INTRODUCTION:
Currently, in the context of a pandemic of
novel coronavirus infection, special attention is paid to people with diabetes1-4.
They are at risk for severe and even critical cases of COVID-19. It is
especially important for people living with diabetes to take precautions to
avoid contracting the virus if possible.
Diabetes mellitus, as defined by the World
Health Organization, is a significant health problem and one of the four
priority non-communicable diseases that are being addressed at the level of
world leaders5-11. According to the latest figures published in the
Diabetes Atlas of the International Diabetes Federation (IDF), 463 million
adults are now living with diabetes12. According to IDF estimates,
there will be 578 million adults with diabetes in the world by 2030 and 700
million by 2045.
According to the federal register of
patients with diabetes mellitus, the total number of patients with this disease
in Russia is 4,584,575 people (3.12% of the population), including type 1
diabetes mellitus (5.6%, or 256.2 thousand), type 2 diabetes mellitus (92.4%,
or 4.24 million), and 2.0% with other types of diabetes13,14.
However, these data underestimate the real number of patients, since only
identified and registered cases of the disease are considered. Thus, the
results of a large-scale Russian epidemiological study (NATION) confirm that
only 50% of cases of type 2 diabetes mellitus are diagnosed15. That
means that the real number of patients with diabetes mellitus in Russia is at
least 8-9 million people (about 6% of the population). Such discrepancies pose
an extreme threat to the long-term prospects, since a significant part of
people remain undiagnosed, and, therefore, do not receive treatment and have a
high risk of developing vascular complications16-18. At the
international interdisciplinary summit "Diabetes mellitus and
cardiovascular diseases" held in Moscow in 2019 which brought together
about 400 endocrinologists and cardiologists from 22 countries, the modern
possibilities of a personalized approach to the management of patients with diabetes
mellitus and cardiovascular diseases were considered19.
Diabetes
mobile applications support patients, help them acquire the necessary
knowledge, and monitor physical activity, nutrition, and medication20-26.
They can be maximally focused on a specific patient with diabetes mellitus,
which improves the quality of the therapeutic care provided. The digital
diabetes market is growing rapidly and is expected to reach USD 742 million in
202227,28. At the moment, a wide selection of diabetes
apps for use is already available in Russia.
Shortly,
the development of such technology as artificial intelligence can change the
understanding of mobile applications and the benefits they bring to patients
with diabetes mellitus29-32.
One of their functions of diabetes mobile
applications is to support patient drug adherence. It is believed that low
adherence determines the main reason for the decrease in the severity of the
therapeutic effect, significantly increases the likelihood of complications,
and leads to a decrease in the quality of life of patients and an increase in
treatment costs33-35.
Currently, there is no single effective
strategy for increasing drug adherence. Previous research has shown that one of
the most common ways to support adherence is through the use of mobile apps for healthcare (mobile health, m-health)36.
In the opinion of doctors and pharmaceutical workers, they can be widely
recommended for use.
Diabetes mobile applications can provide a patient with diabetes
mellitus with a notification about taking or injecting a specific drug at a
certain time and in the required dose, information about its use, indications,
and contraindications, side effects, storage conditions, and shelf life, or a
reminder to buy a new package of the drug. They can control the administration
of drugs, as well as physiological parameters.
For the successful development and expansion of the Russian and
international diabetes mobile applications market, improving the support system for drug administration, dosing, and
control, and increasing the competitiveness of mobile applications, it is
necessary to conduct a marketing study of diabetes apps and their use to
support drug adherence.
This
work aims to analyze popular diabetes mobile applications in Russia and the
possibilities of their use to monitor and support the drug adherence of
patients with type 1 and 2 diabetes mellitus.
MATERIAL
AND METHODS:
A
survey was conducted among 985 consumers of diabetes apps from 32 regions of
Russia. All respondents were divided into two target segments. The first target
segment (S1) included 572 patients with type 1 diabetes mellitus. The second
target segment (S2) consisted of 413 patients with type 2 diabetes mellitus.
