SYSTEMATIC REVIEW
Does mHealth increase adherence to medication? Results of a systematic review H. Anglada-Martinez, G. Riu-Viladoms, M. Martin-Conde, M. Rovira-Illamola, J. M. Sotoca-Momblona, C. Codina-Jane
SUMMARY
Review criteria
Aims: Adherence to medication is a major problem that affects 50–60% of chronically ill patients. As mobile phone use spreads rapidly, a new model of remote health delivery via mobile phone – mHealth – is increasingly used. The objective of this study is to provide a comprehensive overview of how mHealth can be used to improve adherence to medication. Methods: A systematic literature review was conducted using four databases (CINAHL, PubMed, Scopus and PsycARTICLES). Eligible articles available on March 2014 had to be written in English or Spanish and have a comparative design. Articles were reviewed by two authors independently. A Cochrane Collaboration tool was used to assess the studies based on their internal validity. Results: Of the 1504 articles found, 20 fulfilled the inclusion criteria [13 randomised clinical trials (RCT), one quasi-RCT, one non-randomised parallel group study and five studies with a pre-post design]. Nearly all the trials were conducted in high-income countries (80.0%). Articles were categorised depending on the target population into three different groups: (i) HIV-infected patients, n = 5; (ii) patients with other chronic diseases (asthma, coronary heart disease, diabetes mellitus, hypertension, infectious diseases, transplant recipients and psoriasis), n = 11; and (iii) healthy individuals, n = 4. Adherence improved in four of the studies on HIV-infected patients, in eight of the studies on patients with other chronic diseases, and in 1 study performed in healthy individuals. All studies reported sending SMS as medication reminders, healthy lifestyle reminders, or both. Only one trial (HIV-infected patients) had a low risk of bias. Conclusions: Our results showed mixed evidence regarding the benefits of interventions because of the variety of the study designs and the results found. Nevertheless, the interventions do seem to have been beneficial, as 65% of the studies had positive outcomes. Therefore, more high-quality studies should be conducted.
Introduction Adherence to medication is a major problem that affects 50–60% of chronically ill patients (1,2). Poor adherence leads to negative health outcomes, such as treatment failure, increased frequency of hospital admissions, drug resistance in some cases (e.g. HIV or antibiotic regimens), more complex medication plans (second-line treatments), and increased consumption of healthcare resources. Poor adherence causes approximately 33–69% of medication-related hospitalisations and accounts for an annual expenditure of $100 billion (1). Therefore, adherence is crucial and should be promoted. As mobile phone use is spreading rapidly, even in low-income countries, a new model of remote health ª 2014 John Wiley & Sons Ltd Int J Clin Pract doi: 10.1111/ijcp.12582
The review was based on information gathered from a systematic search in four databases (CINAHL, PubMed, Scopus, and PsycARTICLES). The articles covered were randomized clinical trials (RCT), quasiRCT, cross-sectional studies, case-control studies, pre- and post-intervention studies, and literature reviews. Interventions were considered to be eligible when they were based on sending text messages or using a smartphone application. Information on adherence was abstracted from the selected articles and summarised.
Pharmacy Service, Hospital Clinic, Barcelona, Catalonia, Spain Correspondence to: Helena Anglada-Martinez, Pharmacy Service, Hospital Clinic, C/Villarroel 170, Barcelona, Catalonia 08045, Spain Tel.: 932275479 Fax: 932275457 Email: hangladamartinez@gmail. com
Message for the clinic Adherence to medication is a major problem that affects 50% to 60% of chronically ill patients. As mobile phone use is spreading rapidly, even in lowincome countries, a new model of remote health delivery via mobile phone—mHealth—is increasingly used. The use of text messages or mobile applications to enhance adherence to medication do seem to have been beneficial, as 65% of the studies found had positive outcomes. However, more high-quality studies should be conducted in order to demonstrate whether this type of technology reduces the considerable costs to the health system generated by nonadherence.
Disclosure None.
delivery via mobile phone – mHealth – is increasingly used. In fact, the mobile phone is the most quickly adopted technology in the history of the world in both low- and high-income countries. The results of a survey conducted in 2013 in the USA showed that 91% of adult respondents owned a mobile device (3). However, this survey showed that mobile phone technology is less keenly embraced in specific population groups, such as people aged 65 and older, those who did not attend university, those living in households earning less than $30,000, and those living in rural areas. On the other hand, a 2010 survey by the American Association of Retired Persons showed that 89% of individuals over age 50 use a mobile device, the most common being a mobile phone, and 7% use a smartphone (4). In
1
2
mHealth and medication adherence
addition, one in 10 respondents used a mHealth application to track health data (e.g. weight, blood pressure and blood glucose), and four in 10 are interested in using one in the future. In a survey performed in a low-income country (Kenya), 44% of respondents owned a mobile phone, while 88% indicated that they use one (5). The World Health Organisation promotes services of this type, since they contribute to a more equitable delivery of care among patients living in lowincome countries or in rural areas (6). In addition, mHealth facilitates more frequent communication with patients and provides the opportunity to deliver health-related messages when they may have the greatest impact. The objective of this review was to provide a comprehensive picture of how mHealth can be use to improve adherence to medication.
Methods We conducted a systematic literature review, in which relevant studies were categorised in a 2-step process. The first step included a review of the titles and abstracts of all publications that were identified as potentially relevant. In the second step, selected abstracts were categorised using the guidelines of the Cochrane Collaboration to assess studies for their internal validity and to summarise current evidence about mHealth interventions to improve adherence.
Search strategy In March 2014, we performed a systematic search of four electronic databases (CINAHL, PubMed, Scopus and PsycARTICLES). A list of keywords was created around the two domains, ‘medication adherence’ and ‘mHealth’. A search string was constructed using both the conjunction ‘AND’ and the disjunctive ‘OR’ as logical operators [(‘medication therapy management’ OR ‘medication adherence’ OR ‘patient compliance’ OR ‘self-care’) AND (‘mHealth’ OR ‘mobile health’ OR ‘m-health’ OR ‘mobile-health’ OR ‘mobile phone’ OR ‘cell phone’ OR ‘cellphone’ OR ‘cell-phone’ OR ‘smartphone’ OR ‘iPhone’ OR ‘blackberry’ OR ‘android’)]. We included all study participants regardless of age, gender, and ethnicity, as well as all types and stages of diseases, and studies performed in the healthy population. We included studies in all settings, independently of the type of healthcare provider (e.g. nurse, doctor, allied staff). We then examined the references of the studies included and searched reviews on interventions to promote adherence.
No date limits were applied, as mobile phone interventions are relatively new. We included articles written in English and Spanish focusing on the use of mobile technology to improve adherence to medication. The articles covered were randomised clinical trials (RCT), quasi-RCT, cross-sectional studies, case–control studies, pre- and postintervention studies and literature reviews. Interventions were considered to be eligible when they were based on sending text messages or using a smartphone application. Interventions based on telephone consultation were excluded, as they are person-dependent. Medication adherence was included as an outcome. Two authors (HAM and GRV) working independently reviewed the abstracts of all the studies identified through database searches or other means. When eligibility was unclear, we obtained the full text of the article for closer examination.
