Ready to deliver maternal and newborn care? Health providers’ perceptions of their work context in rural Mozambique

listen audio

Study Justification:
– The study aims to address deficiencies in the provision of evidence-based obstetric care in low-income countries, specifically in Mozambique.
– It seeks to understand the healthcare context in order to inform the implementation of new interventions and improve the delivery of maternal and newborn care.
– By assessing the modifiable aspects of the healthcare context, the study aims to identify shortcomings and tailor strategies for successful implementation.
Highlights:
– The study utilized the Context Assessment for Community Health (COACH) tool to assess the healthcare context as perceived by health providers involved in maternal care in Mozambique.
– The tool was found to be comprehensible and demonstrated good reliability, although biases may have influenced participants’ responses.
– The survey data indicated that health providers had a positive perception of the healthcare context, with high ratings on all dimensions.
– However, significant differences between districts were found for the dimensions of Work culture, Leadership, and Informal payment.
Recommendations:
– The study recommends supplementing the COACH tool with qualitative approaches to gain a more in-depth understanding of the healthcare context.
– The findings suggest the potential for using COACH to evaluate the healthcare context and identify areas for improvement before implementing new interventions.
Key Role Players:
– Health providers involved in maternal and neonatal care
– Researchers and data collectors
– Policy makers and government officials
– Health facility administrators and managers
Cost Items for Planning Recommendations:
– Training and capacity building for health providers and researchers
– Data collection and analysis tools
– Travel and logistics for data collection
– Communication and dissemination of findings
– Stakeholder engagement and collaboration activities
– Monitoring and evaluation of implementation strategies

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is based on a cross-sectional survey using the COACH tool, which was administered to 175 health providers in 38 health facilities in Mozambique. The study found that the content of COACH was clear and most items were understood, and the tool demonstrated good reliability. However, biases may have influenced participants’ responses. To improve the evidence, the study could have included a larger sample size and used a randomized controlled trial design to minimize biases and increase the generalizability of the findings.

Background: Deficiencies in the provision of evidence-based obstetric care are common in low-income countries, including Mozambique. Constraints relate to lack of human and financial resources and weak health systems, however limited resources alone do not explain the variance. Understanding the healthcare context ahead of implementing new interventions can inform the choice of strategies to achieve a successful implementation. The Context Assessment for Community Health (COACH) tool was developed to assess modifiable aspects of the healthcare context that theoretically influence the implementation of evidence. Objectives: To investigate the comprehensibility and the internal reliability of COACH and its use to describe the healthcare context as perceived by health providers involved in maternal care in Mozambique. Methods: A response process evaluation was completed with six purposively selected health providers to uncover difficulties in understanding the tool. Internal reliability was tested using Cronbach’s α. Subsequently, a cross-sectional survey using COACH, which contains 49 items assessing eight dimensions, was administered to 175 health providers in 38 health facilities within six districts in Mozambique. Results: The content of COACH was clear and most items were understood. All dimensions were near to or exceeded the commonly accepted standard for satisfactory internal reliability (0.70). Analysis of the survey data indicated that items on all dimensions were rated highly, revealing positive perception of context. Significant differences between districts were found for the Work culture, Leadership, and Informal payment dimensions. Responses to many items had low variance and were left-skewed. Conclusions: COACH was comprehensible and demonstrated good reliability, although biases may have influenced participants’ responses. The study suggests that COACH has the potential to evaluate the healthcare context to identify shortcomings and enable the tailoring of strategies ahead of implementation. Supplementing the tool with qualitative approaches will provide an in-depth understanding of the healthcare context.