The
search for respondents was carried out in medical and pharmaceutical
organizations in Moscow and the Moscow region, on social media like Vkontakte
or Facebook, and on online diabetes forums. The sample size was conditioned by
the time and resource constraints.
The
inclusion criteria for the study were real and potential users of diabetes
mobile applications who took oral hypoglycemic drugs and/or injected insulin,
over 18 years of age, willing to participate in the survey. Participation was
anonymous and voluntary. The respondents were fully aware of the purpose, nature,
potential benefits, and risks of the survey. The study was conducted following
the principles stipulated by the Declaration of Helsinki and the ICC/ESOMAR
international code on market, public opinion, social research, and data
analysis37.
The
field stage of the study was carried out from January to April 2020 using the
methods of personal oral survey (12.6%) and web survey (87.4%). The survey used
a developed structured questionnaire. The questionnaire contained 25 questions
concerning the characteristics of the respondents, the type of diabetes,
consumer preferences for using diabetes mobile applications to support drug
adherence, and assessing the satisfaction of consumers' needs. A cover letter
with information for survey participants was attached to the questionnaire. All
questionnaires were assigned tracking codes, and the codes were securely
stored.
To
assess overall adherence of survey participants to drug regimens, the
questionnaire included questions from the Morisky-Green
ММАS-4 test38: "Do you ever forget to take
your medication?"," Do you skip taking your medication if you feel
well?", "If you feel unwell after taking your medication, do you skip
it next time?". Each negative answer was scored 1 point. The respondents
who scored 4 points were considered highly drug adherent, 3 points as medium
drug adherent, and 2 points or less as low drug adherent. Likert scale was used
in answers to some of the survey questions, as well as the "free
text" field for a deeper understanding of the respondents' opinion.
Positioning
was carried out using a qualitative method using a two-dimensional map-scheme
of perception39.
The
assessment of competitiveness was carried out by 28 experts using the
quantitative method of individual point assessments with the calculation of
integral indicators40. The level of competence of each candidate for
experts was preliminarily determined. Competence was assessed by calculating
the coefficient of competence (Сс) considering
the professional characteristics of candidates41. The level of
competence was considered sufficient if Сс
≥ 0.25. The desirable work experience of experts in the field was 5 years
or more. Competitiveness was assessed on a 5-point scale. The final score for
each parameter was calculated as a weighted average, considering the competence
of experts41. Some experts assessed not all diabetes mobile
applications studied, but only those in which they were competent.
Statistical
data processing was carried out using the SPSS.Statistics.v17.Multilingual-EQUiNOX
program (SPSS Inc). The characteristics of the respondents of the studied
target segments were expressed either in absolute and relative values, or in
metric units such as the median, lower (25%), and upper (75%) quartiles (IQR),
or mean ± standard deviation (SD). Cross tabulations, Mann-Whitney
tests, and Kruskal-Wallis tests were used to assess differences between groups.
The critical level of significance when testing statistical hypotheses in the
study was taken as equal to 0.05.
RESULTS:
Characteristics
of survey participants:
Among
572 respondents in the target segment S1, women predominated (73.4%). In the
target segment S2, out of 413 interviewed participants, 285 were female (69.0%)
and 128 were male (31.0%). The average age of survey participants in segment S1
was 40.2 ± 10.4 years (median 40, IQR: 31-49) and 53.3 ± 9.1 years
(median 53, IQR: 45-61) in segment S2. The respondents in each target
segment were assigned to the age groups: "young", from 18 to 40 years
old, "middle-aged", from 40 to 60 years old, or "elderly",
from 60 years old and older. In this case, no ageism was assumed.
The
overwhelming majority of survey participants had higher professional education.
In segment S1 the share of participants with higher education was 65.7%, and in
segment S2, 73.1%. The share of respondents with secondary vocational education
was 23.4% and 18.4%, respectively.
In
terms of social status, most of the respondents were employees and workers (70.3% in segment S1, 75.5% in segment S2). Retired participants
made up only about 9%. In terms of the average monthly income per family
member, most of the survey participants had an average income (62.2% in segment
S1, 63.9% in segment S2).
