Women's experiences of mistreatment during childbirth: A comparative view of home- and facility-based births in Pakistan.

INTRODUCTION: Respectful and dignified healthcare is a fundamental right for every woman. However, many women seeking childbirth services, especially those in low-income countries such as Pakistan, are mistreated by their birth attendants. The aim of this epidemiological study was to estimate the prevalence of mistreatment and types of mistreatment among women giving birth in facility- and home-based settings in Pakistan in order to address the lack of empirical evidence on this topic. The study also examined the association between demographics (socio-demographic, reproductive history and empowerment status) and mistreatment, both in general and according to birth setting (whether home- or facility-based). MATERIAL AND METHODS: In phase one, we identified 24 mistreatment indicators through an extensive literature review. We then pre-tested these indicators and classified them into seven behavioural types. During phase two, the survey was conducted (April-May 2013) in 14 districts across Pakistan. A total of 1,334 women who had given birth at home or in a healthcare facility over the past 12 months were interviewed. Linear regression analysis was employed for the full data set, and for facility- and home-based births separately, using Stata version 14.1. RESULTS: There were no significant differences in manifestations of mistreatment between facility- and home-based childbirths. Approximately 97% of women reported experiencing at least one disrespectful and abusive behaviour. Experiences of mistreatment by type were as follows: non-consented care (81%); right to information (72%); non-confidential care (69%); verbal abuse (35%); abandonment of care (32%); discriminatory care (15%); and physical abuse (15%). In overall analysis, experience of mistreatment was lower among women who were unemployed (β = -1.17, 95% CI -1.81, -0.53); and higher among less empowered women (β = 0.11, 95% CI 0.06, 0.16); and those assisted by a traditional birth attendant as opposed to a general physician (β = 0.94, 95% CI 0.13, 1.75). Sub-group analyses for home-based births identified the same significant associations with mistreatment, with ethnicity included. In facility-based births, there was a significant relationship between women's employment and empowerment status and mistreatment. Women with prior education on birth preparedness were less likely to experience mistreatment compared to those who had received no previous birth preparedness education. CONCLUSION: In order to promote care that is woman-centred and provided in a respectful and culturally appropriate manner, service providers should be cognisant of the current situation and ensure provision of quality antenatal care. At the community level, women should seek antenatal care for improved birth preparedness, while at the interpersonal level strategies should be devised to leverage women's ability to participate in key household decisions

Are underprivileged and less empowered women deprived of respectful maternity care: Inequities in childbirth experiences in public health facilities in Pakistan

Background: Attainment of healthcare in respectful and dignified manner is a fundamental right for every woman regardless of the individual status. However, social exclusion, poor psychosocial support, and demeaning care during childbirth at health facilities are common worldwide, particularly in low- and middle-income countries. We concurrently examined how women with varying socio-demographic characteristics are treated during childbirth, the effect of women\u27s empowerment on mistreatment, and health services factors that contribute to mistreatment in secondary-level public health facilities in Pakistan.Methods: A cross-sectional survey was conducted during August-November 2016 among 783 women who gave birth in six secondary-care public health facilities across four contiguous districts of southern Sindh. Women were recruited in health facilities and later interviewed at home within 42 days of postpartum using a WHO\u27s framework-guided 43-item structured questionnaire. Means, standard deviation, and average were used to describe characteristics of the participants. Multivariable linear regression was applied using Stata 15.1.Results: Women experiencing at least one violation of their right to care by hospital staff during intrapartum care included: ineffective communication (100%); lack of supportive care (99.7%); loss of autonomy (97.5%); failure of meeting professional clinical standards (84.4%); lack of resources (76.3%); verbal abuse (15.2%); physical abuse (14.8%); and discrimination (3.2%). Risk factors of all three dimensions showed significant association with mistreatment: socio-demographic: primigravida and poorer were more mistreated; health services: lesser-education on birth preparedness and postnatal care leads to higher mistreatment; and in terms of women\u27s empowerment: women who were emotionally and physically abused by family, and those with lack of social support and lesser involvement in joint household decision making with husbands are more likely to be mistreated as compared to their counterparts. The magnitude of relationship between all significant risk factors and mistreatment, in the form of β coefficients, ranged from 0.2 to 5.5 with p-values less than 0.05.Conclusion: There are glaring inequalities in terms of the way women are treated during childbirth in public health facilities. Measures of socio-demographic, health services, and women\u27s empowerment showed a significant independent association with mistreatment during childbirth. At the health system level, there is a need for urgent solutions for more inclusive care to ensure that all women are treated with compassion and dignity, complemented by psychosocial support for those who are emotionally disturbed and lack social support

District decision-making for health in low-income settings: a systematic literature review.

