_MD__MPH_PhD.png)
Changes in Health Facility Readiness for Providing Quality Maternal and Newborn Care After Implementing the Safer Births Bundle of Care Package in Five Regions of Tanzania
by
, , , , and
Damas Juma
1,2,*, 
Ketil Stordal
3,
Benjamin Kamala
4,5,
Dunstan R. Bishanga
5,6,
Albino Kalolo
7,
Robert Moshiro
4,8,
Jan Terje Kvaløy
9,10,
Godfrey Guga
4 and
Rachel Manongi
1 1
School of Public Health, KCMC University, Moshi P.O. Box 2240, Tanzania
2
Kigoma Regional Secretariat, Kigoma P.O. Box 125, Tanzania
3
Department of Pediatric Research, Institute of Clinical Medicine, University of Oslo, 03128 Oslo, Norway
4
Department of Research, Haydom Lutheran Hospital, Haydom, Manyara P.O. Box 4000, Tanzania
5
Department of Epidemiology and Biostatistics, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam P.O. Box 65001, Tanzania
6
Ifakara Health Institute, Dar es Salaam P.O. Box 70373, Tanzania
7
Department of Public Health, St. Francis University College of Health and Allied Sciences, Ifakara P.O.Box 175, Tanzania
8
Department of Paediatrics and Child Health, Muhimbili National Hospital, Dar es Salaam P.O. Box 65000, Tanzania
9
Department of Mathematics and Physics, University of Stavanger, 4036 Stavanger, Norway
10
Department of Research, Stavanger University Hospital, 4068 Stavanger, Norway
*
Author to whom correspondence should be addressed.
Healthcare 2025, 13(23), 3060; https://doi.org/10.3390/healthcare13233060
Submission received: 28 September 2025
/
Revised: 14 November 2025
/
Accepted: 19 November 2025
/
Published: 26 November 2025
(This article belongs to the Special Issue Continuous Quality Improvement and Patient Safety in Healthcare)
Abstract
Background: Maternal and newborn morbidity and mortality remain a pressing challenge with uneven progress globally and in Tanzania. The capacity of health facilities to provide quality care is critical to improving outcomes. This study aimed to assess changes in health facilities’ readiness to provide quality maternal and newborn care, and hence aimed to inform improvements in quality-of-care interventions in Tanzania. Methods: A before and after assessment of 28 comprehensive emergency obstetric and newborn care health facilities implementing the Safer Births Bundle of Care package in five regions of Tanzania was carried out in December 2020 and January 2023. We adapted the World Health Organization’s Service Availability and Readiness Assessment tool, which covered amenities, equipment, staff, guidelines, medicines, and diagnostic facilities. Composite readiness scores were calculated for each category and results were compared at the health facility level. For categorical variables, we tested for differences by Fisher’s exact test; for readiness scores, differences were tested by linear fixed and mixed model analyses, considering dependencies within the regions. We used p < 0.05 as our level of significance and measured change from baseline using a paired t-test. Results: The overall readiness improved significantly from 67.6% to 83.7% (p < 0.05). Statistically significant improvements were seen in medical equipment (77.1% to 94.0%), diagnostic/treatment commodities (69.3% to 83.1%), and availability of guidelines (50.8% to 96.7%). Changes in amenities (78.1% to 84.2%) and staff (63.0% to 61.7%) were not significant. The overall readiness improved in all facility types and the change was statistically significant in district hospitals and health centres (p < 0.05). There were significant differences in improvement between regions (p < 0.05) Conclusions: The overall readiness has improved significantly, reflecting a positive change. However, there remains a need for further enhancement, particularly in terms of staffing, to ensure high-quality maternal and newborn care. Authorities should take swift action to address the identified gaps, selecting the most effective and practical interventions while closely monitoring progress in readiness and sustaining the gains.
1. Introduction
Maternal and neonatal mortality rates remain a pressing global issue. In recognition of this challenge, a worldwide consensus was reached in 2015, setting the Sustainable Development Goals (SDG). SDG 3 set forth to reduce maternal mortality to 70 per 100,000 live births and neonatal mortality to 12 per 1000 live births by 2030 [1]. Progress to reach these goals has been uneven, with some countries making little to no advancement [2]. In 2023, approximately 260,000 women worldwide lost their lives due to pregnancy- and childbirth-related complications, resulting in a maternal mortality rate of roughly 197 per 100,000 live births [3,4]. The global neonatal mortality has declined from 31 in 2000 to 17 per 1000 live births in 2023 [5].
Tanzania, like many developing nations, continues to face higher maternal mortality rates than the global target, despite significant improvements [1,6]. In 2012, the country recorded a maternal mortality rate of 454 per 100,000 live births, which has since declined to 104 per 100,000 [6]. However, neonatal mortality has only slightly improved, decreasing from 26 per 1000 live births in 2010 to 24 per 1000 in 2022, highlighting the need for intensified efforts to meet global benchmarks [6,7].
Despite global efforts to reduce preventable mortality, progress is often hindered by systemic health system challenges such as inadequately skilled personnel and lack of appropriate protocols, necessary infrastructure, essential medicines, and reliable diagnostic tools [2,8,9].
For healthcare to be of high quality, facilities must be sufficiently prepared [8,10]. According to the World Health Organization (WHO), facility readiness refers to the ability of a health centre to provide the services it advertises [8]. Health facility readiness is indispensable not only for achieving positive health outcomes, experience, and trust but also for building health system resilience and achieving universal health coverage [11].
