Costs and cost-effectiveness analyses of mCARE strategies for promoting care seeking of maternal and newborn health services in rural Bangladesh

Economic Evaluations of Digital Health Interventions for Children and Adolescents: Systematic Review

BACKGROUND

Digital health interventions (DHIs) are defined as digital technologies such as digital health applications and information and communications technology systems (including SMS text messages) implemented to meet health objectives. DHIs implemented using various technologies, ranging from electronic medical records to videoconferencing systems and mobile apps, have experienced substantial growth and uptake in recent years. Although the clinical effectiveness of DHIs for children and adolescents has been relatively well studied, much less is known about the cost-effectiveness of these interventions.

OBJECTIVE

This study aimed to systematically review economic evaluations of DHIs for pediatric and adolescent populations. This study also reviewed methodological issues specific to economic evaluations of DHIs to inform future research priorities.

METHODS

We conducted a database search in PubMed from 2011 to 2021 using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. In total, 2 authors independently screened the titles and abstracts of the search results to identify studies eligible for full-text review. We generated a data abstraction procedure based on recommendations from the Panel on Cost-Effectiveness in Health and Medicine. The types of economic evaluations included in this review were cost-effectiveness analyses (costs per clinical effect), cost-benefit analyses (costs and effects expressed in monetary terms as net benefit), and cost-utility analyses (cost per quality-adjusted life year or disability-adjusted life year). Narrative analysis was used to synthesize the quantitative data because of heterogeneity across the studies. We extracted methodological issues related to study design, analysis framework, cost and outcome measurement, and methodological assumptions regarding the health economic evaluation.

RESULTS

We included 22 articles assessing the cost-effectiveness of DHI interventions for children and adolescents. Most articles (14/22, 64%) evaluated interventions delivered through web-based portals or SMS text messaging, most frequently within the health care specialties of mental health and maternal, newborn, and child health. In 82% (18/22) of the studies, DHIs were found to be cost-effective or cost saving compared with the nondigital standard of care. The key drivers of cost-effectiveness included population coverage, cost components, intervention effect size and scale-up, and study perspective. The most frequently identified methodological challenges were related to study design (17/22, 77%), costing (11/22, 50%), and economic modeling (9/22, 41%).

CONCLUSIONS

This is the first systematic review of economic evaluations of DHIs targeting pediatric and adolescent populations. We found that most DHIs (18/22, 82%) for children and adolescents were cost-effective or cost saving compared with the nondigital standard of care. In addition, this review identified key methodological challenges directly related to the conduct of economic evaluations of DHIs and highlighted areas where further methodological research is required to address these challenges. These included the need for measurement of user involvement and indirect effects of DHIs and the development of children-specific, generic quality-of-life outcomes.

Systematic review on the cost and cost-effectiveness of mHealth interventions supporting women during pregnancy

OBJECTIVES

The increased integration of digital health into maternity care-alongside growing use of, and access to, personal digital technology among pregnant women-warrants an investigation of the cost-effectiveness of mHealth interventions used by women during pregnancy and the methodological quality of the cost-effectiveness studies.

METHODS

A systematic search was conducted to identify peer-reviewed studies published in the last ten years (2011-2021) reporting on the costs or cost-effectiveness of mHealth interventions used by women during pregnancy. Available data related to program costs, total incremental costs and incremental cost-effectiveness ratios (ICERs) were reported in 2020 United States Dollars. The quality of cost-effectiveness studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS).

FINDINGS

Nine articles reporting on eight studies met the inclusion criteria. Direct intervention costs ranged from $7.04 to $86 per woman, total program costs ranged from $241,341 to $331,136 and total incremental costs ranged from -$21.16 to $1.12 million per woman. The following ICERs were reported: $2168 per DALY averted, $203.44 per woman ceasing smoking, and $3475 per QALY gained. The full economic evaluation studies (n = 4) were moderate to high in quality and all reported the mHealth intervention as cost-effective. Other studies (n = 4) were low to moderate in quality and reported low costs or cost savings associated with the implementation of the mHealth intervention.

CONCLUSIONS FOR PRACTICE

Preliminary evidence suggests mHealth interventions may be cost-effective and "low-cost" but more evidence is needed to ascertain the cost-effectiveness of mHealth interventions regarding positive maternal and child health outcomes and longer-term health service utilisation.

mHealth interventions to reduce maternal and child mortality in Sub-Saharan Africa and Southern Asia: A systematic literature review

Background

Reducing maternal mortality, neonatal mortality and under 5-year mortality are important targets addressed by the United Nations' Sustainable Development Goals. Despite studies reported an improvement in maternal and child health indicators, the progress achieved is not uniform across regions. Due to the increasing availability of mobile phones in low and middle-income countries, mHealth could impact considerably on reducing maternal and child mortality and maximizing women's access to quality care, from the antenatal stage to the post-natal period.

