Effectiveness of mobile technology and utilization of maternal and neonatal healthcare in low and middle-income countries (LMICs): a systematic review
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SUBMITTER: De P
PROVIDER: S-EPMC10714653 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundThere is no consistent operationalization of effective coverage (EC) across studies. Therefore, this scoping review synthesized evidence on the definitions and measurement approaches, outcomes reported, and the factors that are associated with variations in quality-adjusted EC estimates of maternal and neonatal healthcare services in low- and middle-income countries.MethodsArticle search was conducted using PubMed, Embase, Google Scholar, and other databases. Then, title, abstract, and full text screenings for inclusion were performed by two authors independently and disagreements were resolved through discussion. In case of duplication, the full-text published articles were retained, and the results are presented using the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for Scoping Reviews checklist as a guide.ResultsOverall, 36 articles were included in this scoping review. In most articles, EC has been defined from the perspectives of people in need utilizing healthcare services in well-equipped health facilities and from actual receipt of quality services. In addition, usage, instead of need, has been used as a domain in estimating EC in some instances. Effective coverage ranged from 0% for different services including for post-partum care, to 84% for antenatal care. Moreover, different socio-demographic factors including wealth index, education, and residence are found to have an association with variations in EC of maternal and neonatal healthcare services with the wealthiest, most educated, and those living in urban areas having higher estimates. From the supply side, numerous factors, particularly health facility capacity-related constraints, have been reported to be associated with low EC of those services.ConclusionsThe variability in the definition and measurement approaches of EC across studies emphasizes the need for standardization for better comparison in future research. We recommend that quality-adjusted EC be defined in two ways: intervention-specific service delivery EC and general service delivery EC. In addition, disparities in EC are observed among women with different socioeconomic status including educational level and wealth index. Organizational capacity constraints and other health system and societal factors also contributed to variations in EC.
| S-EPMC11654249 | biostudies-literature
Project description:Purpose of Review:Surveillance of communicable diseases is essential in all countries to prevent and control infections, to detect outbreaks and also to see the effects of interventions. The data should be reliable, and collection, analysis and feedback as well as the action based on this data should be fast. In this article, author discusses the limitations the Low Middle income Countries (LMICs) have in implementing disease surveillance and some suggestions for improvement. Recent Findings:Integrated Disease Surveillance and Response (IDSR) has been implemented successfully through most of the countries in Africa though they belong to low or LMIC. Major barriers for surveillance of Healthcare Associated Infections in LMICs are non-availability of adequate number of healthcare personnel such as infection control personnel as well as not having an integrated healthcare system with an effective data flow. For some infections, not having proper diagnostic facilities is a major obstacle. An important capacity limitation in clinical laboratories of LMICs is identification of antimicrobial resistant organisms as well as other pathogens to species level. This affects the surveillance of infections and antimicrobial resistance. Summary:Use of modern technology, capacity building including the human resources as well as the laboratory capacity in healthcare setting, improving data communication methods, are the main recommendations made. Education and training of healthcare staff as well as educating the general public to change the attitudes of people is another aspect that we need to concentrate.
| S-EPMC7453076 | biostudies-literature
Project description:Currently, more than five times more people live in low- and middle-income countries (LMICs) than in high-income countries (HICs). As such, the downward trend in cardiac surgical needs in HICs reflects only the situation of one sixth of the world population while the vast majority living in LMICs has still no or limited access to life saving heart operations. In these countries, rheumatic heart disease (RHD) still accounts for a significant proportion of cardiac surgical needs. In low- and lower-middle income countries it remains the single most common cardiovascular disease in young adult and adolescent patients in need of heart surgery outweighing other indications such as congenital cardiac defects almost 4-fold. Compared to HICs with their predominance of calcific aortic stenosis in the elderly mitral valve surgery is required in >90% of the largely young patients with RHD in low-income countries (LICs) and still in 70% of the often middle aged patients in middle-income countries (MICs). Although recent government initiatives in LICs led to the establishment of local, independent cardiac surgical services gradually replacing fly-in missions, these centers still only cover less than 2% of the needs of their populations. In MICs, cardiac surgical needs continually grow with the emergence of degenerative diseases. As such, in spite of the concomitant growth of cardiac surgical capacity, significantly less than half the estimated patients in need have access. Capacities in LICs range from 0.5 to 7 cardiac operations/million population; 100-481/million in MICs and >1,200/million in HICs such as the USA and Germany. While a new level of awareness of the scope and magnitude of the problem has begun to emerge in LICs and the establishment of local cardiac surgical capacity has given rise to a glimpse of hope, the challenges of expanding these fledgling services to a significant proportion of the population still seem insurmountable. Challenges in MICs are on the other hand the widening gap between private cardiac medicine for the affluent few and overwhelmed public services for the many and the rural urban divide with the underappreciation of the ongoing dominance of RHD in the rural and indigent population on the other. Overshadowing all LMICs is the low level of valve-repair skills associated with insufficient cardiac surgical capacity and the unavailability of suitable replacement valves which address the young age of the patients and the difficulties of anticoagulation in a socioeconomic environment distinctly different from the elderly patients of HICs.
