Skip to main content

Referral care for high-risk pregnant women in rural Rajasthan, India: a qualitative analysis of barriers and facilitators

Abstract

Objective

To qualitatively assess the barriers and facilitators to uptake of referral services amongst high-risk pregnant women in rural Rajasthan.

Methods

A purposive sample of pregnant women with high-risk conditions requiring referral follow-up care (severe hypertension, moderate anemia, and severe anemia) were considered for inclusion. In-depth individual interviews were conducted in the local dialect, Mewari. Interviews were transcribed, coded, and organized for thematic generation as per the analytical framework described in the socio-ecological model.

Results

19 high risk pregnant women of low socioeconomic backgrounds across 15 villages were interviewed. Barriers to referral care included lack of transportation, household responsibilities, and limited awareness, education, and social support. The most prominent barrier was lack of accompaniment to the referral center by a family member or health worker. Facilitators included available husbands, engaged heath workers, supportive neighbors, and other female family members who shared past experiences.

Conclusions

Social support at the interpersonal and community level was key to overcoming referral care barriers faced by high-risk pregnant women in rural Rajasthan. Interventions that enhance social support may improve uptake of referral care services by high-risk pregnant women.

Peer Review reports

Background

In India, an estimated 30,000 mothers die annually from preventable causes related to pregnancy and childbirth [1]. Meanwhile, 800,000 children under the age of five die from vaccine preventable disease, neonatal infection, birth asphyxia and malnutrition. In 2017, the Indian Council of Medical Research (ICMR), Public Health Foundation of India (PHFI) and National Institute of Nutrition (NIN), reported malnutrition as the main risk factor for under-5 deaths nationally, accounting for 68% of total deaths. A major predictor of low birthweight and infant malnutrition is maternal anemia (and associated poor maternal nutrition), which occurs in greater than 50% of women between the ages of 15–49 years [2].

Rajasthan, India’s largest state, is a high-focus state with respect to reproductive and child health (RCH). It has a population of 80 million citizens [3], 75% of whom live in rural areas [4], and a maternal and infant mortality rate of 199 (India MMR: 130) and 41 (India IMR: 34) respectively [5, 6]. Annually, an estimated 420,000 pregnant women in Rajasthan are at high-risk of delivery complications from carrying three or more pregnancies[7].

India’s public health system (Fig. 1) [8] provides a large set of cost effective, successful solutions across the ante-, intra-, and post-natal care continuum that have been implemented to prevent avoidable maternal, neonatal, and child mortality: iron folic acid supplementation for pregnant women, regular antenatal care checkups, institutional deliveries, training on newborn care, immunizations, and treatment of febrile illness [9].

Fig. 1
figure 1

In India, the public health system begins at the village level, where the ASHA (accredited social health activist) spreads health awareness for multiple health programs, identifies and counsels eligible couples for family planning, guides pregnant women to referral facilities, and identifies postnatal infant danger signs. At the sub-center, the ANM (auxiliary nurse midwife) conducts antenatal care and child checkups, provides nutritional supplements, and performs immunizations. Here, women and children are identified as high risk and referred for higher level care at the primary health center, where the Medical Officer (MO) treats them and conducts deliveries

However, since data for these interventions is collected on paper at the point of care, the public health system faces the following problems: missing and inconsistent data, poor coordination between health workers at different levels of care, lack of accountability, delays in reporting data for action, unregistered populations, and a disconnected continuum of care [10, 11].

To address these gaps, Khushi Baby, a non-profit organization based in the Udaipur District of Rajasthan, developed and implemented a digital health intervention for community health workers to track key reproductive and child health indicators over the last five years. The system also includes field staff who support community health workers by facilitating referral care visits for high risk beneficiaries. So far, 15 field staff have conducted more than 2000 home and hospital visits to encourage completion of referral care for maternal anemia and infant malnutrition. Overall, the Khushi Baby system has been shown to improve data completeness, data consistency, infant immunization rates and infant malnutrition [12].

