An interventional study of Mobile Phone and Cloud-based Electronic Contact and Recording System in Maternal Health, Infant Health and Institutional Delivery, sponsored by Amit Arjyal. Status unknown at 1 site in Nepal. Open to female participants, including healthy volunteers. Per ClinicalTrials.gov, last updated 2023-02-14.
Sponsored by Amit Arjyal · Not applicable, Interventional, and Health services research
The goal of this cluster randomized controlled trial is to study the effect of a mobile-phone based application used by pregnant women on maternal and newborn health indicators. The main objective is to compare the rates of institutional deliveries in the intervention and control arms. Ancillary objectives are to compare the birth-preparedness and complication readiness parameters, severe maternal morbidity rates and neonatal adverse outcomes rates in the two arms. The participants are pregnant women.
In the intervention arm pregnant women will be given a smart mobile phone with an application that they will use to input information related to their health. This information can be shared with their healthcare workers. The healthcare workers will also be able to access all the health-related details of the pregnant women and mothers under their care by accessing this app in their mobile phones and be in touch with their patients through the mobile phone application.
The control arm will adhere to existing practices of pregnant woman and health worker communication without the use of a smart mobile phone with an existing application. Records related to the pregnant woman will be kept in paper-based forms as is the usual norm.
The investigators will compare the intervention arm and the control arm to see if there are differences in the rates of the outcomes.
Improving maternal and newborn health requires innovative approaches that are flexible and cater to the need of the end-user, the patient. In the recent years telecommunication services that have seamlessly entered the lives of the both providers and receivers of health care both in developing and underdeveloped nations and have been a fertile ground for such innovations. There has been rapid growth of the use of mobile phone technologies (mobile health/mHealth) in low and middle income countries (LMICs). These function predominantly in the areas of client education and behavior change communication, registries and vital event tracking, data collection and reporting, provider to provider communication and electronic health records. In our setting as well, there has been successful implementation of the electronic medical records at health facility level and community based institutions and mobile health applications for the community level health providers. The major users of these digital platforms are service providers rather than patients.
However, using electronic medical records that a pregnant woman and/or a mother can fill up at home may provide more opportunities to identify risks and practices that reflect the real situation better than surveys or registries which rely on recall. So far, there is no such intervention in our setting to incorporate the users as the direct data keepers in the health system. Also, there is lack of evidence on the benefit of such applications for maternal and child health. Therefore, we are conducting a cluster randomized controlled trial on user based advanced data systems to improve health in early life in rural Nepal.
The intervention will be evaluated using a cluster randomized controlled trial design. The rationale is that the intervention is applied to the entire community and individual randomization is not feasible due to contamination. A rural municipality ward, the lowest administrative level in Nepal, will be randomized into intervention or control cluster. Because of the nature of the intervention, allocation is not masked. This project will be carried out in three rural municipalities of southern Lalitpur District, namely Konjyosom, Mahankal and Bagmati Rural Municipalities. Eighteen wards or clusters, nine(9) in the intervention arm and nine(9) in the control arm are included.
The investigators will implement the mobile-phone based system in the intervention clusters while non-intervention clusters will have the currently existing health care data management and patient contact system.
In the intervention arm, a data-system with mobile phone-based application will be deployed. The application will be used by pregnant women to obtain useful information related to their pregnancy and also enter vital information related to their health. The database will be accessible to healthcare providers at various levels of our health system such as health posts, and district or municipal level hospitals. The healthcare providers will also be able to access the data and enter clinical information when the pregnant women go to the health centre. The application will also be used during the time of labour and after delivery to record information about the post-partum state and infancy of the newborn child.
The investigators will carry out a prospective follow-up in which all institutional/home deliveries, birth preparedness and complication readiness parameters, severe maternal morbidity, neonatal adverse outcomes, stillbirths, neonatal and later infant deaths and deaths of women in the study population are recorded through interviews conducted during the recruitment, at 6-9 months of pregnancy, right after delivery and at 42 days after delivery.
This study is led by Patan Academy of Health Sciences, Lalitpur, Nepal in collaboration with Purbanchal University, Lalitpur, Nepal. The investigators have received a grant from University Grants Commission, Nepal for this project. The investigators have signed a Memorandum of Understanding with the three rural municipalities of southern Lalitpur namely, Bagmati, Konjyosom and Mahankal Rural Municipalities and plan to work in close liaison with the Ministry of Health, Department of Health Services, Health Office for Lalitpur District and Government Integrated Data centre (GIDC) to undertake this project.
This is the only study on the registry with Amit Arjyal as lead sponsor.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
In this arm pregnant women will be given a smart mobile-phone with an application installed which will have their detailed health-related information. They will be able to use this application to input their daily symptoms. This will also contain results of examinations or investigations that they have undergone in a clinic. All this information will be stored in a cloud and the healthcare worker at the local health post will also be able to access this information in their mobile phone and keep track of the pregnant women under their care. In the event of a concerning symptom, the health worker will be flagged. The health coordinators in the rural municipality will also be able to keep track of the pregnant women in their area through a cloud-based database.
