Babul Bezbaruah1, Amrit Krishna Bora2, Krishnaram Bora3, Shakuntala Chhabra4, Saswati S Choudhury5, Arup Choudhury6, Dipika Deka7, Gitanjali Deka8, Vijay Anand Ismavel9, Swapna D Kakoty10, Roshine M Koshy9, Pramod Kumar4, Pranabika Mahanta11, Robin Medhi10, Pranoy Nath1, Anjali Rani12, Indrani Roy13, Usha Sarma8, Carolin Solomi V9, Ratna Kanta Talukdar5, Farzana Zahir14, Manisha Nair15, Michael Hill16, Nimmi Kansal17, Reena Nakra17, Colin Baigent18, Marian Knight15, Jenny J Kurinczuk15. 1. Silchar Medical College and Hospital (SMCH), Ghungoor Road, Masimpur, Assam, 788014, India. 2. Mahendra Mohan Choudhury Hospital, Panbazar, Guwahati, Assam, 781001, India. 3. Nagaon Bhogeswari Phukanani Civil Hospital, Haibargaon, Daccapatty, Nagaon, Assam, 782001, India. 4. Mahatma Gandhi Institute of Medical Sciences, Sevagram, Maharashtra, 442102, India. 5. Gauhati Medical College and Hospital (GMCH), Bhangagarh, Guwahati, Assam, 781032, India. 6. Dhubri Civil Hospital, Jhagrarpar, Dhubri, Assam, 783324, India. 7. Srimanta Sankaradeva University of Health Sciences, Narkashur Hilltop, Bhangagarh, Assam, 781032, India. 8. Tezpur Medical College, NH 15, Tezpur, Assam, 784153, India. 9. Makunda Christian Leprosy and General Hospital, Bazaricherra, Karimganj, Assam, 788727, India. 10. Fakhruddin Ali Ahmed Medical College and Hospital (FAAMCH), Barpeta-Hospital-Jania Rd, Joti Gaon, Assam, 781301, India. 11. Jorhat Medical College and Hospital, Kushal Konwar Path, Barbheta, Jorhat, Assam, 785001, India. 12. Institute of Medical Sciences, Banaras Hindu University, Aurobindo Colony, Banaras Hindu University Campus, Varanasi, Uttar Pradesh, 221005, India. 13. Nazareth Hospital, Arbuthnot Rd, Nongkynrih, Laitumkhrah, Shillong, Meghalaya, 793003, India. 14. Assam Medical College (AMC), Barbari, Dibrugarh, Assam, 786002, India. 15. National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Headington, Oxford, Oxfordshire, OX3 7LF, UK. 16. NDPH Wolfson Laboratories, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, Oxfordshire, OX3 7LF, UK. 17. National Reference Laboratory, Dr Lal PathLabs, B7 Rd, Block E, Sector 18, Rohini, New Delhi, Delhi, 110085, India. 18. MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxfordshire, OX3 7LF, UK.
Abstract
Background: Maternal and perinatal Health Research collaboration, India (MaatHRI) is a research platform that aims to improve evidence-based pregnancy care and outcomes for mothers and babies in India, a country with the second highest burden of maternal and perinatal deaths. The objective of this paper is to describe the methods used to establish and standardise the platform and the results of the process. Methods: MaatHRI is a hospital-based collaborative research platform. It is adapted from the UK Obstetric Surveillance System (UKOSS) and built on a pilot model (IndOSS-Assam), which has been extensively standardised using the following methods: (i) establishing a network of hospitals; (ii) setting up a secure system for data collection, storage and transfer; (iii) developing a standardised laboratory infrastructure; and (iv) developing and implementing regulatory systems. Results: MaatHRI was established in September 2018. Fourteen hospitals participate across four states in India - Assam, Meghalaya, Uttar Pradesh and Maharashtra. The research team includes 20 nurses, a project manager, 16 obstetricians, two pathologists, a public health specialist, a general physician and a paediatrician. MaatHRI has advanced standardisation of data and laboratory parameters, real-time monitoring of data and participant safety, and secure transfer of data. Four observational epidemiological studies are presently being undertaken through the platform. MaatHRI has enabled bi-directional capacity building. It is overseen by a steering committee and a data safety and monitoring board, a process that is not normally used, but was found to be highly effective in ensuring data safety and equitable partnerships in the context of low and middle income countries (LMICs). Conclusion: MaatHRI is the first prototype of UKOSS and other similar platforms in a LMIC setting. The model is built on existing methods but applies new standardisation processes to develop a collaborative research platform that can be replicated in other LMICs. Copyright:
Background: Maternal and perinatal Health Research collaboration, India (MaatHRI) is a research platform that aims to improve evidence-based pregnancy care and outcomes for mothers and babies in India, a country with the second highest burden of maternal and perinatal deaths. The objective of this paper is to describe the methods used to establish and standardise the platform and the results of the process. Methods: MaatHRI is a hospital-based collaborative research platform. It is adapted from the UK Obstetric Surveillance System (UKOSS) and built on a pilot model (IndOSS-Assam), which has been extensively standardised using the following methods: (i) establishing a network of hospitals; (ii) setting up a secure system for data collection, storage and transfer; (iii) developing a standardised laboratory infrastructure; and (iv) developing and implementing regulatory systems. Results: MaatHRI was established in September 2018. Fourteen hospitals participate across four states in India - Assam, Meghalaya, Uttar Pradesh and Maharashtra. The research team includes 20 nurses, a project manager, 16 obstetricians, two pathologists, a public health specialist, a general physician and a paediatrician. MaatHRI has advanced standardisation of data and laboratory parameters, real-time monitoring of data and participant safety, and secure transfer of data. Four observational epidemiological studies are presently being undertaken through the platform. MaatHRI has enabled bi-directional capacity building. It is overseen by a steering committee and a data safety and monitoring board, a process that is not normally used, but was found to be highly effective in ensuring data safety and equitable partnerships in the context of low and middle income countries (LMICs). Conclusion: MaatHRI is the first prototype of UKOSS and other similar platforms in a LMIC setting. The model is built on existing methods but applies new standardisation processes to develop a collaborative research platform that can be replicated in other LMICs. Copyright:
Authors: G Fellmeth; M T Kishore; A Verma; G Desai; O Bharti; P Kanwar; S Singh; H Thippeswamy; P S Chandra; J J Kurinczuk; M Nair; F Alderdice Journal: J Public Health (Oxf) Date: 2021-10-08 Impact factor: 2.341