Digital tracking, provider decision support systems, and targeted client communication via mobile devices to improve primary health care

Targeted client communication via mobile devices for improving maternal, neonatal, and child health

BACKGROUND

The global burden of poor maternal, neonatal, and child health (MNCH) accounts for more than a quarter of healthy years of life lost worldwide. Targeted client communication (TCC) via mobile devices (MD) (TCCMD) may be a useful strategy to improve MNCH.

OBJECTIVES

To assess the effects of TCC via MD on health behaviour, service use, health, and well-being for MNCH.

SEARCH METHODS

In July/August 2017, we searched five databases including The Cochrane Central Register of Controlled Trials, MEDLINE and Embase. We also searched two trial registries. A search update was carried out in July 2019 and potentially relevant studies are awaiting classification.

SELECTION CRITERIA

We included randomised controlled trials that assessed TCC via MD to improve MNCH behaviour, service use, health, and well-being. Eligible comparators were usual care/no intervention, non-digital TCC, and digital non-targeted client communication.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures recommended by Cochrane, although data extraction and risk of bias assessments were carried out by one person only and cross-checked by a second.

MAIN RESULTS

We included 27 trials (17,463 participants). Trial populations were: pregnant and postpartum women (11 trials conducted in low-, middle- or high-income countries (LMHIC); pregnant and postpartum women living with HIV (three trials carried out in one lower middle-income country); and parents of children under the age of five years (13 trials conducted in LMHIC). Most interventions (18) were delivered via text messages alone, one was delivered through voice calls only, and the rest were delivered through combinations of different communication channels, such as multimedia messages and voice calls. Pregnant and postpartum women TCCMD versus standard care For behaviours, TCCMD may increase exclusive breastfeeding in settings where rates of exclusive breastfeeding are less common (risk ratio (RR) 1.30, 95% confidence intervals (CI) 1.06 to 1.59; low-certainty evidence), but have little or no effect in settings where almost all women breastfeed (low-certainty evidence). For use of health services, TCCMD may increase antenatal appointment attendance (odds ratio (OR) 1.54, 95% CI 0.80 to 2.96; low-certainty evidence); however, the CI encompasses both benefit and harm. The intervention may increase skilled attendants at birth in settings where a lack of skilled attendants at birth is common (though this differed by urban/rural residence), but may make no difference in settings where almost all women already have a skilled attendant at birth (OR 1.00, 95% CI 0.34 to 2.94; low-certainty evidence). There were uncertain effects on maternal and neonatal mortality and morbidity because the certainty of the evidence was assessed as very low. TCCMD versus non-digital TCC (e.g. pamphlets) TCCMD may have little or no effect on exclusive breastfeeding (RR 0.92, 95% CI 0.79 to 1.07; low-certainty evidence). TCCMD may reduce 'any maternal health problem' (RR 0.19, 95% CI 0.04 to 0.79) and 'any newborn health problem' (RR 0.52, 95% CI 0.25 to 1.06) reported up to 10 days postpartum (low-certainty evidence), though the CI for the latter includes benefit and harm. The effect on health service use is unknown due to a lack of studies. TCCMD versus digital non-targeted communication No studies reported behavioural, health, or well-being outcomes for this comparison. For use of health services, there are uncertain effects for the presence of a skilled attendant at birth due to very low-certainty evidence, and the intervention may make little or no difference to attendance for antenatal influenza vaccination (RR 1.05, 95% CI 0.71 to 1.58), though the CI encompasses both benefit and harm (low-certainty evidence). Pregnant and postpartum women living with HIV TCCMD versus standard care For behaviours, TCCMD may make little or no difference to maternal and infant adherence to antiretroviral (ARV) therapy (low-certainty evidence). For health service use, TCC mobile telephone reminders may increase use of antenatal care slightly (mean difference (MD) 1.5, 95% CI -0.36 to 3.36; low-certainty evidence). The effect on the proportion of births occurring in a health facility is uncertain due to very low-certainty evidence. For health and well-being outcomes, there was an uncertain intervention effect on neonatal death or stillbirth, and infant HIV due to very low-certainty evidence. No studies reported on maternal mortality or morbidity. TCCMD versus non-digital TCC The effect is unknown due to lack of studies reporting this comparison. TCCMD versus digital non-targeted communication TCCMD may increase infant ARV/prevention of mother-to-child transmission treatment adherence (RR 1.26, 95% CI 1.07 to 1.48; low-certainty evidence). The effect on other outcomes is unknown due to lack of studies. Parents of children aged less than five years No studies reported on correct treatment, nutritional, or health outcomes. TCCMD versus standard care Based on 10 trials, TCCMD may modestly increase health service use (vaccinations and HIV care) (RR 1.21, 95% CI 1.08 to 1.34; low-certainty evidence); however, the effect estimates varied widely between studies. TCCMD versus non-digital TCC TCCMD may increase attendance for vaccinations (RR 1.13, 95% CI 1.00 to 1.28; low-certainty evidence), and may make little or no difference to oral hygiene practices (low-certainty evidence). TCCMD versus digital non-targeted communication TCCMD may reduce attendance for vaccinations, but the CI encompasses both benefit and harm (RR 0.63, 95% CI 0.33 to 1.20; low-certainty evidence). No trials in any population reported data on unintended consequences.

