• Axel C Mühlbacher, Uwe Junker, Christin Juhnke, Edgar Stemmler, Thomas Kohlmann, Friedhelm Leverkus, and Matthias Nübling.
• IGM Institute Health Economics and Healthcare Management, Hochschule Neubrandenburg, Brodaer Straße 2, 17033, Neubrandenburg, Germany, muehlbacher@hs-nb.de.
• Eur J Health Econ. 2015 Jul 1; 16 (6): 613-28.

ObjectiveThe objective of this study was to identify, document, and weight attributes of a pain medication that are relevant from the perspective of patients with chronic pain. Within the sub-population of patients suffering from "chronic neuropathic pain", three groups were analyzed in depth: patients with neuropathic back pain, patients with painful diabetic polyneuropathy, and patients suffering from pain due to post-herpetic neuralgia. The central question was: "On which features do patients base their assessment of pain medications and which features are most useful in the process of evaluating and selecting possible therapies?"MethodsA detailed literature review, focus groups with patients, and face-to-face interviews with widely recognized experts for pain treatment were conducted to identify relevant treatment attributes of a pain medication. A pre-test was conducted to verify the structure of relevant and dominant attributes using factor analyses by evaluating the most frequently mentioned representatives of each factor. The Discrete-Choice Experiment (DCE) used a survey based on self-reported patient data including socio-demographics and specific parameters concerning pain treatment. Furthermore, the neuropathic pain component was determined in all patients based on their scoring in the painDETECT(®) questionnaire. For statistical data analysis of the DCE, a random effect logit model was used and coefficients were presented.ResultsA total of 1,324 German patients participated in the survey, of whom 44 % suffered from neuropathic back pain (including mixed pain syndrome), 10 % complained about diabetic polyneuropathy, and 4 % reported pain due to post-herpetic neuralgia. A total of 36 single quality aspects of pain treatment, detected in the qualitative survey, were grouped in 7 dimensions by factor analysis. These 7 dimensions were used as attributes for the DCE. The DCE model resulted in the following ranking of relevant attributes for treatment decision: "no character change", "less nausea and vomiting", "pain reduction" (coefficient: >0.9 for all attributes, "high impact"), "rapid effect", "low risk of addiction" (coefficient ~0.5, "middle impact"), "applicability with comorbidity" (coefficient ~0.3), and "improvement of quality of sleep" (coefficient ~0.25). All attributes were highly significant (p < 0.001).ConclusionsThe results were intended to enable early selection of an individualized pain medication. The results of the study showed that DCE is an appropriate means for the identification of patient preferences when being treated with specific pain medications. Due to the fact that pain perception is subjective in nature, the identification of patients´ preferences will enable therapists to better develop and implement patient-oriented treatment of chronic pain. It is therefore essential to improve the therapists´ understanding of patient preferences in order to make decisions concerning pain treatment. DCE and direct assessment should become valid instruments to elicit treatment preferences in chronic pain.

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