The Government has approved a business case and $83m in funding for a new Waikato University medical school, as part of a plan to strengthen the health workforce.

The New Zealand Graduate School of Medicine will receive more than $150 million from the university — supported by philanthropy — according to the Government, bringing total funding to more than $200 million.

Prime Minister Christopher Luxon said the third medical school for New Zealand would not just be a “significant investment” for the health system but for Hamilton and the Waikato region.

“New Zealand simply isn’t training enough doctors to meet the future needs of our growing aging population or to replace those doctors retiring, and that has to change.”

The new school was a “practical step” to change that by boosting the medical workforce, creating new educational opportunities in the Waikato and helping deliver better care closer to home, he said.

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“It’s certainly a big win for the future of our health workforce; it’s a big win for the Waikato; and, most importantly, for patients.”

Health Minister Simeon Brown said the school would focus on primary care and rural health.

“Today’s decision will enable the University of Waikato to begin construction on new teaching facilities later this year and start planning for clinical placements, while giving more students the opportunity to study medicine in New Zealand,” he said.

Experts have warned that the initial proposal for the facility was likely to be unaffordable. (Source: 1News)

The medical school would add 120 doctor training places annually from 2028, offering a graduate-entry programme “providing a flexible new pathway into medicine that helps attract a broader range of students and build a stronger, more diverse workforce”.

“It’s an innovative model that supports our focus on strengthening primary care, making it easier for people to see their doctor, helping Kiwis stay well and out of hospital.”

The Government approved precisely $82.85 million in direct funding for the project.

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Brown’s office said a full cost-benefit analysis was presented to Cabinet before any proposal was finalised. ACT had negotiated for the analysis to be completed before any binding funding decision could be approved, in its coalition agreement with National.

Universities Minister Shane Reti said the funding decision represented a “real boost for tertiary education in the Waikato”.

“By expanding access to medical training, we’re creating new opportunities for students from across the region and beyond, while also helping to future-proof the local workforce,” he said.

“This is exactly the kind of forward-thinking initiative this Government wants to see from our universities – investing in regional growth, building local capability, and delivering on the needs of rural communities.”

The Health Minister added the new places were “on top of the 100 additional medical training places that are being added over the term of this Government across the University of Auckland and University of Otago”.

Report found more cost effective training could be delivered by the two existing schools and both universities could increase intakes quicker with increased funding. (Source: 1News)

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Auckland and Otago universities had previously offered to train more medical students if that could be supported by the Government.

Pro-Vice-Chancellor Health Sciences at Otago, Associate Professor Megan Gibbons, acknowledged today’s announcement of a third medical school as part of the Government’s strategy to address New Zealand’s healthcare workforce needs.

“We are disappointed that Government did not follow the alternative and more cost-effective option of further increasing the intakes into the country’s existing medical schools,” she said.

“However, any investment that supports growing and sustaining the health workforce is a step toward strengthening care for our communities — particularly in rural and underserved regions.”

Four-year programme to begin in 2028, first graduates by 2032

University of Waikato vice-chancellor Professor Neil Quigley called the announcement a “landmark moment” for New Zealand.

“We will be offering a programme that selects and trains doctors in a fundamentally different way and will complement New Zealand’s two existing medical schools.

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“It will be designed to produce more graduates who choose to become GPs and who want to work in regional and rural communities.”

Quigley said the four-year programme would begin in 2028, with first cohort graduating and entering the workforce in 2032.

Pro vice-chancellor of health Professor Jo Lane said the New Zealand Graduate School of Medicine curriculum would train “the doctors New Zealand needs”.

“Our curriculum will prioritise clinical placements in regional and rural health settings, allowing graduates to experience working with diverse populations while building deep connections in the communities they serve.”

Conclusions: Socioeconomic disparities are associated with ANC facility choice, which in turn affects subsequent decisions regarding facilities for delivery and PNC in Eastern Visayas. As such, facility selection should be guided by healthcare needs rather than socioeconomic status.

Results: Among 1,414 postpartum mothers, 35.6% received ANC at BHS, 34.1% at RHU, 32.7% at hospital/clinic, and 0.6% did not receive ANC. Most deliveries (83.3%) and PNC (61.4%) services occurred in hospital/clinic settings. Mothers who received ANC at a hospital/clinic were more likely to have higher education (aRRR = 7.04, 95% CI: 3.97, 12.50) and be wealthier (aRRR = 2.00, 95% CI: 1.09, 3.69) compared to those who received ANC at BHS. Mothers receiving ANC at RHU (aRRR = 0.52, 95% CI: 0.34, 0.79) or hospital/clinic (aRRR = 0.55, 95% CI: 0.38, 0.78) were less likely to be single with a partner compared to those receiving ANC at BHS. Mothers who received ANC at hospital/clinic were more likely to deliver at a hospital/clinic (aRRR = 8.49, 95% CI: 3.56, 20.26) than at a RHU/BHS, and to receive PNC at a hospital/clinic (aRRR = 2.07, 95% CI: 1.32, 3.24) instead of at a BHS, compared to those receiving ANC at BHS. Mothers receiving ANC at RHU were more likely to also receive PNC at an RHU (aRRR = 16.13, 95% CI: 7.80, 33.36) compared to those receiving ANC at BHS.

