Financing networks of care: a cross-case analysis from six countries.

OBJECTIVES: Describe experiences of countries with networks of care's (NOCs') financial arrangements, identifying elements, strategies and patterns. DESIGN: Descriptive using a modified cross-case analysis, focusing on each network's financing functions (collecting resources, pooling and purchasing). SETTING: Health systems in six countries: Argentina, Australia, Canada, Singapore, the United Kingdom and the USA. PARTICIPANTS: Large-scale NOCs. RESULTS: Countries differ in their strategies to implement and finance NOCs. Two broad models were identified in the six cases: top-down (funding centrally designed networks) and bottom-up (financing individual projects) networks. Despite their differences, NOCs share the goal of improving health outcomes, mainly through the coordination of providers in the system; these results are achieved by devoting extra resources to the system, including incentives for network formation and sustainability, providing extra services and setting incentive systems for improving the providers' performance. CONCLUSIONS: Results highlight the need to better understand the financial implications and alternatives for designing and implementing NOCs, particularly as a strategy to promote better health in low- and middle-income settings.

Adverse birth outcomes among women with 'low-risk' pregnancies in India: findings from the Fifth National Family Health Survey, 2019-21.

Background: Despite substantial progress in improving maternal and newborn health, India continues to experience high rates of newborn mortality and stillbirths. One reason may be that many births happen in health facilities that lack advanced services-such as Caesarean section, blood transfusion, or newborn intensive care. Stratification based on pregnancy risk factors is used to guide 'high-risk' women to advanced facilities. To assess the utility of risk stratification for guiding the choice of facility, we estimated the frequency of adverse newborn outcomes among women classified as 'low risk' in India. Methods: We used the 2019-21 Fifth National Family Health Survey (NFHS-5)-India's Demographic and Health Survey-which includes modules administered to women aged 15-49 years. In addition to pregnancy history and outcomes, the survey collected a range of risk factors, including biomarkers. We used national obstetric risk guidelines to classify women as 'high risk' versus 'low risk' and assessed the frequency of stillbirths, newborn deaths, and unplanned Caesarean sections for the respondent's last pregnancy lasting 7 or more months in the past five years. We calculated the proportion of deliveries occurring at non-hospital facilities in all the Indian states. Findings: Using data from nearly 176,699 recent pregnancies, we found that 46.6% of India's newborn deaths and 56.3% of stillbirths were among women who were 'low risk' according to national guidelines. Women classified as 'low risk' had a Caesarean section rate of 8.4% (95% CI 8.1-8.7%), marginally lower than the national average of 10.0% (95% CI 9.8-10.3%). In India as a whole, 32.0% (95% CI 31.5-32.5%) of deliveries occurred in facilities that were likely to lack advanced services. There was substantial variation across the country, with less than 5% non-hospital public facility deliveries in Punjab, Kerala, and Delhi compared to more than 40% in Odisha, Madhya Pradesh, and Rajasthan. Newborn mortality tended to be lower in states with highest hospital delivery rates. Interpretation: Individual risk stratification based on factors identified in pregnancy fails to accurately predict which women will have delivery complications and experience stillbirth and newborn death in India. Thus a determination of 'low risk' should not be used to guide women to health facilities lacking key life saving services, including Caesarean section, blood transfusion, and advanced newborn resuscitation and care. Funding: Bill and Melinda Gates Foundation and the World Bank. The findings, interpretations and conclusions expressed in the paper are entirely those of the authors, and do not represent the views of the Gates Foundation or of the World Bank, its Executive Directors, or the countries they represent.

How does the effectiveness of strategies to improve healthcare provider practices in low-income and middle-income countries change after implementation? Secondary analysis of a systematic review.

