Disparities in health outcomes, health determinants, access, and quality of health care are ongoing policy priorities in the United States. Studies have shown disparities across multiple domains for a wide range of chronic conditions, including cardiovascular diseases, respiratory diseases, diabetes, cancers, psychiatric disorders, and musculoskeletal conditions. Behavioral risk factors, such as tobacco smoking, physical inactivity, and poor diet, are likely to play a big role in health disparities. However, health disparities are also reflected in differing levels of access to health care and the quality of medical care.
To track disparities in chronic diseases and the effectiveness of health policies in reducing them, national data alone are not sufficient. More clinically detailed and localized information is required to understand how differences in risk factors, quality of care, access to interventions, and other factors impact health at the US-county level.
The primary aim of the Monitoring Disparities in Chronic Conditions (MDCC) Study is to design and test a population-based surveillance system that integrates multiple data sources to track disparities in chronic diseases at the local level. This system will capture the complete spectrum of relevant information, from socioeconomic and health risk factors to disease incidence and the consequent cascade of hospitalizations, outpatient visits, and use of and adherence to interventions.
This project represents what we hope will be a pilot for a much larger, nationally relevant system. It is important to pilot this in a relatively data-rich environment with a heterogeneous population. King County, Washington, is our pilot location, and the project focuses on three racial and ethnic groups for which there are demonstrated disparities in health outcomes nationally: white non-Hispanics, Hispanics, and black non-Hispanics. The study is intended to resolve a series of outstanding technical measurement issues, develop operational protocols, and produce results relevant to health policy formulation.
1. Design data systems
The MDCC Study team is designing a novel, cost-effective, multisource data collection system for producing high-quality data in the four domains. In order to track race/ethnicity disparities in chronic diseases and the effectiveness of health policy in reducing these disparities, national data alone are not sufficient. In this project, our data system integrates data from emergency medical services (EMS), hospital discharge databases, outpatient care databases, Medicare databases, selective chart review and extraction, and pharmacy records.
2. Develop surveys
To supplement database and record information, the MDCC Study team has developed surveys that can be administered in one of four formats: a computer-adapted telephone interview (CATI) survey; a computer-assisted personal interview (CAPI); a Web-based survey; and a paper-based survey. These various modalities allow study participants to choose the method that works best for them and enhances the completeness and quality of the survey data. The MDCC surveys ask questions about health and well-being, demographic information (i.e., race/ethnicity, employment, income), functional health, risk factors (i.e., physical activity, weight, tobacco/alcohol use, diet), self-reported symptoms, prior diagnosis of specific chronic conditions (i.e., diabetes, asthma), and health service utilization.
3. Review medical records and conduct physical examinations
Data from hospitalization, outpatient care, and pre-hospital events are critical for tracking disparities. We will undertake a retrospective chart review of inpatient hospital records, outpatient records, pharmacy records, and pre-hospital (EMS) events records for consenting participants reporting one or more of the conditions of interest. We are primarily interested in admission and discharge dates, administration of interventions and medications, diagnostic/laboratory tests, frequency of visits, preventive care (i.e., screening), provider and payer type, and any other care specific to the chronic conditions of interest.
All of these variables will be tracked and used to determine how individuals with chronic conditions are treated within King County’s health care network. Physical examinations will be conducted by a registered nurse at King County clinics on a subsample of 750 study participants. This component is critical for validating survey responses, identifying undiagnosed conditions, measuring intervention effectiveness, and tracking other biological outcomes.
4. Link data sources
The value of each component of the surveillance data (surveys, service provider data, and physical examination data) will be enhanced through record linkage. Record linkage across these data systems will allow us to trace sequences of events for individuals, from socioeconomic contexts and risk factors to interactions with the health system and health outcomes.
Cost-effective local data collection that provides an integrated approach to the different types of needed data has not been tested. In this two-year project, we will take advantage of the commitment of King County’s public health department, the long history of innovative health research in King County, and the presence of considerable racial and ethnic diversity to demonstrate the feasibility of an integrated, linked data system.
5. Pilot test and disseminate information
Each of the components of the MDCC Study will be pilot tested in King County, and recommendations will be made for using this novel surveillance system in other counties throughout the United States. The pilot test provides an opportunity to achieve the following objectives:
- Streamline operational details (i.e., working with local health authorities and community leaders to ensure high response rates).
- Refine instruments (i.e., insure comparability across cultures and languages).
- Establish protocols for linkage and demonstrate operational feasibility.
- Enable researchers to better understand health issues among multicultural populations with varying geography and income.
- Expand the project to other race/ethnic groups and counties throughout the United States.
The methods and strategies used in King County should be applicable in diverse communities across the United States. An integrated multisource data system that is cost-effective and could be implemented across the country would provide a powerful tool to track disparities and the effect of policies on programs.
It would provide a much more precise understanding as to why there is such enormous variation within race/ethnicity groups across geographic communities. Improved information that addresses these challenges is essential to policymakers interested in targeting effective interventions.
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This project is supported by award number RC2HL101759 from the National Heart, Lung, and Blood Institute, which is part of the US National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute or the National Institutes of Health.