In spite of these interventions, high-risk pregnant women and infants in rural Udaipur still receive inadequate referral care services, motivating the objective of this study – to investigate the barriers and facilitators to uptake of referral services amongst high-risk pregnant women in rural Rajasthan.

As described by Thaddeus and Maine, mothers face three key delays to referral care: delays in seeking care, delays in arriving at the healthcare facility, and delays in provision of adequate care [13]. These delays are rooted in socio-economic, cultural, and environmental characteristics (patient factors) and quality of health care (health system factors). Health system factors are thought to carry more weight than patient factors because of their potential to affect all three phases of delay [13].

A 2019 narrative review of barriers of maternal and neonatal referral systems in developing countries by Harahap et al. noted challenges in both patient and health systems factors. Patient barriers included: environments, knowledge about the referral, poverty, maternal health status, and culture. Health system barriers included: transportation, communication, quality of care, referral documentation, standard procedures for referral and monitoring, and network infrastructure. The five studies from India (between 2014–2018) included in the review focused more on the health system and did not identify barriers related to network infrastructure, knowledge about referral, maternal health status, and culture [14].

Barriers to maternal and child referral care have been under-researched in the Indian context, and most relevant for our study, no such studies have been conducted in Rajasthan. We hypothesize that beyond the globally identified barriers to maternal and child referral care, several specific barriers may emerge from a local application of the socio-ecological model.

The objective of this study is to conduct qualitative interviews with high risk pregnant (HRP) women living in rural communities in Udaipur to 1) identify barriers and facilitators to referral care completion, 2) categorize them into individual, interpersonal, community and structural factors, 3) study the interactions and combined effects of individual/interpersonal factors and community/structural factors on referral care completion, and 5) discuss potential policy, human resource and technology solutions to improve referral care completion and improve maternal and infant health. To our knowledge, this study is the first to use the socio-ecological model (SEM) to qualitatively assess the barriers and facilitators of antenatal referral care in India.

Methods

Selection and recruitment of participants

Pregnant women suffering from moderate to severe anemia (Hb < 10) and/or hypertension (BP > 140/90) were identified as high risk by the Khushi Baby digital health mobile application (data collection tool at government health camps) and eligible for our study. Using purposive sampling, recruitment and interviews were conducted with participants from four geographical blocks: Gogunda, Sarada, Salumbar, and Jhadol. These participants were selected to represent varying geographical terrains, community values and referral completion rates. Participants were recruited from these blocks until data saturation had been achieved for the majority of themes [15]. We restricted our selection process to these four blocks because of long term relationships between Khushi Baby field monitors and community members living in these areas. Khushi Baby field monitors selected participants and organized interviews but were not personally involved in the interview process. Only individuals who provided verbal consent and felt able to complete the interview were recruited.

Data collection

In-depth interviews were conducted in January 2021 in Mewari, the local dialect, by a native of Udaupir and experienced public health researcher, SV. All interviews were conducted in participants’ homes and lasted 30–45 min. Several participants performed the interview with their infants present due to unavailability of child care. Although it was advised against, some relatives or neighbors supported the participants in their personal responses. In some cases, we requested a trusted member of the community, such as the ASHA, to be present to provide support or additional information regarding community values and societal resources. Participants were told they could decline to answer any questions and could stop the interview at any time.

The interviews followed a semi-structured interview guide which included open-ended questions on personal background, socio-economic status, past experiences with public health services and personal and community attitudes towards pregnancy, antenatal care and family planning.

During the in-depth interviews, verbal responses were translated by the interviewer and transcribed by one of the researchers. Participant transcripts and surveys were labelled with participant ID numbers in order to maintain confidentiality in the reported data. All files were password protected and stored on a secure computer network with restricted access.

