Pre-appointment online assessment of patient complexity: Towards a personalized model of neuropsychological assessment

ABSTRACT

Recent events such as the global pandemic of COVID-19 have challenged neuropsychologists to scale up their capacity to conduct portions of their assessment remotely. While more complex patients will likely continue to require on-site, office-based interaction and assessment, the current emergency-based expansion of online and telehealth evaluation practices may ultimately lay the groundwork for more routine, online assessment of patients with less complex presentations in the future. To this end, the current study evaluated a pre-appointment, online methodology for differentiating referred pediatric patients based upon the scope and severity of their caregiver-reported adaptive, academic, attentional, behavioral, and emotional impairment. Prior to on-site assessment, parents/caregivers of 2197 children (Mean age = 10.0y, range = 4–19y, 62% male) completed an online developmental history form screening for symptoms of adaptive, attentional, learning, affective, and behavioral impairment; 71% of those children eventually underwent assessment. Using latent class analysis, the data supported a reproducible 4-class model consisting of groups of children at increased risk for: 1) severe multi-domain dysfunction; the “High Complexity” group, 30%, 2) behavioral-affective (but not academic) dysregulation; the “Behavioral Focus” group, 13%, 3) academic (but not behavioral-affective) problems; the “Academic and Inattention” group, 37%, and 4) patients with minimal clinical complexity; the “Low Complexity” group, 20%. Comparison of pre-visit classification with day-of-assessment standardized test scores supported the validity of patient subtypes. Moving forward, pre-appointment clarification of patient complexity may support efficient patient triage with regard to assessment modality (e.g., on-site or online) and length of appointment (e.g., comprehensive or targeted).

KEYWORDS:

• Clinical decision-making
• decision-support systems
• precision medicine
• personalized medicine
• neuropsychology

Disclosure statement

No potential conflict of interest was reported by the author(s).