Assessing the Quality of Structured Data Entry for the Secondary Use of Electronic Medical Records

Abstract

Objective: The raw material of quality improvement is information, whose building block is data. Data in an electronic medical record system have many secondary uses beyond their primary role in patient care, including research and organizational management. This study investigates the data quality of clinical observations recorded using a structured data entry format and assesses the impact of erroneous data. Methods: A total of 4,580,846 input events from 3,348 inpatients, gathered over a three year period in a teaching hospital, were analyzed by using a 2-by-2 conceptual matrix framework for he appropriateness of data types and semantics. The data were classified into three categories: fully usable, partially usable, and not usable. Results: The fully usable data constituted 88.6% of the correctly entered data the remaining 11.4% were erroneous. Among the erroneous data, 0.8% were partially usable (n=3,929), and the remaining 99.2% (n= 510,437) were identified as needing further assessment to improve their quality. Conclusion: Clinical information systems have increasingly used structured data entry or record templates, but the low quality of collected data has severely limited their secondary use potential.