A unified conceptual framework for metabolic phenotyping in diagnosis and prognosis

Understanding metabotype (multicomponent metabolic characteristics) variation can help generate new diagnostic and prognostic biomarkers and models with the potential to impact patient management. Here we present a suite of conceptual approaches for the generation, analysis and understanding of metabotypes from body fluids and tissues. We describe and exemplify four fundamental approaches to the generation and utilization of metabotype data via multiparametric measurement of: i) metabolite levels; ii) metabolic trajectories; iii) metabolic entropies and iv) metabolic networks and correlations in space and time. This conceptual framework can underpin metabotyping in the scenario of personalised medicine, with the aim of improving clinical outcomes for patients, but it will have value and utility in all areas of metabolic profiling well beyond this exemplar

Changing Work and COVID-19: Intragovernmental Response Best Practices

23 pagesThis report looks to examine the question: How has work changed for Lane County departments since the outbreak of COVID-19? Our report contains a literature review, evaluative framework, example survey, and a set of workforce best practices for managers during a pandemic. We begin with a review of the most current literature pertaining to worker and managerial challenges caused by the coronavirus. The literature review outlines unique problems caused by work from home mandates and highlights difficulties faced by essential employees working on the frontlines. The review culminates with a list of best practices that managers can implement to ensure their employees have safe and effective working conditions during the pandemic. We present an evaluative framework describing how the County can create a survey tool to gauge employee perception of changes in work during COVID-19. Using Lean Data methodology and Ecosystem Strategy by Alnoor Ebrahim et al (Stanford Center for Social Innovation), we describe how to gather and operationalize data effectively to create positive organizational change. Then we use the tenets of Lean Data to suggest an online survey tool and a set of potential questions culled from the literature. A quantitative, easy to complete survey is presented for employees, with a more qualitative interview style survey example presented to gather manager perspectives. Finally, the report concludes with recommendations and best practices that Lane County’s managers can utilize to maintain employee wellness during this pandemic and in future emergencies.Lane County, Orego

Intra-database validation of case-identifying algorithms using reconstituted electronic health records from healthcare claims data

BACKGROUND: Diagnosis performances of case-identifying algorithms developed in healthcare database are usually assessed by comparing identified cases with an external data source. When this is not feasible, intra-database validation can present an appropriate alternative. OBJECTIVES: To illustrate through two practical examples how to perform intra-database validations of case-identifying algorithms using reconstituted Electronic Health Records (rEHRs). METHODS: Patients with 1) multiple sclerosis (MS) relapses and 2) metastatic castration-resistant prostate cancer (mCRPC) were identified in the French nationwide healthcare database (SNDS) using two case-identifying algorithms. A validation study was then conducted to estimate diagnostic performances of these algorithms through the calculation of their positive predictive value (PPV) and negative predictive value (NPV). To that end, anonymized rEHRs were generated based on the overall information captured in the SNDS over time (e.g. procedure, hospital stays, drug dispensing, medical visits) for a random selection of patients identified as cases or non-cases according to the predefined algorithms. For each disease, an independent validation committee reviewed the rEHRs of 100 cases and 100 non-cases in order to adjudicate on the status of the selected patients (true case/ true non-case), blinded with respect to the result of the corresponding algorithm. RESULTS: Algorithm for relapses identification in MS showed a 95% PPV and 100% NPV. Algorithm for mCRPC identification showed a 97% PPV and 99% NPV. CONCLUSION: The use of rEHRs to conduct an intra-database validation appears to be a valuable tool to estimate the performances of a case-identifying algorithm and assess its validity, in the absence of alternative