Local health departments (LHDs) and state health agencies (SHAs) require quantitative data to fulfill their obligation to ensure public health. However, data collection and sharing are not straightforward processes in the US public health system. Responsibilities are divided among many actors, jurisdictions overlap, events that can occur elsewhere, and not every public health agency possesses information systems capable of sharing data. Collectively, these characteristics define a system that likely has gaps in data sharing among public health entities.
A data-sharing gap is the inability to transmit, in near real time, data among public health agencies within a state for a specific public health activity. This article presents theoretically and empirically based typology of data-sharing gaps between LHDs and SHAs and describes the extent of data-sharing types for 6 activities.
Drawing on concepts from network theory, public health responsibilities, and technological capacity, we conceptualize a 9-category data-sharing typology that characterizes the flow of data between SHAs and LHDs. Using existing organizational surveys, we created a sample of LHD-SHA exchange dyads, which we use to describe the distribution of sharing and gaps for immunizations, vital records, reportable conditions, laboratory, well water, and electronic health records. State-level maps describe the prevalence of data-sharing gaps nationwide.
For vital records, reportable conditions, and well-water assessments, gaps in data sharing were the norm. For the other 3 public health activities, a lower portion of the dyads experienced gaps, but gaps were still very common. Most troubling was the relatively infrequent occurrence of truly bidirectional information sharing.
The data-sharing typology provides a useful basis for the formulations of policies to improve public health information systems and to guide future research.
This article presents typology of data-sharing gaps between local health departments and state health agencies and describes the extent of data-sharing types for 6 key public health activities. This gap typology provides a useful basis for the formulation of policies to improve public health information systems and to guide future research.
Center for Healthcare Informatics & Policy, Department of Public Health, Weill Cornell Medical College, New York, NY (Dr Vest); and University of Illinois at Chicago School of Public Health, Chicago (Dr Issel).
Correspondence: Joshua R. Vest, PhD, MPH, Center for Healthcare Informatics & Policy, Department of Public Health, Weill Cornell Medical College, 425 E. 61st Street, Suite 301, New York, NY 10065 (email@example.com).
This work was supported by the Robert Wood Johnson's Dissertation and Junior Faculty Awards in Public Health Services and Systems Research (PHSSR) in conjunction with the PHSSR Coordinating Center (Dr Vest: PI). The authors thank NACCHO and ASTHO. The Centers for Disease Control and Prevention and the Robert Wood Johnson Foundation provided funding for the 2008 Profile study. Data from this study was obtained from the 2007 and 2010 ASTHO Profile Survey, a project supported through a cooperative agreement between the Association of State and Territorial Health Officials and the Centers for Disease Control and Prevention and the Robert Wood Johnson Foundation.
The authors declare no conflicts of interest.