Data extraction and management After having identified the articles susceptible of being included, the two reviewers separately extracted the following information: study design, number of randomised participants, participant characteristics (sex, mean age, type of disease or preventive measure), intervention (mobile phone type, content of text messaging, frequency of text messaging, period of intervention, comparator), aim of the study, duration, outcome measure, results and author conclusions. The assessment of the internal validity of each individual study was based on a Cochrane Collaboration tool (7). For RCT and quasi-RCT, the tool assesses risk of bias in individual studies across six domains: sequence generation, allocation concealment, blinding (of participants, personnel, and outcome assessors), incomplete outcome data, selective outcome reporting and other sources of bias.
Results Of the 1504 potential articles, 20 fulfilled the inclusion criteria (Figure 1). A total of 7402 patients were included. As for the type of article, 13 were RCT, 1 a quasi-RCT, 1 a nonrandomised parallel group trial, and 5 studies with a pre–post design. The characteristics of the study are shown in Table 1. Most of the studies (n = 16) were conducted in high-income countries, and most were published from 2009 to 2012 (85.0%). Articles were categorised depending on the target population into three different groups: HIV-infected patients, 5; patients with other chronic diseases (asthma, coronary heart disease, diabetes mellitus, ª 2014 John Wiley & Sons Ltd Int J Clin Pract
Identification
mHealth and medication adherence
Records identified through CINAHL, PubMed, PsycARTICLES, Scopus (n = 881+339+58+138 = 1416)
Additional records identified through other sources (n = 88)
Screening
Records after duplicates (42) removed (n = 1462) Records excluded (n = 1300)
Included
Eligibility
Records screened (n = 30+99+1+32 = 162)
Full-text articles assessed for eligibility (n = 40)
Studies included in the qualitative synthesis N = 20
Full-text articles excluded, with reasons (n = 20) - Phone call intervention: 3 - Adherence to medication not evaluated: 10 - No comparative design study: 3 - No mobile phone intervention: 1 - Intervention performed in the control group: 1 - Intervention performed using mobile phone or computers: 1 - Intervention in the control group consisted of mobile alerts and smart SPD: 1
Figure 1 Flow chart showing the inclusion process
hypertension, infectious diseases, transplant recipients and psoriasis), 11; healthy individuals, 4.
Studies focused on HIV-infected patients A total of five studies were identified. Three were RCT (8–10), one a quasi-RCT (11), and one followed a pre–post design (12). Overall, 1399 patients were recruited, with sample sizes ranging from 52 to 538 participants. Patients included were na€ıve in one study (8), had initiated antiretroviral treatment within 1–3 months in three studies (9–11) and in another study this issue was not addressed (12). The duration of the studies varied from 3 months to 1 year. The intervention consisted of sending short messages (SMS) (8–12), in one case along with an interactive voice response (11). In one study (10), the ª 2014 John Wiley & Sons Ltd Int J Clin Pract
intervention was limited to medication reminders (11), while in the remainder the message also provided motivational and reinforcement content (8– 10,12). In one study, adherence was evaluated using several methods: visual analogue scale (VAS), selfreported adherence and pharmacy refills. Other methods used to measure adherence included the Medication Event Monitoring System (MEMS) (n = 1) (9), self-reported adherence (n = 2) (8,12) and pill counts (n = 1) (11). Motivational content included statements such as ‘You are important to your family. Please remember to take your medication. You can call us at this number:’ (10) or ‘This is your reminder. Be strong and courageous, we care about you’ (9) or a simple question ‘How are you?’ (8). Three studies used 2-way communications encouraging participants to use their mobile phones
3
(9)
Pop Eleches 2011
Lester 2010 (8)
HIV studies
Study (Ref)
outcomes (suppression of plasma HIV-1 RNA load, quality of life, retention, and mortality).
care); Mean age (years): Intervention, 36.7 8.5; Control, 36.6 7.9; Male: Intervention, 45%; Control, 44%
weekly basis. The
Interventions groups: G1: short SMS +
35.65; Intervention: 35.64–37.74; Male:
59–69%
Intervention,
weekly
G4: long SMS +
weekly
G3: short SMS +
daily
G2: long SMS +
daily
control group.
age (years): Control:
Control, 44%;
and sent on a daily or
reminder systems vs
≥ 18 years. Mean
We care about you’
strong and courageous.
your reminder. Be
message was ‘This is
content of the long
your reminder’, the
reminder was ‘This is
content of the short
either short or long
reminders that were
Patients received SMS
different phone
ART aged
system vs. usual care.
Medication reminder
48 h.
to respond within
problem or who failed
reported having a
the patients who
clinician then called
a problem. The
doing well or they had
that either they were
respond within 48 h
were instructed to
intervention group
Patients in the
asked ‘How are you?’
language, the SMS
support. In Kiswahili
of phone-based
about the availability
status and to remind
enquire about patient
via SMS each week to
A text message was sent
Intervention
Kenya
rates between four
12 months
12 months
Duration
least 3 months on
Compare adherence
and clinical
265 to standard of
HIV infection
adherence to ART
intervention group;
431 patients with at
patients improves
randomised to
between healthcare
sending SMS
Assess whether
Aims
providers and
initiating ART
infected patients
Treatment-na€ıve HIV-
Disease
(273 patients
three clinics in Kenya
538 adults aged ≥ 18, na€ıve patients from
Participants
RCT; Country:
Parallel group,
Kenya
RCT; Country:
Parallel group
Study design, country
Table 1 Summary of study characteristics.
Usual care
Usual care
Comparator
treatment drugs
MEMS in one of the
Self-report
Method used to measure adherence
Yes
Yes
Improvement in adherence?
4 mHealth and medication adherence
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Lewis 2012 (12)
(10)
Mbuagbaw 2012
Study (Ref)
adherence and clinical outcomes.
aged ≥ 25 years. Mean age: 38 (25– 60); Male: 100%
Country: USA
messages enhance
change. The content of
Intervention, 31.7%
52 homosexual adults
model of behaviour
Control, 21.2%;
pre–post study;
One group
and the health belief
41.3 10.1. Males:
meds now’
and pop. Take your
basis: e.g. ‘Stop, drop
were sent on a daily
adherent participants
Great job!’ while non-
Perfect med adherence.
shoots! He scores!
weekly basis e.g. ‘He
received them on
adherent patients
adherence rates:
were tailored to
Motivational messages
medication.
patients to take
were sent to remind
Daily text messages
needed help.
call back if they
number that they could
contained a phone
The message also
call us at this number.
medication. You can
remember to take your
your family. Please
‘You are important to
reminder component:
motivational, with a
the message was
focus group discussions
Intervention,
3 months
to ART.
