The role of partners in promoting self-care for misoprostol and subcutaneous DMPA in Pakistan.

BACKGROUND: Pakistan is among a number of countries facing protracted challenges in addressing maternal mortality with a concomitant weak healthcare system complexed with inequities. Sexual and reproductive health and rights (SRHR) self-care interventions offer the best solution for improving access to quality healthcare services with efficiency and economy. This manuscript documents country experience in introducing and scaling up two selected SRHR self-care interventions. A prospective qualitative study design was used and a semi-structured questionnaire was shared with identified SRHR private sector partners selected through convenience and purposive sampling. The two interventions include the use of misoprostol for postpartum hemorrhage and the use of subcutaneous depomedroxyprogesterone acetate (DMPA) as injectable contraceptive method. Data collection was done through emails and telephone follow-up calls. RESULTS: Nine of the 13 partners consulted for the study responded. The two selected self-care interventions are mainly supported by private sector partners (national and international nongovernmental organizations) having national or subnational existence. Their mandates include all relevant areas, such as policy advocacy, field implementation, trainings, supervision and monitoring. A majority of partners reported experience related to the use of misoprostol; it was introduced more than a decade ago, is registered and is procured by both public and private sectors. Subcutaneous DMPA is a new intervention, having been introduced only recently, and commodity availability remains a challenge. It is being delivered through health workers/providers and is not promoted as a self-administered contraceptive. Community engagement and awareness raising is reported as an essential element of successful field implementation; however, no beneficiary data was collected for the study. Training approaches differ considerably, are standalone or integrated with SRHR topics and their duration varies between 1 and 5 days, covering a range of cadres. CONCLUSION: Pubic sector ownership and patronage is essential for introducing and scaling up self-care interventions as a measure to support the healthcare system in delivering quality sexual and reproductive health services. Supervision, monitoring and reporting are areas requiring further support, as well as the leadership and governance role of the public sector. Standardization of trainings, community awareness, supervision, monitoring and reporting are required together with integration of self-care in routine capacity building activities (pre- and in-service) on sexual and reproductive health in the country.

Fall Detection System for the Elderly Based on the Classification of Shimmer Sensor Prototype Data.

OBJECTIVES: Falling in the elderly is considered a major cause of death. In recent years, ambient and wireless sensor platforms have been extensively used in developed countries for the detection of falls in the elderly. However, we believe extra efforts are required to address this issue in developing countries, such as Pakistan, where most deaths due to falls are not even reported. Considering this, in this paper, we propose a fall detection system prototype that s based on the classification on real time shimmer sensor data. METHODS: We first developed a data set, 'SMotion' of certain postures that could lead to falls in the elderly by using a body area network of Shimmer sensors and categorized the items in this data set into age and weight groups. We developed a feature selection and classification system using three classifiers, namely, support vector machine (SVM), K-nearest neighbor (KNN), and neural network (NN). Finally, a prototype was fabricated to generate alerts to caregivers, health experts, or emergency services in case of fall. RESULTS: To evaluate the proposed system, SVM, KNN, and NN were used. The results of this study identified KNN as the most accurate classifier with maximum accuracy of 96% for age groups and 93% for weight groups. CONCLUSIONS: In this paper, a classification-based fall detection system is proposed. For this purpose, the SMotion data set was developed and categorized into two groups (age and weight groups). The proposed fall detection system for the elderly is implemented through a body area sensor network using third-generation sensors. The evaluation results demonstrate the reasonable performance of the proposed fall detection prototype system in the tested scenarios.