The MacNeill-Lichtenberg Decision Tree: a unique method of triaging mental health problems in older medical rehabilitation patients

Abstract

Objective: Evaluation of the utility of a "decision tree" that identifies potential mental health problems in older medical patients and guides decision making for referrals.

Design: Measures of utility including sensitivity, specificity, and predictive power were examined. Independent t tests and nonparametric statistics were used to evaluate group differences where appropriate.

Setting: The stroke and geriatric unit of a freestanding urban medical rehabilitation hospital.

Subjects: In study 1,173 older, consecutively admitted medical rehabilitation patients completed all cognitive measures. In study 2, a separate sample of 313 older adults completed the Geriatric Depression Scale during admission.

Main outcome measure: The MacNeill-Lichtenberg Decision Tree (MLDT) was compared with the Mini-Mental State Exam (MMSE), the Mattis Dementia Rating Scale, and the 30-item Geriatric Depression Scale.

Results: Study 1: The decision tree accurately triaged 87% of mental health problems and allowed for deferral of 41% of cases, for whom further assessment was unnecessary. The MLDT was superior to the MMSE, with higher sensitivity and a lower failure rate. Study 2: The emotional status component of the MLDT was useful in triaging cases for depression evaluation.

Conclusion: The MLDT was useful in prioritizing cases with regard to mental health problems (eg, dementia, depression) and making quick referral decisions. The MLDT is a unique instrument that not only evaluates cognitive status, but also considers psychosocial factors and emotional status in older adults.