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BACKGROUND: Tobacco causes substantial morbidity, mortality and healthcare costs. A key public health (PH) response is easy access to cessation services. A PH monitoring system should efficiently track cessation referral trends, and outcomes of clinical- and community-based interventions. Q-LINe seeks to establish a well-integrated, PH referral and surveillance system that blends data from several health care systems to monitor and improve population health.
METHODS: Q-LINe leverages: 1) a normalized data model (virtual data warehouse [VDW]) 2) a nationally deployed federated query service (PopMedNet) and 3) a regional data sharing governance model; these are integrated with automated electronic health record (EHR) referral (e-Referral) for tobacco use status (prevalence) and cessation service reporting. Using a distributed data network, integrated e-Referral and tobacco status data from multiple institutions may be geographically analyzed to identify patterns to encourage specific, community-based, PH interventions (e.g., non-smoking policy initiatives). e-Referral activities use Stage 2 Meaningful Use consolidated clinical document architecture ([cCDA] i.e., Transition of Care document) . EHR messages to/from the Quitline service use cCDA; a specification standard is being developed in conjunction with the North American Quitline Consortium, ONC and CDC. Clinical EHR data include demographics (gender, address and race) and tobacco use status. Data are geocoded, transformed, and loaded into each clinical site’s VDW for federated query using PopMedNet. Across sites, patient data is aggregated into a tobacco registry to be visualized on business intelligence dashboards.
RESULTS: The Quitline has implemented an interface to receive e-Referrals in the cCDA format. One clinical partner has been electronically sending preliminary data for testing with the interface. Since inception in 2012, the federated query tool has been installed and tested with data formatted to VDW specifications. Multiple healthcare sites mapped local data to VDW specifications for loading and testing. Concurrently, a separate data integration effort was used to assess registry coverage, geo-location processes and quality assurance. An initial assessment compared with 2010 US Census data showed combined EHR representation of 30% for adults and 50% for children; 95% of patient records were accurately matched for geocoding.
CONCLUSIONS: Federated query of EHR data is feasible for monitoring tobacco use status and cessation services in a local environment. Use of cCDA for e-Referral has the potential for easy dissemination and implementation of automated referrals due to national standards. Q-LINe can facilitate data-driven decision making with accurate, timely, local health data to monitor implementation and evaluate clinical- and community-based interventions.