Clinical Decision Support Decreases Volume of Imaging for Low Back Pain in an Urban Emergency Department.

PURPOSE: To determine whether point-of-care clinical decision support can effectively reduce inappropriate medical imaging of patients who present to the emergency department (ED) with low-back pain (LBP). MATERIALS AND METHODS: This was a prospective, single-center study of lumbar imaging referrals made by 43 emergency physicians at a major acute care center. Each physician saw at least 10 LBP cases in both pre- and post-intervention periods. A point-of-care checklist of accepted red flags for LBP was designed by a working group of physicians and embedded in the computerized order entry form for lumbar imaging. We compared imaging rates of LBP and physician variation in imaging ordering before and after the implementation of the checklist. We then measured the potential harms of reduced imaging. RESULTS: After intervention, the proportion of LBP patients with an imaging order fell significantly (median: 22% to 17%; mean: 23% to 18%; P = .0002) compared with pre-intervention baseline. The percentage of patients without imaging who were later imaged at a hospital outpatient clinic within 30 days was 2.3% before intervention and 2.2% after (P = .974). In addition, the proportion of patients discharged from the ED without imaging who returned to the ED within 30 days was 8.2% before intervention and 6.9% after (P = .170). One minor thoracic spine compression fracture was missed, but management was not impacted. No serious diagnoses were missed. CONCLUSION: Clinical decision support integrated in electronic order entry forms can safely and effectively reduce imaging orders for LBP patients in the ED.

Operations research methods improve chemotherapy patient appointment scheduling.

BACKGROUND: Clinical complexity, scheduling restrictions, and outdated manual booking processes resulted in frequent clerical rework, long waitlists for treatment, and late appointment notification for patients at a chemotherapy clinic in a large cancer center in British Columbia, Canada. A 17-month study was conducted to address booking, scheduling and workload issues and to develop, implement, and evaluate solutions. METHODS: A review of scheduling practices included process observation and mapping, analysis of historical appointment data, creation of a new performance metric (final appointment notification lead time), and a baseline patient satisfaction survey. Process improvement involved discrete event simulation to evaluate alternative booking practice scenarios, development of an optimization-based scheduling tool to improve scheduling efficiency, and change management for implementation of process changes. Results were evaluated through analysis of appointment data, a follow-up patient survey, and staff surveys. RESULTS: Process review revealed a two-stage scheduling process. Long waitlists and late notification resulted from an inflexible first-stage process. The second-stage process was time consuming and tedious. After a revised, more flexible first-stage process and an automated second-stage process were implemented, the median percentage of appointments exceeding the final appointment notification lead time target of one week was reduced by 57% and median waitlist size decreased by 83%. Patient surveys confirmed increased satisfaction while staff feedback reported reduced stress levels. CONCLUSION: Significant operational improvements can be achieved through process redesign combined with operations research methods.