Methods: This secondary data analysis uses baseline and one-year follow-up survey data from a quasi-experimental study conducted in September 2023 and 2024. Data from 1,414 women with information on maternal health facility utilization was analyzed. ANC facilities were categorized into four groups: Barangay Health Station (BHS), Rural Health Unit (RHU), hospital/clinic and others. Multinomial logistic regressions were applied, adjusting for socio-economic status and Barangay location, to examine associations between socio-economic factors and ANC facility choice, as well as trends in delivery and PNC facility utilization based on ANC facility type.

Background: This study aims to identify socioeconomic factors associated with the choice of antenatal care (ANC) facilities and to analyze trends in the utilization of health facilities for delivery and postnatal care (PNC) based on the type of ANC facility in Eastern Visayas, Philippines.

1 Introduction

The Philippine government has been actively working to provide universal maternal and child health services (1, 2). In 2019, the Universal Health Care (UHC) Act (Republic Act No. 11223) was implemented to ensure comprehensive maternal health services and equitable access for all women, particularly in underserved areas (3). The Act emphasizes strengthening primary health care by establishing a system where every Filipino is assigned a primary care provider who serves as the initial contact, care navigator, and coordinator within the health system. Access to higher levels of care is coordinated through this provider, except in emergencies or urgent cases (3). In addition, the Act encourages the establishment of Service Delivery Networks to improve coordination and referrals across different facilities (4).

These efforts have led to increases in the percentage of women who received four or more ANC visits, rising from 70% in 2003 to 83% in 2022. Simultaneously, the proportion of women delivering in health facilities with skilled birth attendants in the Philippines has dramatically increased from 38% to 89%. Postnatal care within the first two days after delivery also rose from 34% in 2003 to 75% in 2022 (5, 6).

Despite these improvements, equitable access to antenatal, delivery, and PNC services remains a significant challenge in the country. Geographic challenges and socioeconomic factors continue to pose hinder access to these services (7). Previous studies indicate that women residing in rural areas, with lower income levels, less education, and a higher number of children are less likely to receive prenatal care and give birth at health facilities in the Philippines (8–13). Data from the DHS 2022 further indicate that women from rural areas and lower socio-economic backgrounds are less likely to receive postnatal care compared to their urban and wealthier counterparts (6).

Meanwhile, overcrowding in maternity hospitals is a growing issue in LMICs (14). Despite the availability of primary healthcare options, an increasing number of women pursue hospital-based maternal services in search of higher quality care (15–20). Recent studies indicate that women’s decision to seek care at primary health facilities is largely shaped by their perceptions of the facility’s service capacity to provide timely and necessary care (21). This preference for higher-level facilities exacerbates healthcare disparities and contributes to overcrowding in referral hospitals.

The Philippine government faces several challenges in its efforts to implement Universal Health Care, including strengthening primary care and integrating maternal and child health services. Therefore, a comprehensive understanding of facility utilization is necessary. It is important to investigate where women initially receive ANC and how socioeconomic factors influence their choice of facilities, and how these choices subsequently affect decisions regarding delivery and PNC. Given these circumstances, this study aims to explore the socioeconomic determinants associated with women’s ANC facilities choices and analyze the trends in the selection of health facility for delivery and PNC.

2 Methods

2.1 Study settings and design

The study was conducted in Eastern Visayas, located in the eastern part of the central Philippines (Region VIII). This predominantly rural region has high poverty rates and a maternal mortality ratio that exceeds the national average (22). This cross-sectional study uses data from the baseline survey of a quasi-experimental study that evaluates the Timed and Targeted Care for Family (ttCF) program by World Vision, as detailed in our previous manuscript under review (23). The impact evaluation was conducted in 12 municipalities across Eastern and Western Samar provinces. Of these municipalities, six were located in Eastern Samar province: Taft, General MacArthur, Quinapondan, Giporlos, Oras, and San Julian. The remaining six municipalities are in Western Samar province: Marabut, Basey, San Jorge, Pinabacdao, Hinabangan, and San Sebastian. The baseline survey was conducted in September 2023 and enrolled 1,518 pregnant women or mothers aged 15 to 49 years with one or more children aged 0 to 11.9 months. One year later, 1,313 women were followed up (86.5% out of 1,518).

2.2 Participants

In this study, we included only mothers who provided information about the facilities where they received maternal health care (n = 1,414). Participants with missing data on ANC or PNC facility types, as well as delivery location, were reassessed during the follow-up a year later, resulting in 373 additional responses. After incorporating this information, those who still had missing data on ANC (n = 83), delivery location (n = 19), and PNC service facility type (n = 2) were excluded (Figure 1).

Figure 1

Figure 1. Flowchart of total analytic sample.

2.3 Variables

In this study, the primary outcome variables were the type of ANC and PNC facility, and the delivery location. These variables were derived from responses to the following survey questions: “What kind of health facility did you most often visit during your pregnancy with this baby?” for ANC, “Where did you give birth to this baby?” for delivery, and “Where did you receive postnatal care?” for PNC.

