title: Characterizing the pain score trajectories of hospitalized adult medical and surgical patients: a retrospective cohort study.
abstract: Pain care for hospitalized patients is often suboptimal. Representing pain scores as a graphical trajectory may provide insights into the understanding and treatment of pain. We describe a 1-year, retrospective, observational study to characterize pain trajectories of hospitalized adults during the first 48 hours after admission at an urban academic medical center. Using a subgroup of patients who presented with significant pain (pain score >4; n = 7762 encounters), we characterized pain trajectories and measured area under the curve, slope of the trajectory for the first 2 hours after admission, and pain intensity at plateau. We used mixed-effects regression to assess the association between pain score and sociodemographics (age, race, and gender), pain medication orders (opioids, nonopioids, and no medications), and medical service (obstetrics, psychiatry, surgery, sickle cell, intensive care unit, and medicine). K-means clustering was used to identify patient subgroups with similar trajectories. Trajectories showed differences based on race, gender, service, and initial pain score. Patients presumed to have dissimilar pain experiences (eg, sickle vs obstetrical) had markedly different pain trajectories. Patients with higher initial pain had a more rapid reduction during their first 2 hours of treatment. Pain reduction achieved in the 48 hours after admission was approximately 50% of the initial pain, regardless of the initial pain. Most patients' pain failed to fully resolve, plateauing at a pain score of 4 or greater. Visualizing pain scores as graphical trajectories illustrates the dynamic variability in pain, highlighting pain responses over a period of observation, and may yield new insights for quality improvement and research.
authors.affiliation: Departments of Family Medicine.
authors.forename: Thomas
authors.initials: T
authors.lastname: Kannampallil
authors.affiliation: Medicine, and.|Pharmacy Practice, Pharmacy Systems, Outcomes and Policy, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: William L
authors.initials: WL
authors.lastname: Galanter
authors.affiliation: Medicine, and.
authors.forename: Suzanne
authors.initials: S
authors.lastname: Falck
authors.affiliation: Institute for Safe Medication Practices, Horsham, PA, USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Gaunt
authors.affiliation: Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL, USA.
authors.forename: Robert D
authors.initials: RD
authors.lastname: Gibbons
authors.affiliation: Medicine, and.
authors.forename: Robert
authors.initials: R
authors.lastname: McNutt
authors.affiliation: Chicago, IL, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Odwazny
authors.affiliation: Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
authors.forename: Gordon
authors.initials: G
authors.lastname: Schiff
authors.affiliation: Institute for Safe Medication Practices, Horsham, PA, USA.
authors.forename: Allen J
authors.initials: AJ
authors.lastname: Vaida
authors.affiliation: College of Nursing, University of Florida, Gainesville, FL, USA.
authors.forename: Diana J
authors.initials: DJ
authors.lastname: Wilkie
authors.affiliation: Center for Communication and Health, Department of Communication Studies, Northwestern University, Chicago, IL, USA.
authors.forename: Bruce L
authors.initials: BL
authors.lastname: Lambert
mesh_terms: D000328:Adult; D016000:Cluster Analysis; D015331:Cohort Studies; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010146:Pain / Q000175:diagnosis* / Q000453:epidemiology*; D059408:Pain Management; D012044:Regression Analysis