Actualizing Personalized Healthcare for Women through Connected Data Systems: Breast Cancer Screening and Diagnosis

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Abstract
Background: Healthcare organizations have invested in electronic patient data systems, yet use of health data to optimize personalized care has been limited. Primary Study Objective: To develop and pilot an integrated source of health system data related to breast healthcare. Methods/Design: This study is a quality improvement project. Patient-level data from multiple internal sources were identified, mapped to a common data model, linked, and validated to create a breast healthcare-specific data mart. Linkages were based on matching algorithms using patient identifiers to group data from the same patient. Data definitions, a data dictionary, and indicators for quality and benchmarking aligned with standardized measures. Clinical pathways were developed to outline the patient populations, data elements, decision points, and outcomes for specific conditions. Setting: Electronic data sources in a community-based health system in the United States. Participants: Women receiving breast cancer screening, prevention, and diagnosis services. Main Outcome Measures: Distribution of mammography examinations and pathologic results of breast biopsies. Results: From 2008 to 2011, 200 768 screening and 50200 diagnostic mammograms were obtained; rates varied by age over time. Breast biopsies for 7332 women indicated 23.3% with invasive breast cancer, 6.7% with ductal carcinoma in situ, and 70.0% with nonmalignant diagnoses that would not have been further differentiated by administrative codes alone. Limitations: Evaluation of validity and efficiency and additional tracking of clinical outcomes are needed. Conclusions: The creation of a patient-centered data system by connecting and integrating disparate data sources within a large health system allows customized analyses of data and improves capacity for clinical decision making and personalized healthcare.

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