This study examined the readiness of health facilities before and after the 3-year continuous quality improvement (CQI) initiative, the Safer Births Bundle of Care (SBBC). The SBBC integrates scientifically validated clinical and training innovations with new strategies to establish CQI processes and sustain enhanced care, and it commenced in Tanzania in 2020 [12,13,14]. The bundle comprises clinical innovations including the Fetal Heart Rate Monitor (MOYO), newborn heart monitor (Neobeat), and upright bag-mask. Training innovations include a smart training manikin (NeoNatalie Live) for simulating neonatal resuscitation and providing feedback, and Mama Natalie for simulation training in postpartum hemorrhage management. Continuous QI is integrated through regular, on-the-job, low-dose, high-frequency, simulation-based training. Adequate training of local facility champions, who can facilitate CQI simulation training, is considered essential for these processes to occur and stimulate a gradual, sustainable culture change [13,15].
The goal of this study was to evaluate facility readiness to support SBBC implementation and provide insights for other stakeholders seeking to improve the quality of healthcare services.
2. Materials and Methods
2.1. Study Design and Setting
This before and after study was conducted in 28 health facilities in five selected regions of Tanzania: Manyara, Tabora, Geita, Shinyanga, and Mwanza [12]. The initial facility assessment was performed before the implementation of SBBC and then another assessment was performed three years after the implementation in the same facilities. These health facilities were selected based on the high burden of maternal and perinatal mortality and the volume of deliveries, and absence of other similar interventions. The selected regions account for about 25% of deliveries and about 35% of all maternal and newborn deaths in the country [12]. The annual average number of births that occurred during the study ranged between 400 and 8000 across the study facilities [13]. Two SBBC facilities were excluded from this study because baseline data were not collected, as the decision from the regional and ministry authorities was still pending during data collection, regarding a similar intervention.
The health delivery system in Tanzania is pyramidal, with dispensaries (small outpatient facilities) meant to serve a village at the bottom. Then, there are inpatient health centres, followed by district hospitals (referral points for health centres and dispensaries). Higher up the pyramid, we have regional and then national hospitals. Some health centres and all hospitals are expected to provide comprehensive emergency obstetric and newborn care (CEmONC) services. Health centres typically refer complex cases—or in situations where essential medical personnel or supplies are unavailable—to district hospitals, which may then escalate referrals to regional hospitals. Dispensaries do not provide CEmONC services.
This study was conducted in CEmONC centres where nine cardinal items are expected to be offered: parenteral antibiotics, parenteral anticonvulsants, parenteral oxytocics, assisted delivery, manual removal of the placenta, removal of retained products of conception, basic neonatal resuscitation, cesarian section, and blood transfusion [16].
2.2. Data Collection
The data collection for the readiness assessment was performed using a questionnaire adapted from the WHO’s Service Availability and Readiness Assessment (SARA) tool that was initially developed with the participation of several partners to systematically gauge and monitor health services by generating tracer indicators related to the services including emergency obstetric care [17]. We assessed amenities, equipment, staff, guidelines, medicines, and diagnostic facilities. It was administered by trained research teams, composed of medical and nursing health workers with university degrees, to facility and maternity ward in-charges (medical doctors or nurse trained managers). Data collectors were trained for two days at Haydom Research Centre on the data collection tools and data collection process. Data were collected using an interviewer-administered electronic Open Data Kit and then transferred to Excel. Data collection for facility readiness took place first between December 2020 and January 2021 (baseline) and then in December 2023 (endline).
2.3. Variables
We assessed 58 items across five domains: seven for amenities, fifteen for basic equipment, eleven for diagnostic and treatment commodities, eleven for staff, and fourteen for guidelines. A 0–1 item score was assigned for each item, according to whether the item was in place or not at a facility. For single item considerations, the percentage of facilities with the item in place was calculated. For each facility, readiness scores for each domain were calculated as the average of the item scores within that domain. The overall readiness was calculated as the average of the readiness scores for each domain, thus giving equal weight to each of the five domains [17].
2.4. Data Analysis
The data collected were entered into R software version 4.4.1 for analysis. A comparison of item scores within domains across different levels of facilities was conducted. Fisher’s exact test was used to test for any differences in item scores across different types of health facilities. The comparison between the baseline readiness and endline readiness was performed by comparing the average readiness of each domain and overall readiness at the baseline and endline using a paired t-test. For readiness scores, differences were tested by a linear mixed model analysis, considering dependencies within regions. To test for differences in changes between regions, a linear fixed effect model adjusting for facility level was used. The appropriateness of the models was checked by residual plots. We used 0.05 as our level of significance. Due to many tests, for each table with significant sub-scores an indication is given of which tests remain significant after a per-table Bonferroni adjustment for multiple testing.
3. Results
The overall readiness in the 28 studied facilities changed from 67.6 percent in 2021 to 83.7 percent in 2023 as shown in Figure 1. The change in overall readiness was statistically significant (p < 0.0001), as well as the average scores for commodities, equipment, and guidelines as seen in Table 1. The change in amenities and staffing average score from 63.0 to 61.7 was not statistically significant.
Table 2 tracks the changes in readiness by facility type. The overall readiness improved across all types of facilities. There were increases in most of the domains, except for staff. Observed staff availability decreased in health centres and regional referral hospitals, but the difference was not significant. There was a significant improvement/increase in the overall readiness in both district hospitals and health centres. The change in equipment was significant for all facility levels.
Table 3, Table 4, Table 5, Table 6 and Table 7 show the readiness level at the end of the implementation of the quality improvement initiative in 2023. As shown in Table 3 on the visiting day, facilities had on average 84 percent of items available in the amenities domain. Most items were available in over 90 percent of facilities; however, solar backup was present in only four (14%) of health facilities, all of which were health centres. In the case of a national grid blackout, most facilities rely on generators as their backup power source.
