Analytic Approach

PPOR puts local data in the hands of community stakeholders, providing them with an analytic framework and steps that allow communities to make full use of all available data and information for evidence-based public health planning. 

PPOR analysis begins with vital records data files - electronic lists of all births, infant deaths, and fetal deaths, to community residents. It provides a simple framework and steps for investigating the reasons for the deaths and prioritizing among potential prevention efforts.The birth certificates include birth weight, gestational age, maternal characteristics, and details about the pregnancy and birth. Death certificates include the age at death and cause of death. Fetal death certificates include both sets of data elements. PPOR analysis requires a minimum of 60 deaths over at most a five year period, and works best if there are more deaths.

In Phase 1 of PPOR analysis, the analyst sorts fetal and infant deaths into four periods of risk based on birth weight and gestational age, and calculates a mortality rate for each period.  Then the community must select a reference group, which is a population whose low mortality serves as a goal that the study population should be able to reach. In each period of risk, and overall, the reference population's rate is subtracted from the rate for the study population. The differences, (called "gaps" or "excess mortality rates") represent preventable deaths that occurred in the study population. Generally, a community will benefit most from addressing the populations and periods of risk with the largest gaps. Additional (Phase 2) analysis is required to help the community determine what actions will have the most impact.

Phase 2 of PPOR analysis has three steps. In the first step, the community uses vital records and other local, population-based data to determine what causes of fetal and infant mortality are most likely to be contributing to the gaps discovered in Phase 1. Once the most important causes are determined, the second step uses local data to determine which of the known risk factors for those causes are most likely to be contributing to those gaps. The third step estimates the potential impact of addressing the contributing risk factors, so that the community can better prioritize its prevention efforts.

PPOR Phase 2 analytic methods facilitate the use of data sources beyond vital records to identify factors that may be contributing to infant mortality gaps. These might include PRAMS, BRFSS, Child Death Reviews, hospital discharge databases, etc. Communities can benefit from incorporating into the decision making process information about special populations (such as WIC, Medicaid, and low income health clinics), or results from case study methods (such as Fetal Infant Mortality Reviews). All rights reserved©