For both ANC and PNC, the responses were categorized into four groups: BHS, RHU, hospital/clinic, and Others. BHSs are community-based primary healthcare facilities that provide basic health services, such as immunizations and health education, and are typically staffed by nurses or midwives. RHUs are more comprehensive public health facilities that offer primary and secondary care—including maternal and child health services, basic treatment, and emergency care—and are usually staffed by doctors, nurses, and other healthcare professionals (24). The “Others” group for ANC (n = 8) was included only in the distribution graph and excluded from the analysis. For the delivery location, the responses were categorized into three groups: BHS/RHU, hospital/clinic, and home/others, as deliveries at BHS were very rare (n = 29).

During the categorization process, all responses were carefully reviewed, and those that did not fit into the predefined categories were placed in the “Others” category. For ANC, responses such as “no health facility” or “not received” were categorized as “Others” (n = 8). For delivery, responses indicating that births occurred at home (n = 76) or in unconventional locations such as “in the car” or “on the road” (n = 8) were categorized as “home/others”. For PNC, responses such as “None”, “Not yet”, or “Don’t know” were included in the “None/Others” category (n = 97).

The “hospital/clinic” category included all types of hospitals and clinics, regardless of whether they were private or public. The original response options included City/District hospital, Private Birthing Facilities, Private Clinics, and Private Hospitals. Any responses that specified the name of a hospital or clinic were also categorized under “hospital/clinic”.

Socioeconomic factors included in the study were age, age of first pregnancy, number of pregnancies, marital status, occupation, education level, asset index, mobile phone ownership, and health insurance. Age and age at first pregnancy were collected as continuous variables and categorized as follows: age was grouped into <25y, 25–34y, and ≥35y, and age at first pregnancy was grouped into <20y, 20–25y, and ≥26y. The number of pregnancies was categorized as 1, 2, or 3 or more. Marital status was categorized into cohabiting, married, single with a partner, and single/widowed/divorced. Occupation was classified as either housewife or employed. Education levels were categorized as primary (including some primary and completed primary), secondary (including some secondary and completed secondary), and more than secondary. The asset index was generated using principal component analysis, based on ownership of various assets, including electricity, radio, TV, landline, freezer, oven, stove, microwave, DVD player, karaoke machine, cable service, air conditioner, watch, mobile phone, computer, bicycle, tricycle, e-trike, animal-drawn cart, car, tractor, boat, improved water source, and improved toilet facility. Mobile phone ownership and health insurance were categorized as “yes” or “no”. For health insurance, “yes” indicated coverage by either PhilHealth or any other health insurance provider.

2.4 Data analysis

Exploratory analysis was conducted for all outcome variables and covariates. Multinomial logistic regression was then used to identify socio-economic factors influencing the choice of ANC facility and to examine trends in delivery and PNC facilities based on the type of ANC facility. For all models, relative risk ratios (RRRs) and 95% confidence intervals (CIs) were estimated, using the BHS or BHS/RHU group as the reference category. These models were adjusted for covariates, including age, age of first pregnancy, times of pregnancy, marital status, occupation, education level, asset index, mobile phone ownership, health insurance, and Barangay location. All variables used in the analysis had no missing values, except for 19 participants with missing asset index data; these were imputed using the median asset index score. Participants who did not receive ANC (n = 8) were excluded, resulting in a total of 1,406 participants. All statistical analyses were performed with Stata v14.0 software (Stata Corp, College Station, TX, USA).

2.5 Ethical approval

The study was approved by the Johns Hopkins Bloomberg School of Public Health Ethics Board (IRB No. 25392) and the Eastern Visayas Health Research and Development Consortium Ethics Review Committee (Protocol No. 2023-023).

3 Results

3.1 Participants' characteristics by type of ANC facility choices

Table 1 presents the characteristics of women based on the type of ANC facility they used. The BHS group had a higher proportion of women aged 35 or older (20.3%) compared to other groups, but the hospital/clinic group had a higher average age at first pregnancy. Across all groups, many women had 3 or more pregnancies (45.6%). Nearly half of the women were cohabiting (48.0%) with the BHS group having a higher proportion of single with partners (31.5%) and the hospital/clinic group having more married women (33.5%). Higher proportions women with better education, higher wealth status, mobile phone ownership, and health insurance were observed in the hospital/clinic group, followed by the RHU group, and then the BHS group.

Table 1

Table 1. Sociodemographic characteristics based on ANC facility type (n = 1,406)a.

3.2 Facility choices for prenatal, delivery, and postnatal care by type

Of the 1,414 mothers, 99.4% (n = 1,406) received antenatal care at a health facility, 93.4% (n = 1,320) delivered at healthcare facilities, and 93.1% (n = 1,317) accessed postnatal care. Specifically, 34.6% received antenatal visits at BHS, 33.1% at RHU, and 31.8% at hospital/clinic, and 0.6% had no ANC. Delivery locations were 80.9% hospital/clinic, 10.4% RHU, 2.1% BHS, and 6.6% at home or others. For PNC, 59.6% of mothers received care in hospital/clinic, 19.9% in RHU, 13.6% in BHS, and 6.9% had no PNC (Figure 2). The hospital/clinic category was predominantly hospitals. Most deliveries (73.1%) and over half of PNC (53.5%) occurred in hospitals, compared to 7.9% and 6.1%, respectively, in clinics (Supplementary Figure S1).

Figure 2

Figure 2. Distribution of facility utilization for antenatal, delivery, and postnatal service (n = 1,414).