Facilities surveyed had 61.7 percent of the key staff required (Table 4). Staffing was more available in district hospitals and referral hospitals than in health centres. Gynecologists and pediatricians were available in the majority of referral hospitals, while clinical officers and assistant clinical officers were only in health centres and district hospitals.
Availability of equipment was 94 percent on average, with the penguin sucker (a silicon penguin shaped nasal aspirator), newborn suction apparatus, weighing scale, caesarian set, and oxygen cylinders being universally available, as seen in Table 5. The vacuum extractor was the least available equipment, more so in district hospitals and health centres, followed by the room thermometer and small oxygen cylinder for transport.
The average availability of commodities for treatment and diagnosis was 82.1 percent, as seen in Table 6. There was a variation though, with district hospital recording more availability than regional hospitals and health centres. The item that was least available was safe blood.
Table 7 shows the availability of guidelines which was on average 96.7 percent with regional hospitals recording a universal availability.
We also assessed if there would be regional differences in the readiness changes. All regions showed an improvement in readiness and a linear fixed effect regression model showed that there were significant differences between regions in terms of the improvement in readiness. For overall readiness, the mean improvements were in Geita (23.3), Manyara (15.1), Mwanza (14.5), Shinyanga (7.6), and Tabora (19.3), p = 0.01. Regions with the lower initial readiness level registered more readiness change. The mean baseline and endline for each region were in Geita 55 to 79, Manyara 71 to 87, Mwanza, 72 to 86, Shinyanga 75 to 83, and Tabora 66 to 85.
4. Discussion
This study examined readiness in 28 facilities providing comprehensive emergency obstetric and newborn care in 2023 and compared it with 2021 readiness in the same facilities. The findings indicate positive progress in overall readiness, increasing from 68% to 84%, though there is still room for improvement as is aspired by Tanzania and the global community [1,18,19].
The government of Tanzania has been making efforts to improve health service systems to attain universal health coverage, and this might be at play in the observed readiness improvement in the studied facilities [20]. The change observed in this study is larger than the national readiness change in comprehensive emergency care during a partially overlapping period, which increased from 68% in 2020 to 71% in 2023 [21,22].
The improvement observed might have been, at least in part, attributable to the Plan–Do–Study–Act (PDSA) quality improvement strategy, as facilities in this study were measuring their performance using local data, reviewing and devising action plans, and implementing them for improvement in various areas of readiness [12,13,14,23]. This way of improving readiness and quality of care has been shown to be effective in other studies [24,25,26].
At the endline, the overall readiness was still highest in regional hospitals, followed by district hospitals, and then health centres. This finding aligns with previous studies conducted in Tanzania and other low- and middle-income countries, which have shown that higher-level healthcare facilities tend to exhibit greater overall readiness [18,21,27,28]. This finding highlights a disparity: while CEmONC centres at all levels are expected to provide comparable essential services, mothers and newborns in lower-level facilities often receive lower-quality care. In recent years, however, the Tanzanian government has taken steps to improve existing facilities and construct new ones to expand access to surgical services, particularly cesarean section availability in health centres [20,21]. This indicates that further efforts are needed to strengthen health centres to meet the required readiness standards. Additionally, factors like limited staffing and management capabilities may also play a role in the lower readiness observed in these facilities [29,30].
The improvement in readiness was larger in lower-level facilities than in regional hospitals which had higher initial readiness and therefore less potential to improve further; or, authorities give emphasis to the lesser-performing facilities [22,31,32]. Nevertheless the improvement means that with time, patients in lower-level facilities receive relatively better quality services than is usual, in the context of the usual disparity of poor quality in lower facilities in developing countries [18,21,27,28].
Staffing did not improve significantly. In Tanzania, health employees are usually recruited and work under the central government, local government, or faith-based organizations. However, permits and salaries are funded by the central government. As a result, employment and deployment decisions are not made at the facility level, which helps to explain why there was no improvement in staffing, let alone local issues regarding the rational allocation of staff at the current staffing situation [22]. Additionally, the Tanzanian government has been expanding its healthcare facilities in terms of number and infrastructure, creating a demand for additional staffing—yet the rate of new employment has not kept pace with this growth [20]. Given that the national average for human resource for health remains low, with only 48 percent of the required staff, the insufficient staffing levels at these facilities are unsurprising, sharing trends with other developing nations [33,34].
Guidelines play a crucial role in ensuring that patients receive standardized, evidence-based, or consensus-driven quality care [35]. In this study, guideline availability was nearly universal across all facilities as opposed to the national average availability of guidelines for CEmONC which stood at 56% [22]. The widespread improvement in the availability of various guidelines may be attributed to several factors, including the government and healthcare facilities prioritizing their implementation through dissemination initiatives and distribution. Another reason could be that a long time has passed, allowing for guidelines to integrate into the health system and their adoption, as noted by Pereira and colleagues [36]. For example, in Tanzania, the newborn care guidelines were finalized in 2019, leaving a reasonably long time for their full implementation within the health system [37].
This study has several strengths, including direct facility visits rather than reliance on self-assessment reports. It also encompasses both rural and urban settings and various levels of the health system. However, certain limitations exist: we measured readiness, but the actual service delivery was not observed, and availability does not necessarily indicate utilization. Additionally, staffing levels were not adjusted for client volume or equipment usage. Another constraint is that commodity and amenity availability may fluctuate over time, yet assessments were conducted during a single visit. We did not have control facilities, so we cannot determine whether the changes might have occurred regardless.
