Meeting Maternal and Reproductive Health Needs in a Post-Disaster Setting: A Qualitative Case Study From Indonesia

Meeting and planning for maternal and reproductive health (MRH) needs during post-disaster scenarios is paramount, however, not without considerable challenges. This study was aimed at understanding the provision of MRH services in Siosar, a relocation site for a population displaced by the volcanic eruption in 2013 of Mount Sinabung, Indonesia. A qualitative case study approach was used, and data were collected through focus group discussions and individual interviews with women of reproductive age, community leaders, health personnel, and policymakers. The findings show that while considerable efforts were made to provide MRH services, these were described as "unfinished," due to challenges such as changes to funding, inadequate provision of supplies and health personnel, and geographical location. Recommendations are that health and other sectors design a relocation site that counts physical, psychological, and social needs of a community and policymakers integrate humanitarian and development plans that include MRH services into World Health Organization's Building Blocks of Health System.

Survival Analysis with Electronic Health Record Data: Experiments with Chronic Kidney Disease

This paper presents a detailed survival analysis for chronic kidney disease (CKD). The analysis is based on the EHR data comprising almost two decades of clinical observations collected at New York-Presbyterian, a large hospital in New York City with one of the oldest electronic health records in the United States. Our survival analysis approach centers around Bayesian multiresolution hazard modeling, with an objective to capture the changing hazard of CKD over time, adjusted for patient clinical covariates and kidney-related laboratory tests. Special attention is paid to statistical issues common to all EHR data, such as cohort definition, missing data and censoring, variable selection, and potential for joint survival and longitudinal modeling, all of which are discussed alone and within the EHR CKD context.