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Introduction:Intermountain Healthcare is a fully integrated delivery system based in Salt Lake City, Utah. As a learning healthcare system with a mission of performance excellence, it became apparent that population health management and our efforts to move towards shared accountability would require additional patient-centric metrics in order to provide the right care to the right patients at the right time. Several European countries have adopted social deprivation indices in measuring the impact that social determinants can have on health. Such indices provide a geographic, area-based measure of how socioeconomically deprived residents of that area are on average. Intermountain’s approach was to identify a proxy measure that did not require front-line data collection and could be standardized for our patient population, leading us to the area deprivation index or ADI. This paper describes the specifications and calculation of an ADI for the state of Utah. Results are presented along with introduction of three use cases demonstrating the potential for application of an ADI in quality improvement in a learning healthcare system.Case Description:The Utah ADI shows promise in providing a proxy for patient-reported measures reflecting key socio-economic indicators useful for tailoring patient interventions to improve health care delivery and patient outcomes. Strengths of this approach include a consistent standardized measurement of social determinants, use of more granular block group level measures and a limited data capture burden for front-line teams. While the methodology is generalizable to other communities, results of this index are limited to block groups within the state of Utah and will differ from national calculations or calculations for other states. The use of composite measures to evaluate individual characteristics must also be approached with care. Other limitations with the use of U.S. Census data include use of estimates and missing data.Conclusion:Initial applications in three meaningfully different areas of an integrated health system provide initial evidence of its broad applicability in addressing the impact of social determinants on health. The variation in socio-economic status by quintile also has potential for clinical significance, though more research is needed to link variation in ADI with variation in health outcomes overall and by disease type.

Purpose:The advent of genomic diagnostic technologies such as next-generation sequencing has recently enabled the use of genomic information to guide targeted treatment in patients with cancer, an approach known as precision medicine. However, clinical outcomes, including survival and the cost of health care associated with precision cancer medicine, have been challenging to measure and remain largely unreported.Patients and Methods:We conducted a matched cohort study of 72 patients with metastatic cancer of diverse subtypes in the setting of a large, integrated health care delivery system. We analyzed the outcomes of 36 patients who received genomic testing and targeted therapy (precision cancer medicine) between July 1, 2013, and January 31, 2015, compared with 36 historical control patients who received standard chemotherapy (n = 29) or best supportive care (n = 7).Results:The average progression-free survival was 22.9 weeks for the precision medicine group and 12.0 weeks for the control group (P = .002) with a hazard ratio of 0.47 (95% CI, 0.29 to 0.75) when matching on age, sex, histologic diagnosis, and previous lines of treatment. In a subset analysis of patients who received all care within the Intermountain Healthcare system (n = 44), per patient charges per week were $4,665 in the precision treatment group and $5,000 in the control group (P = .126).Conclusion:These findings suggest that precision cancer medicine may improve survival for patients with refractory cancer without increasing health care costs. Although the results of this study warrant further validation, this precision medicine approach may be a viable option for patients with advanced cancer.