Identifier |
006_RR2016_CCTS_Development_Provider_Feedback_SSIS_Dashboard_HE.pdf |
Title |
Development of a Provider Feedback SSIS Dashboard Using SAS Analytic Modules Specifically Designed for Transparent and Reusable Workflows Using Veteran Affairs Healthcare Data |
Creator |
Tao He; Celena Peters; Zachary Burningham; Chris Leng; Tina Hyun; Brian C. Sauer |
Subject |
Data Analysis; Research; Research Reproducibility; Workflow Development |
Description |
The reproducibility of data analysis and reuse of standardized processes are increasingly recognized as critical to the mission of healthcare operational and research endeavors. The purpose of this abstract is to explain how we operationalized generalized workflows to perform real time provider profiling and feedback using Microsoft Business Intelligence tools to execute analytic workflows that integrated the use of our SASO based Transparent ReUsable Statistical Tools (TRUST) modules. SQL Server Integration Services (SSIS) is a platform to help extract, transform and load data for analytic treatment and display in SQL Server Reporting Service (SSRS) and SharePoint, respectively. The Microsoft tools, unfortunately, are limited in their analytic capabilities. Integration with SASO or R is needed for implementing predictive and inferencing analytics. The Veterans Affairs maintains a SAS GRID that supports parallel processing and has some efficiency advantages over SQL. We develop a workflow package with well-defined SQL stored procedure and TRUST modules designed for providers to evaluate the use of opioids for their patient panel within the VA. We developed a tool to extend the SSIS platform for SAS support. SAS programs can be executed in SSIS as SQL code within our development environment. We can easily detect and flag SAS errors and provide users a SAS execution log file to locate where the error occurred. Our opioid feedback dashboard was developed using our SSIS workflow package with SAS extensions. This project is being extended to other clinical domains and drug surveillance projects. |
Relation is Part of |
2016 Research Reproducibility Conference & Lectures |
Publisher |
Spencer S. Eccles Health Sciences Library, University of Utah |
Date Digital |
2016 |
Date |
2016 |
Format |
application/pdf |
Rights Management |
Copyright 2016. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright |
Language |
eng |
ARK |
ark:/87278/s6rr69v4 |
Type |
Text |
Setname |
ehsl_rr |
ID |
1400677 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6rr69v4 |