People
from Moscow and the Moscow region accounted for 25.7% of the respondents. The
share of survey participants from Central Russia was 33.4%, from Southern
regions 13.4%, the Far East and Siberia 21.5%, and other regions 6.0% The ratio
of respondents from different socio-demographic groups corresponded to the main
structure of the prevalence of diabetes mellitus in Russia and the consumer
market of diabetes mobile applications42-45.
Analysis
of drug adherence:
One
of the main problems in patients with diabetes mellitus, as indicated by the
survey participants, is the control of drug intake and
insulin injections (Table 1, segment S1: 23.4% of respondents, segment S2:
38.3%).
Table
1: The main problems in the self-care of patients with diabetes mellitus in two
target segments in Russia
|
The main difficulties
encountered in patients with diabetes mellitus
|
Share of respondents,
% (one or more answer
options)
|
|
S1
(n = 572)
|
S2
(n = 413)
|
|
Feeling unwell with low
blood sugar
|
62.4
|
18.9
|
|
Feeling unwell with high
blood sugar
|
51.2
|
28.6
|
|
I sometimes forget to
measure my blood sugar
|
22.7
|
32.7
|
|
I sometimes forget to take
my medication and/or an inject insulin
|
23.4
|
38.3
|
|
I don't know how to tell if
my blood sugar is high or low
|
4.7
|
14.0
|
|
I don't know who to turn to
when I need help
|
3.3
|
12.6
|
|
Uncertainty about the
correct calculation of the dose of medication or insulin
|
16.8
|
24.2
|
|
Fear of being left without
medication or insulin
|
18.9
|
8.5
|
An
analysis of the adherence of patients with type 1 and 2 diabetes mellitus to
drug administration regimens was carried out using the Morisky-Green test. The
results showed that 72.4% of respondents in the target segment S1 and 46.5% in
the target segment S2 had a high degree of drug adherence (Fig. 1). Only 74.1%
of segment S2 respondents adhered to the regimen of taking medications and/or
insulin injections, regardless of their state of health, and 11.4% skipped
medications if they felt unwell after their previous use.
Fig.
1: Results of the analysis of drug adherence of respondents in two target
segments in Russia (in %)
Factors
impeding the use of mobile applications:
According
to the terms of this marketing study, all survey participants were real or
potential consumers of the diabetes mobile application. A
significant part of the respondents were users of the mobile operating system
for Android smartphones (segment S1: 74.8%, segment S2: 81.6%). According
to the frequency of using the mobile application, the respondents were
distributed as follows: several times a day: 56.6% (segment S1) and 61.3%
(segment S2), daily: 28.5% and 24.0%, respectively, several times a week: 9.4%
and 11.1%, respectively. The rest of the survey participants used or expected
to use the application only on a weekly or monthly basis.
To
identify barriers to the use of mobile applications, respondents in each segment
were asked to answer the question "What factors, in your opinion, make it
difficult to use diabetes mobile applications and
support drug adherence?". The survey results are presented in Table 2.
Table 2: Factors impeding the use of diabetes mobile
applications and maintenance of drug adherence among consumers of the S1 and
segment S2 in Russia
It
was found that all survey participants considered the insufficient formation of
the adherence support system or its absence to be a key problem in the use of
mobile applications (segment S1: 76.6%, segment S2: 84.3%). This was especially
pronounced in the group of elderly people (segment S1: 89.3%, p<0.01;
segment S2: 94.4%, p<0.05). This was followed by technical
difficulties when working with the application (segment S1: 51.6%, segment S2:
48.7%), insufficient security (segment S1: 28.3%, segment S2: 23.2%), and
insufficiently logical and clear navigation (segment S1: 27.4%, segment S2:
24.7%). In the cohort of young people, both in the target segment S1 and in
segment S2, the data on some of the most significant obstacles were approximately
the same: technical difficulties, insufficient safety, and insufficiently
logical and clear navigation (about 25% each).
Positioning
consumer preferences for using mobile applications:
Positioning
was carried out by drawing up a schematic map of perception according to two
indicators: consumer preferences for using diabetes mobile applications and the formation of the drug adherence support system in diabetes apps (Fig. 2).