| S-EPMC7225428 | biostudies-literature
Project description:The spread of machine learning models, coupled with by the growing adoption of electronic health records (EHRs), has opened the door for developing clinical decision support systems. However, despite the great promise of machine learning for healthcare in low-middle-income countries (LMICs), many data-specific limitations, such as the small size and irregular sampling, hinder the progress in such applications. Recently, deep generative models have been proposed to generate realistic-looking synthetic data, including EHRs, by learning the underlying data distribution without compromising patient privacy. In this study, we first use a deep generative model to generate synthetic data based on a small dataset (364 patients) from a LMIC setting. Next, we use synthetic data to build models that predict the onset of hospital-acquired infections based on minimal information collected at patient ICU admission. The performance of the diagnostic model trained on the synthetic data outperformed models trained on the original and oversampled data using techniques such as SMOTE. We also experiment with varying the size of the synthetic data and observe the impact on the performance and interpretability of the models. Our results show the promise of using deep generative models in enabling healthcare data owners to develop and validate models that serve their needs and applications, despite limitations in dataset size.
| S-EPMC10295936 | biostudies-literature
Project description:Early identification of high-risk pregnancies can reduce global neonatal mortality rate. Using the most recent Demographic and Health Surveys from 56 low- and middle-income countries, we examined the proportion of mothers with history of neonatal deaths. Logistic regression models were used to assess the association between maternal history of neonatal death and subsequent neonatal mortality. The adjusted models controlled for socioeconomic, child, and pregnancy-related factors. Country-specific analyses were performed to assess heterogeneity in this association across countries. Among the 437,049 live births included in the study, 6910 resulted in neonatal deaths. In general, 22.4% (1549) occurred to mothers with previous history of neonatal death; at the country-level, this proportion ranged from 1.2% (95% confidence interval [CI] 0.0, 2.6) in Dominican Republic to 38.1% (95% CI 26.0, 50.1) in Niger. Maternal history of neonatal death was significantly associated with subsequent neonatal death in both the pooled and the subgroup analyses. In the fully adjusted model, history of neonatal death was associated with 2.1 (95% CI 1.9, 2.4) times higher odds of subsequent neonatal mortality in the pooled analysis. We observed large variation in the associations across countries ranging from fully adjusted odds ratio (FAOR) of 0.4 (95% CI 0.0, 4.0) in Dominican Republic to 16.1 (95% CI 3.6, 42.0) in South Africa. Our study suggests that maternal history of neonatal death could be an effective early identifier of high-risk pregnancies in resource-poor countries. However, country-specific contexts must be considered in national policy discussions.
| S-EPMC8497561 | biostudies-literature
Project description:Background: Pregnant women and neonates represent one of the most vulnerable groups, especially in low- and middle-income countries (LMICs). A recent analysis reported that most vaccine pharmacovigilance systems in LMICs consist of spontaneous (passive) adverse event reporting. Thus, LMICs need effective active surveillance approaches, such as pregnancy registries. We intend to identify currently active maternal and neonatal data collection systems in LMICs, with the potential to inform active safety electronic surveillance for novel vaccines using standardized definitions. Methods: A scoping review will be conducted based on established methodology. Multiple databases of indexed and grey literature will be searched with a specific focus on existing electronic and paper-electronic systems in LMICs that collect continuous, prospective, and individual-level data from antenatal care, delivery, neonatal care (up to 28 days), and postpartum (up to 42 days) at the facility and community level, at the national and district level, and at large hospitals. Also, experts will be contacted to identify unpublished information on relevant data collection systems. General and specific descriptions of Health Information Systems (HIS) extracted from the different sources will be combined and duplicated HIS will be removed, producing a list of unique statements. We will present a final list of Maternal, Newborn, and Child Health systems considered flexible enough to be updated with necessary improvements to detect, assess and respond to safety concerns during the introduction of vaccines and other maternal health interventions. Selected experts will participate in an in-person consultation meeting to select up to three systems to be further explored in situ. Results and knowledge gaps will be synthesized after expert consultation.