3.3 Patterns of facility utilization for ANC, delivery, and PNC

Figure 3 shows the proportion of women using different health facilities—BHS/RHU, hospital/clinic, and others—at each stage of maternal care. The most common pattern, observed in 34.8% of women, involved using BHS/RHU for ANC, and hospital/clinic for both delivery and PNC. The second most common pattern, seen in 23.5% of women, involved using hospital/clinic for all three stages of maternal health care. The third pattern, followed by 13.2% of women, involved using BHS/RHU for ANC, hospital/clinic for delivery, and returning to BHS/RHU for PNC. The fourth pattern, observed in 10.2% of women, involved using BHS/RHU for all three stages of care.

Figure 3

Figure 3. Patterns of facility utilization for antenatal, delivery, and postnatal service (n = 1,414).

3.4 Socioeconomic factors affecting ANC facility utilization

In the multinominal logistic regression analysis, women who received ANC at RHU or hospital/clinic were less likely to be single with a partner, compared to mothers who received ANC at BHS (aRRR = 0.52, 95% CI: 0.34, 0.79; aRRR = 0.55, 95% CI: 0.38, 0.78) (Table 2). Mothers who received ANC at hospital/clinic were more likely to have higher levels of education (aRRR = 7.04, 95% CI: 3.97, 12.50) and wealth status (aRRR = 2.00, 95% CI: 1.09, 3.69), compared to those who received ANC at BHS. Women who received ANC at hospital/clinic were also more likely to belong to the 25–34 age group (aRRR = 1.51, 95% CI: 1.04, 2.20), compared to mothers who received ANC at BHS.

Table 2

Table 2. Adjusted relative risk ratios and 95% confidence intervals for socioeconomic factors associated with ANC facility choice (n = 1,406)a,b.

3.5 Trends in delivery location by type of ANC facility

Table 3 presents the association between ANC facility type and place of delivery. Compared to mothers who received ANC at BHS, those who received ANC at hospital/clinic were more likely to deliver at hospital/clinic rather than at RHU/BHS (aRRR = 8.49, 95% CI: 3.56, 20.26).

Table 3

Table 3. Adjusted relative risk ratios and 95% confidence intervals for delivery location based on the type of ANC facility (n = 1,406)a,b.

3.6 Trends in PNC facility utilization by type of ANC facility

Table 4 presents differences in PNC facility selection based on ANC facility selection. Mothers who received ANC at hospital/clinic were more likely to receive PNC at hospital/clinic rather than at BHS (aRRR = 2.07, 95% CI: 1.32, 3.24), compared to those who received ANC at BHS. Mothers who received ANC at RHU were more likely to receive PNC at RHU (aRRR = 16.13, 95% CI: 7.80, 33.36), or at hospital/clinic (aRRR = 5.11, 95% CI: 2.71, 9.60) rather than at BHS. Mothers who received ANC at RHU were more likely to forgo PNC (aRRR = 7.73, 95% CI: 3.92, 15.21), compared to those who received ANC at BHS.

Table 4

Table 4. Adjusted relative risk ratios and 95% confidence intervals for PNC facility utilization based on the type of ANC facility (n = 1,406)a,b.

4 Discussion

This study examined socioeconomic determinants associated with the choice of ANC facilities and analyzed trends in the utilization of health facilities for delivery and PNC based on the type of ANC facility in Eastern Visayas, Philippines. The majority of women (67.7%) received ANC at BHS and RHU. Most women preferred hospital/clinic, with 80.9% choosing these facilities for delivery and 59.6% for PNC. Women who received ANC at hospital/clinic were more likely to maintain continuity of care at the same facility for delivery and PNC. Likewise, women who received ANC at RHU were more likely to receive PNC at RHU rather than at BHS. Such patterns suggest that the initial choice of ANC facility significantly influences subsequent maternal health decisions.

The association between higher socioeconomic status and the utilization of hospital/clinic for ANC highlights disparities in access to maternal health services. This suggests that economic and educational levels are key determinants of facility choice, consistent with previous research identifying these factors as important in the utilization of ANC services (10). The type of health facilities where women receive antenatal care is closely linked to the quality of care provided. A study analyzing 91 national surveys in low and middle-income countries (LMICs) reported that, despite high coverage of antenatal care, the quality of care remains significantly lower and inequitable (25).

In the Philippines, BHS is not intended to serve as a routine delivery facility, but rather is designated for emergency situations. Women can give birth at RHU that are certified as delivery facilities; however, the number of RHU with such certification in the surveyed areas are limited. Of the 12 RHU, 5 received certification for delivery services in 2023 and 7 in 2024. While a portion of the delivery rate in hospitals can be attributed to referrals from primary health facilities like BHS and RHU, the high rate of PNC in hospitals is likely due to women typically receiving PNC prior to discharge following delivery.

In the Philippines, maternal healthcare guidelines recommend hospital deliveries for high-risk pregnancies (26), which includes first-time mothers, teenage pregnancies, and women who have had five or more previous births. The Department of Health's Administrative Order No. 2019-0026 specifies that such cases should be managed under a doctor's supervision in facilities capable of providing Comprehensive Emergency Obstetrics and Newborn Care (CEmONC) (26). While this policy ensures that pregnant women receive appropriate care and support, it also likely contributes to the high rate of hospital utilization for deliveries.

