Background

In the last 25 years, the global maternal mortality ratio (MMR) declined nearly 44% [1]. Despite this global decline, the burden of maternal mortality differs considerably by country economic development status and geographic region [1]. For example, low- and middle-income countries (LMICs) account for approximately 99% of global maternal deaths [1]. Among high-income countries (HICs), MMR rates steadily declined from 1990 to 2015, with the USA having the highest rates of maternal deaths compared to its peer HICs [2]. In 2015, all United Nations member countries adopted the 2030 Agenda for Sustainable Development [3]. The agenda outlines 17 Sustainable Development Goals (SDGs) and 169 targets that represent a call to action for all countries—developed and developing—to “ensure healthy lives and promote well-being for all at all ages” [3]. In particular, the aim of SDG Target 3.1 is to “reduce the global maternal mortality ratio to less than 70 maternal deaths per 100,000 live births by 2030” [3]. Available evidence suggests that if all participating countries meet SDG Target 3.1, the lives of an estimated 1.6 million women could be saved [4]. There is growing consensus that targeting maternal care quality (MCQ) will be a necessary approach to achieving the SDG Target 3.1 [5,6,7]. While there has been extensive work focused on developing and examining clinical performance indicators of MCQ (e.g., cesarean delivery for low-risk nulliparious women; receipt of postpartum care within 8 weeks after delivery), less is known about patient-reported measures of MCQ, which can be useful for monitoring and improving factors known to influence women’s health outcomes and maternal care utilization behaviors [8]. Also, a focus on perceived MCQ is crucial because women’s experiences in the maternal care continuum (prenatal, intrapartum, and postpartum care) can influence care seeking and utilization of essential, potentially life-saving maternal care services [5, 9,10,11,12].

In order to achieve SDG Target 3.1 and reduce the global burden of maternal mortality, health practitioners and researchers must be able to continuously measure and assess perceived MCQ. There is, however, no standard definition, conceptualization, or measurement of perceived MCQ. An example of a contemporary MCQ definition is “the degree to which maternal health services for individuals and populations increase the likelihood of timely and appropriate treatment for the purpose of achieving desired outcomes that are both consistent with current professional knowledge and uphold basic reproductive rights” [13]. Moreover, several frameworks have been developed or adapted to conceptualize MCQ [13,14,15,16,17]. An example is Donabedian’s model for examining and evaluating three components of care quality: structure (e.g., material resources, human resources, organizational structure), process (e.g., what is done in giving and receiving care), and outcomes (e.g., effects of care on the health status of patients and populations) [15]. Furthermore, several challenges exist regarding the measurement of perceived MCQ. For example, many studies documenting existing measures of MCQ have been largely focused on the monitoring of provider- or facility-reported indicators, with little emphasis on patients’ experience of care [8, 18, 19]. In fact, little is known about existing validated instruments designed to measure perceived MCQ among women. Also, perceived MCQ has been measured at distinct stages of the maternal care continuum (prenatal, intrapartum, and postpartum care) which may provide a disconnected understanding of women’s perceptions regarding the quality of care received.

Overall, there appears to be great heterogeneity in the way in which perceived MCQ is defined, conceptualized, and measured. This heterogeneity may limit generalizability across country contexts and maternal care contexts [14, 20]. Prior empirical reviews have focused primarily on provider- or facility-reported measures of MCQ [8, 18] or primarily low- or middle-income country contexts only [21,22,23]. A comprehensive knowledgebase regarding MCQ may be needed to facilitate coordinated efforts to measure and improve the provision of maternal care across diverse country economic contexts (i.e., low-, middle-, and high-income contexts). In turn, countries may be able to make progress toward achieving SDG Target 3.1, and subsequently reduce the global burden of maternal mortality.

Thus, the objective of this review is to systematically map the literature on the definition, conceptualization, and measurement of perceived MCQ across low-, middle-, and high-income countries. To ensure a comprehensive understanding of perceived MCQ, this review will focus on the maternal care continuum including prenatal care, intrapartum care, and postpartum care. Scoping review is the chosen approach because its objective is to provide a comprehensive overview of the available literature rather than critically appraise individual studies [24]. Also, given the heterogeneous and “globally siloed” nature of the literature on perceived MCQ, a scoping review is needed to map and summarize the literature in a systematic manner. In doing so, the findings from this scoping review can inform the development of more focused research questions. More specifically, the findings may inform future work focused on building consensus around the definition and conceptualization of MCQ and lay the groundwork for future research aimed at developing comprehensive and context-specific measures of perceived MCQ that are cross culturally relevant. Consequently, this work has the potential to guide efforts to improve MCQ, and ultimately make progress toward achieving SDG Target 3.1.

