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Background: Targeted client communication (TCC) using text messages can inform, motivate and remind pregnant and postpartum women of timely utilization of care. The mixed results of the effectiveness of TCC interventions points to the importance of theory based interventions that are co-design with users. The aim of this paper is to describe the planning, development, and evaluation of a theory led TCC intervention, tailored to pregnant and postpartum women and automated from the Palestinian electronic maternal and child health registry.Methods: We used the Health Belief Model to develop interview guides to explore women's perceptions of antenatal care (ANC), with a focus on high-risk pregnancy conditions (anemia, hypertensive disorders in pregnancy, gestational diabetes mellitus, and fetal growth restriction), and untimely ANC attendance, issues predefined by a national expert panel as being of high interest. We performed 18 in-depth interviews with women, and eight with healthcare providers in public primary healthcare clinics in the West Bank and Gaza. Grounding on the results of the in-depth interviews, we used concepts from the Model of Actionable Feedback, social nudging and Enhanced Active Choice to compose the TCC content to be sent as text messages. We assessed the acceptability and understandability of the draft text messages through unstructured interviews with local health promotion experts, healthcare providers, and pregnant women.Results: We found low awareness of the importance of timely attendance to ANC, and the benefits of ANC for pregnancy outcomes. We identified knowledge gaps and beliefs in the domains of low awareness of susceptibility to, and severity of, anemia, hypertension, and diabetes complications in pregnancy. To increase the utilization of ANC and bridge the identified gaps, we iteratively composed actionable text messages with users, using recommended message framing models. We developed algorithms to trigger tailored text messages with higher intensity for women with a higher risk profile documented in the electronic health registry.Conclusions: We developed an optimized TCC intervention underpinned by behavior change theory and concepts, and co-designed with users following an iterative process. The electronic maternal and child health registry can serve as a unique platform for TCC interventions using text messages. [ABSTRACT FROM AUTHOR]

Background: The proportion of women attending four or more antenatal care (ANC) visits is widely used for monitoring, but provides limited information on quality of care. Effective coverage metrics, assessing if ANC interventions are completely delivered, can identify critical gaps in healthcare service delivery. We aimed to measure coverage of at least one screening and effective coverage of ANC interventions in the public health system in the West Bank, Palestine, and to explore associations between infrastructure-related and maternal sociodemographic variables and effective coverage. Methods: We used data from paper-based clinical records of 1369 pregnant women attending ANC in 17 primary healthcare clinics. Infrastructure-related variables were derived from a 2014 national inventory assessment of clinics. Sample size calculations were made to detect effective coverage ranging 40–60% with a 2–3% margin of error, clinics were selected by probability sampling. We calculated inverse probability weighted percentages of: effective coverage of appropriate number and timing of screenings of ANC interventions; and coverage of at least one screening. Results: Coverage of one screening and effective coverage of ANC interventions were notably different for screening for: hypertension (98% vs. 10%); fetal growth abnormalities (66% vs. 6%); anemia (93% vs. 14%); gestational diabetes (93% vs. 34%), and antenatal ultrasound (74% vs. 24%). Clinics with a laboratory and ultrasound generally performed better in terms of effective coverage, and maternal sociodemographic factors had no associations with effective coverage estimates. Only 13% of the women attended ANC visits according to the recommended national schedule, driving effective coverage down. Conclusion: Indicators for ANC monitoring and their definitions can have important consequences for quantifying health system performance and identifying issues with care provision. To achieve more effective coverage in public primary care clinics in the West Bank, efforts should be made to improve care provision according to prescribed guidelines. [ABSTRACT FROM AUTHOR]

Background: In most low- and middle-income settings, national aggregate health data is the most consistently available source for policy-making and international comparisons. In the West Bank, the paper-based health information system with manual aggregations is transitioning to an individual-level data eRegistry for maternal and child health at the point-of-care. The aim of this study was to explore beforehand how routine health information systems indicators for antenatal care can change with the introduction of the eRegistry. Methods: Data were collected from clinical antenatal paper records of pregnancy enrollments for 2015 from 17 primary healthcare clinics, selected by probability sampling from five districts in the West Bank. We used the individual-level data from clinical records to generate routinely reported health systems indicators. We weighted the data to produce population-level estimates, and compared these indicators with aggregate routine health information systems reports. Results: Antenatal anemia screening at 36 weeks was 20% according to the clinical records data, compared to 52% in the routine reports. The clinical records data showed considerably higher incidences of key maternal conditions compared to the routine reports, including fundal height discrepancy (20% vs. 0.01%); Rh-negative blood group (6.8% vs. 1.4%); anemia with hemoglobin<9.5 g/dl (6% vs. 0.6%); and malpresentation at term (1.3% vs. 0.03%). Only about a sixth of cases with these conditions were referred according to guidelines to designated referral clinics. Conclusions: Differences between indicators from the clinical records data and routine health information systems reports can be attributed to human error, inconsistent denominators, and complexities of data processes. Key health systems indicators were prone to underestimations since their registration was dependent on referral of pregnant women. With a transition to individual-level data, as in the eRegistry under implementation, the public health authorities will be able to generate reliable health systems indicators reflective of the population’s health status. [ABSTRACT FROM AUTHOR]

Background: Estimated dates of delivery have important consequences for clinical decisions during pregnancy and labour. The Electronic Maternal and Child Health Registry (MCH eRegistry) in Palestine includes antenatal care data and birth data from hospitals. Our objective was to compare computed best estimates of gestational age in the MCH eRegistry with the gestational ages recorded by health-care providers in hospital delivery units.Methods: We obtained data for pregnant women in the West Bank registered in the MCH eRegistry from Jan 1, 2017 to March 31, 2017. Best estimates of gestational age in the registry are automated and based on a standard pregnancy duration of 280 days and ultrasound-based pregnancy dating before 20 weeks' gestation or the woman's last menstrual period date. Hospital recorded gestational ages are reported by care providers in delivery units and are rounded to the nearest week. We calculated proportions of gestational ages (with 95% CIs) from both sources that fell into the categories of term, very preterm (24-32 weeks' gestation), preterm (33-37 weeks), or post-term (>42 weeks).Findings: 1924 women were included in the study. The median hospital recorded gestational age was 39 weeks (IQR 38-40 weeks) and according to MCH eRegistry estimates was 39 weeks and 5 days (IQR 38 weeks and 1 day to 40 weeks and 5 days). Proportions of very preterm, preterm, and post-term deliveries were higher based on MCH eRegistry estimates than on hospital recorded gestational ages (very preterm 3%, 95% CI 2-4 vs 2%, 1-2; preterm 6%, 5-7 vs 5%, 3-6 ; post-term 6%, 5-7 vs 1%, 1-2).Interpretation: In addition to clinical care, the proportions of term, very preterm, preterm, and post-term births can have implications for public health monitoring. The proportion of deliveries within the normal range of term gestation was calculated to be higher by care providers in delivery units than by MCH eRegistry estimates. Extending the access of hospitals to information from antenatal care in the MCH e-Registry could improve continuity of data and better care for pregnant women.Funding: European Research Council, Research Council of Norway. [ABSTRACT FROM AUTHOR]