The Philippine government launched the Health Facility Enhancement Program (HFEP) in 2008 to enhance primary healthcare services and organize hospital levels more effectively, thereby reducing overcrowding in major referral hospitals (27). The HFEP focuses on strengthening infrastructure and expanding access across government health facilities, such as BHS and RHU. Achieving this goal requires investment in healthcare workforce recruitment and training, ensuring sufficient medical supplies and infrastructure (28), and obtaining the licenses and certifications needed to meet national healthcare standards (24). Strengthening the capacity of BHSs and RHUs to provide quality antenatal and postnatal services can reduce reliance hospitals or private clinics, despite the economic and time burdens involved during the perinatal period (8).

Enhancing continuity of care across different levels of health facilities is another key recommendation. For women living far from hospitals, utilizing antenatal and postnatal care services at BHS or RHU can enable them to access timely services. However, a well-functioning referral system is a prerequisite for this approach. Prioritizing the implementation of the Universal Health Care Act's Service Delivery Network is important, as it facilitates integration and coordination of health services across various facilities (3). This ensures that women receive timely and appropriate care at each stage of pregnancy by establishing clear referral pathways between primary health facilities, such as BHS and RHU, and higher-level health facilities like hospitals and clinics (29).

Current maternal healthcare guidelines in the Philippines recommend hospital deliveries for all first-time mothers to ensure safety (26). However, it may be worth reconsidering this policy, as broadly classifying all first-time mothers as high-risk results in a significant number of mothers seeking care at hospitals rather than at BHS or RHU (30). Instead of applying this classification universally, it would be more appropriate to limit its application to cases where prenatal check-ups indicate abnormal findings. To support this, appropriate antenatal care must be made available at BHS and RHU to effectively identify any abnormalities. This approach could reduce the burden on hospital facilities while ensuring that high-risk pregnancies receive the appropriate level of care.

4.1 Strengths and limitations

To date, most studies have focused on the frequency of ANC service use and its determinants, without examining how facility choice during ANC affects the location of delivery and postnatal care (10, 13, 25). To the best of our knowledge, the present study is the first to holistically investigate the socio-economic factors influencing health facility choices for both maternal and newborn care. This study stands out by focusing on the types of facilities used throughout the maternal care continuum, providing a broader understanding of maternal health service utilization. The large sample size and robust statistical analysis also enhance the reliability of our findings.

Nevertheless, this study has several limitations. First, although the distance was adjusted for barangay location, the distance from home to the health facility may still be a contributing factor. Second, we did not differentiate between public and private hospitals, which may have distinct characteristics that affect service utilization. Moreover, our research did not include Geographically Isolated and Disadvantaged Areas (GIDA), where physical access to care is particularly challenging. This may limit our understanding of health facility utilization among the most underserved populations. Lastly, women without complete data of ANC, delivery, or PNC location, as well as those who reported not receiving ANC services were excluded in the analysis. However, their socioeconomic and demographic characteristics are comparable to the analytic samples (Supplementary Table S1).

5 Conclusion

The findings highlight that socioeconomic disparities are associated with the choice of ANC facility, which in turn is associated with decisions on where to seek delivery and PNC in Eastern Visayas, Philippines. Women from higher economic backgrounds were more likely to utilize hospitals and clinics for their maternal care. Additionally, the study underscores the importance of improving the quality and accessibility of primary healthcare facilities, such as BHS and RHU, to enhance service delivery for antenatal and postnatal care. By reevaluating current maternal healthcare guidelines and implementing a robust referral system, the government may reduce the burden on hospitals while ensuring that all women receive timely and appropriate maternal care. Health facility selection should be guided by clinical needs rather than socioeconomic factors. Addressing these disparities is essential to improving maternal health outcomes and promoting health equity in the region.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were approved by Johns Hopkins Bloomberg School of Public Health Ethics Board, Eastern Visayas Health Research and Development Consortium Ethics Review Committee. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants' legal guardians/next of kin.

Author contributions

AC: Writing – original draft, Writing – review & editing, Data curation, Visualization. HK: Writing – review & editing, Data curation, Validation. SP: Data curation, Writing – review & editing, Validation. HSK: Writing – review & editing, Data curation, Validation. RJ: Project administration, Validation, Writing – review & editing. DL: Writing – review & editing, Project administration, Validation. HJ: Project administration, Validation, Writing – review & editing. JJ: Project administration, Supervision, Writing – review & editing. YK: Conceptualization, Data curation, Supervision, Validation, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was based on the title of “KOICA Eastern Visayas Maternal Newborn and Child Health Project” funded by the Korea International Cooperation Agency, implemented by World Vision Korea between 2021 and 2025 (No. 2021-033).

Acknowledgments

We acknowledge the Korea International Cooperation Agency (KOICA) for funding this study. We thank the Tacloban office of World Vision Philippines and World Vision Korea for requesting research permission from local governments and for seeking the support of each Barangay captain for field data collection. We appreciate the Alliance for Improving Health Outcomes (AIHO) for recruiting enumerators and coordinating the overall survey procedures. Special thanks to Aileen Sefuentes and Ritchel Quilaga for supervising data collection, as well as the 24 enumerators for their efforts in data collection through household visits. We thank Seyoung Kim for the initial data analytic support. We also thank Brandon Kwon for reviewing the manuscript and editing the English.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that Generative AI was used in the creation of this manuscript. Generative AI (ChatGPT Version 4) was utilized to enhance the clarity, expression, and grammatical accuracy of the content in this paper.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgwh.2025.1575896/full#supplementary-material

Supplementary Figure S1 | Distribution of facility utilization for antenatal, delivery, and postnatal services (n = 1,414).

