title: mHealth Series: Measuring maternal newborn and child health coverage by text messaging - a county-level model for China.
abstract: BACKGROUND
  Effective interventions in maternal, newborn and child health (MNCH), if achieving high level of population coverage, could prevent most of deaths in children under five years of age. High-quality measurements of MNCH coverage are essential for tracking progress and making evidence-based decisions.
  
  
  METHODS
  MNCH coverage data are mainly collected through fieldworkers' interview with preselected households in standard programs of Demographic and Health Surveys (DHS) or Multiple Indicator Cluster Surveys (MICS) in most low- and middle-income countries. Household surveys will continue to be the major data source for MNCH coverage in the foreseeable future. However, face-to-face data collection broadly used in household surveys is labor-intensive, time-consuming and expensive. Mobile phones are drawing more and more interest in medical research with the rapid increase in usage and text messaging could be an innovative way of data collection, that is, we could collect DHS data through mHealth method. We refer to it as "mDHS".
  
  
  RESULTS
  We propose in this paper a conceptual model for measuring MNCH coverage by text messaging in China. In developing this model, we considered resource constraints, sample representativeness, sample size and survey bias. The components of the model are text messaging platform, routine health information system, health facilities, communities and households.
  
  
  CONCLUSIONS
  Measuring MNCH interventions coverage by text messaging could be advantageous in many ways and establish a much larger evidence-base for MNCH health policies in China. Before mDHS could indeed be launched, research priorities would include a systematic assessment of routine health information systems and exploring feasibility to collect name lists, mobile phone numbers and general demographic and socio-economic data; qualitative interviews with health workers and caregivers; assessment of data validity of all indicators to be collected by text messaging; and exploring approaches to increase participation rate.
authors.affiliation: Department of Integrated Early Childhood Development, Capital Institute of Pediatrics, Beijing, China.
authors.forename: Yanfeng
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Integrated Early Childhood Development, Capital Institute of Pediatrics, Beijing, China.
authors.forename: Li
authors.initials: L
authors.lastname: Chen
authors.affiliation: Global eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.
authors.forename: Michelle H M M T
authors.initials: MH
authors.lastname: van Velthoven
authors.affiliation: Department of Integrated Early Childhood Development, Capital Institute of Pediatrics, Beijing, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.affiliation: Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Liu
authors.affiliation: Department of Integrated Early Childhood Development, Capital Institute of Pediatrics, Beijing, China.
authors.forename: Xiaozhen
authors.initials: X
authors.lastname: Du
authors.affiliation: Department of Integrated Early Childhood Development, Capital Institute of Pediatrics, Beijing, China.
authors.forename: Qiong
authors.initials: Q
authors.lastname: Wu
authors.affiliation: Department of Integrated Early Childhood Development, Capital Institute of Pediatrics, Beijing, China.
authors.forename: Ye
authors.initials: Y
authors.lastname: Li
authors.affiliation: Global eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom.
authors.forename: Josip
authors.initials: J
authors.lastname: Car