Positioning
was carried out by drawing up a schematic map of perception according to two
indicators: consumer preferences for using diabetes mobile applications and the
formation of the drug adherence support system in diabetes apps (Fig. 2).
Fig. 2: Schematic map of perception of diabetes mobile applications to
support drug adherence in two target segments of the Russian market: 
– segment S1, 
– segment S2
Mobile
apps: 1: Diabetes: M, 2:
OneTouch Reveal, 3: DiaMeter, 4: Diabetes, 5: MedM Diabetes, 6: Diabetes
Studio, 7: Diabetes mellitus-Blood glucose diary-Insulin, 8: Diabetes-glucose
diary, 9: Beatrix Diabetic Diary, 10: Self-Control-Diabetes Mellitus, 11:
Glycemic Index, 12: Insulin Diary, 13: Diabetes Journal, 14: Diabetes Connect,
15: SiDiary, 16: One Drop, 17: Glucose Buddy Diabetes Tracker, 18: Diabetes
control APP, 19: Сontour diabetes app, 20: mySugr:
Diabetes App and Blood Sugar Tracker, 21: Dexcom Studio, 22: Beyond Type 1
Diabetes, 23: Easy Diabetes, 24: SocialDiabetes, 25: MediSafe
The
results showed that the most preferred diabetes mobile
applications for respondents in the two target segments were Diabetes: M (Sirma Medical Systems), Diabetes (High
Solutions), MediSafe (Medisafe Project), Diabetes — Glucose Diary (Klimaszewski
Szymon), and Glycemic Index (Oleg Ukhabin). Among
the S1 survey participants, Beyond Type 1 Diabetes (Mighty Networks) and
Insulin Diary (F. ZanderMySugr Companion) were also the most preferred ones.
The drug adherence support system, according to the respondents in the S1 and
segment S2s, was optimally formed by MediSafe (Medisafe Project), Diabetes: M
(Sirma Medical Systems), mySugr — Diabetes App and Blood Sugar Tracker (mySugr
GmbH), Diabetes (High Solutions)), Diabetes Connect (SquareMed Software GmbH),
and Diabetes Mellitus-Blood Glucose Diary-Insulin (mEL Studio).
To
support and promote patient drug adherence for diabetes apps located in the
upper right corner of the diagram map (group A, Fig. 2), it is rational to use a defensive strategy with flank protection,
mobile defense, or counterattack. However, this strategy is only suitable for
true market leaders. For mobile applications "following the leader",
it is possible to use an offensive strategy against the strengths of
competitors, as well as using the weaknesses of competitors or with preemptive
strikes. If the company is small and not very strong, which does not have
sufficient forces and means to conduct large-scale operations, then it will be
preferable to apply the strategy of guerrilla warfare. For mobile applications
located in the upper left corner of the schematic map (group B), it is possible
to use an offensive strategy with a focused development of a drug adherence
support system. This strategy requires a lot of effort and expense to dislodge
existing leaders from their niche and take their position. For diabetes mobile
applications located at the bottom of the schematic map (group C), it is more
relevant to use a distribution flank attack or a low price flank attack
strategy. A blow to the system of drug adherence of competitors is struck not
where the positions of the attacking company are the strongest, but where the
positions of the leaders are the weakest. This strategy requires a lot of
effort and expense, so only large companies can carry out offensive actions.
For small organizations, it is possible to use a guerrilla warfare strategy.
Some
mobile applications of group A (Fig. 2) were included in the list of the most
famous and popular diabetes apps among survey
participants (Table 3).
Marketing
analysis of competitive advantages of 25 studied diabetes
mobile applications showed that the most competitive apps in the Russian
market were Diabetes: M (Pn
= 4.8, Fig. 3), MediSafe (Pn = 4.8), mySugr: Diabetes App and
Blood Sugar Tracker (Pn = 4.8),
and Dexcom Studio (Pn = 4.8). The
first two applications, Diabetes: M and MediSafe, also held leading positions
in the minds of survey participants, according to the positioning results (Fig.