5. Conclusions
While there has been positive progress, with some areas having an adequate supply of essential items, significant gaps persist in terms of amenities, equipment, diagnostic and treatment commodities, guidelines, and, most notably, staffing. Strengthening health facilities’ readiness is crucial for ensuring high-quality maternal and newborn care. To achieve this, the government, development partners, and other stakeholders must allocate sufficient resources, including amenities, equipment, commodities, and personnel, while carefully selecting the most effective and feasible interventions. We strongly advocate for a continuous quality improvement system to address existing deficiencies. Additionally, regular assessments are vital for monitoring progress in facility readiness and ensuring the successful implementation of measures to enhance service quality. These efforts are essential to reduce preventable maternal and newborn morbidity and mortality.
Author Contributions
Conceptualization, D.J., K.S., B.K., D.R.B., A.K., R.M. (Rachel Manongi), R.M. (Robert Moshiro), G.G. and J.T.K.; methodology, D.J., K.S., B.K., D.R.B., A.K., R.M. (Rachel Manongi), R.M. (Robert Moshiro), G.G. and J.T.K.; validation, D.J., K.S., B.K., D.R.B. and R.M. (Rachel Manongi); formal analysis, G.G. and J.T.K.; investigation, D.J., K.S., B.K. and D.R.B.; data curation, D.J., J.T.K. and G.G.; writing—original draft preparation, D.J.; writing—review and editing, D.J., K.S., B.K., D.R.B., A.K., R.M. (Rachel Manongi), R.M. (Robert Moshiro) and J.T.K.; visualization, D.J.; supervision, R.M. (Rachel Manongi) and D.R.B.; project administration, B.K. and R.M. (Robert Moshiro); resources R.M. (Robert Moshiro); and funding acquisition, B.K. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the SBBC project, which is financed by the World Bank, Global Financing Facility for Women, Children and Adolescents, through UNICEF grant number TZA/PCA202066/HPD2020107. APC was paid by The Laerdal Foundation. Neither of the funders had a role in this publication.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and received approval from multiple Institutional Review Boards. Ethical clearance was granted by the National Institute for Medical Research Ethical Review Board in Tanzania (Ref. NIMR/HQ/R.8a/Vol.IX/3458) of 30 June 2020, and the Regional Ethical Committee RecWest in Norway (Ref. 229725) on 6 August 2021. Additionally, the Kilimanjaro Medical University College Research Ethical Committee provided approval under certificate number 2603.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data are available on reasonable request from Haydom Lutheran Hospital, P.O. Box 9000 Haydom, Manyara, Tanzania Tel. + 255(0)27 253 3194/5 Fax + 255(0)27 253 3734 E-mail: post@haydom.co.tz. This is due to ethical and privacy reasons.
Acknowledgments
We acknowledge each and every person involved for their cooperation.
Conflicts of Interest
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Abbreviations
The following abbreviations are used in this manuscript:
| CEmONC | Comprehensive Emergency Obstetric and Newborn Care |
| CQI | Continuous Quality Improvement |
| PDSA | Plan, Do, Study, Act |
| SBBC | Safer Births Bundle of Care |
| PPROM | Preterm Premature Rupture of Membranes |
| SDG | Sustainable Development Goals |
References
- United Nations. Transforming Our World: The 2030 Agenda for Sustainable Development; United Nations: New York, NY, USA, 2015. [Google Scholar]
- Souza, J.P.; Day, L.T.; Rezende-Gomes, A.C.; Zhang, J.; Mori, R.; Baguiya, A.; Jayaratne, K.; Osoti, A.; Vogel, J.P.; Campbell, O.; et al. A Global Analysis of the Determinants of Maternal Health and Transitions in Maternal Mortality. Lancet Glob. Health 2024, 12, e306–e316. [Google Scholar] [CrossRef]
- World Health Organisation. Trends in Maternal Mortality 2000 to 2020: Estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division; WHO: Geneva, Switzerland; UNICEF: New York, NY, USA; UNFPA: New York, NY, USA; World Bank Group: Washington, DC, USA; UNDESA/Population Division: New York, NY, USA, 2023. [Google Scholar]
- World Health Organisation. World Health Statistics 2025: Monitoring Health for the SDGs, Sustainable Development Goals; WHO Press: Geneva, Switzerland, 2025. [Google Scholar]
- UNICEF. Levels & Trends in Child Mortality Report; UNICEF: New York, NY, USA, 2025. [Google Scholar]
- National Bureau of Statistics. Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS); National Bureau of Statistics: Dodoma, Tanzania; Rockville, MD, USA, 2023.
- National Bureau of Statistics. Tanzania Demographic and Health Survey and Malaria Indicator Survey 2022 Key Indicators Report; National Bureau of Statistics: Dodoma, Tanzania; Rockville, MD, USA, 2023.