Health management information systems (HMIS) produce large amounts of data about health service provision and population health, and provide opportunities for data-based decision-making in decentralized health systems. Yet the data are little-used locally. A well-defined approach to district-level decision-making using health data would help better meet the needs of the local population. In this second of four papers on district decision-making for health in low-income settings, our aim was to explore ways in which district administrators and health managers in low- and lower-middle-income countries use health data to make decisions, to describe the decision-making tools they used and identify challenges encountered when using these tools. A systematic literature review, following PRISMA guidelines, was undertaken. Experts were consulted about key sources of information. A search strategy was developed for 14 online databases of peer reviewed and grey literature. The resources were screened independently by two reviewers using pre-defined inclusion criteria. The 14 papers included were assessed for the quality of reported evidence and a descriptive evidence synthesis of the review findings was undertaken. We found 12 examples of tools to assist district-level decision-making, all of which included two key stages-identification of priorities, and development of an action plan to address them. Of those tools with more steps, four included steps to review or monitor the action plan agreed, suggesting the use of HMIS data. In eight papers HMIS data were used for prioritization. Challenges to decision-making processes fell into three main categories: the availability and quality of health and health facility data; human dynamics and financial constraints. Our findings suggest that evidence is available about a limited range of processes that include the use of data for decision-making at district level. Standardization and pre-testing in diverse settings would increase the potential that these tools could be used more widely

District decision-making for health in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia.

Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India's extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step

Applying the COM-B Model to Understand the Drivers of Mistreatment During Childbirth: A Qualitative Enquiry Among Maternity Care Staff

INTRODUCTION: Respectful maternity care (RMC) during childbirth is an integral component of quality of care. However, women's experiences of mistreatment are prevalent in many low- and middle-income countries. This is a complex phenomenon that has not been well explored from a behavioral science perspective. We aimed to understand the behavioral drivers of mistreatment during childbirth among maternity care staff at public health facilities in the Sindh province of Pakistan. METHODS: Applying the COM-B (capability-opportunity-motivation that leads to behavior change) model, we conducted semistructured in-depth interviews among clinical and nonclinical staff in public health facilities in Thatta and Sujawal, Sindh, Pakistan. Data were analyzed using thematic deductive analysis, and findings were synthesized using the COM-B model. RESULTS: We identified several behavioral drivers of mistreatment during childbirth: (1) institutional guidelines on RMC and training opportunities were absent, resulting in a lack of providers' knowledge and skills; (2) facilities lacked the infrastructure to maintain patient privacy and confidentiality and did not permit males as birth companions; (3) lack of provider performance monitoring system and patient feedback mechanism contributed to providers not feeling appreciated or recognized. Staff bias against patients from lower castes contributed to patient abuse and mistreatment. The perspectives of clinical and nonclinical staff overlapped regarding potential drivers of mistreatment during childbirth. CONCLUSIONS: Addressing mistreatment during childbirth requires improving the knowledge and capacity of maternity staff on RMC and psychosocial support to enhance their understanding of RMC. At the health facility level, governance and accountability mechanisms in routine supervision and monitoring of staff need to be improved. Patients' feedback should be incorporated for continuous improvement in providing maternity care services that meet patients' preferences and needs

Socioeconomic inequity in coverage and quality of maternal postnatal care in Ethiopia