2, group A). Diabetes apps: mySugr — Diabetes App and Blood Sugar Tracker and
Dexcom Studio, were little known and not popular enough among Russian
consumers. It can be assumed that this is due to the lack of a Russian version
and insufficient advertising campaign in Russia.
Fig.
3: Results of assessing the competitiveness of diabetes mobile applications
with an emphasis on supporting drug adherence
One
of the main indicators of support for drug adherence in patients with diabetes
mellitus such as control of drug intake and/or insulin injections (Ri = 34, Table 4) was highly
appreciated by experts in almost all diabetes apps
studied (Ai within 4.5-4.8). This was due to the presence in the
applications of the function of monitoring the administration of medications,
as well as a diary or journal for self-monitoring, in which the registration of
medications and/or insulin injections, blood glucose levels, adherence to
dietary regimes, physical activity, and more was carried out. The insignificant
range of changes in this indicator was mainly determined by the degree of
development and ease of use of the corresponding software option. Another of
the most important functions of diabetes mobile applications to support drug
adherence was the reminder function for taking medications and/or injecting
insulin (Ri = 26, Table 4). In some mobile apps, it was
insufficiently expressed or required the use of additional resources (for
example, Аi = 2.54 for SiDiary or Аi = 2.16 for Сontour diabetes app, Table 4). The following
parameters were also relevant to support drug adherence: technical ease of use
(Ri = 33), reliability (Ri = 32),
availability with the necessary software (Ri
= 30), data visualization function in the form of graphs (Ri = 12), additional reminder
functions: about the purchase of medicines, their expiration dates (Ri = 7), push notifications (Ri
= 3), and others.
Some
diabetes mobile applications, Dexcom Studio (Pn
= 4.8, Fig. 3), Diabetes-Glucose Diary (Pn
= 4.6), and Glycemic Index (Pn = 4.5), according to experts, had a higher
competitive advantage with an emphasis on supporting drug adherence compared
with positioning results (group B, Fig. 2). In this case, these diabetes apps require further marketing research using
a differentiated market coverage strategy46.
DISCUSSION:
Currently,
more than 90 diabetes mobile applications are known on the world market47.
More than 50 diabetes apps are available on the
Russian market. About 20% of them are focused only on nutritional control and a
healthy lifestyle for patients with diabetes. According to the analytical
company App Annie, in 2020 the number of downloads of mobile applications in
the world had increased by 10%, and their expenses by 25%48.
Noteworthy is the ratio of the number of foreign developers of diabetes mobile
applications to Russian ones (10 to 1), as well as the uneven distribution of
the number of products between the niche of highly functional applications and other
niches (5 to 100)45.
Diabetes
apps of the latest generation are represented by OrbitDN + IPFS (Mobile
Crowdsourcing Health Things)49. It has been created based on mobile
fog computing technology, blockchain system, conscious
glucose monitoring (CGM), and Internet of Things (IoT) systems. The
proposed complex uses a smartphone to continuously monitor the blood glucose
content, sending the data to a remote cloud or distributed fog computing nodes.
OrbitDN + IPFS allows exchanging reliable and cyber-secure data with medical
scientists and doctors and includes an information block in which data is
received, processed, and stored. To motivate users to expand the functions of
diabetes apps, an incentive system has been developed based on the use of a
digital cryptocurrency called GlucoCoin. Currently, there is only one such
mobile application. Due to the lack of a trade name, it can be assumed that
this is a prototype.
The
conducted marketing research has shown that on the Russian market there are
consumer preferences for diabetes mobile applications with average
functionality. These are applications with the ability
to work with the SMBG (Self Monitoring of Blood
Glucose) system, or BGM (Blood Glucose Meters)45,50. Perhaps it
would be rational to introduce support for adherence of patients with diabetes
to drugs in diabetes mobile applications as a separate program unit, for
example, in the form of "Support systems for modes, dosing, and
control" (Fig. 4).
