Previously, the overall process (from data collection to reporting) of the LAM system was mostly done by hand, particularly in the data collection and data entry stages. With Indonesia’s high rate of maternal and infant mortality, improved care for pregnant women and newborns is a key area of concern. To accelerate the LAM feature, a tracking mechanism is needed within the existing government program, PWS KIA (Local Area Monitoring or LAM). It is expected that such modification would help making informed and evidence-based decisions for Maternal, Newborn and Child Health (MNCH) planning. LAMAT, an extension of the LAM system, offers this tracking solution.
The additional “active monitoring” or tracking function of LAMAT provides an innovative operation process and automated solutions for data analysis and reporting. LAMAT stimulates a tight partnership between multi-stakeholders-Dukun Bayi, Kader, Bidan Desa, and Bidan Koordinator to stimulate referrals to the Bidan Desa, for mapping and registering women of child-bearing age. The reports generated from the software provide information about the antenatal care, obstetric complications, and the nutritional status of pregnant women and newborns in a certain area - information needed by implementers to make informed decisions for precise planning.
LAMAT has 13 performance indicators to measure the progress and impact of program implementation in an area annually. These indicators include access to the first and the fourth antenatal visits (K1, K4), delivery by skilled birth attendants (PN), coverage of newborn services by skilled health workers (KF3), first neonatal services (KN1), 0-28 days neonatal services (complete KN), detection for risk factors and complications by the community through referral services, handling of obstetric complications (PK) and neonatal complications, services for babies 29 days-12 months and children under five (12-59 months), coverage of health services for children under five by MTBS standard, and family planning services (contraceptive prevalence rate).