Assess whether text
Messages were based
improving adherence
age: Control, 39.0 10.0;
HIV infection
once a week. on data collected from
intervention group
reminder for
Cameroon
messaging as a
ART-experienced treatment). Mean
SMS was sent to each
Intervention
(at least 1 month on
6 months
Duration
participant in the
Evaluate the
Aims
effectiveness of text
HIV-infected adults on
228 adults aged ≥ 21, ART
Disease
Participants
RCT; Country:
Parallel group,
Study design, country
Table 1 Continued
study.
the 7 days before the
Adherence rate during
Usual care
Comparator
surveys.
weekly adherence
Self-reporting through
Pharmacy refill data
Self-report
VAS
Method used to measure adherence
Yes
No
Improvement in adherence?
mHealth and medication adherence 5
medication morning respiratory unit”
and evening. From the
your asthma
57.0%
“Remember to take
take their medication
daily SMS reminder to
received the following
Intervention subjects
of a lamp.
form of a line diagram
The SMS was in the
and ‘2’ if they had.
in the previous 24 h
not missed any doses
with a ‘1’ if they had
Patients responded
medicines yesterday?’
you take all your
of the IVR was: ‘Did
6 months. An example
SMS once a week for
picture delivered as an
interactive neutral
and (ii) a non-
medicines yesterday?’)
(‘Did you take all your
automated IVR
50.0%; Control,
asthma treatment.
reminders on the
receiving daily SMS
Male: Intervention,
daily symptoms
12 weeks
reminder on their
Evaluate the impact of
two types of adherence
the intervention).
rate of adherence to
(years): Intervention,
Denmark
clinical history and
Asthma based on
participants received
discontinuation of
34.4; Control, 30.7;
45 years; Mean age
RCT; Country:
2009 (13)
26 patients aged 18–
Parallel group,
Strandbygaard
Asthma
Other chronic diseases
reminders. All
6 months after
mobile phones: (i) an
and 6 months without
and IVR call reminders
6 months with SMS
Adherence rate over
Intervention
intervention and
Country: India
12 months
Duration
during the
period (6 months
age: 38.54 7.7; Male: 73%.
cohort study;
Change in adherence
Aims
over a 12-month
HIV infection
Disease
≥ 18 years. Mean
150 adults aged
Participants
experimental
Quasi-
Rodrigues 2012
(11)
Study design, country
Study (Ref)
Table 1 Continued
Usual care
intervention withdrawn
6 months after
Comparator
the disc of Seretide.
Record of doses left on
Pill counts
Method used to measure adherence
Yes
Yes
Improvement in adherence?
6 mHealth and medication adherence
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(23)
Foreman 2012
Chronic diseases
Petrie 2012 (14)
Study (Ref)
calcium channel blockers, angiotensinconverting enzyme inhibitors, angiotensin receptor
Control, 64.7 13.7; Intervention, 64.8 11.9; Male: Control, 53.8%; Intervention, 46.6%.
and thyroid agents.
bisphosphonates,
antidepressants,
inhibitors, statins,
platelet aggregation
blockers, diuretics,
after the
drugs, b-blockers,
Mean age (years):
group.
compare to a control
programme and
an SMS reminder
implementation of
medication before-
oral antidiabetes
290 control group).
USA
to chronic oral
To compare adherence
study; Country:
on treatment with
intervention group,
Chronically ill patients
8 months
weeks
580 adults (290
SMS per day during
month period.
control cohort
Retrospective
a tailored frequency (2
follow-ups over a 9-
medication today’.
context ‘Take your
reminders with the
sends daily medication
programme, which
text messaging
medication reminder
implementing ‘My
oral medication after
Adherence to chronic
medication).
little need for
(for example, belief in
to modify that belief
different text messages
patients were sent
score in the BIPQ,
Depending on the
from week 13 to 18).
and 3 SMS per week
from weeks 7 to 12,
1–6, 1 SMS per day
Messages were sent at
Questionnaire (BIPQ)].
Illness Perception
preventive inhaler at
period
their illness [Brief
their perception of
adherence to their
medication beliefs as
follow-up
9-month
questionnaire to assess
All participants fill in a
Intervention
well as improved
prescribed.
(years): ND (aged
illness and
modify patient’s
intervention,
18-week
Duration
years) Males: ND
medication as
asthma. Mean age
messages would
Whether text
Aims
between 16–45
their preventive
diagnosed with
UK
currently adhering to
Asthma patients not
147 adults (control, 73; intervention, 74)
Disease
Participants
RCT; Country:
Parallel group,
Study design, country
Table 1 Continued
the intervention group)
control population with
to patients in the
Usual care (matched 1:1
Usual care
Comparator
PDC
as at 6 and 9 months.
and 12 weeks, as well
by phone calls at 6
Self-reported adherence
Method used to measure adherence
Yes
Yes
Improvement in adherence?
mHealth and medication adherence 7
Study design, country
Park 2014 (15)
and health education; (ii) patients who received text messages for health education; (iii) patients who did not receive text messages.
statin medications. Explore whether patient education delivered three times a week would improve medication adherence compared with twice-daily medication reminders
percutaneous coronary intervention on antiplatelet or statin treatment
Male: 78%
antiplatelet and
adherence to
respond.
requiring patients to
messages were 2-way,
hospitalisation’. Text
2 weeks after your
primary physician 1–
cardiologist and/or
‘Remember to see your
message was
health education
and an example of a
AM. Respond with 1’
Plavix 75 mg at 9:00
reminder is ‘John, take
of a medication
per week. An example
were sent three times
education messages
evening), while health
reminder in the
morning and statin
reminder in the
twice daily (antiplatelet
messages were sent
Medication text
medication reminders
messages for
who received text
groups: (i) patients
randomised into three
infarction and/or
messaging improved
(years): 59.2 9.4;
of myocardial
group); Mean age
Patients were
Intervention
USA
1 month
Duration
old (30 patients per
Assess whether text
Aims
90 adults > 21 years Patients with a history
Disease
RCT; Country:
Participants
Parallel groups,
Coronary heart disease
Study (Ref)
Table 1 Continued
Usual care (1:1:1)
Comparator
(CareSpeak)
Mobile phone
MEMS
adherence survey
Morisky Medication
Method used to measure adherence
Yes
Improvement in adherence?
8 mHealth and medication adherence
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RCT; Country:
Spain
(17)
Parallel group
pressure on monotherapy or hypertension in patients eligible to start treatment with combined antihypertension
56.26 10.22; Control, 59.43 10.94; Male: Intervention, 52.9%; Control, 57.6% drugs.
uncontrolled blood
Intervention,
patients with
Hypertension in
aged (years):
> 18 years; Mean
104 patients
drugs.
antihypertensive
adherence to
reminders improved
send alerts and
text messaging to
on mobile telephone
intervention based
Evaluate whether
6 months
required to receive a
attended
medication.
to take their
and reminded patients
hygienic dietary habits,
adherence, suggested
hypertension,
gave information about
weekends. Messages
week except
SMS were sent twice a
this week?’).
you check your feet
‘How many times did
about foot care (e.g.
and a weekly question
medication today?’)
your diabetes
(e.g. ‘Did you take
blood sugar reminder
daily medication or
participant was
appointments
blood sugar. Each
foot care, and monitor
medication, perform
remind patients to take
Daily text messages to
Intervention
33%
adherence, health
medication
4 weeks
Duration
behaviours and
insulin)
Mean age (years): 55
message to enhance
Feasibility of text
Aims
(range 38–72); Male:
antidiabetic drugs or
African Americans.
