Evaluation of a Teleform-based data collection system: A multi-center obesity research case study

Abstract

Utilizing electronic data capture (EDC) systems in data collection and management allows automated validation programs to preemptively identify and correct data errors. For our multi-center, prospective study we chose to use TeleForm, a paper-based data capture software that uses recognition technology to create case report forms (CRFs) with similar functionality to EDC, including custom scripts to identify entry errors. We quantified the accuracy of the optimized system through a data audit of CRFs and the study database, examining selected critical variables for all subjects in the study, as well as an audit of all variables for 25 randomly selected subjects. Overall we found 6.7 errors per 10,000 fields, with similar estimates for critical (6.9/10,000) and non-critical (6.5/10,000) variables – values that fall below the acceptable quality threshold of 50 errors per 10,000 established by the Society for Clinical Data Management. However, error rates were found to widely vary by type of data field, with the highest rate observed with open text fields.

Electronic data capture for large scale typhoid surveillance, household contact tracing, and health utilisation survey: Strategic Typhoid Alliance across Africa and Asia

“…4). The data accuracy of ~0.22% errors (21.7 errors per 10,000 data points) reported in this study meets the acceptable quality threshold of 50 errors per 10,000 data points recommended by the Society of Clinical Data Management (SCDM, McLean, Virginia, USA) [22,23].…”

“…We were able to use SQL to pull seasonal data from MySQL-defined database, and automate summaries of demographics in order to monitor progress of field work, and collective and individual performance of field workers. SQL was preferred because of its simple but powerful syntax, and its wider use in handling complex queries to epidemiological datasets [22,24,29,32]. Since the STRATAA consortium continuously generates laboratory data, post-census, the EDC also allows scalability, pushing laboratory data from laboratory database systems to MySQL-defined databases while keeping the database structure homogeneous across sites.…”

A new method of mark detection for software-based optical mark recognition

“…When compared with the commercial RecoFlex recognition engine in Hewlett-Packard’s industry-standard TeleForm, which is a neural-based recognition system that combines multiple recognition engines for improved accuracy, the SOMR component yielded an error rate of 0.02% which is comparable to the new detection method described. Moreover, the stated accuracy for TeleForm required 153 out of 636 questionnaires to have the bubble markings darkened, amended, or marked over with a black pen when tested on untrained respondents [ 13 , 22 , 23 ]. Internal labels were also not used.…”

“…The low error rates for the “X-Mark Detection” and “Pixel Counting” methods were achieved only by looking for specific types of marks, which were crosses and completely filled bubbles respectively, while favorable testing conditions were created for TeleForm [ 3 , 5 , 22 ]. The new detection method can achieve similar results under a wide variety of conditions, which these other methods are not able to do.…”

Protocol for establishing an infant feeding database linkable with population-based administrative data: a prospective cohort study in Manitoba, Canada

“…We selected the Teleform Fax Tool 42 since it is compliant with Manitoba's personal health information legislation and can be used without internet access. Fax technology is also routinely used to collect health information in jurisdictions across Canada, [43][44][45][46] and as such, is an accepted tool for collecting survey data.…”