| S-EPMC7199220 | biostudies-literature
Project description:ObjectiveTo quantify maternal, fetal and neonatal mortality in low- and middle-income countries, to identify when deaths occur and to identify relationships between maternal deaths and stillbirths and neonatal deaths.MethodsA prospective study of pregnancy outcomes was performed in 106 communities at seven sites in Argentina, Guatemala, India, Kenya, Pakistan and Zambia. Pregnant women were enrolled and followed until six weeks postpartum.FindingsBetween 2010 and 2012, 214,070 of 220,235 enrolled women (97.2%) completed follow-up. The maternal mortality ratio was 168 per 100,000 live births, ranging from 69 per 100,000 in Argentina to 316 per 100,000 in Pakistan. Overall, 29% (98/336) of maternal deaths occurred around the time of delivery: most were attributed to haemorrhage (86/336), pre-eclampsia or eclampsia (55/336) or sepsis (39/336). Around 70% (4349/6213) of stillbirths were probably intrapartum; 34% (1804/5230) of neonates died on the day of delivery and 14% (755/5230) died the day after. Stillbirths were more common in women who died than in those alive six weeks postpartum (risk ratio, RR: 9.48; 95% confidence interval, CI: 7.97-11.27), as were perinatal deaths (RR: 4.30; 95% CI: 3.26-5.67) and 7-day (RR: 3.94; 95% CI: 2.74-5.65) and 28-day neonatal deaths (RR: 7.36; 95% CI: 5.54-9.77).ConclusionMost maternal, fetal and neonatal deaths occurred at or around delivery and were attributed to preventable causes. Maternal death increased the risk of perinatal and neonatal death. Improving obstetric and neonatal care around the time of birth offers the greatest chance of reducing mortality.
| S-EPMC4147405 | biostudies-literature
Project description:BackgroundOligohydramnios is a condition of abnormally low amniotic fluid volume that has been associated with poor pregnancy outcomes. To date, the prevalence of this condition and its outcomes has not been well described in low and low-middle income countries (LMIC) where ultrasound use to diagnose this condition in pregnancy is limited. As part of a prospective trial of ultrasound at antenatal care in LMICs, we sought to evaluate the incidence of and the adverse maternal, fetal and neonatal outcomes associated with oligohydramnios.MethodsWe included data in this report from all pregnant women in community settings in Guatemala, Pakistan, Zambia and the Democratic Republic of Congo (DRC) who received a third trimester ultrasound as part of the First Look Study, a randomized trial to assess the value of ultrasound at antenatal care. Using these data, we conducted a planned secondary analysis to compare pregnancy outcomes of women with to those without oligohydramnios. Oligohydramnios was defined as measurement of an Amniotic Fluid Index less than 5 cm in at least one ultrasound in the third trimester. The outcomes assessed included maternal morbidity and fetal and neonatal mortality, preterm birth and low-birthweight. We used pairwise site comparisons with Tukey-Kramer adjustment and multivariable logistic models using general estimating equations to account for the correlation of outcomes within cluster.ResultsOf 12,940 women enrolled in the clusters in Guatemala, Pakistan, Zambia and the DRC in the First Look Study who had a third trimester ultrasound examination, 87 women were diagnosed with oligohydramnios, equivalent to 0.7% of those studied. Prevalence of detected oligohydramnios varied among study sites; from the lowest of 0.2% in Zambia and the DRC to the highest of 1.5% in Pakistan. Women diagnosed with oligohydramnios had higher rates of hemorrhage, fetal malposition, and cesarean delivery than women without oligohydramnios. We also found unfavorable fetal and neonatal outcomes associated with oligohydramnios including stillbirths (OR 5.16, 95%CI 2.07, 12.85), neonatal deaths < 28 days (OR 3.18, 95% CI 1.18, 8.57), low birth weight (OR 2.10, 95% CI 1.44, 3.07) and preterm births (OR 2.73, 95%CI 1.76, 4.23). The mean birth weight was 162 g less (95% CI -288.6, - 35.9) with oligohydramnios.ConclusionsOligohydramnos was associated with worse neonatal, fetal and maternal outcomes in LMIC. Further research is needed to assess effective interventions to diagnose and ultimately to reduce poor outcomes in these settings.Trial registrationNCT01990625.
| S-EPMC6993413 | biostudies-literature
Project description: Not available
| S-EPMC7607603 | biostudies-literature
Project description:AimThe aims of the study were to synthesize the role of technology-based healthcare interventions (TBIs) and to identify the most effective interventions for the best functional maternal and child health (MCH) outcomes among low-risk pregnant women in low- and middle-income countries (LMICs).DesignA systematic review and network meta-analysis (NMA).MethodsWe will perform a comprehensive search in electronic databases and other resources to identify relevant randomized controlled trials. Two reviewers will independently perform study selection, data extraction and quality assessment. Our primary outcomes include proportion of recommended antenatal care visits, skilled delivery care, postnatal care visits and exclusive breastfeeding practices. We will use pairwise random-effects meta-analysis and NMAs to estimate direct, indirect and relative effects using the relevant intervention classifications for each outcome separately. We plan to assess hierarchy of interventions, statistical inconsistency and certainty of evidence.ResultsThis review will compare the effectiveness of different form of TBIs on a comprehensive range of MCH outcomes and will provide the outcome-specific reliable evidence of the most effective interventions on improving MCH in LMICs. The review findings will guide researchers, stakeholders or policymakers on the potential use of TBIs in the given contexts that could achieve the best functional MCH outcomes in LMICs.
| S-EPMC9748107 | biostudies-literature