A longitudinal linear model of patient characteristics to predict failure to attend an inner-city chronic pain clinic

Naum Shaparin, Robert White, Michael Andreae, Charles Hall, Andrew Kaufman

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Patients often fail to attend appointments in chronic pain clinics for unknown reasons. We hypothesized that certain patient characteristics predict failure to attend scheduled appointments, pointing to systematic barriers to accessing chronic pain services for certain underserved populations. We collected retrospective data from a longitudinal observational cohort of patients at an academic pain clinic in Newark, New Jersey. To examine the effect of demographic factors on appointment status, we fit a marginal logistic regression using generalized estimating equations with exchangeable correlation. A total of 1,394 patients with 3,488 total encounters between January 1, 2006, and December 31, 2009, were included. Spanish spoken as a primary language (alternatively Hispanic or other race) and living between 5 and 10 miles from the clinic were associated with reduced odds of arriving for an appointment; making an appointment for a particular complaint such as cancer pain or back pain, an interventional pain procedure scheduled in connection with the appointment, unemployed status, and continuity of care (as measured by office visit number) were associated with increased odds of arriving. Spanish spoken as a primary language and distance to the pain clinic predicted failure to attend a scheduled appointment in our cohort. If these constitute systematic barriers to access, they may be amenable to targeted interventions. Perspective We identified certain patient characteristics, specifically Spanish spoken as a primary language and geographic distance from the clinic, that predict failure to attend an inner-city chronic pain clinic. These identified barriers to accessing chronic pain services may be modifiable by simple cost-effective interventions.

Original languageEnglish (US)
Pages (from-to)704-711
Number of pages8
JournalJournal of Pain
Volume15
Issue number7
DOIs
StatePublished - Jul 2014

All Science Journal Classification (ASJC) codes

  • Neurology
  • Clinical Neurology
  • Anesthesiology and Pain Medicine

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