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mHealth Integrated Model of Hypertension, Diabetes and Antenatal Care in India and Nepal

P

Public Health Foundation of India

Status

Not yet enrolling

Conditions

Anemia
Gestational Diabetes Mellitus (GDM)
Pregnancy Induced Hypertension (PIH)

Treatments

Other: mHealth Integrated Model of Antenatal Care

Study type

Interventional

Funder types

Other

Identifiers

NCT03700034
CTRI/2019/01/016857

Details and patient eligibility

About

Our research aims to address a critical gap in the provision of quality antenatal care (ANC) in India and Nepal, by developing and evaluating an intervention comprising of a tablet-based electronic decision support system (EDSS). This intervention -"mIRA" - is an mHealth integrated model of hypertension, diabetes, and antenatal care in primary care settings. mIRA aims to (a) prompt frontline health workers (FHWs) to provide evidence-based routine ANC, and also enhance the detection and management of Pregnancy Induced Hypertension (PIH), Gestational Diabetes Mellitus (GDM), and anemia, whilst improving adherence to National ANC guidelines; (b) facilitate record-keeping and reporting and; (c) link providers across various levels of care to improve continuity of care.

A cluster randomized controlled (cRCT) to assess the effectiveness of the mIRA EDSS in improving ANC and enhancing the detection and management of Pregnancy Induced Hypertension (PIH), Gestational Diabetes Mellitus (GDM), and anemia will be conducted in Telangana, India. A mixed-methods process evaluation will be conducted in both India and Nepal. The process evaluation will contribute to our understanding of the mechanisms contributing to changes (improvement) in the quality of ANC by using the EDSS intervention.

Full description

The cRCT aims to evaluate the effectiveness of a tablet-based EDSS in improving the quality of ANC and enhancing the detection and management of PIH, GDM, and anemia at primary care level health facilities in five districts of Telangana State: Medak, Rangareddy, Siddipet, Vikarabad, and Yadadri Bhuvangiri. The EDSS will use evidence-based algorithms to suggest recommendations to the FHWs for providing ANC, based on the pregnant woman's history, examination, and investigations, as well as incorporate reminders to ensure all relevant components of ANC are recorded. The aim is to ensure that ANC components received during multiple visits from multiple healthcare providers are captured and contribute to coordinated care. FHWs, primarily Auxiliary Nurse Midwives (ANMs), will use the EDSS during ANC consultations with pregnant women at Sub-Centres, while at the Primary Health Centres (PHCs), this will be used by Medical Officers (MOs) and staff nurses.

In these selected districts, which are predominantly rural, 66 clusters with each cluster comprising a PHC and its two reporting Sub-Centres, will be randomized with a 1:1 allocation ratio to the intervention arm (providing ANC using the mIRA EDSS intervention) and the control arm (providing usual care), using a computer-generated randomization schedule stratified by the district. Covariate constrained randomization will be used to balance the arms on the following baseline covariates: the presence of a laboratory and laboratory technician (yes/no); more than three staff providing ANC (yes/no); facility type (PHCs that are open 24/7 or those not open 24/7).

The cRCT will not be conducted In Nepal, however, the mIRA EDSS will be implemented at government Health Posts (HP), government Primary Health Care Centers (PHCCs), and Dhulikhel Hospital Outreach Centers (DHORCs), in four catchment districts (Kavrepalanchok, Sindhupalchowk, Sindhuli, and Dolakha) of Dhulikhel Hospital. A pre-post EDSS implementation outcome evaluation will be conducted. The process evaluation research activities conducted in India and Nepal will be the same (including a baseline facility survey, routine monitoring, and audit of record-keeping), except for a longitudinal case study and a time-motion study that will be conducted only in Nepal. Additionally, endline qualitative in-depth interviews with healthcare providers, facility managers, district and state health officials and policymakers, and with members of the Public Health Foundation of India team (intervention implementors) will be conducted only in India.

Enrollment

1,320 estimated patients

Sex

Female

Ages

18 to 49 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Pregnant women visiting a trial facility up to the end of the 28th week of gestation
  • Women who are planning to remain within the five study districts until at least one-month post-partum OR women whose mothers reside in the selected districts

Exclusion criteria

• Women coming to the trial facility for a non-routine ANC visit (for example, to get a laboratory investigation, to collect a report or her medicine)

Trial design

Primary purpose

Health Services Research

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

1,320 participants in 2 patient groups

mHealth integrated model of hypertension, diabetes, anemia, and antenatal care
Experimental group
Description:
The mIRA trial intervention will consist of an electronic decision support system (EDSS), provided to healthcare providers at primary-level facilities in India and Nepal to deliver enhanced ANC with improved detection and management of pregnancy-induced hypertension (PIH), gestational diabetes mellitus (GDM) and anemia.
Treatment:
Other: mHealth Integrated Model of Antenatal Care
Routine antenatal care
No Intervention group
Description:
In the control clusters, pregnant women will receive the existing standard of care (usual care) from Frontline Health Workers (FHWs). Evidence-based guidelines in the form of posters/pamphlets on current national and state guidelines on screening and management of pregnancy-induced hypertension (PIH), gestational diabetes mellitus (GDM), anemia, and routine ANC procedures will be provided to all the control health facilities.

Trial contacts and locations

6

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Central trial contact

Sailesh Mohan, PhD

Data sourced from clinicaltrials.gov

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