This article emphasizes the significance of the Monitoring, Evaluation, and Learning (MEL) system within Babies and Mothers Alive (BAMA) Foundation in building effective sustainable interventions at scale. The foundation aims to enhance the availability of high-quality reproductive, maternal, and newborn care services within the government health sector. The distinguishing characteristic of the MEL system is its integration of organizational learning as a strategic approach to inform the development of dynamic program designs. To do this, it has been necessary to identify crucial requirements through open data exchange with all pertinent stakeholders. This paper demonstrates that our approach to evidence-based learning in a diverse population of locally-based actors and stakeholders, gives voice to the community-based health practitioners and patients that is necessary for transformative maternal health delivery systems. The act of sharing data has presented several possibilities for enhancing current initiatives and extending the reach and scale of our partnership model. We trace the development of the core components of learning and decision making, and reflect on the transition of the program to scale using the LADDERS paradigm. The application of our model of practice has been associated with the increased financially viability and the potential for the sustainable scaling of the program intervention.
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http://dx.doi.org/10.3389/fpubh.2024.1188584 | DOI Listing |
Breast Cancer Res Treat
January 2025
Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Purpose: To evaluate the prognostic significance of changes in pre- and post-neoadjuvant chemotherapy (NACT) Ki67 in patients with primary invasive triple-negative breast cancer (TNBC).
Methods: Population-based registry data were retrieved for patients diagnosed with TNBC between 2007 and 2021 (n = 9262). Multivariable Cox regression analysis was performed for disease-specific survival (DSS) and overall survival (OS) adjusted for age and residual disease in the breast and nodes (RDBN).
Int J Comput Assist Radiol Surg
January 2025
Advanced Medical Devices Laboratory, Kyushu University, Nishi-ku, Fukuoka, 819-0382, Japan.
Purpose: This paper presents a deep learning approach to recognize and predict surgical activity in robot-assisted minimally invasive surgery (RAMIS). Our primary objective is to deploy the developed model for implementing a real-time surgical risk monitoring system within the realm of RAMIS.
Methods: We propose a modified Transformer model with the architecture comprising no positional encoding, 5 fully connected layers, 1 encoder, and 3 decoders.
Eur Arch Otorhinolaryngol
January 2025
Sleep Disorders Center, Ataturk Chest Diseases and Thoracic Surgery Training and Research Hospital, Ankara, Turkey.
Objective: In this study, we aimed to evaluate the localization and configuration of vibration and obstruction in drug-induced sleep endoscopy(DISE) in obstructive sleep apnea patients and to investigate the optimal sedation depth.
Materials And Methods: The study was conducted prospectively with 42 patients. After achieving sedation with intravenous anesthetic agents, simultaneous monitoring of the patient's bispectrometry (BIS), DISE and sleep testing with a type 2 polysomnography device were performed.
BMC Health Serv Res
January 2025
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, 21205, USA.
Background: Since the inception of the ASHAs in the year 2005, their work horizons have increased from Reproductive, Maternal, Newborn, Child, and Adolescent health (RMNCH + A), Communicable and Non-Communicable Diseases (CD & NCD) to oral health, ophthalmologic care, and other supportive community level healthcare services. The present literature lacks comprehensive understanding and synthesis of domain-wise knowledge of ASHAs and the factors affecting their knowledge. Therefore, this study aimed to synthesize and collate the relevant evidence to understand the overall knowledge of ASHAs.
View Article and Find Full Text PDFJ Expo Sci Environ Epidemiol
January 2025
Department of Environmental and Occupational Health, Joe C. Wen School of Population & Public Health, University of California, Irvine, CA, USA.
Background: Children living in communities with lower socioeconomic status and higher minority populations are often disproportionately exposed to particulate matter (PM) compared to children living in other communities.
Objective: We assessed whether adding HEPA filter air cleaners to classrooms with existing HVAC systems reduces indoor air pollution exposure.
Methods: From July 2022 to June 2023, using a block randomized crossover trial of 17 Los Angeles Unified School District elementary schools, classroom PM concentrations were monitored and compared for 99 classrooms with HEPA filter air cleaners and 87 classrooms with non-HEPA filter air cleaners.
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