advancements in digital and wireless

technology have provided unprecedented

opportunities to overcome such challenges and

transform and ‘scale-up’ healthcare delivery. This has

motivated large amounts of recent research and

investments of digital health companies into

developing digital solutions (Kvedar et al., 2016),

aiming to harness pervasive digital technology to

improve and scale up the prevention and management

of T2D (Alexander Fleming et al., 2020). Promising

results have been found in many digital programs of

T2D on glucose control, medication adherence,

weight loss, and quality of life (Alexander Fleming et

al., 2020). However, digital health programs have so

far been hampered by low user engagement and high

attrition rates, and long-term evidence is lacking to

comprehensively assess practical values (Garg &

Parkin, 2019). To address these issues, ‘virtual

diabetes coaching’ via Conversational Agents (CAs)

has been identified as an encouraging component of

current and future digital health offering for T2D care

(Garg & Parkin, 2019; O’brien, 2017; Ramchandani,

2019).

CAs are computer systems that imitate human

conversation using images, text or spoken language

and they can offer personalized human-like

interactions and social contacts (Laranjo et al., 2018;

Schachner et al., 2020). Recent studies have shown

promising results of CAs with regard to patient

satisfaction (T. W. Bickmore et al., 2010), treatment

outcomes (Ma et al., 2019), and the ability to build

work alliances with the patient (T. W. Bickmore &

Picard, 2005; Hauser-Ulrich et al., 2020; Kowatsch et

al., 2020). In addition, CAs have been found to be safe

for T2D care and even provide comparable

effectiveness to peer human coaching (Car et al.,

2020; King et al., 2020).

However, despite an increasing evidence base of

utilizing CAs for T2D prevention and management,

little is known about the actual adoption of CAs in the

burgeoning digital health industry and its most

successful companies. Moreover, there is a need to

identify the characteristics of those CAs in order to

guide future developments in the industry. Therefore,

this study aims to provide an observational analysis

of the uptake and characteristics of CAs among

digital services of the top-funded companies in the

T2D digital health industry.

2 METHODS

2.1 Databases and Companies

Top-funded digital health companies targeting the

prevention and management of T2D were identified

using the two venture capital databases Crunchbase

Pro and Pitchbook (Crunchbase, n.d.; PitchBook,

n.d.). These databases have been found to be among

the most comprehensive and accurate venture capital

databases and both are commonly used in academic

reports and by investors (Retterath & Braun, 2020).

We decided to select the fifteen companies with the

most funding in terms of total funding amount

through July 23, 2020.

2.1.1 Search Strategy

The search strategy included an extensive list of terms

describing the constructs “verticals & methods &

industries”, “diabetes”, and “management &

prevention”. The overview of the complete search

strategy for Crunchbase and Pitchbook is shown in

Table 1.

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812

Table 1: The search strategy used in Crunchbase and

Pitchbook.

cate

Search terms

Verticals &

methods &

industries

Monitoring Equipment OR diagnostic

OR HealthTech OR healthcare

devices OR connected health* OR

Therapeutic Devices OR Digital

Health OR digital health* OR health*

technology OR health* app* OR

wearables OR Mobile health OR

mhealth OR mobile app OR personal

health OR virtual care OR e-health

OR assistive technology OR

telehealth OR telemedicine OR

health* platform OR healthcare it OR

data management OR Artificial

Intelligence & Machine Learning OR

Cloud data services OR analytics OR

health* diagnostics OR Big Data OR

information OR digital OR data OR

biometrics OR home health care OR

medtech OR self-monitorin

Diabetes obesity OR blood sugar OR blood

lucose OR insulin OR diabet*

Management

Prevention

diabetes management OR diabetes

treatment OR diabetes control OR

diabetes monitoring OR blood sugar

monitoring OR disease monitoring

OR disease management OR risk

reduction OR disease prevention OR

diabetes prevention OR prevention

OR prediabet*

2.1.2 Selection Criteria

We included companies if they offered a digital

health intervention that involved the prevention or

management of T2D. A digital health intervention

was defined as a discrete functionality of digital

technology that is applied to achieve health objectives

and followed the definition of the WHO classification

of digital health interventions (World Health

Organization, 2018).