BACKGROUND: A recent systematic review evaluated the effectiveness of strategies to improve healthcare provider (HCP) performance in low-income and middle-income countries. The review identified strategies with varying effects, including in-service training, supervision and group problem-solving. However, whether their effectiveness changed over time remained unclear. In particular, understanding whether effects decay over time is crucial to improve sustainability. METHODS: We conducted a secondary analysis of data from the aforementioned review to explore associations between time and effectiveness. We calculated effect sizes (defined as percentage-point (%-point) changes) for HCP practice outcomes (eg, percentage of patients correctly treated) at each follow-up time point after the strategy was implemented. We estimated the association between time and effectiveness using random-intercept linear regression models with time-specific effect sizes clustered within studies and adjusted for baseline performance. RESULTS: The primary analysis included 37 studies, and a sensitivity analysis included 77 additional studies. For training, every additional month of follow-up was associated with a 0.19 %-point decrease in effectiveness (95% CI: -0.36 to -0.03). For training combined with supervision, every additional month was associated with a 0.40 %-point decrease in effectiveness (95% CI: -0.68 to -0.12). Time trend results for supervision were inconclusive. For group problem-solving alone, time was positively associated with effectiveness, with a 0.50 %-point increase in effect per month (95% CI: 0.37 to 0.64). Group problem-solving combined with training was associated with large improvements, and its effect was not associated with time. CONCLUSIONS: Time trends in the effectiveness of different strategies to improve HCP practices vary among strategies. Programmes relying solely on in-service training might need periodical refresher training or, better still, consider combining training with group problem-solving. Although more high-quality research is needed, these results, which are important for decision-makers as they choose which strategies to use, underscore the utility of studies with multiple post-implementation measurements so sustainability of the impact on HCP practices can be assessed.

Health System Redesign to Shift to Hospital Delivery for Maternal and Newborn Survival: Feasibility Assessment in Kakamega County, Kenya.

Maternal and newborn health (MNH) service delivery redesign aims to improve maternal and newborn survival by shifting deliveries from poorly equipped primary care facilities to adequately prepared designated delivery hospitals. We assess the feasibility of such a model in Kakamega County, Kenya, by determining the capacity of hospitals to provide services under the redesigned model and the acceptability of the concept to providers and users. We find many existing system assets to implement redesign, including political will to improve MNH outcomes, a strong base of support among providers and users, and a good geographic spread of facilities to support implementation. There are nonetheless health workforce gaps, infrastructure deficits, and transportation challenges that would need to be addressed ahead of policy rollout. Implementing MNH redesign would require careful planning to limit unintended consequences and rigorous evaluation to assess impact and inform scale-up.

Being Known: A Grounded Theory Study of the Meaning of Quality Maternity Care to People of Color in Boston.

INTRODUCTION: Experiences of people of color with maternity care are understudied but understanding them is important to improving quality and reducing racial disparities in birth outcomes in the United States. This qualitative study explored experiences with maternity care among people of color to describe the meaning of quality maternity care to the cohort and, ultimately, to inform the design of a freestanding birth center in Boston. METHODS: Using a grounded theory design and elements of community-based participatory research, community activists developing Boston's first freestanding birth center and academics collaborated on this study. Semistructured interviews and focus groups with purposefully sampled people of color were conducted and analyzed using a constant comparative method. Interviewees described their maternity care experiences, ideas about perfect maternity care, and how a freestanding birth center might meet their needs. Open coding, axial coding, and selective coding were used to develop a local theory of what quality care means. RESULTS: A total of 23 people of color participated in semistructured interviews and focus groups. A core phenomenon arose from the narratives: being known (ie, being seen or heard, or being treated as individuals) during maternity care was an important element of quality care. Contextual factors, including interpersonal and structural racism, power differentials between perinatal care providers and patients, and the bureaucratic nature of hospital-based maternity care, facilitated negative experiences. People of color did extra work to prevent and mitigate negative experiences, which left them feeling traumatized, regretful, or sad about maternity care. This extra work came in many forms, including cognitive work such as worrying about racism and behavioral changes such as dressing differently to get health care needs met. DISCUSSION: Being known characterizes quality maternity care among people of color in our sample. Maternity care settings can provide personalized care that helps clients feel known without requiring them to do extra work to achieve this experience.

