Maternal HealthCITHNCT05697822
Using Advanced Data Systems to Improve Health in Early Life in Rural Nepal
A study testing Mobile Phone and Cloud-based Electronic Contact and Recording System in people with Maternal Health and Infant Health, run by Amit Arjyal at 1 site in Nepal.
Trial summary
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. Read more about this study
- Who is it for?
- Any age, women onlyHealthy volunteers can take part
- Conditions the study is for
- Maternal Health, Infant Health, Institutional Delivery
- What is being tested?
- Mobile Phone and Cloud-based Electronic Contact and Recording System
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 360 participants
- Where
- 1 siteNepal
- Study dates
- Mar 2023to Dec 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- Women only
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- Pregnant with less than 20 weeks of gestation
- Usual resident of the study ward at the time of enrollment (A woman is considered a usual resident if the house she normally lives is in, is in that ward)
- Provides informed written consent
Who cannot join
- Temporary resident of the ward
- Cannot read and write
- Cannot use a mobile phone
- Has any disability, such as blindness, that prevents the use of mobile phone
Trial locations and contacts
1 site in 1 country.
Nepal1 site
Patan Academy of Health Sciences
Lalitpur, Bagmati
Amit Arjyal, MBBS, DPhil
About this study
Official title: The Effect of a Patient-involved Mobile Phone and Cloud-based Electronic Contact and Recording System on Institutional Deliveries and Other Maternal and Infant Health Outcomes in Rural Nepal: A Cluster Randomized Controlled Trial
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.
Read more
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.
Read the detailed description
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.
- Conditions
- Maternal Health, Infant Health, Institutional Delivery, Birth Preparedness and Complication Readiness, Severe Maternal Morbidity, Neonatal Adverse Outcome
- Being tested
- Mobile Phone and Cloud-based Electronic Contact and Recording System
- Keywords
- electronic health database, maternal health, infant health, institutional delivery, birth preparedness and complication readiness, severe maternal morbidity, neonatal adverse outcome, mobile health, mHealth
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Mobile Phone and Cloud-based Electronic Contact and Recording SystemOther
Also called Mobile Phone Application
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.
| Study group | Role | What they receive |
|---|---|---|
| Mobile Phone and Cloud-based Electronic Contact and Recording System | Experimental | 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. Receives: Other: Mobile Phone and Cloud-based Electronic Contact and Recording System |
| Usual Standard of Care Arm | No intervention | 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Institutional Delivery Rate
Delivery at a birthing center, health post, primary health care center, or any hospital
Measured: At the time of delivery
Secondary outcomes (5)
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.
Measured: 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:
- 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.
- Intensive care unit (ICU) admission
- Prolonged length of postnatal hospital stay (> 48 hours and >96 hours for vaginal delivery and cesarean section respectively)
- Transfusion of >/= 4 units of packed blood cells
- Hospital readmission
Measured: 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
Measured: Upto 42 days after delivery
Newborn Mortality Indicators
Number of still births, early and late neonatal mortality, or infant mortality
Measured: Upto 42 days after delivery
Maternal Mortality Indicator
Number of maternal deaths
Measured: Upto 42 days after delivery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jan 2023
- Study startMar 2023 (estimated)
- Primary completionJun 2024 (estimated)
- Study completionDec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (8)Papers the sponsor has linked to this study.
- Other trials for Maternal HealthStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 360 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Amit Arjyal
- Sponsor type
- University, hospital or other
- Collaborators
- Bagmati Rural Municipality, Lalitpur, Nepal, Konjyosom Rural Municipality, Lalitpur, Nepal, Mahankal Rural Municipality, Lalitpur, Nepal, School of Health Sciences, Purbanchal University, Nepal
- Responsible party
- Sponsor-investigator, Amit Arjyal, Patan Academy of Health Sciences
- Investigators
- Ranjan P Devbhandari, MBBS,PhD, Principal investigator, Patan Academy of Health Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05697822
- Sponsor's protocol ID
- 2-2022
- Other IDs
- CTSR - 77/78 - 4
- Acronym
- CITH
- Status last verified
- Feb 2023
- First submitted
- 10 Jan 2023
- Last updated
- 14 Feb 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: When the dataset is available we will decide in what form we will share it with other researcher after determining their objective
Publications
Del Barco R, editor. JHPIEGO Monitoring Birth Preparedness and Complication Readiness, Tools and Indicators for Maternal and Newborn Health. Baltimore (USA): JHPIEGO; 2004. Available from: https://pdf.usaid.gov/pdf_docs/Pnada619.pdf
Main EK, Abreo A, McNulty J, Gilbert W, McNally C, Poeltler D, Lanner-Cusin K, Fenton D, Gipps T, Melsop K, Greene N, Gould JB, Kilpatrick S. Measuring severe maternal morbidity: validation of potential measures. Am J Obstet Gynecol. 2016 May;214(5):643.e1-643.e10. doi: 10.1016/j.ajog.2015.11.004. Epub 2015 Nov 12.