Data analysis

Summary notes informed the preliminary analysis of participant transcripts. In developing an analytic thematic framework, data was initially indexed and categorized using an inductive approach. To further identify relevant themes in our study, a subsample of transcripts (< 20%) were studied by four members of our research team: Saachi Dalal (BA, MD and MSc Population Medicine candidate), Ruchit Nagar (BA,MPH,MD), Rohaan Hegde (BA), Hamid Abdullah (MSW, Field Implementation Lead at Khushi Baby). The reviewers assigned codes to specific responses, constructed thematic maps and compared themes that showed a significant level of consistency. Through discussion, prominent categories were refined, new categories were identified and discrepancies were resolved. Data was summarized using thematic matrices [15] and a socio-ecological model (SEM) was used to organize relevant themes and present results. The model selected for our study was inspired by the SEM as conceived by McLeroy, et al. [16, 17]. Noteworthy narratives and quotes were also selected to encapsulate themes and their interactions.

Results

We completed interviews with 19 participants. Sociodemographic details are shown in Table 1 below. We report individual and interpersonal barriers and facilitators such as personal and family awareness, beliefs and attitudes, and social support in Tables 2 and 3 below. We then present factors at the community and structural level such as opportunities for peer learning and access to public transportation in Tables 4 and 5 below. The relative importance of factors which influence referral completion are illustrated in the discussion section.

Table 1 Socioeconomic factors at an individual level among the study population
Table 2 Individual and Interpersonal Barriers
Table 3 Individual and Interpersonal Facilitators
Table 4 Community and Structural Barriers
Table 5 Community and Structural Facilitators

Discussion

This qualitative study among high-risk pregnant women in rural Udaipur identified barriers and facilitators to completing referral care at both an individual/interpersonal level and a community/structural level in rural Rajasthan, India. Although the presence and relative importance of factors varied for each participant, our findings reveal a broader understanding of referral care experience among this population.

In comparison to conclusions of Harahap et al.’s narrative review of barriers of maternal and neonatal referral systems in developing countries, this study found patient factors to be of greater relevance than health system factors for successful completion of referral care. [14] Specifically, the most prominent facilitator of referral care was identified as social support, specifically by a husband, family member or the ASHA for travel and care navigation. Even women with no additional barriers at the individual or structural level failed to complete referrals without accompaniment. Outliers who completed referrals without accompaniment had one or more prior deliveries, and access to child-care support and convenient transportation options nearby. Unlike the three delays model which identifies quality of the public health system as the leading factor for referral completion, our analysis showed that the patient’s connectedness to a long-term accompagnateur was more relevant. Similarly, other research in India has found that the degree of social support, especially by husbands and ASHAs, significantly influences prenatal health behaviors, institutional delivery, and health outcomes for pregnant women [18, 19].

At a village level, ASHAs have been recruited to fill gaps of low health awareness and social support through counseling, accompaniment, and facilitation of health seeking behaviors. ASHAs are financially incentivized to ensure pregnant women receive at least one antenatal care checkup, to accompany them during delivery, and to complete seven home visits for post-natal screening. Notably, ASHAs are responsible for but not financially incentivized to motivate pregnant women to complete advanced antenatal screening and high-risk referral care. All participants, except two, stated that ASHAs did not visit their home regularly to deliver reminders and awareness messages, did not accompany them to the referral center for high-risk care or deliveries, and did not screen newborns for danger signs.

Lack of initiative by ASHAs in Udaipur may be associated with being overburdened and underpaid by the government health system. ASHAs in Rajasthan, despite having equal responsibility, receive a lower base salary compared to ASHAs in other states. They are expected to make up the difference through task-based incentives; however, they do not receive support or financial incentives for facilitation of referrals. Additionally, poor communication and coordination between ASHAs and MOs at the primary health center leaves ASHAs without information regarding which beneficiaries have missed their referral care visit. Finally, based on our field observations over many years, poor monitoring from higher level authorities leads to ASHAs falsely reporting tasks as completed for the sake of receiving incentives. Ultimately, poor accountability, capacity building, support and incentives for ASHAs negatively affects the beneficiaries they serve.

Studies based in Pakistan and Bangladesh have found concordance with our findings, citing similar key barriers to referral completion: limited coordination between community health workers and the referral facility, lack of incentives or support to community health workers in facilitating the referral and lack of peer groups for social support [20, 21]. Studies in Bangladesh also emphasized the following facilitators in direct association with our findings: 1) community engagement and self-help groups to develop action plans, promote awareness and provide support; 2) reimbursement schemes or community funding linked to referral care support, and 3) community health workers accompanying the patient to the referral facility [21, 22].