USA
medication (oral
Diabetes I or II taking
Disease
≥ 18 years, urban
18 adults aged
Participants
post; Country:
One group pre–
Study design, country
Contreras 2004
Marquez-
Hypertension
Dick 2011 (16)
Diabetes mellitus
Study (Ref)
Table 1 Continued
Usual care
No control
Comparator
Pill counts
intervention.
1 month after the
study period and
at baseline, during the
Self-reported adherence
Method used to measure adherence
No
Yes
Improvement in adherence?
mHealth and medication adherence 9
Patel 2013 (18)
Study (Ref)
age (years): 53 (range
Country: USA 33–78); Male: 31%
hypertension; Mean
open label; medications
antihypertensive
on at least two
Essential hypertension
50 adults aged ≥ 18– 80, with
Disease
Participants
sequential study,
3-phase
Study design, country
Table 1 Continued
reminder system
acceptance.
patterns and
patient usage
Pill Phone; Evaluate
withdrawal of the
3 months after
adherence over
medication
continuation of
Assess the
mobile phones;
application for
medication reminder
an automated
during activation of
postphase medication
reminder system and
prephase medication
reminder system vs.
Cell-phone medication
Intervention
intervention vs.
10 months
Duration
3 months of the
the previous
medication during
antihypertensive
Assess adherence to
Aims
reminder system.
withdrawal of the
3 months after
and postactivation of
medication reminders
prior to automated
Prephase of 3 months
Comparator
medication scale
Morisky self-reported
Pharmacy refill rates
Method used to measure adherence
Yes
Improvement in adherence?
10 mHealth and medication adherence
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(20)
Iribarren 2013
(19)
Suffoletto 2012
Infectious diseases
Study (Ref)
department.
Mean age (years):
2 months
adherence to antituberculosis treatment.
treatment
control group and
n = 18 SMS group); Mean age (years): Control, 35.05 17;
Country:
Argentina
Educational SMS messages were sent biweekly and the
(%): Control, 42%; Intervention, 44%.
phase provided
the intensive treatment
during the 2 months of
option to consult
a reminder was sent.
33.78 15. Male
patient did not text in,
medication. When a
administration of
after self-
instructed to text in
Participants were
prescription?’
you to pick up your
many days did it take
in your bottle?’ ‘How
many pills do you have
questions like ‘How
assessment included
antibiotic. Follow-up
completion of their
following the intended
phone call on the day
Intervention,
messages promotes
antituberculosis
≥ 18 years (n = 19
group, RCT;
sending text
back. Participants in
37 adults aged
were requested to text
Intervention, 29%. both groups received a
antibiotics. Participants
Control, 34%;
and to ask them how
up their prescription
remind them to pick
received SMS to
intervention group
Participants in the
Intervention
they were taking their
Assess whether
4 months
Duration
34 13. Male (%):
prescriptions.
antibiotic
adherence to
system improves
automated SMS
Assess whether
Aims
Intervention,
Patients initiating first
emergency
intervention groups);
Parallel control
discharged from the
in the control and
Country: USA
Control, 31 11;
antibiotics
Patients on oral
Disease
≥ 18 years (n = 100
200 adults aged
Participants
group, RCT;
Parallel control
Study design, country
Table 1 Continued
Usual care
Usual care
Comparator
reported through SMS
Intervention: self-
Control: patient diaries
questionnaires
Self-reported
Method used to measure adherence
No
No
Improvement in adherence?
mHealth and medication adherence 11
medications strictly according to the
life, disease severity, patient-perceived disease severity, and the patient-physician relationship).
Intervention, 60%
Miloh 2009 (22)
immunosuppressors. The messages were structured as ‘Take [name of medication] at [set time]. To confirm intake, press
to immunosuppressive medication for paediatric patients undergoing orthotopic liver transplant.
(years): 15 (range, 1– 27); Males (%): 34%
not respond.
that the patient did
caregiver indicating
was sent to the
1 h), then a message
individually (15 min to
a time frame set
to the message within
patient did not respond
and press SEND’. If the
REPLY, type CARE 1,
take their
to remind patients to
USA
improve adherence
patients. Mean age transplant recipients
41 paediatric and adult
post; Country:
Daily text messages sent
psoriasis today’
you use to treat your
medication or product
remember to use the
doctor’ or ‘Please
directions of your
three times weekly,
(medication reminders
selected order
One group pre– 13 months
example, ‘Take the
outcomes (quality of
(%): Control, 50%;
Use text messages to
times weekly). For
and patient
38.4 (9.5). Males
Paediatric liver
educational tools four
treatment adherence
the same randomly
messages improves
daily for 12 weeks in
Patients received 1 SMS
Intervention
(10.2); Intervention,
12 weeks
Duration
(years): Control, 39.3
sending text
Assess whether
Aims
Country: Italy
Psoriasis
Disease
65 years. Mean age
40 adults aged 18–
Participants
group RCT;
Parallel control
Study design, country
Transplant recipients
(21)
Balato 2012
Psoriasis
Study (Ref)
Table 1 Continued
in the previous year.
tacrolimus blood levels
Standard deviation of
Usual care
Comparator
tacrolimus blood levels.
Standard deviation of
and patient diaries
choice questionnaire
Self-report by multiple-
Method used to measure adherence
Yes
Yes
Improvement in adherence?
12 mHealth and medication adherence
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(25)
Ollivier 2009
(24)
Vilella 2004
Travellers
Healthy population
Study (Ref)
6 months) and hepatitis A (Schedule: 0 and 6 months)
27.1 5.0; Intervention, 28.6 4.2; Male (%): Control 2001,
medication ‘Remember to take your doxycycline pill at midday. In case of fever, consult a physician and tell him
soldiers to take their malaria chemoprophylaxis and to assess the impact of SMS on adherence to chemoprophylaxis.
area. Malaria prophylaxis was 100 mg doxycycline monohydrate once a day.
control, 26.7; intervention, 26.4. Male (%): 96.1 overall
device to remind
via mobile phone
reminder message
sending a daily SMS
d’Ivoire’.
you have recently returned from C^ote
to take their malaria
reminding participants
message at midday
automated daily
standardised
used to send a
a malaria-endemic
acceptability of
month deployment in
Mean age (years):
messaging service was
A commercial SMS
malaria-endemic area.
return
28 days after
you’
vaccine dose. Thank
receive your hepatitis
vaccination centre to
should go to the
to remind you that you
vaccine dose, ‘This is
the date of the next
SMS a few days before
Travellers received the
Intervention
France
feasibility and
To assess the
4 months
Duration
from duty in a returning after a 4-
group.