PubMed 26582168Callaghan WM, Creanga AA, Kuklina EV. Severe maternal morbidity among delivery and postpartum hospitalizations in the United States. Obstet Gynecol. 2012 Nov;120(5):1029-36. doi: 10.1097/aog.0b013e31826d60c5.
PubMed 23090519Nam JY. Comparison of global indicators for severe maternal morbidity among South Korean women who delivered from 2003 to 2018: a population-based retrospective cohort study. Reprod Health. 2022 Aug 13;19(1):177. doi: 10.1186/s12978-022-01482-y.
PubMed 35964088Todd S, Bowen J, Ibiebele I, Patterson J, Torvaldsen S, Ford F, Nippita M, Morris J, Randall D. A composite neonatal adverse outcome indicator using population-based data: an update. Int J Popul Data Sci. 2020 Aug 12;5(1):1337. doi: 10.23889/ijpds.v5i1.1337.
PubMed 33644407Huda TM, Chowdhury M, El Arifeen S, Dibley MJ. Individual and community level factors associated with health facility delivery: A cross sectional multilevel analysis in Bangladesh. PLoS One. 2019 Feb 13;14(2):e0211113. doi: 10.1371/journal.pone.0211113. eCollection 2019.
PubMed 30759099Neupane B, Rijal S, Gc S, Basnet TB. A Multilevel Analysis to Determine the Factors Associated with Institutional Delivery in Nepal: Further Analysis of Nepal Demographic and Health Survey 2016. Health Serv Insights. 2021 Jun 14;14:11786329211024810. doi: 10.1177/11786329211024810. eCollection 2021.
PubMed 34177270Hemming K, Girling AJ, Sitch AJ, Marsh J, Lilford RJ. Sample size calculations for cluster randomised controlled trials with a fixed number of clusters. BMC Med Res Methodol. 2011 Jun 30;11:102. doi: 10.1186/1471-2288-11-102.
PubMed 21718530
Study at a glance
From the registry record, last updated by the sponsor on 14 Feb 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Effect of a Patient-involved Mobile Phone and Cloud-based Electronic Contact and Recording System on Institutional Deliveries and Other Maternal and Infant Health Outcomes in Rural Nepal: A Cluster Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT05697822
- Acronym / sponsor ID
- CITH / 2-2022
- Conditions
- Maternal Health, Infant Health, Institutional Delivery, Birth Preparedness and Complication Readiness, Severe Maternal Morbidity, Neonatal Adverse Outcome
- Keywords
- electronic health database, maternal health, infant health, institutional delivery, birth preparedness and complication readiness, severe maternal morbidity, neonatal adverse outcome, mobile health
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 360 participants (estimated)
- Lead sponsor
- Amit ArjyalUniversity, hospital or other
- Collaborators
- Bagmati Rural Municipality, Lalitpur, Nepal, Konjyosom Rural Municipality, Lalitpur, Nepal, Mahankal Rural Municipality, Lalitpur, Nepal, School of Health Sciences, Purbanchal University, Nepal
- Study start
- Mar 2023 (estimated)
- Primary completion
- Jun 2024 (estimated)
- Study completion
- Dec 2024 (estimated)
- First posted
- 26 Jan 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Mobile Phone and Cloud-based Electronic Contact and Recording System | Experimental | Other: Mobile Phone and Cloud-based Electronic Contact and Recording SystemIn 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. |
| Usual Standard of Care Arm | No intervention | –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. |
Who may qualify
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (3 listed)
- Pregnant with less than 20 weeks of gestation
- Usual resident of the study ward at the time of enrollment (A woman is considered a usual resident if the house she normally lives is in, is in that ward)
- Provides informed written consent
Key exclusion criteria (4 listed)
- Temporary resident of the ward
- Cannot read and write
- Cannot use a mobile phone
- Has any disability, such as blindness, that prevents the use of mobile phone
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Mobile Phone and Cloud-based Electronic Contact and Recording SystemAlso: Mobile Phone ApplicationA 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. | Other | Mobile Phone and Cloud-based Electronic Contact and Recording System |
Primary outcome
Institutional Delivery Rate
Time frame: At the time of delivery
Delivery at a birthing center, health post, primary health care center, or any hospital
5 secondary outcomes
Birth Preparedness and Complication Readiness Index Score
Time frame: Upto 42 days after delivery
Severe Maternal Morbidity (SMM) Rate
Time frame: Upto 42 days after delivery
Neonatal Adverse Outcome (NAO) Rate
Time frame: Upto 42 days after delivery
Newborn Mortality Indicators
Time frame: Upto 42 days after delivery
Maternal Mortality Indicator
Time frame: Upto 42 days after delivery
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 Feb 2023.
