Background Measuring facility readiness to manage basic obstetric emergencies is a critical step toward reducing persistently elevated maternal mortality ratios (MMR). Currently, the Signal Functions (SF) is the gold standard for measuring facility readiness globally and endorsed by the WHO. The presence of tracer items classifies facilities’ readiness to manage basic emergencies. However, research suggests the signal functions may be an incomplete indicator. The Clinical Cascades (CC) have emerged as a clinically-oriented alternative to measuring readiness. The purpose of this study is to determine Amhara's clinical readiness and quantify the relationship between SF and cascade estimates of readiness. Methods Data were collected in May 2021via Open Data Kit (ODK) and KoBo Toolbox. We surveyed 20 hospitals across three levels of the health system. Commodities were used to create measures of SF-readiness (e.g., % tracers) and cascade-readiness. We calculated differences in SF and cascade estimates and calculated readiness loss across five emergencies and 3 stages of care in the cascades. Results The overall Signal Function estimate for all 6 obstetric emergencies was 17.5% greater than the estimates using the cascades. Consistent with global patterns, hospitals were more prepared to provide medical management (70.0% ready) compared to manual procedures (56.7% ready). The SF overestimate was greater for manual procedures (26.7% overall for retained placenta and incomplete abortion) and less for medical treatments (8.3%). Hospitals were least prepared to manage retained placentas (30.0% of facilities were ready at treatment and 0.0% were ready at monitor and modify) and most able to manage hypertensive emergencies (85.0% of facilities were ready at the treatment stage). When including protocols in the analysis, no facilities were ready to monitor and modify the initial therapy when clinically indicated for 3 common emergencies—sepsis, post-partum hemorrhage and retained placentas. Conclusions We identified a significant discrepancy between SF and CC readiness classifications. Those facilities that fall within this discrepancy are unprepared to manage common obstetric emergencies, but regional health planners are unable to identify the need. Future research should explore the possibility of modifying the SF or replacing it with a new readiness measurement.

Introduction Women with physical disabilities experience barriers to accessing patient‐centered and accommodative care during the prenatal and childbirth periods. While there is a growing body of work in high‐income countries to address these needs, there is little research detailing specific challenges in low‐ and middle‐income countries (LMICs) where a woman's’ burden— and need—is greatest. Methods We conducted an integrative review to synthesize the experiences of women with physical disabilities accessing prenatal care and childbirth services in LMICs. Five databases were searched for systematic reviews, retrospective cohort studies, cross‐sectional studies, narrative literature reviews, as well as other evidence types. We used Ediom's EvidenceEngine™, a machine‐assisted search engine that uses artificial intelligence to conduct this search using pertinent keywords to identify original research published between January 2009 ‐ September 2018. These results were augmented by hand searching of reference lists. Forty articles were identified using this method and 11 retained after duplicates were removed and inclusion and exclusion criteria applied. Results Four types of experiences are described in these 11 studies: (1) limited physical and material resources; (2) health care worker knowledge, attitudes, and skills; (3) pregnant people's knowledge; and (4) public stigma and ignorance. Discussion People with physical disabilities face specific challenges during pregnancy and childbirth. Importantly, these findings offer targets for enhanced clinical training for nurses, midwives, traditional birth attendants and public health workers, as well as opportunities for the improved delivery of prenatal care and childbirth services to these vulnerable women.

UNSTRUCTURED Electronic data capture systems are critical to sustaining, evaluating, and improving population health. Globally, some Low-and-Middle Income Countries face barriers to implementing data systems related to limited data infrastructure, human resources, or financial capital. This paper presents two case examples on the initial development of electronic data capture systems to improve population health from two global contexts– Ethiopia and Myanmar. We analyze these cases using Sittig and Singh’s Socio-technical Model for Studying Health Information Technology in Complex Adaptive Healthcare Systems. Both cases also describe how the electronic data capture systems facilitated continued population health research under dual crises—both civil unrest and the COVID-19 pandemic. Notably, the sociotechnical model highlights how critical social and cultural considerations are in technically designing electronic data capture systems to improve population health and surveillance. These applied cases offer practical lessons to inform data system efforts for similar global contexts.

Objective The aim of this study was to explore the state of health information technology (HIT) usability evaluation in Africa. Materials and Methods We searched three electronic databases: PubMed, Embase, and Association for Computing Machinery. We categorized the stage of evaluations, the type of interactions assessed, and methods applied using Stead’s System Development Life Cycle (SDLC) and Bennett and Shackel’s usability models. Results Analysis of 73 of 1002 articles that met inclusion criteria reveals that HIT usability evaluations in Africa have increased in recent years and mainly focused on later SDLC stage (stages 4 and 5) evaluations in sub-Saharan Africa. Forty percent of the articles examined system-user-task-environment (type 4) interactions. Most articles used mixed methods to measure usability. Interviews and surveys were often used at each development stage, while other methods, such as quality-adjusted life year analysis, were only found at stage 5. Sixty percent of articles did not include a theoretical model or framework. Discussion The use of multistage evaluation and mixed methods approaches to obtain a comprehensive understanding HIT usability is critical to ensure that HIT meets user needs. Conclusions Developing and enhancing usable HIT is critical to promoting equitable health service delivery and high-quality care in Africa. Early-stage evaluations (stages 1 and 2) and interactions (types 0 and 1) should receive special attention to ensure HIT usability prior to implementing HIT in the field.

Measuring facility readiness to manage basic obstetric emergencies is a critical step toward reducing persistently elevated maternal mortality ratios (MMR). Currently, the Signal Functions (SF) is the gold standard for measuring facility readiness globally and endorsed by the World Health Organization. The presence of tracer items classifies facilities’ readiness to manage basic emergencies. However, research suggests the SF may be an incomplete indicator. The Clinical Cascades (CC) have emerged as a clinically-oriented alternative to measuring readiness. The purpose of this study is to determine Amhara’s clinical readiness and quantify the relationship between SF and CC estimates of readiness. Data were collected in May 2021via Open Data Kit (ODK) and KoBo Toolbox. We surveyed 20 hospitals across three levels of the health system. Commodities were used to create measures of SF-readiness (e.g., % tracers) and CC-readiness. We calculated differences in SF and CC estimates and calculated readiness loss across six emergencies and 3 stages of care in the cascades. The overall SF estimate for all six obstetric emergencies was 29.6% greater than the estimates using the CC. Consistent with global patterns, hospitals were more prepared to provide medical management (70.0% ready) compared to manual procedures (56.7% ready). The SF overestimate was greater for manual procedures 33.8% overall for retained placenta and incomplete abortion) and less for medical treatments (25.3%). Hospitals were least prepared to manage retained placentas (30.0% of facilities were ready at treatment and 0.0% were ready at monitor and modify) and most prepared to manage hypertensive emergencies (85.0% of facilities were ready at the treatment stage). When including protocols in the analysis, no facilities were ready to monitor and modify the initial therapy when clinically indicated for 3 common emergencies—sepsis, post-partum hemorrhage and retained placentas. We identified a significant discrepancy between SF and CC readiness classifications. Those facilities that fall within this discrepancy are unprepared to manage common obstetric emergencies, and employees in supply management may have difficulty identify the need. Future research should explore the possibility of modifying the SF or replacing it with a new readiness measurement.