reminders vs. control
received phone
travellers that
schedules between
rates to vaccination
Compare adherence
Aims
RCT); Country:
424 soldiers returning
55.6%
48.3%; Intervention, French soldiers
A+B (schedule: 0, 1,
control 2000,
Parallel group
against hepatitis
2001, 28.7 5.2;
Spain
48.6%; control 2000,
for vaccination
age (years): Control
trial; Country:
attended the clinic
Travellers who
Disease
≥ 18 years. Mean
4043 travellers aged
Participants
parallel group
Non-randomised
Study design, country
Table 1 Continued
Usual care
Usual care
Comparator
MEMs
administration
Record of vaccine
Method used to measure adherence
No
Yes
Improvement in adherence?
mHealth and medication adherence 13
(26)
Cocosila 2009
Vitamin C
Study (Ref)
participants were
fight cold and flu!’).
vitamins: they help to
your best to take the
(e.g. ‘Again Tim: Do
benefits of vitamin C
reminding them of the
a correcting SMS
not reply, they received
research!’); if they did
from many is
is plagiarism; to steal
ideas from one person
super! Tip: to steal
here again: Ur doing
behaviour (e.g. ‘Tim
SMS reinforcing the
received a subsequent
responded they
to reply). If participants
had at least 5 to 6 h
the same day (i.e. they
than the midnight of
vitamin but no later
after taking the
(i.e. ‘acknowledge’),
a one-letter SMS, ‘A’
requested to reply with
such message,
Intervention, 31%.
Tim: Any vitamin C
tablet, e.g. ‘Hi, it’s 2 day?’). After each
healthy people.
Intervention:
take their vitamin C
daily SMS reminder to
Participants were sent a
Intervention
(%): Control, 29%;
to vitamin C in
34.3 14.2;
1 month
Duration
32.9 13.4. Males
increase adherence
age (years): Control,
SMS reminders
Determine whether
Aims
Canada
vitamin C treatment
Healthy people on
Disease
≥ 18 years. Mean
102 adults aged
Participants
RCT; Country:
Parallel group
Study design, country
Table 1 Continued
Usual care
Comparator
Self-reported adherence
Method used to measure adherence
No
Improvement in adherence?
14 mHealth and medication adherence
ª 2014 John Wiley & Sons Ltd Int J Clin Pract
contraceptive pills 0%
birth control pill’
ART, antiretroviral therapy; MEMS, Medication Event Monitoring System; VAS, visual analogue scale; IVR, interactive voice recognition; ND, no data; PDC, proportion of days during the measurement period that are covered by prescription claims
adherence to 18–31); Males (%): USA
ª 2014 John Wiley & Sons Ltd Int J Clin Pract
remember to take your
adherence ‘Please
Pill diaries reminders promotes contraceptives
New user of oral
(years): 22 (ranged
82 women; Mean age Parallel group Hou 2010 (27)
Contraceptive pills
RCT, Country:
Assess whether SMS
3 months
contraceptive pill
Usual care Daily text message
MEMs
Comparator Intervention Duration Aims Disease Participants Study design, country Study (Ref)
Table 1 Continued
reminders on oral
Method used to measure adherence
No
Improvement in adherence?
mHealth and medication adherence
to ask questions. The frequency of message delivery ranged from daily (n = 1) (12) to once a week (n = 3) (8,10,11), or included both frequencies (n = 1) (9). In four of the five studies, adherence rates improved (Table 2). In one study, the improvement was maintained during the 6 months after the intervention was withdrawn (11). Higher adherence rates were recorded, when SMS were sent on a weekly basis (9). Viral load decreased and CD4 count increased significantly in the two studies where they were evaluated (8,12). However, Mbuagbaw et al. (10) did not observe statistically significant differences in mortality rate, quality of life, weight or body mass index, although the regression analysis revealed that higher levels of education and being on a second-line regimen were statistically significant predictors of adherence > 95%.
Studies on other chronic diseases The chronic diseases analysed were asthma (n = 2) (13,14), coronary heart disease (n = 1) (15), diabetes mellitus (n = 1) (16), hypertension (n = 2) (17,18), infectious diseases (n = 2) (19,20) and psoriasis (n = 1) (21). Patients who had undergone a liver transplant were also analysed (n = 1) (22). One study included patients with various chronic diseases (n = 1) (23). A total of 1333 patients were examined, with an age range of 1–78 years. The characteristics of the studies are summarised in Table 1. Duration varied from 1 to 13 months. All studies reported using SMS, whose content comprised medication reminders (n = 5) (13,18,19,22,23), medication and healthy lifestyle reminders (n = 4) (16,17,20,21), and statements targeting perceptions of illness and beliefs about medications (n = 1)(14). In the study by Park et al., patients were randomised to receive medication reminders and health education messages, only health education messages, or no messages (15). The frequency of message delivery ranged from daily (13,16,18,22,23) to twice weekly (17), or varied depending on the study period (14,19,21) or the randomization arm (15). Three studies used two methods for measuring adherence: refills and the Morisky questionnaire (18); self-reported adherence by multiple-choice questionnaire and patient diaries (21); and the Morisky questionnaire and the MEMS (15). Adherence improved in all the studies except three (17,19,20) (Table 2). In the study by Marquez et al. (17), sending SMS did not improve adherence to antihypertensive treatment in the first, third and sixth month of the study when compared with the control group.
15
Coronary heart disease Park 2014 (15)
Chronic diseases Foreman 2012 (23)
Petrie 2012 (14)
MEMS (Group 1 vs. Group 2 vs. Group 3):
PDC
Percentage of doses taken by the patient: baseline vs. final Average of self-reported adherence: baseline vs. final Proportion of participants achieving optimal asthma control of ≥80%.
Percentage of patients with adherence rate ≥ 95% (preintervention phase vs. end of intervention phase vs. 6 months postintervention)
Rodrigues 2012 (11)
Other chronic diseases Asthma Strandbygaard 2009 (13)
Percentage of patients adherent to ART throughout the study
3.8 (1.48)
Pharmacy refill data (mean, SD)
Lewis 2012 (12)
79.0%
79.2%
G1: 93.7 11.9 G2: 95.8 9.5
G3: 79.1 27.7 G3: 83.3 21.3
77 28%
54 31.8% vs. 43.2 26% 7 patients of 66 (10.6%)
56.5 35.3% vs. 57.8 27.1% 15 of 58 patients (25.9%)
85 20.0%
84.2% vs. 70.1%
–
85% vs. 91% vs. 94%
77.9% vs. 81.5%
–
49%
3.7 (1.34)
71.3%
49% 50% 68% 59%
47%
50%
Control
66.7%
Mbuagbaw 2012 (10)
G1: G2: G3: G4:
62%
Intervention
Percentage of patients with a VAS > 95% adherence Self-report (no missed doses) (%)
Percentage of patients with > 90% of adherence. Intervention groups: G1: short SMS+daily G2: long SMS+daily G3: short SMS+weekly G4: long SMS+weekly
Percentage of patients with adherence rates > 95% (ITT)
Adherence Outcome
Pop Eleches 2010 (9)
HIV Lester 2010 (8)
Study
Table 2 Outcome of adherence in the studies included
p = 0.03 p = 0.28
p < 0.001
Δ 17.8% (95% CI, 3.2–32.3%) Relative average increase of 10% Difference of 15.3%
–
RR (95% CI): 1.06 (0.89–1.29) RR (95% CI): 1.01 (0.87–1.19) Mean difference: 0.1 ( 0.23–0.43) –
RR (95% CI): 0.81 (0.69–0.94)
Effect estimate
Text messages increased adherence to antiplatelet therapy demonstrated by MEMS and text message responses,
Patients opting to receive medication reminders adhered to their medication better than patients not opting to receive them.