Decentralization and Regionalization: Redesigning Health Systems for High Quality Maternity Care Comment on "Decentralization and Regionalization of Surgical Care: A Review of Evidence for the Optimal Distribution of Surgical Services in Low- and Middle-Income Countries".

The question of how to optimally design health systems in low- and middle-income countries (LMICs) for high quality care and survival requires context-specific evidence on which level of the health system is best positioned to deliver services. Given documented poor quality of care for surgical conditions in LMICs, evidence to support intentional health system design is urgently needed. Iverson and colleagues address this very important question. This commentary explores their findings with particular attention to how they apply to maternity care. Though surgical maternity care is a common healthcare need, maternal complications are often unpredictable and require immediate surgical attention in order to avert serious morbidity or mortality. A discussion of decentralization for maternity services must grapple with this tension and differentiate between facilities that can provide emergency surgical care and those that can not.

Assessment of health facility quality improvements, United Republic of Tanzania.

OBJECTIVE: To identify contextual factors associated with quality improvements in primary health-care facilities in the United Republic of Tanzania between two star rating assessments, focusing on local district administration and proximity to other facilities. METHODS: Facilities underwent star rating assessments in 2015 and between 2017 and 2018; quality was rated from zero to five stars. The consolidated framework for implementation research, adapted to a low-income context, was used to identify variables associated with star rating improvements between assessments. Facility data were obtained from several secondary sources. The proportion of the variance in facility improvement observed at facility and district levels and the influence of nearby facilities and district administration were estimated using multilevel regression models and a hierarchical spatial autoregressive model, respectively. FINDINGS: Star ratings improved at 4028 of 5595 (72%) primary care facilities. Factors associated with improvement included: (i) star rating in 2015; (ii) facility type (e.g. hospital) and ownership (e.g. public); (iii) participation in, or eligibility for, a results-based financing programme; (iv) local population density; and (v) distance from a major road. Overall, 20% of the variance in facility improvement was associated with district administration. Geographical clustering indicated that improvement at a facility was also associated with improvements at nearby facilities. CONCLUSION: Although the majority of facilities improved their star rating, there were substantial variations between facilities. Both district administration and proximity to high-performing facilities influenced improvements. Quality improvement interventions should take advantage of factors operating above the facility level, such as peer learning and peer pressure.

Health system redesign for maternal and newborn survival: rethinking care models to close the global equity gap.

Large disparities in maternal and neonatal mortality exist between low- and high-income countries. Mothers and babies continue to die at high rates in many countries despite substantial increases in facility birth. One reason for this may be the current design of health systems in most low-income countries where, unlike in high-income countries, a substantial proportion of births occur in primary care facilities that cannot offer definitive care for complications. We argue that the current inequity in care for childbirth is a global double standard that limits progress on maternal and newborn survival. We propose that health systems need to be redesigned to shift all deliveries to hospitals or other advanced care facilities to bring care in line with global best practice. Health system redesign will require investing in high-quality hospitals with excellent midwifery and obstetric care, boosting quality of primary care clinics for antenatal, postnatal, and newborn care, decreasing access and financial barriers, and mobilizing populations to demand high-quality care. Redesign is a structural reform that is contingent on political leadership that envisions a health system designed to deliver high-quality, respectful care to all women giving birth. Getting redesign right will require focused investments, local design and adaptation, and robust evaluation.

Level of confidence in and endorsement of the health system among internet users in 12 low-income and middle-income countries.

