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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Does mHealth increase adherence to medication? Results of a systematic review.

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...
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