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Rural hospitals across the U.S. say they’re being forced to consider tough choices — like cutting services for children or cancer patients — after President Donald Trump signed into law a sprawling domestic policy bill that includes sweeping cuts to not only Medicaid but the Affordable Care Act, as well.

Benjamin Anderson, CEO of Hutchinson Regional Healthcare System, oversees a 180-bed hospital that serves as the only hospital for many residents in rural South Central Kansas.

Anderson said he’s evaluating how the hospital and its broader health system will be able to afford to keep offering all of its services, which includes hospice and home care, inpatient mental health treatment, and a cardiology program.

Services that aren’t traditionally profitable — such as women’s health and pediatric care — will be the hardest to sustain, Anderson said. He added the system is trying to see which programs can be saved.

The cuts in the bill will also mean the hospital will have to continue its hiring freeze — a move that risks burning out staff members already strained from the pandemic and high patient loads.

The real test, he said, will come this fall when flu, Covid and RSV cases are expected to rise.

“What this does is put us at risk when the respiratory season hits,” Anderson said. “We’re at real risk of wearing out the staff we have right now.”

‘Painful cuts’

Rural hospitals rely heavily on Medicaid funding because they typically serve a higher share of low-income patients.

An estimate from KFF, a health policy research group, found that Trump’s legislation, dubbed the “big, beautiful bill,” could lead to about 17 million people losing coverage due to the changes in Medicaid and the ACA.

More than 300 rural hospitals in the U.S. are at risk of closing down because of the bill, Democratic lawmakers wrote in a letter last month. If more of their patients are uninsured, these hospitals risk not getting paid for their services, the letter said.

The bill includes nearly $1 trillion in cuts to Medicaid, mainly through work requirements, as well as a change to how states are able to help fund their programs known as the provider tax.

It also makes changes to the ACA, including additional paperwork requirements to renew coverage each year, and allows government subsidies that help people pay for health plans to expire at the end of this year. The Congressional Budget Office, a nonpartisan agency that provides budget and economic information to Congress, estimated that nearly 4 million people would lose their coverage in 2026 if the subsidies weren’t extended.

Edwin Park, a research professor at the Georgetown University McCourt School of Public Policy, said the changes to Medicaid pose the greatest threat to rural hospitals. Many of those changes won’t take effect until 2027 at the earliest, but Park said he doesn’t expect states and rural hospitals to wait until the last minute to prepare.

Last week, Nebraska-based Community Hospital said it’s shutting down Curtis Medical Center, a clinic in Curtis — a town of around 900 people — citing, in part, anticipated cuts from the government.

“They’re going to start making cuts now,” Park said. “So, instead of a cliff, they’re trying to cut now so that they don’t have all the painful cuts in a single year.”

Kevin Stansbury, the CEO of the Lincoln Community Hospital and Care Center, a 25-bed rural hospital in Hugo, Colorado, said he may soon have to start cutting services for patients, including long-term care.

The hospital gets about $300,000 a month in provider tax reimbursements, which Stansbury said is still only enough to break even. Losing those reimbursements will have a significant impact.

He said he’s holding early conversations with private insurers about boosting the reimbursement payments they give to rural hospitals to help offset the Medicaid and ACA losses.

“We’ll be working with other hospitals in the state and the state Medicaid agency to see what, if anything, can be done to mitigate the impact,” he added.

A fig leaf

Trump’s bill does include $50 billion for rural hospitals. Those funds will be distributed by the Centers for Medicare and Medicaid Services over five years.

Park called the federal funds a “fig leaf,” noting that it won’t be enough to offset the losses from the Medicaid and ACA cuts.

Toniann Richard, CEO of HCC Network — a community health center with six locations in Missouri — said the government funds appear to focus on infrastructure and improving efficiency at rural hospitals, rather than helping offset their financial losses. About 40% of the center’s patients are on Medicaid.

“While I think the sentiment is appreciated, it’s a little disappointing,” she said.

Richard isn’t planning any immediate changes but said rural hospitals in her state may soon face cuts or be forced to scale back specialty services — such as cardiology and oncology — that often go unreimbursed.

In recent years, several rural hospitals in eastern Missouri and the Bootheel region have shut down due to financial strain.

One of Richard’s primary focuses right now is ensuring her patients, especially those with ACA coverage, make sure they still qualify for their health insurance.

“We will be really focusing on running eligibility checks for people when they come in to help them stay in the know,” she said.

In California, both urban and rural hospitals could lose up to 30% of their revenues over the next decade, meaning many will be forced to make difficult decisions, including cutting access to services, Carmela Coyle, president and CEO of the California Hospital Association, said in an emailed statement.

It “will mean real harm to real people in communities large and small across California,” Coyle said. “These are the largest cuts to our health care system ever enacted and are far too deep for hospitals simply to ‘absorb’.”

‘Outrageous’ health care costs

Stephanie Huser, who runs a farm in Fredonia, Kansas, has five children, all of whom are on Medicaid.

Fredonia, a town of about 2,000 people, is in one of the poorest regions of the state.