Finally, beyond social connectedness and lack of ASHA support, reasonable access to transportation was identified as essential for referral care completion and safe delivery. Since none of the villages are served by government buses, many participants who otherwise go independently to the village health camp (within a 1 km distance), required accompaniment to reach the referral center. If public transport were easily accessible, more women who have health system awareness may be comfortable completing referral care visits on their own.

This study had certain limitations, specifically many participants gave limited responses due to the personal nature of the interview, despite having a female interviewer speaking in their native dialect. These interviews were not electronically recorded, which limited the number and accuracy of quotes captured.

The strengths of the study come from the data-driven recruitment approach. The prior rapport with field monitors and familiarity with a female voice in the local dialect likely strengthened the response quality. The study captured a diversity of sociodemographic conditions by interviewing women over a 100 km + radius around Udaipur.

Future directions

Future studies may explore the perspectives of caregivers, health workers, and government officials to gain a holistic picture at both an individual and structural level. Retrospective studies comparing delivery outcomes with antenatal history of such social determinants may corroborate study findings. Further, the following solutions are proposed to account for the specific barriers and facilitators identified in the study, in the context of the local Khushi Baby intervention and resources:

Digital health census

To improve ASHA engagement, the Khushi Baby team is developing a digital health census mobile application. Through this platform, we plan to screen for social connectedness (e.g. history of participation in a peer learning group, rating of ASHA engagement during pregnancy and postnatal care, number of days husband is away from home each month, number of adult female family members living in the house, or access to family member or trusted neighbor for accompaniment during health-related emergencies or referral visits) and structural issues (e.g. distance to PHC, access to and types of transportation, knowledge about ambulances) to assist with health system navigation.

High risk beneficiary prioritization

Khushi Baby’s mobile application for the ANM has generated a database of more than 20,000 pregnant women to date, of which more than 8,000 women have delivery outcome and infant health data. We will use these details to develop a high-risk score for each beneficiary. From these scores, a list of prioritized high-risk beneficiaries with their degree of their social connectedness, distance to referral facility and due dates, will be displayed for the ASHA and ANM on their mobile applications to inform them which women require extra support during pregnancy and delivery. Additionally, this technology has potential to increase communication and collaboration between ASHAs and ANMs.

Health worker coordination

ASHAs may use this tool to keep running list of home visits and ensure they follow-up with beneficiaries according to program due dates (e.g. deliveries and post-partum maternal and newborn care). The tool will also provide reminders for peer-learning sessions mandated through health policies. To support ASHAs in improving their health communication skills, locally-tailored audiovisual materials to counsel mothers regarding their need for referral care will also be included. To motivate ASHAs to use the tool and complete their responsibilities, the application will automate monthly reports and display the expected monthly incentives payout. It is envisioned that this automated tool will financially empower ASHAs and overcome dependency on data entry operators to report their work to ultimately receive compensation for key services provided at the village level. Accountability mechanisms in the form of data quality checks, GPS tracking and biometric authentication will be integrated into the app to confirm that ASHAs are actually visiting households and interacting with beneficiaries. Altogether, the aim of this application is to digitally empower ASHAs to focus on providing high-quality care in their respective villages, particularly to high-risk beneficiaries.

To complete the chain of referral (Fig. 2), Khushi Baby is developing a mobile application for Medical Officers at the primary health center. Beyond other functions, this app will sync with the ASHA and ANM apps so that all three groups of health care providers (ASHAs, ANMs, MOs) will work from the same list of high-risk beneficiaries due for referral, see who did not complete their referrals and call them through the app to investigate and communicate reminders.

