Keywords

Algorithm, Digital drawing, Pain assessment, Pain quantification, PAIN

 

Authors

  1. Abudawood, Khulud PhD, RN
  2. Yoon, Saunjoo L. PhD, RN
  3. Garg, Rishabh MS
  4. Yao, Yingwei PhD
  5. Molokie, Robert E. MD
  6. Wilkie, Diana J. PhD, RN, FAAN

Abstract

Patient-reported pain locations are critical for comprehensive pain assessment. Our study aim was to introduce an automated process for measuring the location and distribution of pain collected during a routine outpatient clinic visit. In a cross-sectional study, 116 adults with sickle cell disease-associated pain completed PAINReportIt(R). This computer-based instrument includes a two-dimensional, digital body outline on which patients mark their pain location. Using the ImageJ software, we calculated the percentage of the body surface area marked as painful and summarized data with descriptive statistics and a pain frequency map. The painful body areas most frequently marked were the left leg-front (73%), right leg-front (72%), upper back (72%), and lower back (70%). The frequency of pain marks in each of the 48 body segments ranged from 3 to 79 (mean, 33.2 +/- 21.9). The mean percentage of painful body surface area per segment was 10.8% +/- 7.5% (ranging from 1.3% to 33.1%). Patient-reported pain locations can be easily analyzed from digital drawings using an algorithm created via the free ImageJ software. This method may enhance comprehensive pain assessment, facilitating research and personalized care over time for patients with various pain conditions.