Development and validation of the Collaborative Health Outcomes Information Registry body map

Abstract

Introduction: Critical for the diagnosis and treatment of chronic pain is the anatomical distribution of pain. Several body maps allow patients to indicate pain areas on paper; however, each has its limitations. Objectives: To provide a comprehensive body map that can be universally applied across pain conditions, we developed the electronic Collaborative Health Outcomes Information Registry (CHOIR) self-report body map by performing an environmental scan and assessing existing body maps. Methods: After initial validation using a Delphi technique, we compared (1) pain location questionnaire responses of 530 participants with chronic pain with (2) their pain endorsements on the CHOIR body map (CBM) graphic. A subset of participants (n 5 278) repeated the survey 1 week later to assess test-retest reliability. Finally, we interviewed a patient cohort from a tertiary pain management clinic (n 5 28) to identify reasons for endorsement discordances. Results: The intraclass correlation coefficient between the total number of body areas endorsed on the survey and those from the body map was 0.86 and improved to 0.93 at follow-up. The intraclass correlation coefficient of the 2 body map graphics separated by 1 week was 0.93. Further examination demonstrated high consistency between the questionnaire and CBM graphic (,10% discordance) in most body areas except for the back and shoulders (15-19% discordance). Participants attributed inconsistencies to misinterpretation of body regions and laterality, the latter of which was addressed by modifying the instructions. Conclusions: Our data suggest that the CBM is a valid and reliable instrument for assessing the distribution of pain.

The impact of COVID-19 on patients with chronic pain seeking care at a tertiary pain clinic

“…Patient sex, race/ethnicity, disability status, employment status, marital status, and age were collected to assess demographic characteristics. We also included in analyses the number of doctor’s office and ER visits over the past six months and the number of painful sites using a body map 26 . Finally, we analyzed current drinking status and number of drinks per week for those endorsing alcohol use.…”

Hierarchical clustering by patient-reported pain distribution alone identifies distinct chronic pain subgroups differing by pain intensity, quality, and clinical outcomes

“…Areas of pain are selected on two side-by-side manikins, an anterior and posterior representation of the body with lines dividing anatomically distinct body regions and a craniocaudal line dividing left and right sides as previously validated and used in multiple studies [ 23 – 26 , 37 – 39 ]. The instructions were “Select the areas where you are experiencing pain” (see Fig 1 ).…”

“…The body map presented to each patient was either female or male depending on their reported gender in the EMR. Female and male manikins were the same as previously developed and validated, showing excellent face validity, test-retest reliability, and concordance with verbal descriptors of pain location [ 39 ]. The anatomic regions were the same between female and male manikins, however six regions (arbitrary numbers 112–117) on the male body map were not labelled with the same numbers as the female map.…”

Classifying chronic pain using multidimensional pain-agnostic symptom assessments and clustering analysis

“…These measures used a common and validated ( 38 ) 11-point numeric rating scale of 0-10 (0=no pain, 10=pain as bad as you can imagine) for worst and average pain in the last seven days, and current pain. The number of body segments in which chronic pain is experienced were self-reported by patients, who were asked to mark locations of pain on a reliable and valid CHOIR body map scheme that included 36 anterior and 38 posterior symmetrical body segments for a maximum total of 74 segments (Figure 1A) ( 39 ). This measure was used to reflect the extent of pain throughout the body.…”