- World Health Organization. Service Availability and Readiness Assessment (SARA): An Annual Monitoring System for Service Delivery-Implementation Guide; Version 2.2; WHO Press: Geneva, Switzerland, 2015. [Google Scholar]
- Ashish, K.; Raman, D.; Madan, S.; Upadhyaya, K.; Sundar, S. Quality of Care for Maternal and Newborn Health in Health Facilities in Nepal. Matern. Child Health J. 2020, 24 (Suppl. S1), 31–38. [Google Scholar] [CrossRef]
- Chou, V.B.; Walker, N.; Kanyangarara, M. Estimating the Global Impact of Poor Quality of Care on Maternal and Neonatal Outcomes in 81 Low- And Middle-Income Countries: A Modeling Study. PLoS Med. 2019, 16, e1002990. [Google Scholar] [CrossRef]
- Livet, M.; Blanchard, C.; Richard, C. Readiness as a Precursor of Early Implementation Outcomes: An Exploratory Study in Specialty Clinics. Implement. Sci. Commun. 2022, 3, 94. [Google Scholar] [CrossRef] [PubMed]
- Kamala, B.A.; Ersdal, H.L.; Mduma, E.; Moshiro, R.; Girnary, S.; Østrem, O.T.; Linde, J.; Dalen, I.; Søyland, E.; Bishanga, D.R.; et al. SaferBirths Bundle of Care Protocol: A Stepped-Wedge Cluster Implementation Project in 30 Public Health-Facilities in Five Regions, Tanzania. BMC Health Serv. Res. 2021, 21, 1117. [Google Scholar] [CrossRef] [PubMed]
- Kamala, B.A.; Ersdal, H.L.; Moshiro, R.D.; Guga, G.; Dalen, I.; Kvaløy, J.T.; Bundala, F.A.; Makuwani, A.; Kapologwe, N.A.; Mfaume, R.S.; et al. Outcomes of a Program to Reduce Birth-Related Mortality in Tanzania. N. Engl. J. Med. 2025, 392, 1100–1110. [Google Scholar] [CrossRef]
- Ersdal, H.; Mdoe, P.; Mduma, E.; Moshiro, R.; Guga, G.; Kvaløy, J.T.; Bundala, F.; Marwa, B.; Kamala, B. “Safer Births Bundle of Care” Implementation and Perinatal Impact at 30 Hospitals in Tanzania—Halfway Evaluation. Children 2023, 10, 255. [Google Scholar] [CrossRef]
- Mduma, E.; Ersdal, H.; Svensen, E.; Kidanto, H.; Auestad, B.; Perlman, J. Frequent Brief On-Site Simulation Training and Reduction in 24-h Neonatal Mortality—An Educational Intervention Study. Resuscitation 2015, 93, 1–7. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization. Monitoring Emergency Obstetric Care; WHO Press: Geneva, Switzerland, 2009. [Google Scholar]
- World Health Organization. Service Availability and Readiness Assessment (SARA): An Annual Monitoring System for Service Delivery-Reference Manual, Version 2.2; WHO Press: Geneva, Switzerland, 2015. [Google Scholar]
- Juma, D.; Stordal, K.; Kamala, B.; Bishanga, D.R.; Kalolo, A.; Moshiro, R. Readiness to Provide Comprehensive Emergency Obstetric and Neonatal Care: A Cross-Sectional Study in 30 Health Facilities in Tanzania. BMC Health Serv. Res. 2024, 24, 870. [Google Scholar] [CrossRef]
- Ministry of Health. National Human Resource for Health Strategy 2021–2026; Ministy of Health: Dodoma, Tanzania, 2021.
- Kapologwe, N.A.; Meara, J.G.; Kengia, J.T.; Sonda, Y.; Gwajima, D.; Alidina, S.; Kalolo, A. Development and Upgrading of Public Primary Healthcare Facilities with Essential Surgical Services Infrastructure: A Strategy towards Achieving Universal Health Coverage in Tanzania. BMC Health Serv. Res. 2020, 20, 218. [Google Scholar] [CrossRef]
- Ministry of Health. Tanzania Service Availability and Readiness Assessment Report; Ministry of Health: Da es Salaam, Tanzania, 2021.
- Ministry of Health. Tanzania Service Availability and Readiness Assessment; Ministry of Health: Dodoma, Tanzania, 2024.
- Taylor, M.J.; McNicholas, C.; Nicolay, C.; Darzi, A.; Bell, D.; Reed, J.E. Systematic Review of the Application of the Plan-Do-Study-Act Method to Improve Quality in Healthcare. BMJ Qual. Saf. 2014, 23, 290–298. [Google Scholar] [CrossRef]
- Kyte, L.; Sjursen, I.; Kleiven, O.T. The Impact of Pre-Round Meetings on Quality of Care: A Qualitative Study. Nurs. Open 2020, 7, 596–604. [Google Scholar] [CrossRef] [PubMed]
- Hill, J.E.; Stephani, A.M.; Sapple, P.; Clegg, A.J. The Effectiveness of Continuous Quality Improvement for Developing Professional Practice and Improving Health Care Outcomes: A Systematic Review. Implement. Sci. 2020, 15, 23. [Google Scholar] [CrossRef] [PubMed]
- Daniel, M.; Puxty, A.; Miles, B. Making Quality Improvement Happen in the Real World: Building Capability and Improving Multiple Projects at the Same Time. BMJ Qual. Improv. Rep. 2016, 5, u207660.w4159. [Google Scholar] [CrossRef]
- Cavallaro, F.L.; Pembe, A.B.; Campbell, O.; Hanson, C.; Tripathi, V.; Wong, K.L.M.; Radovich, E.; Benova, L. Caesarean Section Provision and Readiness in Tanzania: Analysis of Crosssectional Surveys of Women and Health Facilities over Time. BMJ Open 2018, 8, e024216. [Google Scholar] [CrossRef] [PubMed]
- Leslie, H.H.; Spiegelman, D.; Zhoub, X.; Kruka, M.E. Service Readiness of Health Facilities in Bangladesh, Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Uganda and the United Republic of Tanzania. Bull. World Health Organ. 2017, 95, 738–748. [Google Scholar] [CrossRef]
- Kabene, S.M.; Orchard, C.; Howard, J.M.; Soriano, M.A.; Leduc, R. The Importance of Human Resources Management in Health Care: A Global Context. Hum. Resour. Health 2006, 4, 20. [Google Scholar] [CrossRef]
- Kalolo, A.; Gautier, L.; Radermacher, R.; Srivastava, S.; Meshack, M.; De Allegri, M. Factors Influencing Variation in Implementation Outcomes of the Redesigned Community Health Fund in the Dodoma Region of Tanzania: A Mixed-Methods Study. BMC Public Health 2021, 21, 1. [Google Scholar] [CrossRef]
- WHO. WHO Benchmarks for Strengthening Health Emergency Capacities; World Health Organization: Geneva, Switzerland, 2023. [Google Scholar]
- Mold, J.W.; Hamm, R.M.; Mccarthy, L.H. The Law of Diminishing Returns in Clinical Medicine: How Much Risk Reduction Is Enough? J. Am. Board Fam. Med. 2010, 23, 371–375. [Google Scholar] [CrossRef]
- Ministry of Health. Tanzania Human Resource for Health Profile; Ministry of Health: Dodoma, Tanzania, 2023.
