Evidence map›Paper›PMID 27387548›Full record

ArticleBMC medical informatics and decision making2016

Continuum of Care Services for Maternal and Child Health using mobile technology - a health system strengthening strategy in low and middle income countries.

Ramkrishnan Balakrishnan, Vijayaprasad Gopichandran, Sharadprakash Chaturvedi, Rahul Chatterjee, Tanmay Mahapatra, Indrajit Chaudhuri

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 8 pooled it
17.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 8 syntheses or guidelines pooled it, 117 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Trial
  14. Trial
  15. Trial
  16. Trial
  17. Article
  18. Article
  19. Article
  20. Research progress in postpartum visit competency.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2024
    Review

7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Ramkrishnan BalakrishnanCARE India, Patna, India.
Vijayaprasad GopichandranDepartment of Community Medicine, ESIC Medical College & PGIMSR, KK Nagar, Chennai, 600078, India. vijay.gopichandran@gmail.com.ORCID 0000-0003-2635-9583
Sharadprakash ChaturvediCARE India, Patna, India.
Rahul ChatterjeeCARE India, Patna, India.
Tanmay MahapatraDepartment of Epidemiology, Fielding School of Public Health, University of California Los Angeles, Los Angeles, 90095, USA.
Indrajit ChaudhuriCARE India, Patna, India.
Care India · INESIC Hospital · INUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile phone technology is utilized for better delivery of health services worldwide. In low-and-middle income countries mobile phones are now ubiquitous. Thus leveraging mHealth applications in health sector is becoming popular rapidly in these countries. To assess the effectiveness of the Continuum of Care Services (CCS) mHealth platform in terms of strengthening the delivery of maternal and child health (MCH) services in a district in Bihar, a resource-poor state in India.

methodsThe CommCare mHealth platform was customized to CCS as one of the innovations under a project funded by the Bill and Melinda Gates Foundation to improve the maternal and newborn health services in Bihar. The intervention was rolled out in one project district in Bihar, during July 2012. More than 550 frontline workers out of a total of 3000 including Accredited Social Health Activists, Anganwadi Workers, Auxilliary Nurse Midwives and Lady Health Supervisors were trained to use the mHealth platform. The service delivery components namely early registration of pregnant women, three antenatal visits, tetanus toxoid immunization of the mother, iron and folic acid tablet supply, institutional delivery, postnatal home visits and early initiation of breastfeeding were used as indicators for good quality services. The resultant coverage of these services in the implementation area was compared with rest of Bihar and previous year statistics of the same area. The time lag between delivery of a service and its record capture in the maternal and child tracking system (MCTS) database was computed in a random sample of 16,000 beneficiaries. The coverage of services among marginalized and non-marginalized castes was compared to indicate equity of service delivery. Health system strengthening was viewed from the angle of coverage, quality, equity and efficiency of services.

resultsThe implementation blocks had higher coverage of all the eight indicator services compared to rest of Bihar and the previous year. There was equity of services across castes for all the indicators. Timely capture of data was also ensured compared to paper-based reporting.

conclusionBy virtue of its impact on quality, efficiency and equity of service delivery, health care manpower efficiency and governance, the mHealth inclusion at service provision level can be one of the potential strategy to strengthen the health system.

Indexed as

Developing CountriesAdultChildChild Health ServicesChild, PreschoolContinuity of Patient CareDelivery of Health CareFemaleHumansInfantInfant, NewbornMaternal Health ServicesPregnancyQuality of Health CareTelemedicineEfficiencyHealth systemMaternal and child healthmHealthQuality

Identifiers

PMID27387548
PMCPMC4937606
OpenAlexW2471152413

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.