AUTHORS' CONCLUSIONS

The effect of TCCMD for most outcomes is uncertain. There may be improvements for some outcomes using targeted communication but these findings were of low certainty. High-quality, adequately powered trials and cost-effectiveness analyses are required to reliably ascertain the effects and relative benefits of TCCMD. Future studies should measure potential unintended consequences, such as partner violence or breaches of confidentiality.

Targeted client communication via mobile devices for improving sexual and reproductive health

BACKGROUND

The burden of poor sexual and reproductive health (SRH) worldwide is substantial, disproportionately affecting those living in low- and middle-income countries. Targeted client communication (TCC) delivered via mobile devices (MD) (TCCMD) may improve the health behaviours and service use important for sexual and reproductive health.

OBJECTIVES

To assess the effects of TCC via MD on adolescents' knowledge, and on adolescents' and adults' sexual and reproductive health behaviour, health service use, and health and well-being.

SEARCH METHODS

In July/August 2017, we searched five databases including The Cochrane Central Register of Controlled Trials, MEDLINE and Embase. We also searched two trial registries. A search update was carried out in July 2019 and potentially relevant studies are awaiting classification.

SELECTION CRITERIA

We included randomised controlled trials of TCC via MD to improve sexual and reproductive health behaviour, health service use, and health and well-being. Eligible comparators were standard care or no intervention, non-digital TCC, and digital non-targeted communication.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures recommended by Cochrane, although data extraction and risk of bias assessments were carried out by one person only and cross-checked by a second. We have presented results separately for adult and adolescent populations, and for each comparison.

MAIN RESULTS

We included 40 trials (27 among adult populations and 13 among adolescent populations) with a total of 26,854 participants. All but one of the trials among adolescent populations were conducted in high-income countries. Trials among adult populations were conducted in a range of high- to low-income countries. Among adolescents, nine interventions were delivered solely through text messages; four interventions tested text messages in combination with another communication channel, such as emails, multimedia messaging, or voice calls; and one intervention used voice calls alone. Among adults, 20 interventions were delivered through text messages; two through a combination of text messages and voice calls; and the rest were delivered through other channels such as voice calls, multimedia messaging, interactive voice response, and instant messaging services. Adolescent populations TCCMD versus standard care TCCMD may increase sexual health knowledge (risk ratio (RR) 1.45, 95% confidence interval (CI) 1.23 to 1.71; low-certainty evidence). TCCMD may modestly increase contraception use (RR 1.19, 95% CI 1.05 to 1.35; low-certainty evidence). The effects on condom use, antiretroviral therapy (ART) adherence, and health service use are uncertain due to very low-certainty evidence. The effects on abortion and STI rates are unknown due to lack of studies. TCCMD versus non-digital TCC (e.g. pamphlets) The effects of TCCMD on behaviour (contraception use, condom use, ART adherence), service use, health and wellbeing (abortion and STI rates) are unknown due to lack of studies for this comparison. TCCMD versus digital non-targeted communication The effects on sexual health knowledge, condom and contraceptive use are uncertain due to very low-certainty evidence. Interventions may increase health service use (attendance for STI/HIV testing, RR 1.61, 95% CI 1.08 to 2.40; low-certainty evidence). The intervention may be beneficial for reducing STI rates (RR 0.61, 95% CI 0.28 to 1.33; low-certainty evidence), but the confidence interval encompasses both benefit and harm. The effects on abortion rates and on ART adherence are unknown due to lack of studies. We are uncertain whether TCCMD results in unintended consequences due to lack of evidence. Adult populations TCCMD versus standard care For health behaviours, TCCMD may modestly increase contraception use at 12 months (RR 1.17, 95% CI 0.92 to 1.48) and may reduce repeat abortion (RR 0.68 95% CI 0.28 to 1.66), though the confidence interval encompasses benefit and harm (low-certainty evidence). The effect on condom use is uncertain. No study measured the impact of this intervention on STI rates. TCCMD may modestly increase ART adherence (RR 1.13, 95% CI 0.97 to 1.32, low-certainty evidence, and standardised mean difference 0.44, 95% CI -0.14 to 1.02, low-certainty evidence). TCCMD may modestly increase health service utilisation (RR 1.17, 95% CI 1.04 to 1.31; low-certainty evidence), but there was substantial heterogeneity (I² = 85%), with mixed results according to type of service utilisation (i.e. attendance for STI testing; HIV treatment; voluntary male medical circumcision (VMMC); VMMC post-operative visit; post-abortion care). For health and well-being outcomes, there may be little or no effect on CD4 count (mean difference 13.99, 95% CI -8.65 to 36.63; low-certainty evidence) and a slight reduction in virological failure (RR 0.86, 95% CI 0.73 to 1.01; low-certainty evidence). TCCMD versus non-digital TCC No studies reported STI rates, condom use, ART adherence, abortion rates, or contraceptive use as outcomes for this comparison. TCCMD may modestly increase in service attendance overall (RR: 1.12, 95% CI 0.92-1.35, low certainty evidence), however the confidence interval encompasses benefit and harm. TCCMD versus digital non-targeted communication No studies reported STI rates, condom use, ART adherence, abortion rates, or contraceptive use as outcomes for this comparison. TCCMD may increase service utilisation overall (RR: 1.71, 95% CI 0.67-4.38, low certainty evidence), however the confidence interval encompasses benefit and harm and there was considerable heterogeneity (I² = 72%), with mixed results according to type of service utilisation (STI/HIV testing, and VMMC). Few studies reported on unintended consequences. One study reported that a participant withdrew from the intervention as they felt it compromised their undisclosed HIV status.