OBJECTIVE: High-quality postnatal care is vital for improving maternal health. This study examined the relationship between household socioeconomic status and both coverage and quality of postnatal care in Ethiopia. METHOD: Cross-sectional household survey data were collected in October-November 2013 from 12 zones in 4 regions of Ethiopia. Women reporting a live birth in the 3-24 months prior to the survey were interviewed about the care they received before, during and after delivery and their demographic characteristics. Using mixed effect logistic and linear regression, the associations between household socioeconomic status and receiving postnatal care, location of postnatal care (health facility vs. non-health facility), cadre of person providing care and the number of seven key services (including physical checks and advice) provided at a postnatal visit, were estimated. RESULTS: A total of 16% (358/2189) of women interviewed reported receiving at least one postnatal care visit within 6 weeks of delivery. Receiving a postnatal care visit was strongly associated with socioeconomic status with women from the highest socioeconomic group having twice the odds of receiving postnatal care compared to women in the poorest quintile (OR [95% CI]: 1.98 [1.29, 3.05]). For each increasing socioeconomic status quintile there was a mean increase of 0.24 postnatal care services provided (95% CI: 0.06-0.43, p = 0.009) among women who did not give birth in a facility. There was no evidence that number of postnatal care services was associated with socioeconomic status for women who gave birth in a facility. There was no evidence that socioeconomic status was associated with the provider or location of postnatal care visits. CONCLUSION: Postnatal care in Ethiopia shows evidence of socio-economic inequity in both coverage and quality. This demonstrates the need to focus on quality improvement as well as coverage, particularly among the poorest women who did not deliver in a facility

District decision-making for health in low-income settings: a case study of the potential of public and private sector data in India and Ethiopia.

Many low- and middle-income countries have pluralistic health systems where private for-profit and not-for-profit sectors complement the public sector: data shared across sectors can provide information for local decision-making. The third article in a series of four on district decision-making for health in low-income settings, this study shows the untapped potential of existing data through documenting the nature and type of data collected by the public and private health systems, data flow and sharing, use and inter-sectoral linkages in India and Ethiopia. In two districts in each country, semi-structured interviews were conducted with administrators and data managers to understand the type of data maintained and linkages with other sectors in terms of data sharing, flow and use. We created a database of all data elements maintained at district level, categorized by form and according to the six World Health Organization health system blocks. We used content analysis to capture the type of data available for different health system levels. Data flow in the public health sectors of both counties is sequential, formal and systematic. Although multiple sources of data exist outside the public health system, there is little formal sharing of data between sectors. Though not fully operational, Ethiopia has better developed formal structures for data sharing than India. In the private and public sectors, health data in both countries are collected in all six health system categories, with greatest focus on service delivery data and limited focus on supplies, health workforce, governance and contextual information. In the Indian private sector, there is a better balance than in the public sector of data across the six categories. In both India and Ethiopia the majority of data collected relate to maternal and child health. Both countries have huge potential for increased use of health data to guide district decision-making

Effect of the data-informed platform for health intervention on the culture of data use for decision-making among district health office staff in North Shewa Zone, Ethiopia: a cluster-randomised controlled trial.

BACKGROUND: Similar to other low and middle-income countries, Ethiopia faces limitations in using local health data for decision-making.We aimed to assess the effect of an intervention, namely the data-informed platform for health, on the culture of data-based decision making as perceived by district health office staff in Ethiopia's North Shewa Zone. METHODS: By designating district health offices as 'clusters', a cluster-randomised controlled trial was implemented. Out of a total of 24 districts in the zone, 12 districts were allocated to intervention arm and the other 12 in the control group arms. In the intervention arm district health office teams were supported in four-monthly cycles of data-driven decision-making over 20 months. This support included: (a) defining problems using a health system framework; (b) reviewing data; (c) considering possible solutions; (d) value-based prioritizing; and (e) a consultative process to develop, commit to, and follow up on action plans. To measure the culture of data use for decision-making in both intervention and control arms, we interviewed 120 health management staff (5 per district office). Using a Likert scale based standard Performance of Routine Information System Management tool, the information is categorized into six domains:- evidence-based decision making, emphasis on data quality, use of information, problem solving, responsibility and motivation. After converting the Likert scale responses into percentiles, difference-in-difference methods were applied to estimate the net effect of the intervention. In intervention districts, analysis of variance was used to summarize variation by staff designation. RESULTS: The overall decision-making culture in health management staff showed a net improvement of 13% points (95% C.I:9, 18) in intervention districts. The net effect of each of the six domains in turn was an 11% point increase (95% C.I:7, 15) on culture of evidence based decision making, a 16% point increase (95% C.I:8, 24) on emphasis on data quality, a 20% point increase (95% C.I:12, 28) on use of information, a 21% point increase (95% C.I:13, 29) on problem solving, and a 10% point increase (95% C.I:4, 16) on responsibility and motivation. In terms of variation by staff designation within intervention districts, statistically significant differences were observed only for problem solving and responsibility. CONCLUSION: The data-informed platform for health strategy resulted in a measurable improvement in data use and structured decision-making culture by using existing systems, namely the Performance Monitoring Team meetings. The intervention supported district health offices in identifying and solving problems through a structured process. After further research, DIPH intervention could also be applied to other health administration and facility levels. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT05310682, Dated 25/03/ 2022