This was a cross-sectional survey in which the COACH tool was administered to health providers involved in maternal and neonatal care in 38 health facilities of six districts in southern Mozambique (Figure 1): Bilene-Macia, Chibuto, Chokwe and Xai-Xai districts (in Gaza province), and Magude and Manhiça districts (in Maputo province). Study setting displaying included districts and health facilities, in Maputo and Gaza provinces, Mozambique. Of the 38 facilities, 32 are primary health centres providing essential preventive and curative services, including antenatal and intrapartum care for uncomplicated deliveries. The remaining six facilities are hospitals (four rural, one district and one provincial) to which complicated cases are referred, and routine surgical interventions such as caesarean sections or obstetric hysterectomies, are performed. The tool has 49 items that measure eight dimensions of context (some dimensions have sub-dimensions) and is available in English, Bangla, Vietnamese, Lusoga, isiXhosa, and Spanish [21]. Items for seven of the eight dimensions (see Table 1 for the definitions) measure agreement with statements that theoretically reflect a context supportive of change (hereinafter referred to as the context’s readiness to change). Items on these dimensions were measured on a five-point Likert scale (ranging from ‘strongly disagree’ to ‘strongly agree’). Definitions of COACH dimensions. *Unit refers to the department or primary health care centre where the respondent is working. For the Sources of knowledge dimension, respondents indicate for each of five knowledge sources whether the source is available, and, where available, the frequency of its use (never, rarely, occasionally, frequently and almost always) [14]. In addition to the 49 original COACH items, the version used in this study contained seven demographic questions (age, gender, professional qualification, year professional qualification obtained, health facility, department (if applicable) and years working at the current facility). The translation of the COACH tool from English to Portuguese followed Brislin’s model as summarized by Yu et al. (2008) [22]. The translation was conducted in four phases: (1) Forward translation (English to Portuguese) by a bilingual professional translator with knowledge of the tool in order to assure appropriate language use; (2) Review of the translated tool by a monolingual reviewer with no familiarity of or access to the English version; (3) Backward translation (Portuguese to English) by a different bilingual professional translator from the one engaged in step (1); and (4) Comparison of the original version and the backward-translated version focusing on conceptual clarity and aimed to ensure an appropriate Portuguese translation of the tool. Comprehensibility, in this study, refers to the extent to which a statement is easy to understand by the reader. To uncover difficulties in understanding the instructions for completing COACH or items in the tool, the Portuguese version was administered by structured interview to six purposively selected health providers (two physicians, two midwives and two auxiliary nurses) representing the provider categories the main survey would target. In each interview, the first author introduced COACH before the participants were asked to read and state their level of agreement with each of the items in the tool and reflect upon whether they had any difficulty understanding its content. Attention was paid to the participants’ level of understanding and whether they had any challenges in rating their level of agreement with the items. Identified problems were translated into English and categorized in two ways: (a) by the magnitude of their effect on the collected data (prominent vs. minor) [14]; and (b) by Conrad and Blair’s taxonomy [23] (see Table 2). All identified problems were also discussed in relation to the underlying cause of the problem, i.e. relating to the content of the item or the Portuguese translation of the item. Based on the findings from the response process, we produced the final Portuguese version of the COACH tool for data collection (http://www.kbh.uu.se/imch/coach). Analysis framework for the COACH tool response process in Mozambique. The original COACH tool, designed to be a self-administered questionnaire [16], was amended for administration via an individual structured interview to maximize response and item response rates [24]. An interview guide was designed to ensure that the data collection was standardized and that clear, complete and unambiguous responses to the statements were obtained from the respondents. A member of the research team (R.C.) carried out the interviews, which were undertaken in secluded rooms in the health facilities. Eligible respondents were health providers (doctors, medical assistants, nurses, midwives and auxiliary nurses) who had worked in the targeted facilities for at least 12 months before the study (n = 273). Data were collected between April and June 2016. We were able to interview 175 health providers from the identified 273 eligible respondents (64% response rate). From the 98 who did not participate (46% were nurses and 37% auxiliaries), 55 were absent (vacation, illness leave or not on shift), 42 were not able to answer (busy with patients), and one refused to be interviewed. The non-response rate was higher in hospitals, 41% (47 out of 114) compared to 32% (51 out of 159) in primary facilities. The 175 questionnaires were checked for completeness of responses, with no missing responses detected. Data were double-entered in OpenClinica software, version 3.1 [25] and imported into SPSS v. 24 [26] and R software (version 3.3.1) [27] for further analyses. For the demographic variables age, gender, professional category, healthcare level, district and years working in the current facility, mean and standard deviation or median and interquartile range as appropriate were calculated for continuous variables and proportion (%) for categorical variables. Items 42 to 47 described elements of context obstructive to the implementation of interventions and EBPs and scores were therefore reverse scored to be consistent with the connotation of the other items. Items from the Sources of Knowledge dimension were recoded into 0 (not available, never and rarely), 0.5 (occasionally), and 1 (frequently and always). The internal consistency reliability of each dimension was tested using Cronbach’s α analyses with item trial removal where indicated. Once satisfactory reliability was demonstrated, items within dimensions were summed, and descriptive analysis (minimum and maximum scores, means and standard deviations) of dimensions was performed. Subsequently, individual-level data were aggregated within districts and one-way analysis of variance (ANOVA) with the post hoc Tukey HSD test was performed for each dimension using the district as the group variable. Level of significance was set at p < .05.

