Patient-reported outcomes are reports associated with health conditions, that come directly from the patient, without external interpretation.
Traditionally, patient-reported outcomes are measured subjectively by collecting people’s responses to ‘paper-pencil’ questionnaires.
For more than a decade, PROMinsight has been the trusted provider of valid, reliable and responsive questionnaires to measure vision-related quality of life.
Impact of Vision Impairment
The IVI questionnaires measure the impact of vision impairment on vision-related quality of life. They have been designed specifically for adults, children and people living in residential care facilities with vision impairment.
Diabetic Retinopathy Knowledge and Attitudes (DRKA)
The DRKA assesses patients’ knowledge and attitudes about diabetic retinopathy (DR) and diabetic macular edema (DME), and associated management and treatment.
Paper-pencil questionnaires come with certain drawbacks. They take up storage space, and data must be manually entered which is resource intensive and increases the chance of human error.
PROMinsight strongly recommends using the digital versions of our questionnaires
Digital versions of our questionnaires are supplied via a personalised, password-protected web link and data are stored on our secure server.
Questionnaire scores are automatically computed and presented on screen, and datasets are provided on request.
No need for manual data entry and scoring, or physical storage of questionnaires.
Limitations of traditional scoring
Whether using paper-pencil or digital format, questionnaires are traditionally scored by adding up the values for each item to produce an overall total (also called ‘summed’) score or average score.
This approach is problematic as the data are ordinal in nature. Ideally, only interval-level data (i.e. data that are equal interval, like a ruler) should be used in parametric testing.
Missing data are also problematic in traditional scoring and require complex statistical solutions to manage it.
The issues with traditional scoring can be overcome by modern psychometric methods like Item Response Theory (IRT), such as Rasch Analysis.
We recommend that Rasch analysis is applied to the raw responses from any of our questionnaires, whether administered in paper-pencil or digital format.
Rasch analysis provides:
A quality control system to optimise the psychometric properties of a questionnaire, such as precision, unidimensionality, item ‘fit’, targeting, and item bias.
A way to convert ordinal scores into interval-level estimates.
Improved measurement precision and increased sensitivity to detect change in scores over time.