Computer assessment and diagnostic classification of chronic pain patients.

OBJECTIVE: In order to establish a diagnosis of chronic pain, emphasis is placed on a patient's report of the pain's intensity, location, and character. The aim of this study was to evaluate the feasibility of a computer assessment method to collect self-reports of pain that were then used in discriminant analyses to distinguish among chronic pain diagnoses.
METHODS: A convenience sample of 511 patients from two university-based pain clinics completed a computer pain assessment battery that elicited demographic information, pain drawings, pain and emotion intensity ratings, and intensity ratings of verbal descriptors. Patients classified themselves into one of six chronic pain diagnoses. Discriminant analyses were performed in an attempt to identify the unique features of patients' pain experience associated with each of the diagnostic categories.
RESULTS: Pain drawings successfully classified patients into three of the diagnostic categories (back, head, and neck pain). In a second analysis, two pain descriptors (cramping and stabbing) separated rheumatoid arthritis patients from those with either fibromyalgia or neural pain. One descriptor of pain (cramping) and one descriptor of emotion (frustration) together distinguished between fibromyalgia and neural pain.
CONCLUSIONS: 1) Computer assessment of a range of patient symptoms is feasible in the pain clinic. 2) Discriminant analysis based on pain drawings can distinguish among patient-reported diagnoses of back pain, headache, and neck pain. 3) Discriminant analysis based on three verbal descriptors can help to distinguish among diagnoses of fibromyalgia, neuralgia, and rheumatoid arthritis. 4) However, in general, most computerized descriptive information is not useful in distinguishing differences among pain patient diagnostic groups.