Mortality Data Clause Samples
The Mortality Data clause establishes the requirements and procedures for collecting, reporting, and sharing information related to deaths within the scope of an agreement or project. Typically, this clause outlines the types of mortality data to be provided, the format and frequency of reporting, and the responsibilities of each party in maintaining accurate records. For example, in clinical trials or insurance agreements, it may specify how and when death-related data must be submitted to regulatory authorities or other stakeholders. The core function of this clause is to ensure transparency and compliance in the handling of sensitive mortality information, thereby supporting regulatory oversight and informed decision-making.
Mortality Data. The Contractor must report mortality data annually, by age and gender, in the following categories:
1. The number of Enrollees who died during the past year;
2. Percentage who died in hospitals;
3. Percentage who died in nursing facilities;
4. Percentage who died in non-institutional settings; and
5. Cause of death.
Mortality Data. In a form and format specified by EOHHS, the Contractor shall report mortality data annually, by age and gender, in the following categories: The number of Enrollees who died during the past year; Percentage who died in hospitals; Percentage who died in nursing facilities; Percentage who died in community-based settings; and Cause of death.
Mortality Data. I obtain data for infant and neonatal mortality from the retroactive fertility histories found in the births sample survey. This includes all births to female respondents aged 13-45 at the time of the survey for waves 1 and 2 and all female respondents aged 15-45 for survey wave 4. I limit the sample to include children with non-missing information regarding mother’s district of residence, child’s age, and child’s age at death if deceased. The group of mothers used for analysis includes only those that ever lived within 100 km of a storm path, allowing for a more homogeneous sample. Table 1 presents the averages of core demographic characteristics for children and mothers in each sub-group of the sample, weighted using provided survey weights. Figure 1 illustrates the weighted size of the sub-sample in each district in the treatment and control groups. I find these groups to be balanced in the outcome variables of interest, namely neonatal mortality and infant mortality, meaning that underlying differences in mothers and children near or far from storm paths are unlikely to bias estimates. I do note that mothers in districts ever within 50 km of a storm path are more highly educated by less than 1 year and are more likely to be literate, have less children, and live in a rural area.