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Currently submitted to: JMIR Research Protocols

Date Submitted: Mar 26, 2025
Open Peer Review Period: Mar 26, 2025 - May 21, 2025
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Impact of a multi-component intervention to build capacity of public health workers to make algorithmic diagnosis and management of high-risk pregnancies: Protocol for a matched-control, before-after quasi-experimental study with a mixed-method design in Uttar Pradesh, India.

  • Hanimi Reddy Modugu; 
  • Chetan Purad; 
  • Venkatesh Irugulapati; 
  • Anil Kumar Shukla; 
  • Sandhya NVS Dittakavi; 
  • Sirichandana Reddy Alla; 
  • Anuja Jayaraman; 
  • Karishma Thariani; 
  • Aparna Hegde

ABSTRACT

Background:

In India, 20-30% pregnancies fall under high-risk category, contributing to 75% of perinatal mortality and morbidity. An effective approach to reduce maternal and neonatal mortality/morbidity is early identification, effective management, and timely referral of high-risk pregnancies (HRPs). The Integrated High-Risk Pregnancy Tracking and Management (IHRPTM) program aims to enhance capacity of auxiliary nurse midwives (ANMs), medical officers (MOs), and specialist gynaecologists by: i. providing algorithmic, color-coded, detailed (yet simple) protocols for six HRP conditions, customized for each role, ii. offering live training, iii. delivering digital training and hand-holding, and iv. facilitating tracking pregnancies and management of HRPs. Equipping health workers (HWs) on these interventions facilitates early identification, effective management, and timely referrals, ultimately improving primary care and satisfaction of mothers with HRPs. Stated interventions are implemented in the intervention arm for 18 months, while during this period, HWs of intervention and control arms will receive routine training through state and national programs, ensuring pregnant women have equal access to routine maternity services.

Objective:

At the system level, the program evaluates the impact on improvement in the knowledge and skills of HWs in diagnosing and managing HRPs. At the community level, it assesses the translation of this knowledge and into practice, in terms of early diagnosis and effective management, among women with HRPs.

Methods:

The program will be implemented in two intervention districts (Sambhal and Shravasti) and two matched control districts (Baduan and Gonda) of Uttar Pradesh, on six HRPs. Study uses a ‘quasi-experimental, before-and after trial design’, with intervention and control arms. However, impact of program will be assessed only on three HRPs: moderate/severe anaemia, pregnancy-induced hypertension, and antepartum haemorrhage (APH), including placenta previa/abruptio placenta. System level impacts will be assessed through qualitative data collected from district officials, specialist gynaecologists, MOs and ANMs, at baseline and endline. Community level outcomes will be measured quantitatively using baseline and endline data from recently delivered women (RDW), with or without HRPs.

Results:

The impact evaluation protocol was approved by ARMMAN’s Scientific Review Board and Sigma’s Institutional Review Board. The protocols for six HRP-conditions were vetted by the government of Uttar Pradesh. By November 2024, all the ANMs, MOs, specialist gynaecologists, staff nurses, and community health officers in two intervention districts were trained on six HRP-protocols. Digital learning tool and WhatsApp support system was also introduced to facilitate continued learning and handholding of ANMs in managing HRPs and/or to clear doubts. Pre-intervention/baseline data was collected from two arms, during June-October 2024.

Conclusions:

This trial will provide valuable insights into the feasibility and effectiveness of the program, at system and community levels, in a low resource setting like Uttar Pradesh. If successful, these insights can feed into capacitating HWs, at scale, in all the districts on diagnosis and management of HRPs, with significant potential for improving maternal and neonatal outcomes of the state.


 Citation

Please cite as:

Modugu HR, Purad C, Irugulapati V, Shukla AK, Dittakavi SN, Alla SR, Jayaraman A, Thariani K, Hegde A

Impact of a multi-component intervention to build capacity of public health workers to make algorithmic diagnosis and management of high-risk pregnancies: Protocol for a matched-control, before-after quasi-experimental study with a mixed-method design in Uttar Pradesh, India.

JMIR Preprints. 26/03/2025:74993

DOI: 10.2196/preprints.74993

URL: https://preprints.jmir.org/preprint/74993

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