- BackgroundDel Barco R, editor. JHPIEGO Monitoring Birth Preparedness and Complication Readiness, Tools and Indicators for Maternal and Newborn Health. Baltimore (USA): JHPIEGO; 2004. Available from: https://pdf.usaid.gov/pdf_docs/Pnada619.pdf
- Background: PubMed 26582168Main EK, Abreo A, McNulty J, Gilbert W, McNally C, Poeltler D, Lanner-Cusin K, Fenton D, Gipps T, Melsop K, Greene N, Gould JB, Kilpatrick S. Measuring severe maternal morbidity: validation of potential measures. Am J Obstet Gynecol. 2016 May;214(5):643.e1-643.e10. doi: 10.1016/j.ajog.2015.11.004. Epub 2015 Nov 12.
- Background: PubMed 23090519Callaghan WM, Creanga AA, Kuklina EV. Severe maternal morbidity among delivery and postpartum hospitalizations in the United States. Obstet Gynecol. 2012 Nov;120(5):1029-36. doi: 10.1097/aog.0b013e31826d60c5.
- Background: PubMed 35964088Nam JY. Comparison of global indicators for severe maternal morbidity among South Korean women who delivered from 2003 to 2018: a population-based retrospective cohort study. Reprod Health. 2022 Aug 13;19(1):177. doi: 10.1186/s12978-022-01482-y.
- Background: PubMed 33644407Todd S, Bowen J, Ibiebele I, Patterson J, Torvaldsen S, Ford F, Nippita M, Morris J, Randall D. A composite neonatal adverse outcome indicator using population-based data: an update. Int J Popul Data Sci. 2020 Aug 12;5(1):1337. doi: 10.23889/ijpds.v5i1.1337.
- Background: PubMed 30759099Huda TM, Chowdhury M, El Arifeen S, Dibley MJ. Individual and community level factors associated with health facility delivery: A cross sectional multilevel analysis in Bangladesh. PLoS One. 2019 Feb 13;14(2):e0211113. doi: 10.1371/journal.pone.0211113. eCollection 2019.
- Background: PubMed 34177270Neupane B, Rijal S, Gc S, Basnet TB. A Multilevel Analysis to Determine the Factors Associated with Institutional Delivery in Nepal: Further Analysis of Nepal Demographic and Health Survey 2016. Health Serv Insights. 2021 Jun 14;14:11786329211024810. doi: 10.1177/11786329211024810. eCollection 2021.
- Background: PubMed 21718530Hemming K, Girling AJ, Sitch AJ, Marsh J, Lilford RJ. Sample size calculations for cluster randomised controlled trials with a fixed number of clusters. BMC Med Res Methodol. 2011 Jun 30;11:102. doi: 10.1186/1471-2288-11-102.
- Individual participant dataSharing planned: No. When the dataset is available we will decide in what form we will share it with other researcher after determining their objective
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ranjan P Devbhandari, MBBS,PhD principal investigator
Patan Academy of Health Sciences
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Mobile Phone and Cloud-based Electronic Contact and Recording System in people with Maternal Health and Infant Health, run by Amit Arjyal at 1 site in Nepal.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 14 Feb 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Nepal. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Amit Arjyal, MBBS, DPhil (+9779864478329, amitarjyal@pahs.edu.np), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Institutional Delivery Rate (time frame: At the time of delivery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05697822, which also lists 8 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 14 Feb 2023.