Fig. 2
figure 2

Khushi Baby RCH continuum of care: mobile application for ASHA, ANM, MO, automated voice calls for beneficiaries, NFC, GPS and biometric authentication, and dashboard analytics and AI

Targeted and automated communication

Additionally, Khushi Baby currently sends automated voice calls to the family to complete antenatal care visits and infant immunizations. This system has been very helpful to ASHAs who travel across tough terrain to deliver these reminders door-to-door. Findings from this study will inform new content to specifically remind and motivate pregnant women to complete referrals. We may also refine our voice call content to target fathers, who account for the majority of mobile phone owners, and to address misconceptions regarding ambulance availability. Further, introducing SMS and interactive voice response system messages (IVRS) to gauge whether the respondent understood or found the content useful can also be integrated to evaluate their effectiveness over time. Finally, Khushi Baby call center will make targeted personal call to pregnant women due to deliver in the coming week to discuss and establish a safe delivery plan, including social accompaniment and transportation.

Policy reform

At a larger scale in Rajasthan, policy decisions will need to be made to supercharge potential facilitators to referral care. We recommend that the Department of Medical, Health, and Family Welfare consider an incentive model tied with an accountability mechanism for high-risk pregnant women to avail the Pradhan Mandiri Surakshit Matritva Abhiyan scheme, which provides free advanced antenatal care screenings for pregnant women on the 9th of each month. The Department should also consider how to improve capacity building and financial support for ASHAs who are instrumental to carrying out these referrals through accompaniment. Information, education and communication campaigns may be targeted to close specific awareness gaps at the village level, particularly regarding schemes and availability of specific ambulance support for pregnant women. Leaders of village-level self-help-groups should be motivated and supported to facilitate discussions around women’s health issues during scheduled meetings on loan disbursements. Finally, husbands should be engaged through directed village meetings to discuss the process and importance of referral visits and safe delivery plans. Multiple strategies, addressing each layer of the socio-ecological model, will need to be implemented in a coordinated manner to improve uptake of high-risk pregnancy referral care and ultimately better maternal and child health outcomes in Rajasthan, India.

Conclusions

In rural Udaipur, Rajasthan, high risk pregnant women face numerous barriers to seeking referral care which include lack of accompaniment to the health center, limited education and health awareness, lack of transportation, geographic isolation, and household/financial responsibilities. However, social support at the interpersonal and community level has been shown to overcome barriers—accompaniment to the referral center was identified as the strongest facilitator to completing referral care.

Availability of data and materials

Anonymized quotes have been listed in the results section above. Full transcripts are not available for review because they have personally identifying information. Redacted transcripts may be requested from the corresponding author upon reasonable request.

Abbreviations

ANC:

Antenatal care checkup

ANM:

Auxiliary Nurse Midwife

ASHA:

Accredited Social Health Activist

BeMONC:

Basic emergency obstetric and newborn care

CeMONC:

Critical emergency obstetric and newborn care

CHC:

Community health center

DMHFW:

Department of Medical, Health, and Family Welfare, Government of Rajasthan

Early initiation of breastfeeding:

Provision of colostrum to the child

Full antenatal care completion:

4 ANCs, tetanus injection, 180 Iron Folic Acid tablets received

Full infant immunization:

Completion of PENTA 1–3, OPV 1–3, Measles, and BCG immunization

HRP:

High risk pregnancy

IFA:

Iron folic acid tablets

IMR:

Infant mortality rate

IVRS:

Interactive voice response system

Minimum acceptable diet:

As defined per National Family Health Survey guidelines

MOIC:

Medical Officer in Charge

MMR:

Maternal mortality rate

OBC:

Other backward caste

PHC:

Primary health center

PMSMA:

Pradhan Mandiri Surakshit Matritva Abhiyan scheme

RCH:

Reproductive and child health

RMNCH + A:

Reproductive, maternal, neonatal, child, and adolescent health

Safe delivery:

Delivery in the presence of a certified skilled-birth attendant

SC:

Scheduled caste

SHC:

Sub-health center

ST:

Scheduled tribe

VHND:

Village health and nutrition day camp

References

  1. UNICEF. Maternal health. https://www.unicef.org/india/what-we-do/maternal-health Accessed 27 Mar 2021.

  2. Swaminathan S, Hemalatha R, Pandey A, et al. The burden of child and maternal malnutrition and trends in its indicators in the states of India: the Global Burden of Disease Study 1990–2017. Lancet Child Adolesc Health. 2019;3(12):855–70. https://doi.org/10.1016/S2352-4642(19)30273-1.

