CONTEXT: Either a two-factor representation (pain intensity and interference) or a three-factor representation (pain intensity, activity interference, and affective interference) of the modified Brief Pain Inventory (BPI) is appropriate among cancer patients. OBJECTIVES: To evaluate the extent to which a three-factor representation (pain intensity, activity interference, and affective interference) is appropriate for BPI among patients with noncancer pain seen in an outpatient setting. METHODS: We conducted a prospective, multicenter, observational, nonrandomized study using patient pain registry data from outpatient settings. Seven hundred forty-one patients with acute episodes of noncancer pain requiring treatment with a prescription medication containing oxycodone immediate-release on an as-needed basis for at least five days participated. Baseline measurements included the modified BPI pain intensity (right now, average, and worst in 24 hours) and pain interference with general activities, walking, work, mood, relations with others, sleep, and life enjoyment. Confirmatory factor analysis was conducted for the overall sample and among postoperative patients (n = 133), patients with back and neck pain (n = 202), patients with arthritis (n = 148), and patients with injury or trauma (n = 204). RESULTS: Both the two-factor and three-factor models were statistically better than the one-factor model (P < 0.05), with the two-factor model performing better than the three-factor model. Configural invariance, but not metric invariance by patient cohort group was demonstrated. CONCLUSION: Consistent with analyses among cancer patients, a two-factor representation of BPI is appropriate for noncancer patients seen in an ambulatory setting. This work lends additional support for the psychometric properties of BPI. All rights reserved.

OBJECTIVES: The objective of this paper was to describe primary care prescribers' perspectives on electronic prescribing drug alerts at the point of prescribing. DESIGN: We used a mixed-method study which included clinician surveys (web-based and paper) and focus groups with prescribers and staff. PARTICIPANTS: Prescribers (n = 157) working in one of 64 practices using 1 of 6 e-prescribing technologies in 6 US states completed the quantitative survey and 276 prescribers and staff participated in focus groups. MEASUREMENTS: The study measures self-reported frequency of overriding of drug alerts; open-ended responses to: "What do you think of the drug alerts your software generates for you?" RESULTS: More than 40% of prescribers indicated they override drug-drug interactions most of the time or always (range by e-prescribing system, 25% to 50%). Participants indicated that the software and the interaction alerts were beneficial to patient safety and valued seeing drug-drug interactions for medications prescribed by others. However, they noted that alerts are too sensitive and often unnecessary. Participant suggestions included: (1) run drug alerts on an active medication list and (2) allow prescribers to set the threshold for severity of alerts. CONCLUSIONS: Primary care prescribers recognize the patient safety value of drug prescribing alerts embedded within electronic prescribing software. Improvements to increase specificity and reduce alert overload are needed.