Social media mining for identification and exploration of health-related information from pregnant women

Widespread use of social media has led to the generation of substantial amounts of information about individuals, including health-related information. Social media provides the opportunity to study health-related information about selected population groups who may be of interest for a particular study. In this paper, we explore the possibility of utilizing social media to perform targeted data collection and analysis from a particular population group -- pregnant women. We hypothesize that we can use social media to identify cohorts of pregnant women and follow them over time to analyze crucial health-related information. To identify potentially pregnant women, we employ simple rule-based searches that attempt to detect pregnancy announcements with moderate precision. To further filter out false positives and noise, we employ a supervised classifier using a small number of hand-annotated data. We then collect their posts over time to create longitudinal health timelines and attempt to divide the timelines into different pregnancy trimesters. Finally, we assess the usefulness of the timelines by performing a preliminary analysis to estimate drug intake patterns of our cohort at different trimesters. Our rule-based cohort identification technique collected 53,820 users over thirty months from Twitter. Our pregnancy announcement classification technique achieved an F-measure of 0.81 for the pregnancy class, resulting in 34,895 user timelines. Analysis of the timelines revealed that pertinent health-related information, such as drug-intake and adverse reactions can be mined from the data. Our approach to using user timelines in this fashion has produced very encouraging results and can be employed for other important tasks where cohorts, for which health-related information may not be available from other sources, are required to be followed over time to derive population-based estimates.Comment: 9 page

‘The objective was about not blaming one another’: a qualitative study to explore how collaboration is experienced within quality improvement collaboratives in Ethiopia

Background: Quality improvement collaboratives are a common approach to improving quality of care. They rely on collaboration across and within health facilities to enable and accelerate quality improvement. Originating in high-income settings, little is known about how collaboration transfers to low-income settings, despite the widespread use of these collaboratives.// Method: We explored collaboration within quality improvement collaboratives in Ethiopia through 42 in-depth interviews with staff of two hospitals and four health centers and three with quality improvement mentors. Data were analysed thematically using a deductive and inductive approach.// Results: There was collaboration at learning sessions though experience sharing, co-learning and peer pressure. Respondents were used to a blaming environment, which they contrasted to the open and non-blaming environment at the learning sessions. Respondents formed new relationships that led to across facility practical support. Within facilities, those in the quality improvement team continued to collaborate through the plan-do-study-act cycles, although this required high engagement and support from mentors. Few staff were able to attend learning sessions and within facility transfer of quality improvement knowledge was rare. This affected broader participation and led to some resentment and resistance. Improved teamwork skills and behaviors occurred at individual rather than facility or systems level, with implications for sustainability. Challenges to collaboration included unequal participation, lack of knowledge transfer, high workloads, staff turnover and a culture of dependency.// Conclusion: We conclude that collaboration can occur and is valued within a traditionally hierarchical system, but may require explicit support at learning sessions and by mentors. More emphasis is needed on ensuring quality improvement knowledge transfer, buy-in and system level change. This could include a modified collaborative design to provide facility-level support for spread

Tackling the hard problems: implementation experience and lessons learned in newborn health from the African Health Initiative

Background The Doris Duke Charitable Foundation’s African Health Initiative supported the implementation of Population Health Implementation and Training (PHIT) Partnership health system strengthening interventions in designated areas of five countries: Ghana, Mozambique, Rwanda, Tanzania, and Zambia. All PHIT programs included health system strengthening interventions with child health outcomes from the outset, but all increasingly recognized the need to increase focus to improve health and outcomes in the first month of life. This paper uses a case study approach to describe interventions implemented in newborn health, compare approaches, and identify lessons learned across the programs’ collective implementation experience. Methods Case studies were built using quantitative and qualitative methods, applying the World Health Organization Health Systems Strengthening Framework, and maternal, newborn and child health continuum of care framework. We identified the following five primary themes in health systems strengthening intervention strategies used to target improvement in newborn health, which were incorporated by all PHIT projects with varying results: health service delivery at the community level (Tanzania), combining community and health facility level interventions (Zambia), participatory information feedback and clinical training (Ghana), performance review and enhancement (Mozambique), and integrated clinical and system-level improvement (Rwanda), and used individual case studies to illustrate each of these themes. Results Tanzania and Zambia included significant community-based components, including mobilization and sensitization for increased uptake of essential services, while Ghana, Mozambique, and Rwanda focused more efforts on improving the quality of services delivered once a patient enters a health facility. All countries included aspects that improved communication across levels of the health system, whether through district-wide data sharing and peer learning networks in Mozambique and Rwanda, or improved referral processes and systems in Tanzania, Zambia, and Ghana. Conclusion Key lessons learned include the importance of focusing intervention components on addressing drivers of neonatal mortality across the maternal and newborn care continuum at all levels of the health system, matching efforts to improve service utilization with provision of high quality facility-based services, and the critical role of leadership to catalyze improvements in newborn health

“Quality teaches you how to use water. It doesn’t provide a water pump”: a qualitative study of context and mechanisms of action in an Ethiopian quality improvement program

