Health response plays a major role during disasters and information management plays a crucial role in situational awareness to adapt to evolving needs. Health organizations exchange information often through narrative-based documents called situation reports. Although situation reports are widely shared, they are an increasingly challenging information source from which to infer knowledge for situational awareness. This paper analyzed health information from traditional health reports using mixed methods during the aftermath of the 2010 Haiti Earthquake and provides insights into the patterns of what's being said, how it's being said, and trends over time. Opportunities lie ahead to analyze narrative documents at scale by combining human knowledge from qualitative coding with machine intelligence. In addition, developing unifying health domain ontologies representing diverse humanitarian health concepts will advance computational techniques to improve the efficiency and accuracy of retrieving knowledge for improved situational awareness and potential decision making during humanitarian health response.