Methods

A systematic literature review of mHealth interventions aimed at reducing maternal and child mortality in Sub-Saharan Africa and Southern Asia. Primary outcomes were maternal mortality, neonatal mortality, and under-five mortality. Secondary outcomes were skilled birth attendance, antenatal care (ANC) and post-natal care (PNC) attendance, and vaccination/immunization coverage. We searched for articles published from January 2010 to December 2020 in Embase, Medline and Web of Science. Quantitative comparative studies were included. The protocol was developed according to the PRISMA Checklist and published in PROSPERO [CRD42019109434]. The Quality Assessment Tool for Quantitative Studies was used to assess the quality of the eligible studies.

Results

23 studies were included in the review, 16 undertaken in Sub-Saharan Africa and 7 in Southern Asia. Most studies used SMS or voice message reminders for education purposes. Only two studies reported outcomes on neonatal mortality, with positive results. None of the studies reported results on maternal mortality or under-five mortality. Outcomes on skilled birth attendance, ANC attendance, PNC attendance, and vaccination coverage were reported in six, six, five, and eleven studies, respectively. Most of these studies showed a positive impact of mHealth interventions on the secondary outcomes.

Conclusion

Simple mHealth educational interventions based on SMS and voice message reminders are effective at supporting behavior change of pregnant women and training of health workers, thus improving ANC and PNC attendance, vaccination coverage and skilled birth attendance. Higher quality studies addressing the role of mHealth in reducing maternal and child mortality in resource-limited settings are needed, especially in Southern Asia.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019109434, identifier CRD42019109434.

The cost-effectiveness of digital health interventions: A systematic review of the literature

Background

Digital health interventions have significant potential to improve safety, efficacy, and quality of care, reducing waste in healthcare costs. Despite these premises, the evidence regarding cost and effectiveness of digital tools in health is scarce and limited.

Objectives

The aim of this systematic review is to summarize the evidence on the cost-effectiveness of digital health interventions and to assess whether the studies meet the established quality criteria.

Methods

We queried PubMed, Scopus and Web of Science databases for articles in English published from January 1, 2016 to December 31, 2020 that performed economic evaluations of digital health technologies. The methodological rigorousness of studies was assessed with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2009 checklist.

Results

Search identified 1,476 results, 552 of which were selected for abstract and 35 were included in this review. The studies were heterogeneous by country (mostly conducted in upper and upper-middle income countries), type of eHealth intervention, method of implementation, and reporting perspectives. The qualitative analysis identified the economic and effectiveness evaluation of six different types of interventions: (1) seventeen studies on new video-monitoring service systems; (2) five studies on text messaging interventions; (3) five studies on web platforms and digital health portals; (4) two studies on telephone support; (5) three studies on new mobile phone-based systems and applications; and (6) three studies on digital technologies and innovations.

Conclusion

Findings on cost-effectiveness of digital interventions showed a growing body of evidence and suggested a generally favorable effect in terms of costs and health outcomes. However, due to the heterogeneity across study methods, the comparison between interventions still remains difficult. Further research based on a standardized approach is needed in order to methodically analyze incremental cost-effectiveness ratios, costs, and health benefits.

A mobile education and social support group intervention for improving postpartum health in northern India: Development and usability study (Preprint)

Background

Structural and cultural barriers limit Indian women’s access to adequate postnatal care and support despite their importance for maternal and neonatal health. Targeted postnatal education and support through a mobile health intervention may improve postnatal recovery, neonatal care practices, nutritional status, knowledge and care seeking, and mental health.

Objective

We sought to understand the feasibility and acceptability of our first pilot phase, a flexible 6-week postnatal mobile health intervention delivered to 3 groups of women in Punjab, India, and adapt our intervention for our next pilot phase, which will formally assess intervention feasibility, acceptability, and preliminary efficacy.

Methods

Our intervention prototype was designed to deliver culturally tailored educational programming via a provider-moderated, voice- and text-based group approach to connect new mothers with a social support group of other new mothers, increase their health-related communication with providers, and refer them to care needed. We targeted deployment using feature phones to include participants from diverse socioeconomic groups. We held moderated group calls weekly, disseminated educational audios, and created SMS text messaging groups. We varied content delivery, group discussion participation, and chat moderation. Three groups of postpartum women from Punjab were recruited for the pilot through community health workers. Sociodemographic data were collected at baseline. Intervention feasibility and acceptability were assessed through weekly participant check-ins (N=29), weekly moderator reports, structured end-line in-depth interviews among a subgroup of participants (15/29, 52%), and back-end technology data.

Results

The participants were aged 24 to 28 years and 1 to 3 months postpartum. Of the 29 participants, 17 (59%) had their own phones. Half of the participants (14/29, 48%) attended ≥3 of the 6 calls; the main barriers were childcare and household responsibilities and network or phone issues. Most participants were very satisfied with the intervention (16/19, 84%) and found the educational content (20/20, 100%) and group discussions (17/20, 85%) very useful. The participants used the SMS text messaging chat, particularly when facilitator-moderated. Sustaining participation and fostering group interactions was limited by technological and sociocultural challenges.

