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Grannis Shaun

Traditionally, public health agencies (PHAs) wait for hospital, laboratory or clinic staff to initiate case reports. However, this passive approach is burdensome for reporters and produces incomplete and delayed reports, which can hinder assessment of disease in the community and potentially delay recognition of patterns and outbreaks. Modern surveillance practice is shifting toward greater use of electronically transmitted disease information. The adoption of electronic health record (EHR) systems and health information exchange (HIE) among clinical organizations and systems, driven by policies such as the meaningful use™ program, is creating an information infrastructure that public health organizations can take advantage of to improve surveillance practice.

Objective: To enhance the process by which outpatient providers report surveillance case information to public health authorities following a laboratory-confirmed diagnosis of a reportable disease.

Submitted by elamb on

Given the clear relationship between spatial contexts and health, the Indiana Center of Excellence in Public Health Informatics (ICEPHI) aims to serve both the needs of public health researchers and practitioners by contextualizing the health information of large populations. Specifically, ICEPHI will integrate one of the nation’s largest health information exchanges, the Indiana Network for Patient Care, with well-established community information systems that collect, geocode, organize, and present integrated data on communities in Indiana and surrounding states, including data on public safety, welfare, education, economics, and demographics.

 

Objective

This presentation describes a collaborative approach for realizing the public health potential of a geospatially enabled statewide health information exchange.

Referenced File
Submitted by hparton on

Reporting notifiable conditions to public health authorities by health-care providers and laboratories is fundamental to the prevention, control, and monitoring of population-based disease. To successfully develop community centered health, public health strives to understand and to manage the diseases in its community. Public health surveillance systems provide the mechanisms for public health professionals to ascertain the true disease burden of the population in their community. The information

necessary to determine the disease burden is primarily found in the data generated during clinical care processes.

 

Objective

This poster will present a predictive model to describe the actual number of confirmed cases for an outbreak (H1N1) based on the current number of confirmed cases reported to public health. The model describes the methods used to calculate the number of cases expected in a community based on the lag time in the diagnosis and reporting of these cases to public health departments.

Referenced File
Submitted by hparton on

An increase in tuberculosis (TB) among homeless men residing in Marion County, Indiana was noticed in the summer of 2008. The Marion County Public Health Department (MCPHD) hosted screening events at homeless shelters in hopes of finding unidentified cases. To locate men who had a presumptive positive screen, the MCPHD partnered with researchers at Regenstrief Institute (RI) to create an alert for health care providers who use the Gopher patient management system in one of the city's busiest emergency departments. A similar process was used at this facility to impact prescription behavior.[1] A similar method was also used at the New York City Department of Health and Mental Hygiene.[2]

Referenced File
Submitted by elamb on

Electronic laboratory reporting (ELR) was demonstrated just over a decade ago to be an effective method to improve the timeliness of reporting as well as the number of reports submitted to public health agencies. The quality of data (inc. completeness) in information systems across all industries and organizations is often poor, and anecdotal reports in the surveillance literature suggest that ELR may not improve the completeness of the data in the submitted reports.

 

Objective 

To examine the completeness of data submitted from clinical information systems to public health agencies as notifiable disease reports.

Referenced File
Submitted by elamb on

Completeness of public health information is essential for the accurate assessment of community health progress and disease surveillance. Yet challenges persist with respect to the level of completeness that public health agencies receive in reports submitted by health care providers. Missing and incomplete data can jeopardize information reliability and quality resulting in inaccurate disease evaluation and management (1). Additionally, incomplete data can prolong the time required for disease investigators to complete their work on a reported case. Thus, it is important to determine where the scarcity of information is coming from to recognize the characteristics of provider reporting.

Objective

To examine the completeness of data elements required for notifiable disease surveillance from official, provider-based reports submitted to a local health department.

Submitted by knowledge_repo… on

Disease surveillance is a core public health (PH) function. To manage and adjudicate cases of suspected notifiable disease, PH workers gather data elements about persons, clinical care, and providers from various clinical sources, including providers, laboratories, among others. Current processes often yield incomplete and untimely reporting across different diseases requiring time-consuming follow-up by PH to get needed information [1,2]. To improve the completeness and timeliness of case reporting, health departments have explored accessing EHR systems, which are increasingly available. We examine whether providing PH with EHR access to gather notifiable disease case information affects data completeness.

Objective

To assess the effect of electronic health record (EHR) system access on notifiable disease case data completeness.

Submitted by knowledge_repo… on

The importance transmitting clinical information to public health for disease surveillance is well-documented. Conventional reporting processes require health care providers to complete paper-based notifiable condition reports which are transmitted by fax and mail to public health agencies. These processes result in incomplete reports, inconsistencies in reporting frequencies among different diseases and reporting delays as well as time-consuming follow-up by public health to get needed information. One strategy to address these issues is to electronically pre-populate report forms with available clinical, lab and patient data to streamline reporting workflows, increase data completeness and, ultimately, provide access to more timely and accurate surveillance data for public health organizations. Prior to implementing an intervention that includes using pre-populated forms, we conducted interviews in clinical and public health settings to identify the barriers and facilitators to adopting and utilizing the forms and their potential impact on workflow and perceived burden. These interviews are a component of a larger mixed methods evaluation that will triangulate pre- and post-intervention quantitative data quality measures with qualitative results.

Objective

Introduction of new health information technologies can produce unanticipated consequences on existing user behaviors, workflow, etc. Prior to implementing a public health reporting intervention, we conducted a series of interviews regarding workflow and perceptions of task burden with respect to notifiable condition reporting.

Submitted by knowledge_repo… on

The use of health information systems to electronically deliver clinical data necessary for notifiable disease surveillance is growing. For health information systems to be effective at improving population surveillance functions, semantic interoperability is necessary. Semantic interoperability is “the ability to import utterances from another computer without prior negotiation” (1). Semantic interoperability is achieved through the use of standardized vocabularies which define orthogonal concepts to represent the utterances emitted by information systems. There are standard, mature, and internationally recognized vocabularies for describing tests and results for notifiable disease reporting through ELR (2). Logical Observation Identifiers Names and Codes (LOINC) identify the specific lab test performed. Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) identify the diseases and organisms tested for in a lab test. Many commercial laboratory and hospital information systems claim to support LOINC and SNOMED CT on their company websites and in marketing materials, and systems certified for Meaningful Use are required to support LOINC and SNOMED CT. There is little empirical evidence on the use of semantic interoperability standards in practice.

Objective:

To characterize the use of standardized vocabularies in real-world electronic laboratory reporting (ELR) messages sent to public health agencies for surveillance.

 

Submitted by Magou on

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
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