Development of a screening algorithm for borderline personality disorder using electronic health records. Academic Article uri icon

Overview

abstract

  • Borderline personality disorder (BoPD or BPD) is highly prevalent and characterized by reactive moods, impulsivity, behavioral dysregulation, and distorted self-image. Yet the BoPD diagnosis is underutilized and patients with BoPD are frequently misdiagnosed resulting in lost opportunities for appropriate treatment. Automated screening of electronic health records (EHRs) is one potential strategy to help identify possible BoPD patients who are otherwise undiagnosed. We present the development and analytical validation of a BoPD screening algorithm based on routinely collected and structured EHRs. This algorithm integrates rule-based selection and machine learning (ML) in a two-step framework by first selecting potential patients based on the presence of comorbidities and characteristics commonly associated with BoPD, and then predicting whether the patients most likely have BoPD. Leveraging a large-scale US-based de-identified EHR database and our clinical expert's rating of two random samples of patient EHRs, results show that our screening algorithm has a high consistency with our clinical expert's ratings, with area under the receiver operating characteristic (AUROC) 0.837 [95% confidence interval (CI) 0.778-0.892], positive predictive value 0.717 (95% CI 0.583-0.836), accuracy 0.820 (95% CI 0.768-0.873), sensitivity 0.541 (95% CI 0.417-0.667) and specificity 0.922 (95% CI 0.880-0.960). Our aim is, to provide an additional resource to facilitate clinical decision making and promote the development of digital medicine.

publication date

  • July 13, 2022

Research

keywords

  • Borderline Personality Disorder
  • Electronic Health Records

Identity

PubMed Central ID

  • PMC9279396

Scopus Document Identifier

  • 85133986898

Digital Object Identifier (DOI)

  • 10.1097/NMD.0000000000000225

PubMed ID

  • 35831356

Additional Document Info

volume

  • 12

issue

  • 1