Fig. 4: Platform for
self-monitoring of patients with diabetes mellitus with the "System of
support of modes, dosing, and control" (HbA1c: glycated hemoglobin, LDL:
Low-Density Lipoproteins, HDL: High-Density Lipoproteins, SMBG: Self Monitoring
of Blood Glucose)
Diabetes
apps with a high degree of functionality (for example, Dexcom Studio) and
applications with limited functions (for example, MedM Diabetes, One Drop,
Сontour diabetes app) are used less often. The priority contingent of the
latter is the group of elderly people in the target segments S1 and S2 (p
<0.05).
In
the global market, the greatest consumer preferences are used by
multifunctional diabetes apps with the ability to work with both the SMBG
system and the CGM system47,51. Spike mobile applications belong to
this category. In our study, this is the Dexcom Studio application. The
advantages of Spike applications are their quality, accuracy, stable connection
with a mobile phone, support for various operating modes, design, information
content, and high functionality. However, Spike apps only work with all iOS
devices, there is no Android version. In Russia, as shown by a marketing study,
patients with diabetes mellitus are predominantly users of the Android mobile
operating system. These discrepancies can be eliminated using the optional Xdrip
+ device.
In
recent years, bundled offers have become a
breakthrough sales technology in the digital diabetes market28.
Вundled offers comprise a combination of connected devices, test strip
supplies, app-driven services, and coaching services. They integrate the best
advances in digital diabetes management. Perhaps it would be rational to
include in this complex the program block "System of support of regimes,
dosage, and control" to increase the support of drug adherence of patients
with diabetes mellitus. Bundled offers are especially
important during the COVID-19 pandemic. For patients with diabetes, bundled
offers enable them to access health care more conveniently without exposing
themselves to the risk of infection52,53. Digital diabetes apps can
empower self-care, increase drug adherence, and provide clinically meaningful
improvements in glycemic control by facilitating data collection from mobile
devices. Ultimately, they can lead to cost savings. Health insurance companies
are showing a growing willingness to include bundled offers in their health
plans.
CONCLUSION:
1.
The analysis of monitoring and
adherence of patients with diabetes mellitus to drug administration regimens in
Russia showed that only about 50% of respondents in the target segment S2 and
more than 70% in segment S1 had a high degree of adherence. The main factors
that impede the use of diabetes mobile applications to support drug adherence
were the insufficient formation of the support system for drug administration,
dosing and control modes (76.6%, S1 and 84.3%, S2), as well as technical
difficulties when working with the application (51.6%, S1 and 48.7%, S2).
2.
The results of positioning
consumer preferences for using diabetes apps using a
qualitative method showed that the most popular mobile applications with a
well-formed system for supporting drug adherence in the S1 and segment S2 were
Diabetes: M (Sirma Medical Systems), Diabetes (High Solutions) and MediSafe
(Medisafe Project). According to the results of the survey, we compiled the TOP
10 most well-known and popular diabetes mobile
applications on the Russian market. A strategic mechanism has been proposed
to increase the importance of mobile applications to support drug
administration, dosing, and control regimens in patients with diabetes mellitus
to satisfy consumer preferences better.
3.
Analysis of the competitive
advantages of diabetes apps showed that the most competitive ones in the
Russian market were Diabetes: M (Pn = 4.8), MediSafe (Pn
= 4.8), and mySugr: Diabetes App and Blood
Sugar Tracker (Pn = 4.8). Some apps, such as mySugr:
Diabetes App and Blood Sugar Tracker (Pn = 4.8), Dexcom Studio (Pn
= 4.7), Diabetes Glucose Diary (Pn = 4.6), and Glycemic Index (Pn
= 4.5) had a higher competitive advantage with an emphasis on supporting drug
adherence compared to consumer preferences for medication use. The results
obtained provide a basis for the development of a set of measures for the
further development of the basic segment of the diabetes mobile applications
market for monitoring and supporting drug adherence, increasing the competitive
advantages of mobile applications, which will contribute to the effective
treatment and prevention of diabetes mellitus in Russia and globally.
ACKNOWLEDGEMENT:
The
study was supported by the "Russian Academic Excellence Project
5-100".
CONFLICT OF INTEREST:
The authors declare no conflict of
interest.
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