Innovative Survey Designs for Collecting Information from Healthcare Professionals
There are two setups that are frequently used in surveys for healthcare professionals. The first of these is a Chart Audit setup where a portion of the survey is programmed to look like an actual patient chart. There are pages designed to collect background, diagnosis, previous treatments, current treatments, and other information. Specific instructions are provided to the doctor so that they can pull the relevant patient charts and have these available while filling in the survey. Due to the time required to input the patients’ data, we generally recommend a maximum of 4 patient charts per physician. The purpose of a Chart Audit is to collect real patient information anonymously and compare how patients receive treatment.
The second setup often used in healthcare surveys involves a Patient Simulation where various patient profiles mocked up by the client are displayed, usually with varying demographics and disease levels. Along with the patient profiles, a list of current treatments are displayed so that the physician can select the treatment(s) they deem most appropriate for that specific patient. Additional logic can even be added so that only certain treatments can be selected in combination. This exercise is then repeated for all patient profiles. This exercise typically involves between 8 to 12 patient profiles. Usually, at this point in the survey, a new product is introduced to the physicians. The Patient Simulation exercise is then repeated for the same set of patients with the new product now being a treatment option as well. This helps to determine if treatment regimens would change with the introduction of a new product.
In the two examples here, healthcare professionals are asked to input complex information about the patients they see. It’s important that our usual interface be made completely dynamic, allowing only the right questions to be shown at the right time. This helps to make data entry as quick and efficient as possible, while reducing respondent fatigue and ensuring the highest quality of data.