Words Matter: Content Analysis of Language Used When Documenting in the Medical Records of Patients in Mental Health

Background: Biased healthcare documentation adversely impacts patient outcomes, by affecting providers’ perceptions. Identifying stigmatizing language is crucial for appropriate workforce training. Purpose: To identify, describe, and compare language patterns used in medical records of individuals with mental illness. Methods: Patient encounters within the sole Qatari mental health governmental provider were randomly selected. Rich-text notes documented by any of eight eligible healthcare fields, written October–December/2021, and taking place during outpatient, inpatient, or community-homecare encounters were analyzed qualitatively for positive and negative language, and quantitatively for the percentage of notes with language types/subtypes. Association between language and patient/provider characteristics was tested using Goodness-of-fit chi2 and Fisher’s exact test, as appropriate. Results: Of 300 notes, most included potentially stigmatizing language (62.7%). Disability-first and inappropriate treatment-related language were the top isolated subtypes (33.22% and 31.31% of negative notes, respectively). Similarly, 66.67% of notes incorporated positive statements, mainly personalized language (44%). Positive language was statistically associated with specialty, age, diagnosis, discipline, setting, and patient’s first language. Stigmatizing language was statistically associated with setting, physician level, and discipline. Conclusion: Content analysis of mental health notes highlighted comparable use of positive and negative language. These findings urge policymakers and educators to advocate for recovery-oriented mental health documentation.