Identifying problematic opioid use in electronic health record data: Are we looking in the right place?

OBJECTIVE: To examine the value of data obtained outside of regular healthcare visits (clinical communications) to detect problematic opioid use in electronic health records (EHRs). DESIGN: A retrospective cohort study. PARTICIPANTS: Chronic pain patient records in a large academic medical center. INTERVENTIONS: We compared evidence for problematic opioid use in (1) clinic notes, (2) clinical communications, and (3) full EHR data. We analyzed keyword counts and calculated concordance and Cohen's κ between data sources. MAIN OUTCOME MEASURE: Evidence of problematic opioid use in EHR defined as none, some, or high. RESULTS: Twenty-six percent of records were discordant in determination of problematic opioid use between clinical communications and clinic notes. Of these, 54 percent detected more evidence in clinical communications, and 46 percent in clinic notes. Compared to full EHR review, clinic notes exhibited higher concordance (78 percent; κ = 0.619) than clinical communications (60 percent; κ = 0.290). CONCLUSION: Clinical communications are a valuable addition to opioid EHR research.

Hyperspectral imaging to accurately segment skin erythema and hyperpigmentation in cutaneous chronic graft-versus-host disease.

In 51 lesions from 15 patients with the inflammatory skin condition chronic graft-versus-host-disease, hyperspectral imaging accurately delineated active erythema and post-inflammatory hyperpigmentation. The method was validated by dermatologist-approved confident delineations of only definitely affected and definitely unaffected areas in photographs. A prototype hyperspectral imaging system acquired a 2.5 × 3.5 cm2 area of skin at 120 wavelengths in the 450-850 nm range. Unsupervised extraction of unknown absorbers by endmember analysis achieved a comparable accuracy to that of supervised extraction of known absorbers (melanin, hemoglobin) by chromophore mapping: 0.78 (IQR: 0.39-0.85) vs. 0.83 (0.53-0.91) to delineate erythema and 0.74 (0.57-0.87) vs. 0.73 (0.52-0.84) to delineate hyperpigmentation. Both algorithms achieved higher specificity than sensitivity. Whereas a trained human confidently marked a median of 7% of image pixels, unsupervised and supervised algorithms delineated a median of 14% and 27% pixels. Hyperspectral imaging could overcome a fundamental practice gap of distinguishing active from inactive manifestations of inflammatory skin disease.