    Article  Google Scholar 

  3. Census of India. CensusInfo India 2011Final Population Totals Rajasthan Profile. Published online 2011. https://censusindia.gov.in/2011census/censusinfodashboard/stock/profiles/en/IND008_Rajasthan.pdf

  4. UIDAI Government of India. State/UT wise Aadhaar Saturation. Unique Identification Authority of India. Government of India. Published online December 31, 2020. https://uidai.gov.in/images/state-wise-aadhaar-saturation.pdf

  5. Niti Aayog. Maternal Mortality Ratio (MMR) (per 100000 live births). https://niti.gov.in/content/maternal-mortality-ratio-mmr-100000-live-births Accessed 27 Mar 2021.

  6. Niti Aayog. Infant Mortality Rate (IMR) (per 1000 live births). https://niti.gov.in/content/infant-mortality-rate-imr-1000-live-births. Accessed 27 Mar 2021

  7. Agnani M. RMNCAH+N Issues & Concern: Rajasthan. Presented at: NPCC Meeting: Rajasthan; January 23, 2020; NHRSRC, Dehli. https://drive.google.com/file/d/0B34IjkmAxzS8Z3Z5eU9HUFRhNWpDVkNQQ1pBOFZZS183Szhv/view

  8. Singh S, Doyle P, Campbell O, Mathew M, Gudlavalleti M. Referrals between Public Sector Health Institutions for Women with Obstetric High Risk, Complications, or Emergencies in India – A Systematic Review. PLoS ONE. 2016;11:e0159793. https://doi.org/10.1371/journal.pone.0159793.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Lassi ZS, Mansoor T, Salam RA, Das JK, Bhutta ZA. Essential pre-pregnancy and pregnancy interventions for improved maternal, newborn and child health. Reprod Health. 2014;11(1):S2. https://doi.org/10.1186/1742-4755-11-S1-S2.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Joshi NK, Bhardwaj P, Suthar P, Jain YK, Joshi V, Singh K. Overview of e-Health initiatives in Rajasthan: An exploratory study. J Fam Med Prim Care. 2021;10(3):1369–76. https://doi.org/10.4103/jfmpc.jfmpc_1989_20.

    Article  Google Scholar 

  11. Sheth E, Sisodia K, Songara D. Understanding Barriers to Antenatal Care and Institutional Delivery-Survey. https://globalcenters.columbia.edu/sites/default/files/content/Mumbai/Publications/Understanding%20Barriers%20to%20Antenatal%20Care%20and%20Institutional%20Delivery%20-Survey%20-Part%20I.pdf

  12. Nagar R, Ambiya MS, Singh P, Abdullah H, Banshiwal V, Shahnawaz M. Impacts of a Novel MHealth Platform to Track Maternal and Child Health in Udaipur. https://www.3ieimpact.org/evidence-hub/publications/impact-evaluations/impacts-novel-mhealth-platform-track-maternal-and#. Accessed 27 Mar 2021

  13. Thaddeus S, Maine D. Too far to walk: Maternal mortality in context. Soc Sci Med. 1994;38(8):1091–110. https://doi.org/10.1016/0277-9536(94)90226-7.

    Article  CAS  PubMed  Google Scholar 

  14. Harahap NC, Handayani PW, Hidayanto AN. Barriers and technologies of maternal and neonatal referral system in developing countries: A narrative review. Inform Med Unlocked. 2019;15:100184. https://doi.org/10.1016/j.imu.2019.100184.

    Article  Google Scholar 

  15. Guest G, Namey E, Chen M. A simple method to assess and report thematic saturation in qualitative research. PLoS ONE. 2020;15(5):e0232076. https://doi.org/10.1371/journal.pone.0232076.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. Ritchie J, et al. “Qualitative Research Practice: A Guide for Social Science Students and Researchers.” 2013.

