Sharing and Reusing Computable Phenotype Definitions.

Background: A scalable approach for the sharing and reuse of human-readable and computer-executable phenotype definitions can facilitate the reuse of electronic health records for cohort identification and research studies. Description: We developed a tool called Sharephe for the Informatics for Integrating Biology and the Bedside (i2b2) platform. Sharephe consists of a plugin for i2b2 and a cloud-based searchable repository of computable phenotypes, has the functionality to import to and export from the repository, and has the ability to link to supporting metadata. Discussion: The i2b2 platform enables researchers to create, evaluate, and implement phenotypes without knowing complex query languages. In an initial evaluation, two sites on the Evolve to Next-Gen ACT (ENACT) network used Sharephe to successfully create, share, and reuse phenotypes. Conclusion: The combination of a cloud-based computable repository and an i2b2 plugin for accessing the repository enables investigators to store and retrieve phenotypes from anywhere and at any time and to collaborate across sites in a research network.

Clinical Algorithms with Race: An Online Database.

Some clinical algorithms incorporate a person's race, ethnicity, or both as an input variable or predictor in determining diagnoses, prognoses, treatment plans, or risk assessments. Inappropriate use of race and ethnicity in clinical algorithms at the point of care may exacerbate health disparities and promote harmful practices of race-based medicine. This article describes a comprehensive search of online resources, the scientific literature, and the FDA Drug Label Information that uncovered 39 race-based risk calculators, six laboratory test results with race-based reference ranges, one race-based therapy recommendation, and 15 medications with race-based recommendations. These clinical algorithms based on race are freely accessible through an online database. This resource aims to raise awareness about the use of race-based clinical algorithms and track the progress made toward eradicating the inappropriate use of race. The database will be actively updated to include clinical algorithms based on race that were previously omitted, along with additional characteristics of these algorithms.

Are your asset data as good as you think? Conducting a comprehensive census of built assets to improve urban population health.

Secondary data sources are widely used to measure the built asset environment, although their validity for this purpose is not well-established. Using community-engaged research methodology, this study conducted a census of public-facing, built assets via direct observation and then tested the performance of these data against widely used secondary datasets. After engaging community organizations, a community education campaign was implemented. Using web-enabled cell phones and a web-based application prepopulated with the secondary data, census workers verified, modified, and/or added assets using street-level observation, supplementing data with web searches and telephone calls. Data were uploaded to http://www.SouthSideHealth.org . Using direct observation as the criterion standard, the sensitivity of secondary datasets was calculated. Of 5,773 assets on the prepopulated list, direct observation of public-facing assets verified 1,612 as operating; another 653 operating assets were newly identified. Sensitivity of the commercial list for nonresidential, operating assets was 61 %. Using the asset census as the criterion standard, secondary datasets were incomplete and inaccurate. Comprehensive, accurate built asset data are needed to advance urban health research, inform policy, and improve individuals' access to assets.