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Public Health Informatics

Description

The American Recovery and Reinvestment Act of 2009 authorized the Centers for Medicare and Medicaid Services (CMS) to incentivize hospitals and physicians to become meaningful users of electronic health record (EHR) systems. In a final rule issued August 2012, CMS outlined the requirements for Stage 2 meaningful use to be effective in 2014 (1). The Stage 2 criteria require eligible hospitals to submit electronic laboratory reports to health departments. While many state health departments receive some portion of notifiable disease reports electronically, the final Stage 2 rule is likely to increase the volume of incoming electronic reports. The Centers for Disease Control and Prevention are urging health departments to prepare for the sharp increase in electronic laboratory reporting (ELR). Crucial to preparedness is estimation of how many ELR reports can be expected. However, few health departments have experience with high volume ELR, making estimation difficult. The Indiana Network for Patient Care (INPC), a regional health information exchange, has been processing high volumes of ELR for over a decade (2). To support health departments estimate potential ELR increases, the INPC examined its current volumes from hospitals with advanced EHR capabilities.

Objective:

To support health department estimation of future electronic laboratory report volumes from hospitals that achieve Stage 2 meaningful use.

 

Submitted by Magou on
Description

There is growing interest in leveraging available health information exchange (HIE) infrastructures to improve public health surveillance (1). The Health Information Technology for Clinical and Economic Health Act and Meaningful Use criteria for electronic health record (EHR) systems are among the factors driving the development, adoption and use of HIEs. HIEs deliver or make accessible clinical and administrative data as patients are admitted, discharged, and transferred across hospitals, clinics, medical centers, counties, states and regions (2). While several HIE infrastructures exist (3), there is little evidence on the engagement in HIE initiatives by state and local health agencies.

Objective

To characterize state and local health agency relationships with health information exchange organizations.

 

Submitted by uysz on
Description

ASPR deploys clinical assets, including an EMR system, to the ground per state requests during planned and no-notice events. The analysis of patient data collected by deployed federal personnel is an integral part of ASPR and FDOH’s surveillance efforts. However, this surveillance can be hampered by the logistical issues of field work in a post-disaster environment leading to delayed analysis and interpretation of these data to inform decision makers at the federal, state, and local levels. FDOH operates ESSENCE-FL, a multi-tiered, automated, and secure web-based application for analysis and visualization of clinical data. The system is accessible statewide by FDOH staff as well as by hospitals that participate in the system. To improve surveillance ASPR and FDOH engaged in a pilot project whereby EMR data from ASPR would be sent to FDOH in near realtime during the 2012 hurricane season and the 2012 RNC. This project is in direct support of Healthcare Preparedness Capability 6, Information Sharing, and Public Health Preparedness Capability 13, Public Health Surveillance and Epidemiological Investigation.

Objective:

U.S. Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) partnered with the Florida Department of Health (FDOH), Bureau of Epidemiology, to implement a new process for the unidirectional exchange of electronic medical record (EMR) data when ASPR clinical assets are operational in the state following a disaster or other response event. The purpose of the current work was to automate the exchange of data from the ASPR electronic medical record system EMR-S into the FDOH Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL) system during the 2012 Republican National Convention (RNC).

 

 

 



 

Submitted by Magou on
Description

Hypertension (HTN) is a highly prevalent chronic condition and strongly associated with morbidity and mortality. HTN is amenable to prevention and control through public and population health programs and policies. Therefore, public and population health programs require accurate, stable estimates of disease prevalence, and estimating HTN prevalence at the community-level is acutely important for timely detection, intervention, and effective evaluation. Current surveillance methods for HTN rely upon community-based surveys, such as the BRFSS. While BRFSS is the standard at the state- and national-level, they are expensive to collect, released once per year, and their confidence intervals are too wide for precise estimates at the local level. More timely, frequently updated, and locally precise prevalence estimates could greatly improve the timeliness and precision of public health interventions. The current study evaluated EHR data from a large, mature HIE as an alternative to community-based surveys for timely, accurate, and precise HTN prevalence estimation.

Objective:

To assess the equivalence of hypertension prevalence estimates between longitudinal electronic health record (EHR) data from a community-based health information exchange (HIE) and the Behavioral Risk Factor Surveillance System (BRFSS).

Submitted by elamb on
Description

Under the CDC STD Surveillance Network (SSuN) Part B grant, WA DOH is testing eICR of sexually transmitted infections (STI) with a clinical partner. Existing standard vocabulary codes were identified to represent previously-identified information gaps, or the need for new codes or concepts was identified.

Objective:

Previous research identified data gaps between traditional paper-based STI notifiable condition reporting and pilot electronic initial case reporting (eICR) relying on Continuity of Care Documents (CCDs) exported from our clinical partner’s electronic health record (EHR) software. Structured data capture is needed for automatic processing of eICR data imported into public health repositories and surveillance systems, similar to electronic laboratory reporting (ELR). Coding data gaps (between paper and electronic case reports) using standardized vocabularies will allow integration of additional questions into EHR or other data collection systems and may allow creation of standard Clinical Data Architecture (CDA) templates, Logical Observation Identifiers Names and Codes (LOINC) panels, or Fast Healthcare Interoperability Resources (FHIR) resources. Furthermore, identifying data gaps can inform improvements to other standards including nationwide standardization efforts for notifiable conditions.

Submitted by elamb on