- Boniol, M.; Kunjumen, T.; Nair, T.S.; Siyam, A.; Campbell, J.; Diallo, K. The Global Health Workforce Stock and Distribution in 2020 and 2030: A Threat to Equity and ‘Universal’ Health Coverage? BMJ Glob. Health 2022, 7, e009316. [Google Scholar] [CrossRef]
- Feder, G.; Eccles, M.; Grol, R.; Griffiths, C.; Grimshaw, J.; Grimshaw, J. Using Clinical Guidelines. BMJ 1999, 318, 728–730. [Google Scholar] [CrossRef] [PubMed]
- Pereira, V.C.; Silva, S.N.; Carvalho, V.K.S.; Zanghelini, F.; Barreto, J.O.M. Strategies for the Implementation of Clinical Practice Guidelines in Public Health: An Overview of Systematic Reviews. Health Res. Policy Syst. 2022, 20, 13. [Google Scholar] [CrossRef] [PubMed]
- United Republic of Tanzania. National Guideline for Neonatal Care and Establishment of Neonatal Care Unit; United Republic of Tanzania: Dodoma, Tanzania, 2019; pp. 116–117. [Google Scholar]
Figure 1.
Facility readiness changes in 28 health facilities between 2021 (baseline) and 2023 (endline).
Figure 1.
Facility readiness changes in 28 health facilities between 2021 (baseline) and 2023 (endline).
Table 1.
Comparison of average readiness before and after the implementation of quality improvement in 28 facilities in Tanzania (baseline 2021 and endline 2023).
Table 1.
Comparison of average readiness before and after the implementation of quality improvement in 28 facilities in Tanzania (baseline 2021 and endline 2023).
| Readiness | Baseline N = 28 | Endline N = 28 | Difference 1 | 95% CI 1,2 | p-Value 1 |
|---|---|---|---|---|---|
| Average Facility Readiness | |||||
| Amenity | |||||
| Mean (SD) | 78.1 (14.3) | 84.2 (9.0) | 6.1 | −0.29, 13 | 0.056 |
| Staffing | |||||
| Mean (SD) | 63.0 (16.6) | 61.7 (17.5) | −1.3 | −8.5, 5.9 | 0.714 |
| Basic equipment | |||||
| Mean (SD) | 77.1 (11.5) | 94.0 (6.4) | 16.9 | 12.1, 21.7 | 0.000 † |
| Commodities | |||||
| Mean (SD) | 69.3 (19.8) | 82.1 (14.1) | 12.9 | 6.3, 19.4 | 0.000 † |
| Guidelines | |||||
| Mean (SD) | 50.8 (20.9) | 96.7 (9.2) | 45.9 | 36.5, 55.3 | 0.000 † |
| Overall Readiness | |||||
| Mean (SD) | 67.6 (10.8) | 83.7 (6.3) | 16.1 | 10.7, 17.2 | 0.000 † |
1 Paired t-test; 2 CI = confidence interval; † significant after Bonferroni adjustment.
Table 2.
Comparison of average readiness before and after the implementation of quality improvement in 28 facilities in Tanzania by facility type in 28 health facilities.
Table 2.
Comparison of average readiness before and after the implementation of quality improvement in 28 facilities in Tanzania by facility type in 28 health facilities.
| Regional Referral Hospital | District Hospital | Health Centre | ||||
|---|---|---|---|---|---|---|
| Readiness | Baseline, N = 4 | Endline, N = 4 | Baseline, N = 14 | Endline, N = 14 | Baseline, N = 10 | Endline, N = 10 |
| Amenity | ||||||
| Mean (SD) | 71.4 (11.7) | 75.0 (0.0) | 81.6 (11.8) * | 74.1 (3.3) * | 75.7 (17.9) | 72.5 (12.9) |
| Staffing | ||||||
| Mean (SD) | 70.5 (23.9) | 65.9 (15.5) | 66.2 (12.1) | 68.2 (18.4) | 55.5 (17.9) | 50.9 (12.3) |
| Basic equipment | ||||||
| Mean (SD) | 85.0 (11.4) | 98.3 (3.3) | 78.1 (10.6) *,† | 96.7 (3.5) *,† | 72.7 (11.9) * | 88.7 (7.1) * |
| Commodities | ||||||
| Mean (SD) | 77.5 (18.9) | 84.1 (8.7) | 69.3 (14.9) *,† | 87.0 (8.5) *,† | 66.0 (26.3) | 74.5 (19.1) |
| Guidelines | ||||||
| Mean (SD) | 67.9 (14.9) * | 100.0 (0.0) * | 53.1 (21.8) *,† | 95.4 (11.8) *,† | 40.7 (17.2) *,† | 97.1 (6.9) *,† |
| Overall Readiness | ||||||
| Mean (SD) | 74.5 (14.6) | 84.7 (4.6) | 69.7 (5.6) *,† | 84.3 (5.6) *,† | 62.1 (13.1) *,† | 76.8 (5.1) *,† |
* Change is statistically significant by paired t-test at 0.05 level of significance. † Significant after Bonferroni adjustment.
