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Using Health Information Technology and Data to Improve Chronic Disease Outcomes in Federally Qualified Health Centers in Maryland

Filetype[PDF-250.97 KB]



Details:

  • Alternative Title:
    Prev Chronic Dis
  • Description:
    Federally Qualified Health Centers provide health care services to underserved communities and vulnerable populations. In Maryland, the burden of chronic disease is high among Federally Qualified Health Center patients. Electronic health records (EHRs) are becoming more widely used, and effective use of EHR data may improve chronic disease outcomes. This article describes the process of developing a data aggregation and analytics platform to support health centers in using population health data based on standardized clinical quality measures. This data warehouse, capable of aggregating EHR data across multiple health centers, provides opportunities for benchmarking and elicits a discussion of quality improvement, including identifying and sharing clinical best practices. Phase 1 of the project involved the strategic engagement of health center leadership and staff to get buy-in and to assess readiness. Phase 2 established the technological infrastructure and processes to support data warehouse implementation and began the process of information sharing and collaboration among 4 early adopters. Phase 3 will expand the project to additional health centers and continue quality improvement efforts. The health information technology marketplace is rapidly changing, and staying current will be a priority so that the data warehouse remains a useful quality improvement tool that continues to meet the demands of Maryland health centers. Ongoing efforts will also focus on ways to further add value to the system, such as incorporating new metrics to better inform health center decision making and allocation of resources. The data warehouse can inform and transform the quality of health care delivered to Maryland's most vulnerable populations, and future research should focus on the ability of health centers to translate this potential into actual improvements.
  • Pubmed ID:
    28033091
  • Pubmed Central ID:
    PMC5201151
  • Document Type:
  • Main Document Checksum:
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