Greenspan Joel

Chikungunya virus disease (CHIK) is a mosquito-borne viral infection currently widespread in the Caribbean with the potential for emergence and endemicity in the U.S. via infected travelers and local mosquito vectors. CHIK disease can be severe and disabling with symptoms similar to dengue. CHIK is not a U.S. nationally notifiable disease and tracking travel-associated and locally acquired cases is currently dependent on voluntary reporting via ArboNET. While ArboNET cases are laboratory confirmed and highly specific, ArboNET is a passive surveillance system where representativeness and timeliness may be lacking. In contrast, submitting an electronic bill following HC services is the most mature and widely used form of eHealth. Providers are highly motivated to submit claims for reimbursement and the eHRC process is ubiquitous in the U.S. HC system. HIPAA-compliant eHRCs from provider offices can be captured in e-commerce and consolidated into electronic data warehouses and used for many purposes including public health surveillance. eHRCs are standardized and each claim contains pertinent person, place, and time information as well as ICD-9 diagnostic codes. IMS Health (IMS) is a global HC information company and maintains one of world’s largest eHealth data warehouses that processes ~1 billion provider office eHRCs annually. IMS consolidates eHRCs from >60% of all U.S. office-based providers from all parts of the U.S. The size and predictability of the eHRC flow into the IMS data warehouse supports projections of national estimates and time trends of conditions of interest.

Objective

This paper describes how high-volume electronic healthcare (HC) reimbursement claims (eHRCs) from providers’ offices can be used to supplement Chikungunya surveillance in the U.S.

A Neolithic transformation is underway in public health, where the ubiquity of digital healthcare (HC) data is changing public health’s traditional role as data hunter-gatherers to one of data farmers harvesting huge reserves of electronic data. ILINet 1.0 is the current U.S. outpatient ILI surveillance network dependent on ~2000 volunteer sentinel providers recruited by States to report syndromic ILI. ILINet 1.0 began in the 1980s and represents a largely unchanged, ongoing hunter-gatherer approach to ILI outpatient surveillance involving the independent efforts of all state health departments. Many significant changes have occurred in the U.S. healthcare system since ILINet 1.0 was initiated. For example, eCommerce standards emerged in the 1990s creating ubiquitous amounts of easily accessible electronic healthcare administrative data. Since 2001 new public health surveillance approaches and investments have emerged including methods for syndromic surveillance (e.g. BioSense). Most recently healthcare reform efforts hold great promise (as yet largely unrealized) for public health to access electronic information derived from EHRs/HIEs (e.g., Meaningful Use). Could and should the current U.S. gold standard for ILI outpatient surveillance benefit from these new opportunities, and if so, what approach should be used and who should be responsible?

Objective

This paper outlines the current state of ILINet (ILINet 1.0), the accepted national gold standard for outpatient influenza-like illness (ILI) surveillance, and demonstrates how ILINet 2.0 could be more automated, timely, and locally representative if it were to utilize increasingly available electronic healthcare data rather than a specific group of recruited sentinel providers.

Missed opportunities for influenza vaccination in office-based settings occur when patients (who are inclined to accept influenza vaccination if a provider recommends it) remain unvaccinated after a fall/winter healthcare visit. Healthcare providers can be very influential in encouraging patients to obtain influenza vaccination, but little is known in real-time during annual campaigns of how many and what type of providers are actually giving vaccinations in office settings. Many factors affect the ultimate population coverage including taking advantage of opportunities to vaccinate during medical visits. This suggests that provider vaccination behavior, if leveraged, could result in higher rates of influenza vaccine coverage. “Big” healthcare data in the form of high volume streams of electronic healthcare reimbursement claims (eHRCs) can potentially be used to track influenza vaccine administration practices in office-based settings in near real-time, thus empowering public health officials to provide this feedback to practitioners and potentially modify behaviors.

Objective

This paper describes the results of formative research to develop a new metric for public health officials to use in near-real-time tracking of the weekly participation of office-based providers in community influenza vaccination campaigns.