Companies were excluded if their intervention (1)

did not focus on patients; (2) mainly focused on the

administrational needs of hospitals (hospital

information systems); and (3) did not involve a digital

solution as main intervention component. In addition,

we excluded companies if their intervention (4)

involved any form of continuous blood glucose

monitoring or automated insulin delivery system; (5)

did not involve behaviour change; and (6) mainly

targeted insulin-dependent diabetics, as such

interventions mainly target medication adherence

rather than lifestyle behaviours.

Furthermore, we excluded companies in which

the intervention was any kind of general weight loss

or fitness app without focus on T2D.

2.1.3 Selection Process

The top 15 most-funded companies combined from

both database searches were identified as they

account for over 90% of the total funding in all

companies which gives a representative and

comprehensive insight into current state of the digital

health industry. In case of conflicting funding

information between both databases, Crunchbase

information was preferred as it has been found to have

better coverage with respect to total capital

committed and financing rounds than Pitchbook

(Retterath & Braun, 2020). Eligibility of companies

was determined by two independent investigators.

The results were compared, and disagreements

discussed until a consensus was reached.

After a first list was defined, three independent

experts in the fields of digital health and T2D were

approached to validate the company list. In case of

disagreements between experts, the authors followed

the opinions of the majority. Based on their feedback,

the company selection criteria were slightly adapted,

and the company list was adapted. In particular,

companies that provide interventions for continuous

glucose measurement and automated insulin delivery

systems were excluded from our list, as their digital

solution was not considered to be the main

intervention component. In addition, the services of

those companies mainly focused on insulin-

dependent diabetics and were not involving any

behavioural change strategies. Furthermore, the

company KKT Technology Pte. Ltd. (Holmusk) was

added to the list of top-funded digital health

companies, as the company meets our inclusion

criteria in terms of the amount of funding and offered

digital health intervention but was not identified with

our search strategy.

2.2 Digital Health Interventions

All identified digital services were available in the

form of mobile applications as predominant mode of

intervention delivery. Thus, we searched and

downloaded these apps from the two most popular

app stores: Google Play store and Apple app store

(IDC, 2020). The latest app search was conducted on

November 21, 2020.

If a mobile application was not accessible to the

authors, the companies were systematically

approached via email and requested for access. In

Are Conversational Agents Used at Scale by Companies Offering Digital Health Services for the Management and Prevention of Diabetes?

813

case no reply was received on the first email, a

follow-up email was sent two weeks later.

If the authors were not able to access the app, no

judgement on the presence of a CA could be done.

2.3 Publications

Three databases (PubMed, Google Scholar, and ACM

Digital Library) were systematically searched for

scientific articles, published between database

inception and October 2020, using the search terms

“Name_Intervention” AND (Smartphone OR

Application OR App OR Intervention OR Mobile

Health) relating to the identified company’s T2D app.

In addition, we screened the websites of the

companies for relevant publications on their

conversational agents, as some publications could not

be identified via the databases searches.

2.4 Conversational Agents

Two investigators reviewed the identified accessible

apps and assessed whether a conversational agent was

utilised (Table 2). In a second step, the characteristics

of the identified CA were extracted by reviewing the

app as well as the identified publications. The

conversational agent characteristics included the

health goal, type of agent, input format, output format

and dialogue initiative. Covidence

(www.covidence.org) was used for the data

extraction.

3 RESULTS

The overview of the 15 top-funded digital health

companies in the prevention and management of T2D

and their utilised CAs can be seen in Table 2.

From the reviewed companies, 6 apps were not

accessible because they were only available: (1) with

a subscription service (Virta Health Corp., Dario

Health Corp.); (2) in a specific geographic region

(Virta Health Corp., Welldoc Inc., Liva Healthcare

ApS); or (3) with an employer subscription or when

being referred by a physician (Virta Health Corp.,

Dario Health Corp., Welldoc Inc., Twin Health Inc.,

Sweetch Health Ltd.). Of the 9 accessible apps, 8 apps

did not include any CAs, and Lark Technologies, Inc.

was the only company with an app that employed a

conversational agent.

As Lark Technologies, Inc. was the only company

with a diabetes-relevant conversational agent, only

publications of Lark Technologies, Inc. were

considered for this analysis.

