Minimizing Data Cleaning With The Use Of Electronic Patient Reported Outcome (ePRO) Functionality

By Jennifer Ross, Lead Biostatistician and Elisa Holzbaur, Manager, ePRO Services, Almac Group

Data cleaning is an important process that must occur prior to analysis to ensure data integrity and reliable results. Low quality data can have major impacts on analysis, results, and costs.

Data cleaning consists of querying, diagnosis and resolution. Querying includes identifying missing or out-of-range dates/times, missing responses/records, outliers/out-of-range values, contradictory responses, inconsistencies, and extraneous data.