Method

Design and registration

The review protocol has been registered within the Open Science Framework database [25] and is being reported in accordance with the guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and the PRISMA extension for protocols (PRISMA-P) [26] (see PRISMA-P checklist in Supplemental File 1). The Arksey and O’Malley five-stage framework for conducting scoping reviews was used for this review [27]. This framework stipulates the following steps: (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, and (5) collating, summarizing, and reporting the results.

Stage 1: Identifying the research question

This scoping review is guided by two research questions:

RQ1: How has perceived maternal care quality been defined in low-, middle-, and high-income countries?

RQ2: How has perceived maternal care quality been conceptualized and measured in low-, middle-, and high-income countries?

Stage 2: Identifying relevant studies (eligibility criteria)

Eligible studies will be selected according to the Population-Concept-Context (PCC) framework recommended by the Joanna Briggs Institute as shown in Table 1 [24]. This review will be guided by the World Health Organization’s (WHO) definition of women of childbearing age (15-49). Also, while the timeframe of antenatal care and intrapartum care tends to be consistent across countries, the recommended period of postpartum (or postnatal) care may vary across countries. Therefore, this review will include studies focused on postpartum care to women up to 1 year after delivery—which falls within the WHO’s surveillance period for maternal mortality. Low-, middle-, and high-income countries will be determined by the World Bank list of economies, which has classified the countries according to their economic status [28, 29]. This review will have no time period restrictions. The authors recognize that the English language is not the universal language of science. However, due to the study team’s lack of financial and language resources (e.g., funding, professional translators), only articles published in the English language or with an English-language translation available will be included. Prior research suggests that reviews that are compliant with standard reporting guidelines and use English-language restrictions do not contribute to systematic bias or demonstrate low credibility [30, 31].

Table 1 PCC framework
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This review will include articles from the inception of each respective database to 2020. This review will include experimental studies, quasi-experimental studies, analytical observational studies (including prospective and retrospective cohort, case-control, and cross-sectional studies), qualitative and quantitative studies focused on the measurement of perceived MCQ, systematic and scoping reviews, and meta-analysis papers. To avoid publication bias, unpublished studies and gray literature will be included in this review. This review will exclude editorials, letters, and case reports because these sources will not provide empirical evidence needed to answer the present review’s research questions.

Inclusion criteria

To be included, articles must meet the following criteria:

  • Article includes women and girls of childbearing age (15-49)

  • Evidence published up to recent

  • Studies conducted in low-, middle-, or high-income country

  • All articles will be included irrespective of their study designs

  • Gray literature resources include government and non-governmental organization reports and academic dissertations

Exclusion criteria

Articles reporting the following will be excluded:

  • Articles that do not include women and girls of childbearing age (15-49)

  • Articles that do not measure women (and girls) perceptions of maternal care quality

  • Articles that only measure clinical/objective indicators of maternal care quality

  • Articles focused on measuring maternal care quality outside of a health facility (e.g., home births)

Stage 3: Study selection (search strategy)

The research team will collaboratively identify the key terms for the search strategies, and the research librarians will develop initial strategies utilizing input from all authors and test for maximum sensitivity, keeping in mind specificity. Specificity will be calculated by dividing the total number of records identified by the number of relevant records identified. The research librarians will build the search strategy focusing on four major concepts: pregnancy and its outcomes and complications, maternal health care, quality of care, patient satisfaction, and assessment tools. For each concept, the research librarians will truncate keywords as necessary and include relevant subject headings to achieve a comprehensive set of citations. For the purposes of this protocol, the research team used the aforementioned steps to develop a draft central search strategy and had the draft central search strategy reviewed by an expert medical librarian at a different institution to provide feedback to help refine the strategy. The draft central search strategy is provided in Table 2.

Table 2 . Draft Central Search Strategy
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The research librarians will modify the strategies so that they are appropriate for each database. The review team plans to search for peer-reviewed publications in the following databases from inception to 2020: Ovid MEDLINE, Embase, AMED, WHO Global Index Medicus, Grey: BioMed Central Journals, Google Scholar, and ProQuest Dissertations and Theses. The World Health Organization International Clinical Trials Registry Platform (ICTRP) will not be used because it is currently closed indefinitely to non-WHO staff due to high use during COVID-19 pandemic.