Conclusions

The intervention was considered generally feasible and acceptable, and protocol adjustments were identified to improve intervention delivery and engagement. To address technological issues, we engaged a cloud-based service provider for group calls and an interactive voice response service provider for educational recordings and developed a smartphone app for the participants. We seek to overcome sociocultural challenges through new strategies for increasing group engagement, including targeting midlevel female community health care providers as moderators. Our second pilot will assess intervention feasibility, acceptability, and preliminary effectiveness at 6 months. Ultimately, we seek to support the health and well-being of postpartum women and their infants in South Asia and beyond through the development of efficient, acceptable, and effective intervention strategies.

mCARE, a digital health intervention package on pregnancy surveillance and care-seeking reminders from 2018 to 2027 in Bangladesh: a model-based cost-effectiveness analysis

OBJECTIVE

We estimated the cost-effectiveness of a digital health intervention package (mCARE) for community health workers, on pregnancy surveillance and care-seeking reminders compared with the existing paper-based status quo, from 2018 to 2027, in Bangladesh.

INTERVENTIONS

The mCARE programme involved digitally enhanced pregnancy surveillance, individually targeted text messages and in-person home-visit to pregnant women for care-seeking reminders for antenatal care, child delivery and postnatal care.

STUDY DESIGN

We developed a model to project population and service coverage increases with annual geographical expansion (from 1 million to 10 million population over 10 years) of the mCARE programme and the status quo.

MAJOR OUTCOMES

For this modelling study, we used Lives Saved Tool to estimate the number of deaths and disability-adjusted life years (DALYs) that would be averted by 2027, if the coverage of health interventions was increased in mCARE programme and the status quo, respectively. Economic costs were captured from a societal perspective using an ingredients approach and expressed in 2018 US dollars. Probabilistic sensitivity analysis was undertaken to account for parameter uncertainties.

RESULTS

We estimated the mCARE programme to avert 3076 deaths by 2027 at an incremental cost of $43 million relative to the status quo, which is translated to $462 per DALY averted. The societal costs were estimated to be $115 million for mCARE programme (48% of which are programme costs, 35% user costs and 17% provider costs). With the continued implementation and geographical scaling-up, the mCARE programme improved its cost-effectiveness from $1152 to $462 per DALY averted from 5 to 10 years.

CONCLUSION

Mobile phone-based pregnancy surveillance systems with individually scheduled text messages and home-visit reminder strategies can be highly cost-effective in Bangladesh. The cost-effectiveness may improve as it promotes facility-based child delivery and achieves greater programme cost efficiency with programme scale and sustainability.

Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh

Objective

To assess the extent to which maternal histories of newborn danger signs independently or combined with birth weight and/or gestational age (GA) can capture and/or predict postsecond day (age>48 hours) neonatal death.

Methods

Data from a cluster-randomised trial conducted in rural Bangladesh were split into development and validation sets. The prompted recall of danger signs and birth weight measurements were collected within 48 hours postchildbirth. Maternally recalled danger signs included cyanosis (any part of the infant's body was blue at birth), non-cephalic presentation (part other than head came out first at birth), lethargy (weak or no arm/leg movement and/or cry at birth), trouble suckling (infant unable to suckle/feed normally in the 2 days after birth or before death, collected 1-month postpartum or from verbal autopsy). Last menstrual period was collected at maternal enrolment early in pregnancy. Singleton newborns surviving 2 days past childbirth were eligible for analysis. Prognostic multivariable models were developed and internally validated.

Results

Recalling ≥1 sign of lethargy, cyanosis, non-cephalic presentation or trouble suckling identified postsecond day neonatal death with 65.3% sensitivity, 60.8% specificity, 2.1% positive predictive value (PPV) and 99.3% negative predictive value (NPV) in the development set. Requiring either lethargy or weight <2.5 kg identified 89.1% of deaths (at 39.7% specificity, 1.9% PPV and 99.6% NPV) while lethargy or preterm birth (<37 weeks) captured 81.0% of deaths (at 53.6% specificity, 2.3% PPV and 99.5% NPV). A simplified model (birth weight, GA, lethargy, cyanosis, non-cephalic presentation and trouble suckling) predicted death with good discrimination (validation area under the receiver-operator characteristic curve (AUC) 0.80, 95% CI 0.73 to 0.87). A further simplified model (GA, non-cephalic presentation, lethargy, trouble suckling) predicted death with moderate discrimination (validation AUC 0.74, 95% CI 0.66 to 0.81).

Conclusion

Maternally recalled danger signs, coupled to either birth weight or GA, can predict and capture postsecond day neonatal death with high discrimination and sensitivity.