Other: Mobile Phone and Cloud-based Electronic Contact and Recording System
Pregnant women will visit the health posts or hospitals for antenatal checks routinely as advised. Their records will be kept in paper-based forms and registers. They will not be tracked regularly by their healthcare provider by electronic means. Their daily symptoms will not be recorded anywhere. They will still be able to contact their healthcare providers or visit the health centers if necessary. They will not have a personal electronic health record. No one will keep active track of the pregnant women through electronic means.
A mobile phone application has been developed which is intended to be used by pregnant women and their healthcare workers. A pregnant woman can get registered in this app and enter information and data related to their health and current pregnancy. Their health worker at their health post can access this information on their mobile phone too. The pregnant woman can also input her daily symptom on this app. She can also input and/or access information on examination and tests that have been carried out. If a concerning symptom or event has been entered by a user in the app, the health worker will be notified through this app. The health worker can also track the pregnant women under their care through this application. A cloud-based database of pregnant women will have the details of all the pregnant women in a given ward or rural municipality. Health coordinators in the municipality will be able to access the database for their municipality and track the pregnant women, if needed.
Also known as: Mobile Phone Application
Institutional Delivery Rate
Delivery at a birthing center, health post, primary health care center, or any hospital
Time frame: At the time of delivery
Birth Preparedness and Complication Readiness Index Score
Birth preparedness and complication readiness index score will be used. It is based on JHPIEGO manual on monitoring birth preparedness and complication readiness- tools and indicators for maternal and newborn health. This is based on a set of indicators for monitoring safe motherhood. The final score is the average of thirteen(13) items in three(3) domains, namely, knowledge of key danger signs around pregnancy, service use and planning actions- both intention and behavior, and knowledge of community resources. A score will be calculated for each item as a percentage of the respondents who meet the item criteria. The final score is the mean of the scores in each of the 13 items. The score can range from 0% to 100%, higher score indicating better birth preparedness and complication readiness. The scores will be compared between the intervention and control arms.
Time frame: Upto 42 days after delivery
Severe Maternal Morbidity (SMM) Rate
Severe Maternal Morbidity criteria will be as defined by the American College of Obstetricians and Gynecologists (ACOG) criteria: 1. The occurrence of at least one of 21 SMM indicators: Acute Myocardial Infarction, Aneurysm, Acute renal failure, Adult respiratory distress syndrome, Amniotic fluid embolism, Cardiac arrest/ ventricular fibrillation, Conversion of cardiac rhythm, Disseminated Intravascular coagulation, Eclampsia, Heart Failure/Arrest during surgery or procedure, Puerperal cerebrovascular disorders, Pulmonary edema/ Acute heart failure, Severe anesthesia complication, Sepsis, Shock, Sickle cell disease with crisis, Air and thrombotic embolism, Blood product transfusion, Hysterectomy, Temporary tracheostomy and Ventilation. 2. Intensive care unit (ICU) admission 3. Prolonged length of postnatal hospital stay (\> 48 hours and \>96 hours for vaginal delivery and cesarean section respectively) 4. Transfusion of \>/= 4 units of packed blood cells 5. Hospital readmission
Time frame: Upto 42 days after delivery
Neonatal Adverse Outcome (NAO) Rate
NAO will be defined as the occurrence of at least one of 28 diagnostic and procedure components: Diagnosis: Gestational age \< 32 weeks, birthweight \<1500 grams, death within 28 days of birth, Birth trauma, Cerebral conditions like: Intraventricular haemorrhage, Hypoxic-ischemic encephalopathy, seizures, or other cerebral diagnosis, Respiratory conditions like: Pneumonia, Respiratory distress syndrome, Bronchopulmonary dysplasia and Other respiratory diagnosis, Sepsis/septicaemia, Necrotising enterocolitis Procedure: Resuscitation or intubation recorded on birth record, Transferred to higher center within 24 hours, 2-999 hours of mechanical ventilation, Invasive ventilation procedure, Non-invasive ventilation procedure, Resuscitation procedure, Arterial/central catheter procedure, Transfusion of blood or blood products, Intravenous fluid procedure, Surgical procedures: Abdominal, cardiac, thoracic and urinary system
Time frame: Upto 42 days after delivery
Newborn Mortality Indicators
Number of still births, early and late neonatal mortality, or infant mortality
Time frame: Upto 42 days after delivery
Maternal Mortality Indicator
Number of maternal deaths
Time frame: Upto 42 days after delivery
Plan to share: No — When the dataset is available we will decide in what form we will share it with other researcher after determining their objective
This study is status unknown, as verified in Feb 2023. You cannot join it, but the record below documents what was studied.
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