Huser said that if her local provider were to shut down, she would likely have to travel to Kansas City — a 2 1/2-hour drive — to get care.

“I know it will completely impact us,” she said. “It’s not the people who aren’t working who will be affected. It’s the self-employed people, like us, on family farms, who, when we get a health insurance quote, it’s outrageous.”

Dr. Jennifer Bacani McKenney, Huser’s doctor and the owner of Fredonia Family Care, said the clinic isn’t currently considering closure or service cuts. Instead, they’re focused on helping patients complete the paperwork necessary to keep their coverage — something that affects both patients and providers.

“As family docs in a rural area, we’re also the ER docs,” she said. “Since more people will be uninsured, we’ll probably see more of them in the ER, which, of course, is bad for the hospital because they won’t be getting paid.”

In Vermont, state officials and hospital leaders are under enormous pressure to reduce health care costs as fast as possible. By law, they need to cut over $100 million in hospital spending next year. They’ve set a goal of cutting costs by twice that amount before the year’s end, in a desperate attempt to bring down ballooning health insurance premiums.

So when Copley Hospital in Morrisville recently announced a plan to close its labor and delivery unit by November, leaders at the Agency of Human Services said they support the decision, and that it’s the beginning of more changes to come.

“That’s a decision by the board, and yet it is consistent with the direction that we are going,” Secretary Jenney Samuelson said in a phone interview. “We are going to see other hospitals have to make very difficult decisions.”

Lexi Krupp / Vermont Public Despite relatively low volumes, Copley was among several hospitals found to “have the capability to recapture enough volume for their OB services to be sustainable,” according to Dr. Bruce Hamory, the lead author of a 2024 report commissioned by the state to transform the health care system.

Their support places the agency in an awkward position as it purports to ensure affordable, high quality care remains available across the state.

Copley is the only place in Lamoille County where families can give birth, and at it’s least 45 minutes from the next closest hospital. Between 150 and 210 babies have been born there each year for the past decade.

It’s well established that closures of childbirth units in rural counties nationwide have led to worse outcomes for mothers and infants, including an increase in emergency room and preterm births, as well as negative long-term impacts on the local economy.

More: Concerns grow as Copley Hospital set to vote on fate of birthing center

In a letter to the hospital board, leaders of a regional initiative focused on improving outcomes for mothers and infants based at Dartmouth Health said the center “consistently meets or exceeds state and regional quality metrics.” They warn that pregnant patients will continue to seek urgent care in the emergency department, leading to “potentially dangerous situations.”

I view Copley as a harbinger of things to come, in the sense that all of us are going to have to wrestle with trade-offs. Michael Costa, president of Gifford Medical Center

And while the Agency of Human Services has framed their support for the closure around affordability, Copley Hospital has some of the lowest commercial prices in the state, according to a national hospital transparency study. The model of care at Copley, where midwives are the attendants for the majority of births, has also been shown to reduce overall health care costs.

Regardless, closing the unit will save Copley millions of dollars a year, which state officials say will ultimately translate to lower health insurance premiums. Most directly, it will improve the hospital’s finances, even at the cost of access to care. It’s a reality many hospital leaders acknowledge.

“I view Copley as a harbinger of things to come, in the sense that all of us are going to have to wrestle with trade-offs,” said Michael Costa, the president of Gifford Medical Center.

Lexi Krupp / Vermont Public Copley Hospital has some of the lowest commercial prices in the state. Regardless, closing the unit will save the hospital millions of dollars a year, which state officials say will ultimately translate to lower health insurance premiums.

Hundreds of hospitals across the country have closed childbirth units in recent years, including at Springfield Hospital in Vermont. Their unit closed in 2019, in the months before the hospital declared bankruptcy. Experts say continued closures at rural hospitals shouldn’t be surprising because of the current policies around financing for maternity care.

“Reimbursement rates generally for labor and delivery are below cost. They’re low across the board,” said Katy Backes Kozhimannil, a professor at the University of Minnesota and co-director of the Rural Health Research Center. “It’s an impossible math problem.”

Other hospitals stand by obstetric care

Other rural hospitals in the state with similar or fewer births than Copley have said they will keep their labor and delivery services open, even as some face negative operating margins or limited cash.

“We’re not going anywhere,” said Tom Frank, the CEO of North Country Hospital in Newport, where 70% of patients have coverage from Medicare or Medicaid. “Come hell or high water, we’re going to continue to provide that service.”

In recent years, the Newport hospital has lost several specialty services including pulmonology, neurology and urology as providers have left and the hospital has opted not to replace them. Frank said they’re not planning to close any more patient services.

Come hell or high water, we’re going to continue to provide that service. Tom Frank, president of North Country Hospital

Instead, the hospital is making other changes to reduce costs — they’re sharing a pharmacy director with Northeastern Vermont Regional Hospital in St. Johnsbury, and recently opened a sleep clinic that both hospitals own.

“We’re working very, very closely together on how we can do more things as sort of a Northeast Kingdom health system than individual hospitals,” Frank said.

Zoe McDonald / Vermont Public The main entrance to North Country Hospital in Newport, where 70% of patients have coverage from Medicaid or Medicare.

At Gifford Medical Center in Randolph, President and CEO Michael Costa said the hospital is committed to maintaining and growing the birthing center, “but it’s an enormous financial challenge.”