Table 3.
Endline basic amenities in the 28 facilities providing CEmONC in five regions.
| Characteristic | Overall N = 28 1 | Regional Referral Hospital N = 4 1 | District Hospital N = 14 1 | Health Centre N = 10 1 | p-Value 2 |
|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | n (%) | ||
| Grid electricity | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Solar | 4 (14.3) | 0 (0.0) | 0 (0.0) | 4 (40.0) | 0.02 |
| Generator | 27 (96.4) | 4 (100.0) | 14 (100.0) | 9 (90.0) | 0.5 |
| Solar or Generator | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Water on the visiting day | 26 (92.9) | 4 (100.0) | 13 (92.9) | 9 (90.0) | >0.9 |
| Emergency transportation | 26 (92.9) | 4 (100.0) | 14 (100.0) | 8 (80.0) | 0.2 |
| Fuel for ambulance | 26 (92.9) | 4 (100.0) | 14 (100.0) | 8 (80.0%) | 0.2 |
| Average readiness score | >0.9 | ||||
| Mean (SD) | 84.2 (9.0) | 85.7 (0.0) | 84.7 (3.8) | 82.9 (14.8) | 0.89 # |
1n (%); 2 Fisher’s exact test; # Linear mixed model; no tests significant after Bonferroni adjustment.
Table 4.
Staff in the 28 health facilities in five regions of Tanzania after implementation.
| Characteristic | Overall N = 28 1 | Regional Referral Hospital N = 4 1 | District Hospital N = 14 1 | Health Centre N = 10 1 | p-Value 2 |
|---|---|---|---|---|---|
| Pediatrician | 4 (14.3) | 3 (75.0) | 1 (7.1) | 0 (0.0) | 0.005 † |
| Gynecologist | 4 (14.3) | 3 (75.0) | 1 (7.1) | 0 (0.0) | 0.005 † |
| Medical doctor | 26 (92.9) | 3 (75.0) | 14 (100.0) | 9 (90.0) | 0.12 |
| Assistant Medical Officer € | 18 (64.3) | 2 (50.0) | 11 (78.6) | 5 (50.0) | 0.3 |
| Clinical Officer α | 17 (60.7) | 0 (0.0) | 10 (71.4) | 7 (70.0) | 0.040 |
| Assistant Clinical Officer ¶ | 9 (32.1) | 0 (0.0) | 7 (50.0) | 2 (20.0) | 0.13 |
| Nurse Officer § | 19 (67.9) | 4 (100.0) | 12 (85.7) | 3 (30.0) | 0.007 |
| Assistant Nurse Officer ¥ | 27 (96.4) | 4 (100.0) | 14 (100.0) | 9 (90.0) | 0.5 |
| Enrolled Nurse φ | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Health Information personnel | ¢ 12 (42.9) | 2 (50.0) | 8 (57.1) | 2 (20.0) | 0.2 |
| Anesthetist | 26 (92.9) | 4 (100.0) | 13 (92.9) | 9 (90.0) | >0.9 |
| Average Score | 61.7 | 65.9 | 68.2 | 50.9 | 0.089 # |
1 n (%); 2 Fisher’s exact test; † significant after Bonferroni adjustment; # linear mixed model; § holder of a bachelor degree in nursing; ¥ holder of a diploma in nursing; φ holder of a certificate in nursing; € holder of an advanced diploma in clinical medicine for general medical cores; α holder of a diploma in clinical medicine to diagnose and treat common medical condition and minor surgeries especially in rural areas; ¶ holder of a certificate in clinical medicine—for diagnosis and treatment of medical and minor surgical conditions especially in rural areas; ¢ health worker with training in health management information system.
Table 5.
Endline availability of equipment in the 28 health facilities in five regions of Tanzania.
| Characteristic | Overall N = 28 1 | Regional Referral Hospital N = 4 1 | District Hospital N = 14 1 | Health Centre N = 10 1 | p-Value 2 |
|---|---|---|---|---|---|
| Weighing scale | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Thermometer (room) | 25 (89.3) | 4 (100.0) | 14 (100.0) | 7 (70.0) | 0.082 |
| Wall clock | 25 (89.3) | 3 (75.0) | 13 (92.9) | 9 (90.0) | 0.5 |
| Cesarian section set | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Vacuum extractor | 20 (71.4) | 4 (100.0) | 9 (64.3) | 7 (70.0) | 0.5 |
| Resuscitation space next to the delivery bed | 27 (96.4) | 4 (100.0) | 13 (92.9) | 10 (100.0) | >0.9 |
| Newborn Suction next to the delivery bed | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Newborn Bag/mask next to the delivery bed | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Penguin sucker | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Mask size 0 | 27 (96.4) | 4 (100.0) | 14 (100.0) | 9 (90.0) | 0.5 |
| Mask size 1 | 26 (92.9) | 4 (100.0) | 14 (100.0) | 8 (80.0) | 0.2 |
| Radiant warmer | 26 (92.9) | 4 (100.0) | 14 (100.0) | 8 (80.0) | 0.2 |
| Oxygen cylinder/flow metre, humidifier | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Small oxygen cylinder for transport | 25 (89.3) | 4 (100.0) | 14 (100.0) | 7 (70.0) | 0.082 |
| Oxygen concentrator | 26 (92.9) | 4 (100.0) | 14 (100.0) | 8 (80.0) | 0.2 |
| Average score | 94.0 | 98.3 | 96.7 | 88.7 | 0.0094 # |
1 n (%); 2 Fisher’s exact test; # linear mixed model.