Use of SMS reminders increases adherence Intervention improved adherence to asthma medication
Text messages seem to improve adherence but the sample size was small. Improvement in adherence rate after 6 months of intervention. The effect persists for at least 6 months after the intervention finishes.
Adherence rate to ART did not improve among treatment-na€ıve patients after 6 months of using text messages.
Sending short messages makes good adherence and viral suppression more likely. SMS reminders improve adherence and decrease treatment interruptions
Outcome
16 mHealth and medication adherence
ª 2014 John Wiley & Sons Ltd Int J Clin Pract
ª 2014 John Wiley & Sons Ltd Int J Clin Pract
Iribarren 2013 (20)
Infectious diseases Suffoletto 2012 (19)
Patel 2013 (18)
Hypertension Marquez-Contreras 2004 (17)
Diabetes mellitus Dick 2011 (16)
Study
Table 2 Continued
Percentage of participants who filled their prescription within 24 h of discharge from the ED Percentage of patients adherent to antibiotic prescription (self-reported adherence) Percentage of patients with no pills left on the day after intended completion of prescriptions Percentage of patients who reported having taken their medication
PDC (%): preintervention vs. intervention phase vs. postintervention Morisky Medication Scale (Range, 0–4), mean: Pill Phone Application (PPA): Percentage of doses taken
Percentage of participants with adherence rate > 80%
Number of doses missed in the last week (doses/week): prestudy period vs. study period vs. 1 month after the study
100%. However, only 53% of participants returned the calendars
59% (95% CI, 47–71%)
68% (95% CI, 55–78%)
77% (22–100%)
45% (95% CI, 37–59%)
57% (95% CI, 44–67%)
–
–
RR (95% CI): 1.49 (0.92–2.42)
p = 0.3
p = 0.1
p = 0.26
–
–
69% (95% CI, 57–80%)
Non significant RR (95% CI): 8.9 (0.18–17.62) –
1st month: 85.7% 3rd month: 88.9% 6th month: 78.9% –
p = 0.003
p = 0.005
–
–
p > 0.05
Effect estimate
G3: Baseline 6.01 1.84; Follow-up at 30 days: 6.96 1.44
Control
78% (95% CI, 66–87%)
1st month: 92.1% 3rd month: 77.3% 6th month: 89.5% 57 27% vs. 58 20% vs. 56 31% Beginning: 2.4 End: 3.2 60%
1.9 vs. 0.6 vs. 0.8
G1: 92.4 14.0 G2: 90.1 16.2 G1: Baseline 6.20 1.66; Follow-up at 30 days: 6.43 1.22 G2: Baseline 5.85 2.10; Follow-up at 30 days: 6.73 1.49 90.2 9 vs. 83.4 15.8
Doses of antiplatelet taken (%) Doses of statin taken (%) Self-report (Group 1 vs. Group 2 vs. Group 3)
SMS response rate antiplatelet vs. statin
Intervention
Adherence Outcome
Greater adherence was reported in the intervention group, although the difference with the SMS intervention did not prove to be statistically significant.
Adherence rate in the intervention group did not improve.
Mobile phone-based automated medication reminder system shows promise in improving adherence.
Sending short messages did not improve medication adherence.
Text message seems feasible for improving self-management of diabetes.
but did not increase adherence to statins.
Outcome
mHealth and medication adherence 17
Mean pills missed MEMs Mean pills missed recorded in patient’s diary
Percentage of participants reporting increased adherence Number of doses missed in the last 7 days
Percentage of vaccinations administered Hepatitis A+B 2nd dose (HAB2) Hepatitis A+B 3rd dose (HAB3) Hepatitis A 2nd dose (HA2) % of daily adherence % of early treatment discontinuation Rate of adherence at day 2 and 28 (day 2 vs. day 28)
Tacrolimus level standard deviation
Number of days/week which patients adhere to medication
Adherence Outcome
4.6 3.5 1.1 1.4
3.3
2.5
4.9 3.0 1.3 2.0
From 1.6 to 3.7 (131%)
Control 1 vs. Control 2: HAB2: 77.2% vs. 80.7% HAB3: 23.6% vs. 26.9% HA2: 13.2% vs. 16.4% 21.4% 50.3% 95.2% vs. 65.8%
1.37 1.01 lg/l
Pre: 4.2 Post: 4.0
Control
From 1.3 to 4.5 (246%)
HAB2: 88.4% HAB3: 47.1% HA2: 27.7% 22.3% 42.6% 94.6% vs. 67.6%
3.46 2.17 lg/l
Pre: 3.86 Post: 6.46
Intervention
ED, emergency department; PDC, proportion of days covered; ITT, intention to treat.
Oral contraceptives Hou 2010 (27)
Vitamin C Cocosilla 2009 (26)
Ollivier 2009 (25)
Healthy population Travellers Vilella 2004 (24)
Transplant recipients Miloh 2009 (22)
Psoriasis Balato 2012 (21)
Study
Table 2 Continued
p > 0.5 p > 0.5
RR (95% CI): 1.38 (1.11– 1.71) RR (95% CI): 0.8 ( 1.55 to 0.05)
No significant effect 0.85 (0.67–1.07)
p < 0.05
–
–
Effect estimate
Daily text message reminders did not improve adherence to the oral contraceptive pill.
Inconclusive results.
Use of SMS reminders improves adherence to the vaccination schedule, especially in the third dose of hepatitis A+B. No difference in adherence was observed between the groups.
Adherence improved and the number of rejection episodes fell
The adherence rate improved in the intervention group at the end of the study.
