Alliance to Reduce Disparities in Diabetes

Share and report community-wide health data

Policy Consideration:
What types of incentives or regulatory requirements are needed to prompt health systems to a) share timely patient data and b) consistently collect and report health data by race and ethnicity?

The Problem

Quality improvement efforts designed to reduce health care disparities in diabetes will require providers and health systems to more consistently and uniformly measure disparities. Federal requirements under health reform require providers and federally supported health care programs to collect a detailed list of demographic data. The ACA requires HHS to adopt new standards for data collection by race, ethnicity, sex, primary language and disability These new standards are expected to lead to improved identification of health disparities and the creation of better interventions to address them.

In addition to collecting more complete and uniform patient data, health systems are increasingly being challenged to develop other types of community-based datasets. The datasets could include timely patient data and describe hospitalizations, emergency department or urgent clinic visits, physician office visits, medication prescribed, and other data that describe the range of health services provided. This type of sharing of data can greatly enhance the care coordination so critical in managing diabetes patients.

Health systems face many challenges in their efforts to collect more comprehensive data and to create these datasets. Challenges include tight budgets, inadequate staff expertise, and lack of information technology infrastructure to meet regulatory requirements for data collection and to realize the benefits of such data collection. Furthermore, some providers express concerns that capturing such data could raise privacy concerns among patients and within the community.

The Alliance Experience

The Alliance's sites have demonstrated the impact of consistent and uniform collection and sharing of meaningful performance measures stratified by race and ethnicity. Such patient data are enabling Alliance site providers and health systems to better target interventions and to monitor performance on an ongoing basis. For example:

  • At the Camden Alliance site, data sharing across institutions is helping to identify individuals who need the most intense case management. Data are also enabling the health system to better assess the impact of its various policies to improve health care quality, control costs and expand access to care in at-risk populations.
  • Camden expects that all major EHRs will adopt automatic registry-building capabilities within the next year as a means of remaining competitive. At this point, all major EHR systems in Camden have promised to offer this function, an action that will allow providers across health systems to manage a population without duplicating work. The Camden Health Information Exchange (CHIE) will provide extensive patient data to providers across the city. The CHIE will, in effect, play the role of registry with respect to easy access to patient data across health systems.
  • The use of a diabetes registry in the Diabetes Equity Project (DEP) in Dallas also has yielded benefits. Data from the registry have been included in electronic medical records and patient charts, allowing health staff in the DEP to identify high-risk patients. Program staff also implemented a series of uniform patient data collection protocols across 110 provider network clinics, protocols that systematically ensured the recording of patient self-declared race, ethnicity and language choices from a prescribed list. In combination, these data allowed the DEP to identify the percentage of each group (e.g., ethnic, racial, language) that met the diabetes management goal and to understand statistically significant differences in outcomes at a 95 percent confidence level.
  • However, challenges remain. Providers working with the DEP can only see data on a patient that are recorded as part of the project. To find data on a patient’s experiences in other care delivery settings, providers must engage in a complex matching process to identify that patient and sometimes still cannot gain access to other health systems’ information.


Policy Questions Arising from the Alliance Experience:

  • What is needed to allow state health data reporting requirements to include that clinical care and public health departments report data (e.g. A1C levels) by race, ethnicity, gender and payer? This stratification can reveal where disparities exist and allow for greater targeting of efforts.
  • The American Recovery and Reinvestment Act (ARRA) of 2009 provided incentives for physicians to purchase and implement Health Information Technology (HIT) systems. While this is a good first step, how can these funds also be utilized to develop uniform electronic standards to allow various HIT systems to communicate with each other?
  • What funding mechanisms exist for the development of health information exchanges (HIEs) that share timely patient data and identify at risk and vulnerable patients?
  • How can privacy concerns about aggregation of and access to data through community health information exchanges (HIEs) be reduced? For example, some barriers to sharing data created by HIPPA could be overcome by creating processes for routinely consenting patients to allow for data sharing.
  • How could Accountable Care Organizations serve as aggregators and disseminators of timely health care information from various health providers regarding at risk and vulnerable patients?
  • How can incentives for clinical and public health systems be created to enable reporting on and success in reducing disparities in diabetes?
  • How can health clinics access new funding made available through the ACA to implement health information technologies?