Table 6.
Endline availability of commodities for treatment in the 28 health facilities in five regions.
Table 6.
Endline availability of commodities for treatment in the 28 health facilities in five regions.
| Characteristic | Overall N = 28 1 | Regional Referral Hospital N = 4 1 | District Hospital N = 14 1 | Health Centre N = 10 1 | p-Value 2 |
|---|---|---|---|---|---|
| Haemoglobinometer | 18 (64.3) | 2 (50.0) | 10 (71.4) | 6 (60.0) | 0.7 |
| Glucose metre | 23 (82.1) | 3 (75.0) | 12 (85.7) | 8 (80.0) | >0.9 |
| Dextrose 10% | 25 (89.3) | 4 (100.0) | 13 (92.9) | 8 (80.0) | 0.7 |
| Normal saline | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Vitamin K | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Ampicillin/gentamicin | 26 (92.9) | 4 (100.0) | 14 (100.0) | 8 (80.0) | 0.2 |
| Adrenaline injection | 25 (89.3) | 4 (100.0) | 14 (100.0) | 7 (70.0) | 0.082 |
| Phenobarbital injection | 21 (75.0) | 4 (100.0) | 12 (85.7) | 5 (50.0) | 0.11 |
| Magnesium Sulphate | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Safe blood 24 hrs | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Blood out of stock in 90 days before the study | 3 (10.7) | 0 (0.0) | 3 (21.4) | 0 (0.0) | 0.4 |
| Average score | 82.1 | 84.1 | 87.0 | 74.5 | 0.082 # |
1 n (%); 2 Fisher’s exact test; # linear mixed model.
Table 7.
Endline availability of guidelines in the 28 health facilities in five regions of Tanzania.
Table 7.
Endline availability of guidelines in the 28 health facilities in five regions of Tanzania.
| Characteristic | Overall N = 28 1 | Regional Referral Hospital N = 4 1 | District Hospital N = 14 1 | Health Centre N = 10 1 | p-Value 2 |
|---|---|---|---|---|---|
| National neonatal guidelines | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Essential newborn care guidelines | 27 (96.4) | 4 (100.0) | 13 (92.9) | 10 (100.0) | >0.9 |
| Standard operating procedure set | 26 (92.9) | 4 (100.0) | 12 (85.7) | 10 (100.0) | 0.6 |
| Newborn triage checklist | 25 (89.3) | 4 (100.0) | 12 (85.7) | 9 (90.0) | >0.9 |
| Discharge feedback form | 25 (89.3) | 4 (100.0) | 13 (92.9) | 8 (80.0) | 0.7 |
| Referral form | 27 (96.4) | 4 (100.0) | 14 (100.0) | 9 (90.0) | 0.5 |
| HBB poster | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Prolonged labour | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Pre-eclampsia | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Antepartum hemorrhage | 27 (96.4) | 4 (100.0) | 13 (92.9) | 10 (100.0) | >0.9 |
| Postpartum hemorrhage | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Abnormal fetal heart rate | 27 (96.4) | 4 (100.0) | 13 (92.9) | 10 (100.0) | >0.9 |
| PPROM | 27 (96.4) | 4 (100.0) | 13 (92.9) | 10 (100.0) | >0.9 |
| Antenatal Corticosteroid | 28 (100.0) | 4 (100.0) | 14 (100.0) | 10 (100.0) | |
| Average readiness | 96.7 | 100.0 | 95.4 | 97.1 | 0.6069 # |
1 n (%); 2 Fisher’s exact test; # linear mixed model.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Juma, D.; Stordal, K.; Kamala, B.; Bishanga, D.R.; Kalolo, A.; Moshiro, R.; Kvaløy, J.T.; Guga, G.; Manongi, R. Changes in Health Facility Readiness for Providing Quality Maternal and Newborn Care After Implementing the Safer Births Bundle of Care Package in Five Regions of Tanzania. Healthcare 2025, 13, 3060. https://doi.org/10.3390/healthcare13233060
AMA Style
Juma D, Stordal K, Kamala B, Bishanga DR, Kalolo A, Moshiro R, Kvaløy JT, Guga G, Manongi R. Changes in Health Facility Readiness for Providing Quality Maternal and Newborn Care After Implementing the Safer Births Bundle of Care Package in Five Regions of Tanzania. Healthcare. 2025; 13(23):3060. https://doi.org/10.3390/healthcare13233060
Chicago/Turabian StyleJuma, Damas, Ketil Stordal, Benjamin Kamala, Dunstan R. Bishanga, Albino Kalolo, Robert Moshiro, Jan Terje Kvaløy, Godfrey Guga, and Rachel Manongi. 2025. "Changes in Health Facility Readiness for Providing Quality Maternal and Newborn Care After Implementing the Safer Births Bundle of Care Package in Five Regions of Tanzania" Healthcare 13, no. 23: 3060. https://doi.org/10.3390/healthcare13233060
APA StyleJuma, D., Stordal, K., Kamala, B., Bishanga, D. R., Kalolo, A., Moshiro, R., Kvaløy, J. T., Guga, G., & Manongi, R. (2025). Changes in Health Facility Readiness for Providing Quality Maternal and Newborn Care After Implementing the Safer Births Bundle of Care Package in Five Regions of Tanzania. Healthcare, 13(23), 3060. https://doi.org/10.3390/healthcare13233060
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
