Objective To develop expeditiously a pragmatic, modular, and extensible software framework for understanding and improving healthcare value (costs relative to outcomes).Materials and methods In 2012, a multidisciplinary team was assembled by the leadership of the University of Utah Health Sciences Center and charged with rapidly developing a pragmatic and actionable analytics framework for understanding and enhancing healthcare value. Based on an analysis of relevant prior work, a value analytics framework known as Value Driven Outcomes (VDO) was developed using an agile methodology. Evaluation consisted of measurement against project objectives, including implementation timeliness, system performance, completeness, accuracy, extensibility, adoption, satisfaction, and the ability to support value improvement.Results A modular, extensible framework was developed to allocate clinical care costs to individual patient encounters. For example, labor costs in a hospital unit are allocated to patients based on the hours they spent in the unit; actual medication acquisition costs are allocated to patients based on utilization; and radiology costs are allocated based on the minutes required for study performance. Relevant process and outcome measures are also available. A visualization layer facilitates the identification of value improvement opportunities, such as high-volume, high-cost case types with high variability in costs across providers. Initial implementation was completed within 6 months, and all project objectives were fulfilled. The framework has been improved iteratively and is now a foundational tool for delivering high-value care.Conclusions The framework described can be expeditiously implemented to provide a pragmatic, modular, and extensible approach to understanding and improving healthcare value.

Objectives: To determine the risk and risk factors for mental illness among colorectal cancer (CRC) survivors across short-and long-term follow-up periods.Methods: We used the Utah Cancer Registry to identify CRC survivors diagnosed between 1997 and 2013. Mental health diagnoses were available in electronic medical records and statewide facilities data that were linked by the Utah Population Database. CRC survivors were matched to individuals from a general population cohort. The risk of developing a mental illness was compared between cohorts. The association between mental illness and mortality was also analyzed.Results: 8,961 CRC survivors and 35,897 individuals in a general population cohort were identified. CRC survivors were at increased risk for any mental health diagnosis at 0-2 years (HR

BackgroundSelecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive.MethodsOur evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone.ResultsWe found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc.ConclusionThe i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.

Our findings suggest that examining the effect of thyroid cancer diagnosis, cancer treatment, and demographic characteristics on the risk of CVD is critical.

Background Thyroid cancer is the most rapidly increasing cancer in the U.S., affects a young population, has high survival, and is one of the most common cancers in people under age 40. The aim of this study was to examine the risks of aging-related diseases in a statewide sample of thyroid cancer survivors who were diagnosed <40 years compared to those diagnosed ≥40 and a cancer-free sample. Methods Thyroid cancer survivors diagnosed 1997-2012 were matched to up to 5 cancer-free individuals on birth year, sex, birth state, using the statewide Utah Population Database. Medical records were used to identify disease diagnoses stratified over three time periods: 1-5, >5-10, and 10+ years after cancer diagnosis. Cox proportional hazards models were used to estimate hazard ratios (HR) with adjustment on matching factors, race, BMI, and Charlson Comorbidity Index. Results There were 3,706 thyroid cancer survivors and 15,587 matched cancer-free individuals (1,365 cases diagnosed <40 years old). Both age groups had increased risks for multiple circulatory health conditions 1-5 years after cancer diagnosis compared to cancer-free individuals. Survivors <40 had a higher risk of hypertension, cardiomyopathy, and nutritional deficiencies. Conclusions Increased risks for diseases associated with aging were observed for both age groups, with younger thyroid cancer survivors having higher risks for select diseases. Impact As thyroid cancer survivors in this study were found to have increased risks for aging-related diseases, future studies are needed to assess what can be done to reduce the increased risks of these long-term health effects.