Measuring implementation strength: lessons from the evaluation of public health strategies in low- and middle-income settings.

Evaluation of strategies to ensure evidence-based, low-cost interventions reach those in need is critical. One approach is to measure the strength, or intensity, with which packages of interventions are delivered, in order to explore the association between implementation strength and public health gains. A recent systematic review suggested methodological guidance was needed. We described the approaches used in three examples of measures of implementation strength in evaluation. These addressed important public health topics with a substantial disease burden in low-and middle-income countries; they involved large-scale implementation; and featured evaluation designs without comparison areas. Strengths and weaknesses of the approaches were discussed. In the evaluation of Ethiopia's Health Extension Programme, implementation strength scoring for each kebele (ward) was based on aggregated data from interviews with mothers of children aged 12-23 months, reflecting their reports of contact with four elements of the programme. An evaluation of the Avahan HIV prevention programme in India used the cumulative amount of Avahan funding per HIV-infected person spent each year in each district. In these cases, a single measure was developed and the association with hypothesised programme outcomes presented. In the evaluation of the Affordable Medicines Facility-malaria, several implementation strength measures were developed based on the duration of activity of the programme and the level of implementation of supporting interventions. Measuring the strength of programme implementation and assessing its association with outcomes is a promising approach to strengthen pragmatic impact evaluation. Five key aspects of developing an implementation strength measure are to: (a) develop a logic model; (b) identify aspects of implementation to be assessed; (c) design and implement data collection from a range of data sources; (d) decide whether and how to combine data into a single measure; and, (e) plan whether and how to use the measure(s) in outcome analysis

District decision-making for health in low-income settings: a qualitative study in Uttar Pradesh, India, on engaging the private health sector in sharing health-related data.

Health information systems are an important planning and monitoring tool for public health services, but may lack information from the private health sector. In this fourth article in a series on district decision-making for health, we assessed the extent of maternal, newborn and child health (MNCH)-related data sharing between the private and public sectors in two districts of Uttar Pradesh, India; analysed barriers to data sharing; and identified key inputs required for data sharing. Between March 2013 and August 2014, we conducted 74 key informant interviews at national, state and district levels. Respondents were stakeholders from national, state and district health departments, professional associations, non-governmental programmes and private commercial health facilities with 3-200 beds. Qualitative data were analysed using a framework based on a priori and emerging themes. Private facilities registered for ultrasounds and abortions submitted standardized records on these services, which is compulsory under Indian laws. Data sharing for other services was weak, but most facilities maintained basic records related to institutional deliveries and newborns. Public health facilities in blocks collected these data from a few private facilities using different methods. The major barriers to data sharing included the public sector's non-standardized data collection and utilization systems for MNCH and lack of communication and follow up with private facilities. Private facilities feared information disclosure and the additional burden of reporting, but were willing to share data if asked officially, provided the process was simple and they were assured of confidentiality. Unregistered facilities, managed by providers without a biomedical qualification, also conducted institutional deliveries, but were outside any reporting loops. Our findings suggest that even without legislation, the public sector could set up an effective MNCH data sharing strategy with private registered facilities by developing a standardized and simple system with consistent communication and follow up