Donna D. Ohnmeiss, PhD, President of the Texas Back Institute Research Foundation in Plano, gave a presentation about data collection and outcomes survey design at the North American Spine Society Annual Meeting earlier this year.
She first touched on what makes a good questionnaire for use in clinical practice. The factors for a scientifically good questionnaire in outcomes studies include validity, repeatability and sensitivity. Figure out what you are trying to measure and make sure the questionnaire measures it correctly. For example, if you are measuring success in return to work, are you measuring whether the patient is able to return to the same job or return to work at all?
Additional questions to consider for outcomes questionnaires:
• How outcomes measure up to other disease states
• Validity of responsiveness between different patient populations
• Whether questionnaires can be translated between patients with various spinal conditions
• International collaboration and trials — have they been validated in the different languages and do they have the same responsiveness characteristics across cultures
• Whether patients are willing to complete the questionnaires
o Does it make sense to them?
o Does it take time to complete?
o Is it easy to administer?
o Will it be expensive?
o Can it be administered in electronic formats?
She also touched on what makes a bad questionnaire: something that has not been validated, has a bias design, unclear instructions or includes multiple criteria in a single category. Also make sure the available responses cover all appropriate responses. Modified questionnaires can be problematic, especially if the modifications aren't disclosed or validated.
"When you start modifying questionnaires, you are comparing apples to oranges or other apples," she said. "We just don't really have any way to know what the non-validated, non-investigated instrument really is and what it really tells us."
There have been instances of modification for even the most standard tests, such as Oswestry scale or visual analog scale. "Tampering does very much affect the patient's response," she said. One of the greatest challenges to high quality data collection is lack of standardization, particularly in the modification of questionnaires, she said in summary.
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