AUTHORS' CONCLUSIONS

TCCMD may improve some outcomes but the evidence is of low certainty. The effect on most outcomes is uncertain/unknown due to very low certainty evidence or lack of evidence. High quality, adequately powered trials and cost effectiveness analyses are required to reliably ascertain the effects and relative benefits of TCC delivered by mobile devices. Given the sensitivity and stigma associated with sexual and reproductive health future studies should measure unintended consequences, such as partner violence or breaches of confidentiality.

Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis

BACKGROUND

Mobile health (mHealth), refers to healthcare practices supported by mobile devices, such as mobile phones and tablets. Within primary care, health workers often use mobile devices to register clients, track their health, and make decisions about care, as well as to communicate with clients and other health workers. An understanding of how health workers relate to, and experience mHealth, can help in its implementation.

OBJECTIVES

To synthesise qualitative research evidence on health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services, and to develop hypotheses about why some technologies are more effective than others.

SEARCH METHODS

We searched MEDLINE, Embase, CINAHL, Science Citation Index and Social Sciences Citation Index in January 2018. We searched Global Health in December 2015. We screened the reference lists of included studies and key references and searched seven sources for grey literature (16 February to 5 March 2018). We re-ran the search strategies in February 2020. We screened these records and any studies that we identified as potentially relevant are awaiting classification.

SELECTION CRITERIA

We included studies that used qualitative data collection and analysis methods. We included studies of mHealth programmes that were part of primary healthcare services. These services could be implemented in public or private primary healthcare facilities, community and workplace, or the homes of clients. We included all categories of health workers, as well as those persons who supported the delivery and management of the mHealth programmes. We excluded participants identified as technical staff who developed and maintained the mHealth technology, without otherwise being involved in the programme delivery. We included studies conducted in any country.

DATA COLLECTION AND ANALYSIS

We assessed abstracts, titles and full-text papers according to the inclusion criteria. We found 53 studies that met the inclusion criteria and sampled 43 of these for our analysis. For the 43 sampled studies, we extracted information, such as country, health worker category, and the mHealth technology. We used a thematic analysis process. We used GRADE-CERQual to assess our confidence in the findings.

