A patient-centric data analysis: application of a N-of-1 analysis in a pediatric pain intervention
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Citation
Abstract
Making evidence-based treatment recommendations is very important for clinicians across all medical specialties. This becomes increasingly difficult when taking into consideration the specific characteristics of each individual patient. Most evidence-based knowledge comes from randomized control trials, which often overlooks unique individual concerns. A single case methodology, which assesses treatment responses in individual patients, allows clinicians to collect statistically rigorous data, but also assess improvement in individual patients. In our investigation we show that a single case methodology, using four different analyses, can be applied to assess the efficacy of a CBT intervention delivered to pediatric chronic pain patients. We demonstrate that such a methodology, when we combine results from multiple statistical tests, allows us to make conclusions about treatment responses. Furthermore, we show that our intervention targets several different issues chronic pain patients face, in particular the avoidance of painful activities. While we did see congruence of results across the different statistical analyses, there were also several examples of inconsistency. These inconsistencies seem to occur when patients show considerable variability in their responses to the questions on the daily measures, introducing ‘noise’ that made detecting ‘true signal’ (treatment response) quite difficult.