Last year, the hospital ended their chiropractic and urogynecology services. They have no plans to cut additional patient services in the next year, but will continue to reassess.

“I think every Vermont health care organization, including Gifford, is going to have to go through that exercise on a year by year basis,” Costa said.

They’re experimenting with other ways to bolster revenue, like accepting transfers from larger hospitals like Dartmouth Hitchcock Medical Center when those hospitals are full. So far, the strategy “to be a pressure release valve” has worked — the number of patients admitted at Gifford has grown by 50% in the last six months, according to Costa.

Obstetrical care is the one thing that every human uses at least once in their life — if that’s not essential care, I don’t know what is. April Vanderveer, president, Vermont chapter of the American College of Nurse-Midwives

Eventually though, he said the payment model needs to change, so hospitals are provided a set amount to take care of their community, rather than a “fee-for-service” model, providing payment for individual office visits, tests and procedures.

“Maintaining and strengthening our commitment to women’s health and the birthing center is, in part, a bet that after many, many years in fee-for-service, that insurance companies and government payers are going to get this right,” Costa said.

A wake up call

Until then, providers worry about the future of maternal health care in Vermont and other basic community services as the state scrambles to cut spending as fast as possible.

“I think this should be a wake up call to the state and our legislators and our health care reformers,” said April Vanderveer, president of the state chapter of the American College of Nurse-Midwives.

“Obstetrical care is the one thing that every human uses at least once in their life — if that’s not essential care, I don’t know what is,” she said.

“If we lose whole counties that provide that care, what are we doing as a state?”

AI Use Cases for Clinical and Financial Operations in Rural Healthcare

National Rural Health Association CEO Alan Morgan says three common use cases for AI come up in his conversations with hospitals and health systems.

The first is deploying ambient AI to document patient appointments. This can help practitioners pay more attention to patients’ needs while alleviating the burden of note taking. “It’s amazing how much time this is freeing up,” Morgan says. “I think this is potentially the greatest benefit we may see coming from AI.”

Using AI to take notes improves the patient experience, Kwong explains, as practitioners no longer focus exclusively on their computer keyboard. Beyond the appointment, AI models can assess a patient’s records and flag issues worth a follow-up. For example, if a patient mentions in many visits that they’re having difficulty falling asleep, an AI model trained to detect patterns may flag that issue and prompt the health system to follow up.

“AI can help identify patterns that a doctor may not see at first, or that they may initially think is an offhand comment,” Kwong says. This scenario tends to come with little resistance, as it provides additional information to providers without explicitly telling them what to do.

The second is AI-based second opinions, which can help to reduce diagnostic errors. While hallucinations in AI models and biases in training data sets remain issues, the potential to access consultations in a matter of seconds has a clear benefit, Morgan notes. This is especially true in rural settings, where specialists may be hundreds of miles away or unavailable outside of normal business hours.

RELATED: Here are 13 ways AI enhances healthcare operations, patient care and treatments.

The third is streamlining billing and coding — a use case critical for the survival of rural organizations. Roughly one-third of rural hospitals are at risk of closure due to financial problems that stem from the cost of care delivery, the limitations of federal assistance and low financial reserves, according to a report from the Center for Healthcare Quality and Payment Reform.

Morgan adds that rural hospital leaders see AI in the revenue cycle as a response to insurers’ use of AI to assess claims — a practice facing class-action lawsuits.

In a podcast with the Rural Health Information Hub, Jordan Berg, director of the National Telehealth Technology Assessment Resource Center indicates applying AI to the revenue cycle is more than a matter of automating routine tasks. With the right AI tools, he says, organizations can ensure services are billed at the appropriate level, notify vendors and patients when bills are due, and identify opportunities for further revenue cycle optimization, “all with very minimal input from users and stakeholders.”

Additional use cases for AI in rural settings include optimizing workflows in the electronic health record (EHR), augmenting diagnosis and decision support, deploying mobile clinics with practitioners supported by AI agents, and improving scheduling and follow-up messaging. These examples work well because they don’t cause much friction.

“Patients are fine with getting an automated appointment reminder call,” Kwong says. “For organizations that have limited resources, a tool like that can be a good investment.”

READ MORE: Revolutionize prior authorizations with AI.

Lack of Policy Isn’t Hindering AI Adoption for Rural Healthcare

One wrinkle for rural, independent and community health systems looking for guidance on where and how to best use AI is the lack of direction from Capitol Hill. Recent regulations have closely defined the implementation of EHR systems, the acceptable use cases for telehealth, and the standards and infrastructure necessary to exchange health information, among other things.

Meanwhile, no such framework exists for AI in healthcare. Morgan says this isn’t surprising; given the typical long on-ramp for technology adoption in healthcare, policy moves at a slow pace. Right now, he adds, “it seems very hands-off.”

The Trump Administration’s proposed spending bill includes a 10-year pause on state or local AI laws in lieu of overarching federal regulation with few compliance hurdles. “It’s a very volatile time, and policymakers are still feeling their way around that,” Kwong says.

Even without the guardrails of federal policy — or a body of empirical research into how rural healthcare organizations are using AI — adoption appears to be taking off, Morgan says. “I’ve seen a lot of fads,” such as rolling out robots in hospitals, “but AI has such amazing potential, and we’re basically talking about utilization picking up in just the last year.”