MAIN RESULTS

Most of the 43 included sample studies were from low- or middle-income countries. In many of the studies, the mobile devices had decision support software loaded onto them, which showed the steps the health workers had to follow when they provided health care. Other uses included in-person and/or text message communication, and recording clients' health information. Almost half of the studies looked at health workers' use of mobile devices for mother, child, and newborn health. We have moderate or high confidence in the following findings. mHealth changed how health workers worked with each other: health workers appreciated being more connected to colleagues, and thought that this improved co-ordination and quality of care. However, some described problems when senior colleagues did not respond or responded in anger. Some preferred face-to-face connection with colleagues. Some believed that mHealth improved their reporting, while others compared it to "big brother watching". mHealth changed how health workers delivered care: health workers appreciated how mHealth let them take on new tasks, work flexibly, and reach clients in difficult-to-reach areas. They appreciated mHealth when it improved feedback, speed and workflow, but not when it was slow or time consuming. Some health workers found decision support software useful; others thought it threatened their clinical skills. Most health workers saw mHealth as better than paper, but some preferred paper. Some health workers saw mHealth as creating more work. mHealth led to new forms of engagement and relationships with clients and communities: health workers felt that communicating with clients by mobile phone improved care and their relationships with clients, but felt that some clients needed face-to-face contact. Health workers were aware of the importance of protecting confidential client information when using mobile devices. Some health workers did not mind being contacted by clients outside working hours, while others wanted boundaries. Health workers described how some community members trusted health workers that used mHealth while others were sceptical. Health workers pointed to problems when clients needed to own their own phones. Health workers' use and perceptions of mHealth could be influenced by factors tied to costs, the health worker, the technology, the health system and society, poor network access, and poor access to electricity: some health workers did not mind covering extra costs. Others complained that phone credit was not delivered on time. Health workers who were accustomed to using mobile phones were sometimes more positive towards mHealth. Others with less experience, were sometimes embarrassed about making mistakes in front of clients or worried about job security. Health workers wanted training, technical support, user-friendly devices, and systems that were integrated into existing electronic health systems. The main challenges health workers experienced were poor network connections, access to electricity, and the cost of recharging phones. Other problems included damaged phones. Factors outside the health system also influenced how health workers experienced mHealth, including language, gender, and poverty issues. Health workers felt that their commitment to clients helped them cope with these challenges.

AUTHORS' CONCLUSIONS

Our findings propose a nuanced view about mHealth programmes. The complexities of healthcare delivery and human interactions defy simplistic conclusions on how health workers will perceive and experience their use of mHealth. Perceptions reflect the interplay between the technology, contexts, and human attributes. Detailed descriptions of the programme, implementation processes and contexts, alongside effectiveness studies, will help to unravel this interplay to formulate hypotheses regarding the effectiveness of mHealth.

Development of a targeted client communication intervention to women using an electronic maternal and child health registry: a qualitative study

BACKGROUND

Targeted client communication (TCC) using text messages can inform, motivate and remind pregnant and postpartum women of timely utilization of care. The mixed results of the effectiveness of TCC interventions points to the importance of theory based interventions that are co-design with users. The aim of this paper is to describe the planning, development, and evaluation of a theory led TCC intervention, tailored to pregnant and postpartum women and automated from the Palestinian electronic maternal and child health registry.

METHODS

We used the Health Belief Model to develop interview guides to explore women's perceptions of antenatal care (ANC), with a focus on high-risk pregnancy conditions (anemia, hypertensive disorders in pregnancy, gestational diabetes mellitus, and fetal growth restriction), and untimely ANC attendance, issues predefined by a national expert panel as being of high interest. We performed 18 in-depth interviews with women, and eight with healthcare providers in public primary healthcare clinics in the West Bank and Gaza. Grounding on the results of the in-depth interviews, we used concepts from the Model of Actionable Feedback, social nudging and Enhanced Active Choice to compose the TCC content to be sent as text messages. We assessed the acceptability and understandability of the draft text messages through unstructured interviews with local health promotion experts, healthcare providers, and pregnant women.

RESULTS

We found low awareness of the importance of timely attendance to ANC, and the benefits of ANC for pregnancy outcomes. We identified knowledge gaps and beliefs in the domains of low awareness of susceptibility to, and severity of, anemia, hypertension, and diabetes complications in pregnancy. To increase the utilization of ANC and bridge the identified gaps, we iteratively composed actionable text messages with users, using recommended message framing models. We developed algorithms to trigger tailored text messages with higher intensity for women with a higher risk profile documented in the electronic health registry.

CONCLUSIONS

We developed an optimized TCC intervention underpinned by behavior change theory and concepts, and co-designed with users following an iterative process. The electronic maternal and child health registry can serve as a unique platform for TCC interventions using text messages.