Background Quality improvement collaboratives are a common approach to bridging the quality-of-care gap, but little is known about implementation in low-income settings. Implementers rarely consider mechanisms of change or the role of context, which may explain collaboratives’ varied impacts. Methods To understand mechanisms and contextual influences we conducted 55 in-depth interviews with staff from four health centres and two hospitals involved in quality improvement collaboratives in Ethiopia. We also generated control charts for selected indicators to explore any impacts of the collaboratives. Results The cross facility learning sessions increased the prominence and focus on quality, allowed learning from experts and peers and were motivational through public recognition of success or a desire to emulate peers. Within facilities, new structures and processes were created. These were fragile and sometimes alienating to those outside the improvement team. The trusted and respected mentors were important for support, motivation and accountability. Where mentor visits were infrequent or mentors less skilled, team function was impacted. These mechanisms were more prominent, and quality improvement more functional, in facilities with strong leadership and pre-existing good teamwork; as staff had shared goals, an active approach to problems and were more willing and able to be flexible to implement change ideas. Quality improvement structures and processes were more likely to be internally driven and knowledge transferred to other staff in these facilities, which reduced the impact of staff turnover and increased buy-in. In facilities which lacked essential inputs, staff struggled to see how the collaborative could meaningfully improve quality and were less likely to have functioning quality improvement. The unexpected civil unrest in one region strongly disrupted the health system and the collaborative. These contextual issues were fluid, with multiple interactions and linkages. Conclusions The study confirms the need to carefully consider context in the implementation of quality improvement collaboratives. Facilities that implement quality improvement successfully may be those that already have characteristics that foster quality. Quality improvement may be alienating to those outside of the improvement team and implementers should not assume the organic spread or transfer of quality improvement knowledge

Clinical mentorship to improve pediatric quality of care at the health centers in rural Rwanda: a qualitative study of perceptions and acceptability of health care workers

Background: Despite evidence supporting Integrated Management of Childhood Illness (IMCI) as a strategy to improve pediatric care in countries with high child mortality, its implementation faces challenges related to lack of or poor post-didactic training supervision and gaps in necessary supporting systems. These constraints lead to health care workers’ inability to consistently translate IMCI knowledge and skills into practice. A program providing mentoring and enhanced supervision at health centers (MESH), focusing on clinical and systems improvement was implemented in rural Rwanda as a strategy to address these issues, with the ultimate goal of improving the quality of pediatric care at rural health centers. We explored perceptions of MESH from the perspective of IMCI clinical mentors, mentees, and district clinical leadership. Methods: We conducted focus group discussions with 40 health care workers from 21 MESH-supported health centers. Two FGDs in each district were carried out, including one for nurses and one for director of health centers. District medical directors and clinical mentors had individual in-depth interviews. We performed a hermeneutic analysis using Atlas.ti v5.2. Results: Study participants highlighted program components in five key areas that contributed to acceptability and impact, including: 1) Interactive, collaborative capacity-building, 2) active listening and relationships, 3) supporting not policing, 4) systems improvement, and 5) real-time feedback. Staff turn-over, stock-outs, and other facility/systems gaps were identified as barriers to MESH and IMCI implementation. Conclusion: Health care workers reported high acceptance and positive perceptions of the MESH model as an effective strategy to build their capacity, bridge the gap between knowledge and practice in pediatric care, and address facility and systems issues. This approach also improved relationships between the district supervisory team and health center-based care providers. Despite some challenges, many perceived a strong benefit on clinical performance and outcomes. This study can inform program implementers and policy makers of key components needed for developing similar health facility-based mentorship interventions and potential barriers and resistance which can be proactively addressed to ensure success

Consensus-based approach to develop a measurement framework and identify a core set of indicators to track implementation and progress towards effective coverage of facility-based Kangaroo Mother Care.

BACKGROUND: As efforts to scale up the delivery of Kangaroo Mother Care (KMC) in facilities are increasing, a standardized approach to measure implementation and progress towards effective coverage is needed. Here, we describe a consensus-based approach to develop a measurement framework and identify a core set of indicators for monitoring facility-based KMC that would be feasible to measure within existing systems. METHODS: The KMC measurement framework and core list of indicators were developed through: 1) scoping exercise to identify potential indicators through literature review and requests from researchers and program implementers; and 2) face-to-face consultations with KMC and measurement experts working at country and global levels to review candidate indicators and finalize selection and definitions. RESULTS: The KMC measurement framework includes two main components: 1) service readiness, based on the WHO building blocks framework; and 2) service delivery action sequence covering identification, service initiation, continuation to discharge, and follow-up to graduation. Consensus was reached on 10 core indicators for KMC, which were organized according to the measurement framework. We identified 4 service readiness indicators, capturing national level policy for KMC, availability of KMC indicators in HMIS, costed operational plans for KMC and availability of KMC services at health facilities with inpatient maternity services. Six indicators were defined for service delivery, including weighing of babies at birth, identification of those ≤2000 g, initiation of facility-based KMC, monitoring the quality of KMC, status of babies at discharge from the facility and levels of follow-up (according to country-specific protocol). CONCLUSIONS: These core KMC indicators, identified with input from a wide range of global and country-level KMC and measurement experts, can aid efforts to strengthen monitoring systems and facilitate global tracking of KMC implementation. As data collection systems advance, we encourage program managers and evaluators to document their experiences using this framework to measure progress and allow indicator refinement, with the overall aim of working towards sustainable, country-led data systems