Outcome
18 mHealth and medication adherence
ª 2014 John Wiley & Sons Ltd Int J Clin Pract
mHealth and medication adherence
Table 3 Summary of the risk of bias (based on the Cochrane Collaboration tool)
Trial
HIV studies Lester 2010 (8) Pop Eleches 2011 (9) Mbuagbaw 2012 (10) Rodrigues 2012 (11) Other chronic diseases Strandbygaard 2010 (13) Petrie 2012 (14) Marquez-Contreras 2004 (17) Suffoletto 2012 (19) Balato 2012 (21) Iribarren 2013 (20) Park 2014 (15) Healthy population Vilella 2004 (24) Ollivier 2009 (25) Cocosila 2009 (26) Hou 2010 (27)
Blinding
Incomplete outcome data
Selective outcome reporting bias
Other sources of bias
L U L H
L L L H
L L U L
L U L L
L U L U
L L L L L L L
L L U L U L L
H H U H L U U
U L H L L L L
H L L L L L L
L L L U U U U
H L L L
H U L L
U U U L
L L L L
L U L L
L L H U
Sequence generation
Allocation concealment
L L L H
L, low risk; H, high risk; U, unclear risk
Random sequence generation (selection bias) Allocation concealment (selection bias) Blinding (performance bias) Incomplete outcome data (attrittion bias) Selective reporting (reporting bias) Other bias 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Yes (low risk of bias)
Unclear
No (high risk of bias)
Figure 2 Adherence to medication using mobile device–based interventions according the Cochrane risk of bias tool
This type of intervention did not improve the adherence rate in patients on antibiotic treatment after their discharge from the emergency department (19) or in patients on antituberculosis treatment (20). Clinical outcomes were evaluated in Patel et al. (% of patients with controlled blood pressure) (18), Marquez Contreras et al. (differences in systolic and diastolic blood pressure and in body weight) (17), Strandbygaard et al. (exhaled nitric oxide levels, lung function, and airway responsiveness) (13), and Iribarren et al. (number of patients whose treatment was successful, patients with a clear sputum smear or ª 2014 John Wiley & Sons Ltd Int J Clin Pract
conversion of a culture from positive to negative) (20). The results were clinically significant only in the first of these studies (47% patients at baseline vs. 64% while using the application vs. 60% after withdrawal of the intervention) (18).
Studies in the healthy population A total of 4651 people were included in the four studies, in each of which SMS were sent as a reminder to enhance vaccination rates (24), malaria chemoprophylaxis among soldiers returning from malaria-endemic areas (25), vitamin C intake (26) and use of oral
19
20
mHealth and medication adherence
contraceptives (27). Medication reminders where sent daily (25–27), whereas vaccination reminders were a few days before the appointment (24). The vaccination rate increased, especially for the third dose of hepatitis A + hepatitis B (24). However, in the remaining cases, adherence was not promoted using this type of intervention (25–27) (Table 2). No pregnancies were reported in the study on oral contraceptives (27).
Assessment of internal validity The results of the assessment of the study quality are reported in Table 3, and the Cochrane risk of bias summary is reported in Figure 2.
Patient satisfaction Patient satisfaction was evaluated in 10 studies and was found to be very useful by most authors (8,10,12,16,18,19,21,25,27). Park et al. (15) compared sending medication reminders + educational text messages with education text messages alone and found that a higher percentage of patients strongly agreed that medication reminders + educational text messages helped them to take their medication (57% vs. 32%, respectively). In five studies (8,10,16,21,27), participants were asked if they would recommend the intervention to a friend, and 89.04% said yes (SD = 10.76). In addition, 80.4% (SD = 13.9) of participants expressed their willingness to continue using the SMS reminders (8,10,16,18,19,21,25,27). In two studies, 15% (21) and 57% (25) of participants said they would be willing to pay a small fee for this service. In the malaria prophylaxis trial, 58.2% of the SMS group agreed that it would be very useful to extend the use of SMS reminders to all soldiers returning from malaria-endemic areas.
Mobile phone Only two studies reported having supplied the mobile phone to participants (9,18), and one study did not provide data on the supply of a mobile phone (13). In three studies, patients were paid for their participation (9,15,19).
Discussion We identified 20 articles assessing interventions based on mobile devices used to enhance adherence. To our knowledge, this is the first review to evaluate whether mHealth interventions enhance adherence to medication by taking into account practical issues (such as whether mobile phones are supplied), which may limit subsequent scaling up of this type of intervention. We were unable to perform a meta-analysis, owing to the significant clinical and methodological heterogeneity in the studies included.
Our findings suggest that mHealth enhances adherence to medication, although it was impossible to make comparisons, owing to differences in study design, intervention, comparator, treatment regimen, duration and measurement method. All interventions were based on sending SMS either strictly as a medication reminder or together with motivational content. Thus, a striking result at the time of this review was that although 680 (28) mobile phone applications to enhance adherence are commercially available, the lack of published results from RCT mean that the feasibility and acceptability of this technology cannot be validated, although most studies (83.3%) were conducted in high-income countries, where smartphone applications are widely used. Results have been reported by application developers such us MediSafe Project, whose mobile pillbox application improved adherence to antidiabetic drugs by more than 26% (29). It is important to remember that smartphone applications evolve much faster than other interventions, and while applications can be validated over a specific period, more features could be added to the initial version, thus making it impossible to determine the long-term impact of the baseline version. As for the target population, we found that HIV infection was the most widely studied disease in developing countries, whereas in highincome countries, other chronic diseases such as hypertension and diabetes were more commonly evaluated, and interventions targeting the healthy population were more frequent. This observation highlights the differences in reasons for implementing mHealth between countries: the main reason in developing countries is equity of healthcare delivery; in developed countries, it is optimisation of resources. As for measurement of adherence, only 17.6% of the studies used more than one method. This percentage is extremely low, considering that more than one method is widely recommended owing to the inaccuracy of current approaches. No reference method for measuring adherence has been established (1,2,30), and the available methods are either direct (directly observed treatment, plasma drug or metabolite levels, biomarkers) or indirect (pill count, self-report, medication refills, electronic monitoring devices). Each presents advantages and disadvantages: direct methods are expensive but more objective, whereas indirect methods are easy to implement but not objective, tend to overestimate adherence, and are only useful for specific drugs and populations. Therefore, the definition of adherence and the rate of adherence presented in this review are not uniform across the studies analysed; similarly, the methodology used to assess adherence also varies widely. Most methods were indirect (82.3% of cases), thus potentially leading to an overestimation of adherence levels, although the effect would have ª 2014 John Wiley & Sons Ltd Int J Clin Pract
mHealth and medication adherence
been the same in the control and intervention groups. The results reported by Mbuagbaw et al. (31) did not reveal a significant improvement in adherence. This is an interesting finding, since the study was the only one performed in HIV-infected patients that used more than one method to measure adherence. The authors found that higher levels of education and being on second-line treatment were related to higher adherence rates. A correlation has also been observed between poor adherence and low educational level and treatment regimen (32–35). In low income countries, these factors may be more relevant than in high income countries for several reasons such as: lower educational levels are more frequent in the population; access to medication is difficult and drug stock-outs are frequent. (36). However, most studies agree on the difficulty in defining the sociodemographic characteristics underlying these correlations (37–39). A recent metaanalysis on mobile phone text messages for improving antiretroviral therapy showed that use of SMS has a significant effect on adherence to antiretroviral therapy and that this effect is influenced by educational level, gender, timing (weekly vs. daily) and interactivity (36). Although sending SMS seems to enhance adherence, the fact that adherence rates significantly improve in 65% of the studies, is probably because non-adherence is a complex behaviour with several triggers, such as: presence of psychological problems, in particular depression; lack of primary