Chronic Disease

In the United States, 800,000-1.4 million people are chronically infected with hepatitis B virus (HBV); these persons are at increased risk for chronic liver disease and its sequelae. Current national viral hepatitis surveillance is a passive laboratory-initiated reporting system to state or local health departments with only 39 health departments reporting chronic HBV infection in the National Notifiable Disease Surveillance System. Since active HBV surveillance can be expensive and labor-intensive, the ICD-9 coding system has been proposed for surveillance of chronic hepatitis B.

Objective

To evaluate the sensitivity, specificity, positive and negative predictive values of the ICD-9 coding system for surveillance of chronic hepatitis B virus infection (HBV) using data from an observational cohort study in which ICD-9-coded HBV cases were validated by chart review

A liver disease of unknown etiology, called unknown liver disease (ULD) by the community, was first identified in 2002 in Tigray; a rugged, semi-arid, mountainous region that is considered one of the most drought-prone and food insecure regions of Ethiopia. ULD is a chronic condition characterized by epigastric pain, abdominal distention, ascites, emaciation, and hepato/splenomegaly. In 2005, the Ethiopian Health and Nutritional Research Institute was assigned by the Ethiopia Ministry of Health to assist the Tigray Regional Health Bureau and oversee the disease investigation. In 2008, Centers for Disease Control and Prevention (CDC) assisted the Ethiopian team and jointly developed the surveillance tools. The surveillance system was implemented in 2009 with the objectives to determine the magnitude and distribution of the disease; identify disease trends; detect cases to provide them with clinical care; and inform health officials and funding bodies for resource allocation.  After several investigations, a local plant containing a particular type of pyrrolizidine alkaloid (PA) toxin that contaminated local foodstuffs was identified as the etiologic agent, and ULD was renamed PAILD in 2011.

Objective:

To describe the results of the evaluation of the PAILD active surveillance system and lessons learned for similar surveillance efforts in a resource-limited setting.

COPD is a prevalent chronic disease among older adults; exacerbations often result in ED visits and subsequent hospital admissions. A portion of such patients return to the ED within a few days or weeks. In this study, we investigated patterns of hospital admissions and short-term return visits resulting from COPD-related ED visits.

Objective

To investigate hospital admissions and short-term return visits re- sulting from chronic obstructive pulmonary disease (COPD)-related emergency department (ED) visits. 

Syndromic surveillance is one of the meaningful use public health menu set objectives for eligible professionals. The value of this data for syndromic surveillance as an adjunct to the more widely adopted emergency department registrations has not been studied extensively. It may be that it would improve the sensitivity or timeliness of detecting certain communicable disease events, or it may just contain signals comparable to what is available via other syndromic surveillance data streams. The value of making the effort to collect this data is considered contingent on the answer to that question.

Public health is concerned with more than just communicable diseases, however. Chronic diseases and their underlying causes are also a significant public health concern. Obesity alone is estimated to be responsible for 2.5% of the global disease burden, and represents a higher fraction in many developed nations. Since chronic diseases are not associated with singular events of brief duration, they are difficult to track with traditional surveillance methods. They are also not typically managed via emergency departments, so syndromic surveillance does not capture them well either.

Chronic diseases are often treated by physicians at ambulatory practices. Thus data from eligible professionals may provide a means for monitoring chronic diseases, or metrics associated with chronic diseases, that would not otherwise be as feasible. As a proof of concept, this study seeks to determine if body mass index (BMI), the standard measure of obesity, can be obtained from ambulatory syndromic surveillance messages.

Objective

To demonstrate the utility of ambulatory syndromic surveillance data to public health domains beyond communicable diseases

Clinical data captured in electronic health records (EHR) for patient health care could be used for chronic disease surveillance, helping to inform and prioritize interventions at a state or community level. While there has been significant progress in the collection of clinical information such as immunizations for public health purposes, greater attention could be paid to the collection of data on chronic illness. Obesity is a chronic disease that affects over a third of the US adult population1 , making it an important public health concern. Both HL7 v.2.5.12 and Clinical Document Architecture (CDA) messages3 can be used to facilitate the collection of HW EHR data. These standards include anthropometric and demographic information along with the option to transmit behavioral, continuity of care, community resource identification and care plan information. We worked with vendors participating in the Integrating the Healthcare Enterprise initiative (IHE) in developing, testing and showcasing scenarios to facilitate system development, increase the visibility of HW standards and demonstrate potential usages of obesity-related information.

Objective

To demonstrate the feasibility of using healthy weight (HW) IT standards in public health surveillance through the collection and visualization of patient height, weight and behavioral data.

In 2012, half of all adults in the US had one or more chronic health conditions; at least 25% had two or more chronic health conditions. Seven of the top ten causes of death in 2010 were chronic diseases; two of the seven chronic diseases, heart disease and cancer, account almost for over 50% of all deaths. Chronic disease is one of the most costly contributors in healthcare expenditures; once diagnosed many patients must be followed for a lifetime. In lower-income countries chronic disease is now the biggest contributor to mortality. Socioeconomic inequalities are a major driver of the chronic disease epidemic. Chronic disease in the US, such as cancer, heart disease, renal end stage disease and diabetes are tracked in national datasets but are not linked. Chronic diseases share many risk factors, major risk factors, e.g. tobacco, diet, alcohol, and physical inactivity are already known, their interactions with comorbidities are important and clinical practice indicates that the chronic disease epidemic may be addressed more effectively using a holistic approach. However, this approach has not yet been implemented in disease surveillance activities as data collection is still disease specific. Data collection is still one disease at a time, without connecting our disease surveillance efforts to get better, more complete and encompassing data. Health inequities result in lower quality of healthcare, worse healthcare outcomes for minority racial/ ethnic populations and people with low socioeconomic status, increased direct and indirect healthcare costs, and decreased productivity.

Objective

Utilize existing data sets and data sources to address health equity and improve the management of chronic disease