N/A

Based on the provided description, the study conducted a cross-sectional survey using the Context Assessment for Community Health (COACH) tool to assess the healthcare context as perceived by health providers involved in maternal care in Mozambique. The tool consists of 49 items that measure eight dimensions of context. The study found that the COACH tool was comprehensible and demonstrated good reliability. The survey data indicated positive perceptions of the healthcare context, although there were some differences between districts in certain dimensions. The study suggests that the COACH tool has the potential to evaluate the healthcare context and identify shortcomings, enabling the tailoring of strategies for implementation.
AI Innovations Description
The recommendation based on the study is to use the Context Assessment for Community Health (COACH) tool to assess the healthcare context and identify shortcomings in order to tailor strategies for improving access to maternal health in Mozambique. The COACH tool measures eight dimensions of context that influence the implementation of evidence-based obstetric care. The tool was found to be comprehensible and demonstrated good reliability in the study. By using the COACH tool, healthcare providers can gain a better understanding of the healthcare context and make informed decisions on interventions and strategies to improve access to maternal health. Additionally, supplementing the tool with qualitative approaches can provide a more in-depth understanding of the healthcare context.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Increase human resources: Address the shortage of healthcare providers by recruiting and training more doctors, nurses, midwives, and auxiliary nurses to ensure adequate coverage and availability of skilled maternal care providers.

2. Strengthen health systems: Invest in improving the overall health system infrastructure, including health facilities, equipment, and supply chains. This will help ensure that essential maternal health services are accessible and available in rural areas.

3. Enhance leadership and management: Implement effective leadership and management strategies to improve coordination, supervision, and accountability within the healthcare system. This can help optimize the delivery of maternal health services and ensure quality care.

4. Improve work culture: Foster a positive work culture that promotes teamwork, motivation, and job satisfaction among healthcare providers. This can contribute to better maternal health outcomes and encourage providers to stay in rural areas.

5. Address informal payments: Develop strategies to address the issue of informal payments in the healthcare system, which can create barriers to accessing maternal health services. This may involve implementing transparent payment systems and strengthening anti-corruption measures.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Baseline data collection: Gather data on the current state of maternal health access, including indicators such as the number of healthcare providers, availability of essential services, and patient satisfaction.

2. Define simulation parameters: Determine the specific variables and factors that will be simulated, such as the increase in healthcare providers, improvements in infrastructure, or changes in leadership and management practices.

3. Model development: Develop a simulation model that incorporates the identified parameters and their potential impact on access to maternal health. This may involve using mathematical models, statistical analyses, or computer simulations.

4. Data input and validation: Input the baseline data into the simulation model and validate its accuracy by comparing the simulated results with the actual data.

5. Scenario testing: Run the simulation model with different scenarios that reflect the recommended innovations, such as increasing the number of healthcare providers or improving work culture. Evaluate the impact of each scenario on access to maternal health by analyzing the simulated results.

6. Sensitivity analysis: Conduct sensitivity analyses to assess the robustness of the simulation results and identify the key factors that have the greatest influence on improving access to maternal health.

7. Interpretation and recommendations: Analyze the simulated results and draw conclusions about the potential impact of the recommended innovations on improving access to maternal health. Use these findings to make evidence-based recommendations for policy and programmatic interventions.

8. Monitoring and evaluation: Continuously monitor and evaluate the implementation of the recommended innovations to assess their actual impact on improving access to maternal health. Adjust the simulation model as needed based on new data and insights.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context and available data.

Share this:
Facebook
Twitter
LinkedIn
WhatsApp
Email