efficient public health surveillance. Finally, he noted, linking public health and direct health care services research in this way will serve to strengthen the population-level approach to surveillance.

SUPPORTING PUBLIC HEALTH AND SURVEILLANCE AT THE LOCAL LEVEL

In line with Buehler’s discussion of public health surveillance at the national level, Martin LaVenture shifted the focus to public health at the state and local (city and county) level. LaVenture reinforced the earlier assertion that necessary data quality attributes vary and depend on the context of the local public health activity. For example, timeliness is of particular importance for newborn screening, acute disease surveillance, and outbreaks, while completeness is especially critical for maintenance of immunization records. Accuracy is crucial for monitoring cancer clusters, while currency, comprehensiveness, and access to the primary data source all are relevant for public health surveillance and clinical decision support.

These quality characteristics all contribute to the usability of public health surveillance data today. Currently, surveillance data is collected from many sources, and health facilities increasingly are adopting EHRs for patient information management and decision support. However, frequent miscoding and mismapping of this information can result in loss of trust in both the data and the providers using those data; in which case the value of those data suffers. Moreover, the limited EHR standards and specifications and certification criteria lead to incomplete and invalid records, which create obstacles to efficient use of that data for clinical and disease surveillance purposes. This can lead to additional work by providers and public health officials and delay important public health intervention, prevention, and policy decisions.

In the face of these challenges, LaVenture said, the public health digital environment is changing. Greater EHR use with standards and quality checks built in will increase the prevalence of better quality data, thereby creating the opportunity for quality information exchange for care and public health and improved point-of-care decision support. To facilitate this progress, LaVenture proposed a number of priorities. Health information systems need to move beyond information management to rapid, accurate knowledge creation with support from public health information systems such as an immunization information system. The EHR certification process, he suggested, should include more comprehensive, structured content requirements for data quality, including thresholds at the point of capture, review, and exchange thus helping ensure higher-quality outputs for broader use. Standards for quality checks and improvement are needed to ensure updates and corrections can be completed quickly and propagation



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