INTRODUCTION: People's confidence in and endorsement of the health system are key measures of system performance, yet are undermeasured in low-income and middle-income countries (LMICs). We explored the prevalence and predictors of these measures in 12 countries. METHODS: We conducted an internet survey in Argentina, China, Ghana, India, Indonesia, Kenya, Lebanon, Mexico, Morocco, Nigeria, Senegal and South Africa collecting demographics, ratings of quality, and confidence in and endorsement of the health system. We used multivariable logistic regression to assess the association between confidence/endorsement and self-reported quality of recent healthcare. RESULTS: Of 13 489 respondents, 62% reported a health visit in the past year. Applying population weights, 32% of these users were very confident that they could receive effective care if they were to 'become very sick tomorrow'; 30% endorsed the health system, that is, agreed that it 'works pretty well and only needs minor changes'. Reporting high quality in the last visit was associated with 4.48 and 2.69 greater odds of confidence (95% CI 3.64 to 5.52) and endorsement (95% CI 2.33 to 3.11). Having health insurance was positively associated with confidence and endorsement (adjusted odds ratio (AOR) 1.68, 95% CI 1.49 to 1.90 and AOR 1.34, 95% CI 1.22 to 1.48), while experiencing discrimination in healthcare was negatively associated (AOR 0.67, 95% CI 0.56 to 0.80 and AOR 0.63, 95% CI 0.53 to 0.76). CONCLUSION: Confidence and endorsement of the health system were low across 12 LMICs. This may hinder efforts to gain support for universal health coverage. Positive patient experience was strongly associated with confidence in and endorsement of the health system.

User experience and satisfaction with specialty consultations and surgical care in secondary and tertiary level hospitals in Mexico.

BACKGROUND: To evaluate the association between user experience and satisfaction with specialty consultations and surgical care at the Mexican Institute of Social Security (IMSS) secondary and tertiary level hospitals. METHODS: We conducted secondary data analysis of the cross-sectional 2017 IMSS National Satisfaction Survey. The dependent variables were user satisfaction with outpatient consultation and with surgery. The study's independent variables were user experience with these services. The Lancet Global Health Commission on High Quality Health Systems in the Sustainable Development Era framework was used to guide the analysis. For each dependent variable a double-weighted Poisson regression model with robust variance was performed and considered clustering of the observations within 111 secondary level and 25 tertiary level hospitals. RESULTS: The study included 6713 outpatient consultation users and 528 surgery users. 83% of users attending outpatient consultations and 86.6% of users who underwent inpatient surgery at IMSS hospitals were satisfied with the service received. The common patient negative experiences with specialty consultations and surgical care were long waiting time (40%) and lack of hospital cleanliness (20%). An additional concern was the lack of clinical examination during the consultation (25%). Shorter waiting times, health provider courtesy, good communication, clinical examination, and hospital cleanliness were associated with patient satisfaction with specialty consultations. Having the surgery without prior postponement(s) and without complications increased the probability of patient satisfaction. CONCLUSION: Patient satisfaction with hospital outpatient consultations and surgical care may be raised by focusing on improvement strategies to enhance positive patient experiences with care.

PHC Progression Model: a novel mixed-methods tool for measuring primary health care system capacity.

High-performing primary health care (PHC) is essential for achieving universal health coverage. However, in many countries, PHC is weak and unable to deliver on its potential. Improvement is often limited by a lack of actionable data to inform policies and set priorities. To address this gap, the Primary Health Care Performance Initiative (PHCPI) was formed to strengthen measurement of PHC in low-income and middle-income countries in order to accelerate improvement. PHCPI's Vital Signs Profile was designed to provide a comprehensive snapshot of the performance of a country's PHC system, yet quantitative information about PHC systems' capacity to deliver high-quality, effective care was limited by the scarcity of existing data sources and metrics. To systematically measure the capacity of PHC systems, PHCPI developed the PHC Progression Model, a rubric-based mixed-methods assessment tool. The PHC Progression Model is completed through a participatory process by in-country teams and subsequently reviewed by PHCPI to validate results and ensure consistency across countries. In 2018, PHCPI partnered with five countries to pilot the tool and found that it was feasible to implement with fidelity, produced valid results, and was highly acceptable and useful to stakeholders. Pilot results showed that both the participatory assessment process and resulting findings yielded novel and actionable insights into PHC strengths and weaknesses. Based on these positive early results, PHCPI will support expansion of the PHC Progression Model to additional countries to systematically and comprehensively measure PHC system capacity in order to identify and prioritise targeted improvement efforts.