Table 2: Ranking of the fifteen top-funded digital health

companies in type 2 diabetes prevention and management

and utilisation of CAs in the mobile applications of the

companies as of November 27, 2020, sorted in descending

order of total funding amount. CA = Conversational agent,

Y = CA used, N = No CA used, - = Mobile application not

accessible.

Company

Funding

Rank #

Company legal name

used?

1 Omada Health, Inc. N

2 Livon

o Health, Inc. N

3 Virta Health Corp. -

4 Noom, Inc. N

5 DarioHealth Cor

. -

6 Informed Data Systems, Inc.

(One Drop)

7 Lark Technologies, Inc. Y

8 Vida Health, Inc. N

9 Welldoc, Inc. -

10 Twin Health, Inc. -

11 Oviva, Inc. N

12 KKT Technology Pte. Ltd.

(

Holmusk

)

13 Fruit Street Health P.B.C. N

14 Sweetch Health Ltd. -

15 Liva Healthcare ApS -

Lark Technologies, Inc. offers a digital care platform

for chronic conditions and has specialised health

plans for patients with diabetes, hypertension,

prediabetes and general health risk behaviours such

as stress and anxiety, smoking cessation or weight

management. Lark is accessible to all users via their

employer, health plan, provider or individually

through a subscription. A basic version of the app is

free and available to everyone.

Two publications of Lark Technologies, Inc. were

identified via the company website and both papers

were not published in peer-reviewed journals (Stein

et al., 2019, 2020).

The goals of Lark’s conversational agent

comprised assistance, training, education, prevention

and onboarding. It utilized a counselling type of agent

with a mixed dialogue initiative (system and user

were both able to start a conversation). The input

format allowed for fixed text with predefined answer

options and external input from sensors (E.g.

smartphone accelerometer, location sensor). The

output format was only in text.

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814

4 DISCUSSION

To our knowledge, this is the first study to identify

the degree to which the most successful companies

offering digital health interventions for the prevention

and management of T2D employ CAs. Our study

found that out of nine accessible diabetes apps, only

in one case, a CA is used. This indicates that the T2D

industry uptake of CAs still remains low.

This finding corroborates recent research findings of

literature reviews investigating the state of research

on CAs in healthcare which is still considered to be in

an early developing stage (Bérubé et al., 2020; Car et

al., 2020; Laranjo et al., 2018; Montenegro et al.,

2019; Schachner et al., 2020). With specific focus on

T2D, most reviews only identified a small number of

CAs targeting T2D. For example, a scoping review

by Car et al. only identified two studies involving a

conversational agent to target T2D prevention or

management (Car et al., 2020). Interestingly, one of

the identified studies by Car et al. (Car et al., 2020)

assessed a digital health intervention from Wellthy

(Wellthy Therapeutics Private Limited) which would

have been a relevant company for our study (Sosale

et al., 2018). However, due to insufficient funding

Wellthy did not appear on our list of the top-funded

digital health companies targeting T2D. This shows

that our approach to only focus on the top funded

companies may have left out certain relevant

companies that employ CAs for T2D management or

prevention.

Nonetheless, the general lack of CAs in the identified

digital health interventions is remarkable. One

potential reason for the low utilisation of CAs could

be safety concerns for patients and consumers when

relying on actionable medical information from CAs

(T. W. Bickmore et al., 2018).

The low utilisation of CAs could limit the

interventions’ scalability as traditional nondigital

approaches are generally time and resource intensive.

For example, the use of human health experts is

expensive, and it requires considerable time resources

from experts to provide personalised lifestyle

coaching to each intervention user. In addition, CAs

have recently shown promising results related to

patient acceptance (T. W. Bickmore et al., 2010) and

on building work alliances with patients (T. Bickmore

et al., 2005). Therefore, we advise digital health

companies to increasingly consider CAs in their

digital health interventions for the prevention and

management of T2D.

5 CONCLUSIONS

The use of CAs in digital health interventions of top-

funded digital health companies targeting the

prevention and management of T2D still remains low.

Digital Health companies should increasingly

consider the use of CAs in their interventions to

increase scalability by reducing costs and time

resources.

ACKNOWLEDGEMENTS

This research is supported by the National Research

Foundation, Prime Minister’s Office, Singapore

under its Campus for Research Excellence and

Technological Enterprise (CREATE) programme.

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