support; occurrence of medication side effects; the treatment is focused on treating an asymptomatic disease (1). Patient-centred care is currently considered the gold standard, as it provides sufficient information for the patient to take part in the decision to start treatment and the design of the strategy to be followed. Therefore, a successful strategy must take into account patients’ needs, characteristics, and opinion after appropriate information has been provided. Recent surveys indicate that patients are willing to become more actively involved in managing their own care (40) and that self-monitoring at home is one way to increase their involvement (41). However, Mbuagbaw et al. (10) found that, although participants could interact via mobile phone, only 47.5% in the intervention arm used the feedback option. Therefore, mHealth interventions should not be considered a single intervention, since strategies to promote adherence should be tailored to patients’ specific needs, and more than one intervention could be required. Nevertheless, mHealth can motivate patients and healthy individuals to participate in their own care. In a study conducted to evaluate the feasibility of mobile direct observation treatment (MDOT), the authors showed high acceptability compared with clinical DOT or home visits (42). MDOT also improved adherence to hydroxyurea in paediatric patients with sickle-cell disease (overall medª 2014 John Wiley & Sons Ltd Int J Clin Pract
ian observed adherence of 93.9%) (43). In addition, whilst many studies analyse the impact of technology on the healthcare resources used, few look at how it changes contacts with primary care professionals. Most studies did not include detailed descriptions of their technical implementation processes and message delivery. This gap is important, because the missing information could prove useful for the design of future studies and strengthen the evidence base of this emerging research area. Important considerations that should be taken into account when implementing an interactive system are fatigue messages, logistics of mobile phones (e.g. notifications to determine whether a certain number is receiving messages and is operational, ability to detect changes in numbers), receiving messages gradually (independently of whether coverage is sufficient), adaptable messages, logic texts that allow for different types of response (e.g. yes, Yes, YES, Y), and avoidance of excess intrusiveness in the patient’s life (44). An essential issue in mhealth interventions is data security and confidentiality. American and European agencies have started to regulate some types of mobile applications, especially those that act as medical devices, but not those aimed at tracking adherence (45,46). However, if a mhealth intervention collects, stores and/or transmits information that constitutes Protected Health Information, it must do so following the Health Insurance Portability and Accountability Act (HIPAA) (47), as well as any other applicable laws or regulation of the country concerned. Therefore, data encryption and the use of secure networks are crucial. Rodrigues et al. (11) evaluated whether patients preferred SMS or phone calls and found that of the 136 respondents, 34% preferred phone calls only, 11% preferred SMS only, 44% preferred both and the remaining participants preferred neither. The frequency of text messages may also vary between adherence levels, with messages being more frequent when adherence is low (daily reminders) or more separated in patients with good adherence (weekly reminders). In another study, 93% of the participants responded that they read all the SMS (12). However, only 20% of participants indicated that SMS were sent at the right time, whereas 12% stated they were never at the right time (12). Other options that resulted in increased adherence are devices that attach to the standard pill bottle or blister pack and send an SMS to a web service every time the patient opens the bottle (48) or smart pillboxes that emit a loud beep (or other customised sound) if the compartment is not opened within 30 min of the scheduled time (49) and afterwards triggers an automated phone call or SMS. Nevertheless, mobile phone applications have yet to be evaluated alone and in comparison with other devices such as pillboxes.
21
22
mHealth and medication adherence
Thus, a major challenge for mHealth is to ensure that preventive measures reach the healthy population. Non-adherence is more frequent in preventive treatments because the target individuals are healthy (24). This observation correlates with our results, as only one of the three studies resulted in increased vaccination rates (24). However, Ollivier et al. (25) reported that the absence of a difference in adherence between the intervention and control groups was probably because the population under study consisted of soldiers who stayed together after returning from a malaria-endemic area. Adherence to malaria prophylaxis has been reported to be inadequate, mainly because of adverse events and forgetfulness (50,51). As stated above, multifaceted interventions featuring interactive education and training help to promote adherence in a variety of diseases. Another group of healthy end-users to consider is caregivers, since older age remains a major barrier to mHealth. This technology has been less accepted by older people, as shown in the study by the Pew Research Centre, where 81% of adults aged 25–34 years had smartphones (the group with the highest penetration of smartphones in the USA) compared with 50% of adults older than 55 years (3). These data correspond with the mean age of participants recruited in the studies, which was between 30 and 50 years. However, since this gap will disappear with time, it is important to draw the attention of caregivers to older individuals, who may benefit from the technology. Another important aspect of mHealth is feasibility of implementation. We found that participants were paid in three studies (9,15,19) and that mobile devices were supplied in two studies (9,18). Therefore, these findings do not provide useful insight into the potential scope of the intervention, since it is not feasible to provide mobile phones to the whole target population. However, if these interventions promote adherence, the cost of non-adherence may be higher than the cost of a mobile device. Haberer et al. (52) discuss feasibility issues in implementing the intervention described by Pop-Eleches et al. (9) Based on qualitative interviews with participants, the major issues pointed out were the need for detailed, multisession trainings for patients on the use of mobile phone technologies and PIN numbers and the possible need for monetary
References 1 Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005; 353: 487–97. 2 WHO. Adherence to Long-term Therapies: Evidence for Action. World Health Organization. http://www.who.int/chp/knowledge/publications/ adherence_report/en/ (accessed October 2, 2014).
incentives to keep patients sufficiently motivated to participate in the study. Implementation and updating of mHealth strategies consume resources, and there is no evidence of a reduction in cost. Foreman et al. (23), studied pharmacy medication costs after the start of the text messaging programme, although the differences detected were not statistically significant. Patel et al. (18) found no statistically significant differences in the use of resources, although fewer hospital admissions were detected in patients using the mobile application. In a study performed by Henderson et al. (50) in England including patients with chronic obstructive pulmonary disease (COPD), diabetes mellitus, and heart failure, the intervention did not prove to be cost effective based on health and social care costs and outcomes over 12 months and the willingness-to-pay threshold of £30,000 per QALY recommended by the National Institute for Health and Care Excellence. However, patients were supplied with pulse oximeters (patients with COPD), blood glucose monitors (patients with diabetes), and weighing scales (patients with heart failure), and almost all participants in the intervention received blood pressure monitors. Assuming that equipment costs decrease and working capacity increases, the probability that telehealth is cost effective will be about 61% based on a threshold of £30,000 per QALY (53). In contrast, in the studies analysed in the present review, no equipment was given to patients except the mobile phone in two cases. These results are consistent with those published in other reviews (54–57).
Conclusion Our results showed mixed evidence regarding the benefits of interventions. This is probably because of the variety of the study designs and the results found. Nevertheless, the interventions do seem to have been beneficial, as 65% of the studies had positive outcomes. Therefore, more high-quality studies should be conducted in order to demonstrate whether this type of technology reduces the considerable consequences of non-adherence. However, since mHealth enables real-time interactive self-management, policy-makers should consider funding programmes to establish its efficiency and applicability.
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Paper received June 2014, accepted October 2014
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