Forms-processing system speeds up cancer project
A forms-processing system from Kendata Peripherals has enabled
researchers at the London School of Hygiene & Tropical Medicine (LSHTM)
to obtain results from a cancer study much more quickly than would
otherwise have been the case.
Co-ordinated by the LSHTM’s Public & Environmental Health Research
Unit, the multinational Arsenic Health Risk and Molecular epidemiology
project was designed to assess the cancer risks associated with
cumulative exposure to elevated concentrations of arsenic in drinking
water drawn from communal wells in parts of Hungary, Romania (pictured)
and Slovakia.
Interviewers across the three countries completed two 20-page
questionnaires for each of the 1,800 subjects, and the resultant
information then had to be entered into an Access database for analysis.
According to Giovanni Leonardi, an honorary research fellow and
Consultant Epidemiologist at LSHTM, the amount of work involved in
entering such a large amount of data manually would have been both
excessively time-consuming and laborious. “From previous environmental
health projects I knew that, if we had done it all by hand, it would
have been necessary to use double data-entry techniques to produce a
database of sufficient integrity, and this could easily have involved
dozens of people working on relatively boring tasks for six months or
more.”
Kendata’s AutoData Scannable Office system was the natural choice for
him, as he had already seen it used successfully for surveys on a wide
range of health-related topics in both the NHS and the Health Protection
Agency.
Comprising a high-speed scanner, forms-processing software, Microsoft
Word templates and special TrueType fonts, AutoData Scannable Office
enables data to be scanned from paper forms directly into a spreadsheet
or database without the need for cumbersome data-exporting procedures.
Form designs can include fields for check-mark boxes, barcodes, printed
type and hand-printed characters.
“Since AutoData enables customised forms to be designed in the
familiar environment of Word, the learning curve is greatly reduced”,
said LSHTM research fellow, Rupert Hough. The forms were translated into
the local languages and, for simplicity, used mainly check-mark boxes
and hand-print recognition fields.
“As well as vastly reducing the labour requirements for the
data-entry process, AutoData helped us to minimise the delay between
completing the data collection and obtaining clean data ready for
analysis”, said Leonardi.
Source: bjhc&im May 2006
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