  17. McLeroy KR, Bibeau D, Steckler A, Glanz K. An Ecological Perspective on Health Promotion Programs. Health Educ Q. 1988;15(4):351–77. https://doi.org/10.1177/109019818801500401.

    Article  CAS  PubMed  Google Scholar 

  18. Vincent A, Keerthana K, K. D, Newtonraj A, Bazroy J, Manikandan M. Health care seeking behaviour of women during pregnancy in rural south India: a qualitative study. Int J Community Med Public Health Vol 4 No 10 2017 Oct 2017. Published online 2017. doi:https://doi.org/10.18203/2394-6040.ijcmph20174224

  19. Bhushan NL, Krupp K, Jaykrishna P, et al. The association between social support through contacts with Accredited Social Health Activists (ASHAs) and antenatal anxiety among women in Mysore, India: a cross-sectional study. Soc Psychiatry Psychiatr Epidemiol. 2020;55(10):1323–33. https://doi.org/10.1007/s00127-020-01854-4.

    Article  PubMed Central  PubMed  Google Scholar 

  20. DasGupta, M., et al. "Overcoming gender-based constraints to utilization of maternal and child health services in Pakistan: The role of the doorstep delivery system." Annual Meeting of the Population Association of America, New York, NY. 2007.

  21. Kamiya Y, Yoshimura Y, Islam MT. An impact evaluation of the safe motherhood promotion project in Bangladesh: evidence from Japanese aid-funded technical cooperation. Soc Sci Med. 1982;2013(83):34–41. https://doi.org/10.1016/j.socscimed.2013.01.035.

    Article  Google Scholar 

  22. Quayyum Z, Khan MNU, Quayyum T, Nasreen HE, Chowdhury M, Ensor T. “Can community level interventions have an impact on equity and utilization of maternal health care” – Evidence from rural Bangladesh. Int J Equity Health. 2013;12(1):22. https://doi.org/10.1186/1475-9276-12-22.

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

Ravi Singh Bhadauriya, Navratan Pargi, Bhavishya Purbia, Danny Purbia, Ashok Nama, Rahul Kharadi, and the Khushi Baby field monitors.

Funding

Funding support was provided from Harvard Medical School to support data collection, analysis, and manuscript preparation.

Author information

Authors and Affiliations

Authors

Contributions

SD designed the survey format, conducted surveys, performed data analysis, and lead manuscript writing. RN supported study design, IRB approval, data analysis, and manuscript writing and editing. RH supported survey format design, data analysis, and manuscript writing. HA supported survey format design, data collection, and data analysis. SV supported survey format design and lead data collection efforts. JK was the Principal Investigator on the project, supporting study design, data analysis, and final manuscript preparation. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Saachi Dalal.

Ethics declarations

Ethics approval and consent to participate

Ethical approval was obtained through the Harvard University Institutional Review Board (IRB19-0804). All methods were carried out in accordance with relevant guidelines and regulations. Given that majority of the study participants were illiterate (unable to read/write), verbal informed consent was taken from participants as per the Harvard IRB protocol. No personally identifiable data is shared in this manuscript.

Consent for publication

Not applicable.

Competing interests

Saachi Dalal is the Chief Strategy Officer of Khushi Baby. Ruchit Nagar is the Chief Executive Officer of Khushi Baby. Hamid Abdullah is the Implementation Lead of Khushi Baby and Surya Vaishnav is a Communications Associate of Khushi Baby. Saachi Dalal, Ruchit Nagar, Hamid Abdullah and Surya Vaishnav receive salary from the Khushi Baby organization, a non-profit organization dedicated to developing digital health solutions to improve last-mile health care in India. These solutions are provided to the government free of cost as digital public health goods. All the other authors have no conflict of interest to disclose.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dalal, S., Nagar, R., Hegde, R. et al. Referral care for high-risk pregnant women in rural Rajasthan, India: a qualitative analysis of barriers and facilitators. BMC Pregnancy Childbirth 22, 310 (2022). https://doi.org/10.1186/s12884-022-04601-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12884-022-04601-6

Keywords