Assessing Capacity and Disease Burden in a Virtual Network of New York City Primary Care Providers Following Hurricane Sandy

Abstract

Urban contexts introduce unique challenges that must be addressed to ensure that areas of high population density can function when disasters occur. The ability to generate useful data to guide decision-making is critical in this context. Widespread adoption of electronic health record (EHR) systems in recent years has created electronic data sources and networks that may play an important role in public health surveillance efforts, including in post-disaster situations. The Primary Care Information Project (PCIP) at the New York City Department of Health and Mental Hygiene has partnered with local clinicians to establish an electronic data system, and this network provides infrastructure to support primary care surveillance activities in New York City. After Hurricane Sandy, PCIP generated several sets of data to contribute to the city’s efforts to assess the impact of the storm, including daily connectivity data to establish practice operations, data to examine patterns of primary care utilization in severely affected and less affected areas, and data on the frequency of respiratory infection diagnosis in the primary care setting. Daily patient visit data from three heavily affected neighborhoods showed the health department where primary care capacity was most affected in the weeks following Sandy. Overall transmission data showed that practices in less affected areas were quicker to return to normal reporting patterns, while those in more affected areas did not resume normal data transmissions for a few months. Rates of bronchitis increased after Sandy compared to the two prior years; while this was most likely attributable to a more severe flu season, it demonstrates the capacity of primary care networks to pick up on these types of post-emergency trends. Hurricane Sandy was the first disaster situation where PCIP was asked to assess public health impact, generating information that could contribute to aid and recovery efforts. This experience allowed us to explore the strengths and weaknesses of ambulatory EHR data in post-disaster settings. Data from ambulatory EHR networks can augment existing surveillance streams by providing sentinel population snapshots on clinically available indicators in near real time.