The research librarians will collect and upload metadata from all identified records to EndNote and remove duplicates. This review will use a two-stage screening process as a large number of studies are expected. The first screening phase will consist of reviewing the titles and abstracts of each record and removing articles that are irrelevant. The second screening phase will consist of reviewing the full text of included articles. After reading each paper, further irrelevant articles will be removed from the study sample. The remaining articles will have relevance to the study question and will be put forward for data extraction. Each stage of this process will be completed by two reviewers (KB and GB) independently with disagreement resolved initially by consensus and if needed by a third reviewer. A summary of the study selection process will be presented as a PRISMA flowchart. A table of excluded studies and reasons for exclusion will be provided.

Stage 4: Charting the data (data extraction)

To ensure the most relevant and comprehensive information is extracted in a systematic way, we will create a data extraction table in Microsoft Word. As shown in Table 3, the extraction of charting elements will be based on guidance from the JBI Review’s Manual [32] and additional columns relevant to this review’s research questions using a format illustrated in other protocols [33, 34]. We will record additional result details including (1) database searched, (2) search date, (3) search string with limiters, (4) results retrieved, and (5) number of duplications removed. The data extraction tool will be piloted by two reviewers on two articles first and where needed, modifications will be made to the data extraction tool. However, there may be further refinements added to include any relevant data that was not initially included during the extraction process. Data from all included studies will then be charted by the first reviewer (KB) and extraction checked by the second reviewer (GB).

Table 3 Preliminary table of charting elements and relevant questions for data
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Stage 5: Collating, summarizing, and reporting results

This stage will consist of four major steps that include the use of numerical, graphical, tabular, and narrative summaries. In the first analytic step, the review will provide a descriptive numerical and tabular summary that includes the total number of included articles, including a breakdown of articles by year of publication, country economic classification (low, middle, and high income), type of care (antenatal, intrapartum, and postpartum), type of study design, and type of instrument used (qualitative or quantitative).

The Arksey and O’Malley methodology recommends adopting a framework to collate and summarize the extracted data in a systematic manner [27]. Therefore, the review results will utilize country economic classification (low, middle, high income) and Donabedian’s model of care quality (structure, process, outcome) to organize the results in a structured, systematic manner, and thereby enhance the articulation of the results [27, 32]. The second analytic step will aim to answer the first research question (RQ1: How has perceived maternal care quality been defined in low-middle-, and high-income countries?). This review will present a table (see Table 4 in Supplemental File 2), organized by country economic classification, to report the following information for each included article: author/year, country name, sample description, type of care (antenatal, intrapartum, postpartum), definition of perceived maternal care quality, theoretical framework used to conceptualize maternal care quality from the patient’s perspective. Based on this table, a written narrative will describe similarities and differences in the way in which perceived maternal care quality has been defined within each country economic classification and across the three different classifications. This written narrative will also describe identified gaps in the literature.

The third analytic step will aim to answer the second research question (RQ2: How has perceived maternal care quality been conceptualized and measured in low-, middle-, and high-income countries?). First, this review will include a chart (see Figure 1 in Supplemental File 2) to visually map the number of articles by country economic classification (low, middle, high income) and by Donabedian concept category (process, structure, outcome). If a single article focuses on constructs that fall within two or more Donabedian concept categories, each one will be counted separately. The purpose of this chart is to illustrate trends and patterns in the overarching maternal care quality concepts measured overall and by country economic classification.

Second, this review will present a table (see Table 5 in Supplemental File 2), organized by Donabedian’s concept categories. This table will report the following information for each article: author/year, country income classification, construct(s) measured, type of care (antenatal, intrapartum, and postpartum), and type of instrument used. This table is intended to provide a more detailed breakdown of the information presented in Figure 1. The intent of this table is not to assess the quality of the article or instruments used. Based on this table, a narrative summary will be organized according to the three Donabedian concept categories. For each Donabedian concept category, the written narrative will (a) summarize patterns in the types of constructs measured in the overall literature and by country income classification and (b) patterns in the types of constructs measured by type of care and by country income classification. The narrative summary will also describe any identified gaps.

Discussion

This scoping review will provide a comprehensive view of the existing evidence on perceived MCQ. This review’s proposed methodology for identifying and mapping the existing literature includes a rigorous and transparent approach, documented in such a way to promote replication [27]. The objective of this scoping review is to map the literature on the definition, conceptualization, and measurement of perceived MCQ across low-, middle-, and high-income countries. As the first known scoping review of its kind, the findings from this scoping review are expected to inform future work focused on building consensus around the definition and conceptualization of perceived MCQ and lay the groundwork for future research aimed at developing measures of perceived MCQ that can be applied across diverse country economic contexts. This scoping review has the potential to lay the foundation for future efforts to make progress toward achieving SDG Target 3.1, and subsequently reducing the global burden of maternal mortality.