Jo Youngji, LeFevre Amnesty Elizabeth, Ali Hasmot, Mehra Sucheta, Alland Kelsey, Shaikh Saijuddin, Haque Rezwanul, Pak Esther Semee, Chowdhury Mridul, Labrique Alain B
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
BMJ Open. 2021 Apr 1;11(4):e042553. doi: 10.1136/bmjopen-2020-042553.
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.
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.
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.
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.
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.
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.
我们评估了2018年至2027年期间，在孟加拉国，与现有的纸质记录现状相比，一种针对社区卫生工作者的数字健康干预方案（mCARE）在孕期监测和寻求护理提醒方面的成本效益。
mCARE方案包括数字化增强的孕期监测、针对个人的短信以及对孕妇进行上门家访，以提醒她们寻求产前护理、分娩护理和产后护理。
我们开发了一个模型，以预测随着mCARE方案和现状每年在地理范围上的扩大（10年内从100万人口增加到1000万人口），人口和服务覆盖范围的增长情况。
对于这项建模研究，如果分别提高mCARE方案和现状中卫生干预措施的覆盖范围，我们使用“挽救生命工具”来估计到2027年可避免的死亡人数和伤残调整生命年（DALYs）。从社会角度采用成分法获取经济成本，并以2018年美元表示。进行概率敏感性分析以考虑参数的不确定性。
我们估计，到2027年，mCARE方案相对于现状可避免3076例死亡，增量成本为4300万美元，相当于每避免一个DALY的成本为462美元。mCARE方案的社会成本估计为1.15亿美元（其中48%是方案成本，35%是用户成本，17%是提供者成本）。随着持续实施和地理范围的扩大，mCARE方案的成本效益从每避免一个DALY的1152美元提高到5至10年时的462美元。
在孟加拉国，基于手机的孕期监测系统以及个性化安排的短信和家访提醒策略可能具有很高的成本效益。随着它促进基于医疗机构的分娩，并随着方案规模和可持续性实现更高的方案成本效率，成本效益可能会提高。
