Electronic Health Record (EHR)

The Veterans Affairs (VA) ESSENCE obtains electronic health record data from 152 medical centers plus clinics in all 50 states, U.S. territories, and the Philippines. ESSENCE analyzes ICD-9 diagnosis codes and demographic data from outpatient and emergency department visits using complex aberrancy-detection algorithms. In 2010, a new instance was stood up (VA Inpatient ESSENCE) which receives weekly feeds of inpatient data from all VA acute care hospitals starting at the beginning of the Fiscal Year (FY10, Oct. 1, 2009). Data include demographics, admission/discharge data (including ICD-9 diagnosis codes), diagnosis related group, bedsection, procedure and surgery data.

Objective

To describe the utility of inpatient data in VA ESSENCE biosurveillance system for healthcare-associated infection and public health surveillance.

Although development of computerized medical record systems in the United States is a high priority, there are relatively few instances of such systems supporting disease surveillance systems. The Indian Health Service (IHS) has had an electronic record database for over 30 years, however, implementation of point of care electronic health records (EHR) and use of these data for public health surveillance has begun only over the past 4 years.

Objective

To develop a robust, sensitive, and specific local, regional, and national public health surveillance system utilizing an electronic clinical information system.

Using an electronic health record (EHR) system, we tracked an outpatient population from a series of primary care providers to identify influenza-like illness (ILI) as part of a multi-state effort directed by the Centers for Disease Control and Prevention. From these patients, we also collected de-identified project-specific information and symptoms using an electronic template to evaluate possible differences among patient groupings as well as longitudinal population patterns.

Objective

Evaluate the use of an EHR network to track ILI incidence in an outpatient population and using laboratory testing, identify influenza cases by subtype as well as other respiratory viruses.

Chronic diseases are the leading causes of mortality and morbidity for Americans but public health surveillance for these conditions is limited. Health departments currently use telephone interviews, medical surveys, and death certificates to gather information on chronic diseases but these sources are limited by cost, timeliness, limited clinical detail, and/or poor population coverage. Continual and automated extraction, analysis, and summarization of EHR data could advance surveillance in each of these domains.

Objective

Develop methods for automated chronic disease surveillance and visualization using electronic health record (EHR) data.

EHRs are increasingly being adopted to improve quality of care in health care systems, but they also have potential to monitor health at the population level. There has been relatively little focus on using EHRs for population health surveillance beyond infectious diseases. Current tools to monitor population health (vital statistics, hospital discharge data, population health surveys) are useful but can be expensive, and may be slow to conduct or produce findings. Aggregated EHR-derived data have the potential to deliver cheaper and faster data, and have the capacity to provide information on earlier disease stages, thus increasing the likelihood of timely use. If EHR data can be validated, they can be used to augment existing surveillance methods, resulting in more strategic targeting of health resources and better data to guide and evaluate public health initiatives and policies. New York City (NYC) is currently developing a pilot public health surveillance program known as NYC Macroscope, the first domestic effort to aggregate EHR data from independent primary care practices into a surveillance tool. This EHR-based population health surveillance system will compile summarized data from ambulatory electronic health records to help city health officials monitor and respond to real-time data on conditions of public health importance.

Objective

To describe the potential benefits and challenges of using electronic health record data for population health surveillance, and what to consider when establishing an electronic health record (EHR) surveillance system (EHRSS).

Lack of speed, reliability, and uniformity of data collection limit the ability of syndromic surveillance (SyS) systems to provide public health authorities (PHAs) with timely information on community health threats and trends. Electronic information technologies have long been used to accelerate and automate data collection for more real-time surveillance. There is, however, irregularity in how SyS data are packaged and sent by healthcare providers. In the US, federal programs to improve patient and population health outcomes are promoting enhanced EHR technology interoperability with a newly mandated standard for SyS data communication. Under a federal rule tied to Medicare and Medicaid reimbursement rates, hospitals are now required to provide SyS data to PHAs using HL7 2.5.1 messages that are in conformance with the CDC’s Public Health Information Network (PHIN) guide for SyS. Merely mandating this standard, however, does not necessarily mean that it will be used as intended or that EHR SyS data will be interoperable among systems. Technology standards are frequently implemented with inconsistencies that spring from guidance ambiguities or misinterpretations. Inserting thorough conformance testing early in the technology development life cycle can increase the probability of conformance to standards, interoperability, and product reliability while reducing overall costs.

Objective

Describe how the National Institute of Standards and Technology's (NIST) Syndromic Surveillance Messaging Validation Suite supports federal efforts to increase electronic health record (EHR) interoperability for timelier public health surveillance capabilities in the US.

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.

In the Northern part of Norway, all General Practitioners (GPs) and hospitals use electronic health records (EHR). They are connected via an independent secure IP-network called the Norwegian Health Network. The newly developed “Snow Agent System” can utilize this environment by distributing processes to, and extracting epidemiological data directly from, the EHR system in a geographic area. This system may enable the GPs to discover local disease outbreaks that may have affected the current patient by providing epidemiological data from the local population. Currently, work is being done to add more functionality to the system. The overall goal for this project is to contribute to a system that will share epidemiological information between GPs and provide them with information about contagious diseases that may be useful in a clinical setting.

To achieve this, we need the GPs to accept and use the system. Nearly one half of information systems fail due to user resistance and staff interference despite the fact that they are technologically sound. One of the reasons for user resistance is lack of user involvement and bad design. The more specialized the system, the more you need user research to unsure success. With this in mind we have decided to take a User-Centred-Design approach to the project.

Objective

The Norwegian Centre for Telemedicine plans to establish a peer-to-peer symptom based surveillance network between all GPs, laboratories, accident and emergency units, and other relevant health providers in Northern Norway. This paper describes some initial results from a study of GPs’ user requirements, regarding what they want in return from the system.

In the Northern part of Norway, all general practitioners (GPs) and hospitals use electronic health record systems. They are all connected via an independent secure IP-network called the Norwegian Health Network which enables electronic communication between all institutions involved in disease prevention and healthcare.

Objective

The Norwegian Centre for Telemedicine plans to establish a peer-to-peer based surveillance  network between all GPs, laboratories, accident and emergency units, and other relevant health providers and authorities in Northern Norway. This paper briefly describes the architecture and components of the system and the motivation for using this approach.