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

Biased healthcare documentation adversely impacts patient outcomes, by affecting providers' perceptions. Identifying stigmatizing language is crucial for appropriate workforce training.

To identify, describe, and compare language patterns used in medical records of individuals with mental illness.

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.

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.

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.