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Transitioning STI and Hepatitis Surveillance Analyses from Excel to R: A Process Improvement Project

Video Presentation

View Sara Perlman-Arrow's poster presentation in this video recording:聽聽

Abstract

Sexually Transmitted Infections (STIs) and Hepatitis pose important public health threats. To monitor these important infections, the Canadian Notifiable Diseases Surveillance System (CNDSS) at the Public Health Agency of Canada (PHAC) collects case count data and transmits this information annually to the STI and Hepatitis section. This section performs descriptive analyses on data for chlamydia, gonorrhea, syphilis, hepatitis B and hepatitis C, and produces annual disease reports and infographics to inform policies for disease prevention and management.聽聽

Historically, the team has conducted all analyses using Excel. To make the process more efficient, comprehensive, and reproducible, the section sought to automate the production of analysis tables using R. The goal was to produce a library of R files for each disease of interest that would take the case count and population data sheets as input, and output all relevant descriptive analysis tables, as well as corresponding graphs. This project consisted of 4 primary tasks: 1) The development of a data analysis plan, including a detailed list of expected code outputs ; 2) The development of R code to produce analysis tables for each disease, using CNDSS data from 2010 to 2019 as a reference 3) Validation of the R code outputs using Excel; and 4) The development of a document with Standard Operation Procedures (SOP), outlining the project process and providing detailed guidelines for code usage.聽聽

The team anticipated to receive the 2020 data from CNDSS during the summer of 2022 and to implement this newly developed system during their next analysis. Due to delays, the implementation did not occur during the time of my practicum. However, the team shared preliminary results which illustrated improvement in the process, highlighting the feasibility of implementing R automations to surveillance analyses.聽聽

The section is using similar methods to automate other surveillance analyses, and methodology has been shared within PHAC such that other teams can implement similar process improvement projects. Altogether, improvements will allow teams to dedicate more time to other essential activities, such as interpreting and disseminating results, and contribute more meaningful outputs for PHAC to use in planning interventions and policies.聽

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