Related Experiment Video
Updated: Jun 26, 2025
07:31
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.1K
Classifying Individuals With Rheumatic Conditions as Financially Insecure Using Electronic Health Record Data and
Mia T Chandler1,2, Tianrun Cai2,3, Leah Santacroce3
1Boston Children's Hospital, Boston, Massachusetts.
ACR Open Rheumatology
|May 15, 2024
Summary
Natural language processing (NLP) can detect financial insecurity in rheumatology patients using electronic health records (EHRs). This method shows high accuracy, improving the identification of patients needing support.
Area of Science:
- Medical Informatics
- Computational Linguistics
- Rheumatology
Background:
- Financial insecurity is a significant social determinant of health impacting patient outcomes.
- Identifying financial insecurity in clinical settings is challenging due to its complex and often unstructured documentation in electronic health records (EHRs).
- Integrated care management programs (iCMP) serve diverse patient populations, including those with rheumatologic diseases, who may experience financial challenges.
Purpose of the Study:
- To assess the feasibility of using natural language processing (NLP) to detect financial insecurity among patients with rheumatologic conditions within an iCMP.
- To develop and validate NLP models for identifying financial insecurity from unstructured EHR data.
Main Methods:
- A supervised, rule-based NLP approach was employed on EHR notes from a large cohort of rheumatology patients in an iCMP.
- A custom lexicon for financial insecurity was created, and NLP models (logistic regression, LASSO, random forest) were trained and validated on manually categorized notes.
- Narrative Information Linear Extraction (NILE) was used for NLP processing, with performance compared against a reference standard.
Main Results:
- Over 245,000 EHR notes from 538 patients were analyzed.
- Financial insecurity was identified in 27% of the training cohort and 37% of the validation cohort.
- LASSO and random forest models demonstrated high performance, achieving a positive predictive value of 0.90 and specificity of 0.98.
Conclusions:
- Rule-based NLP with a context-driven lexicon is a feasible and accurate method for identifying financial insecurity in EHRs.
- The developed NLP approach enhances the capture of financial insecurity, aiding in patient support.
- Further research is necessary to optimize algorithm sensitivity and establish construct validity for financial insecurity detection.
More Related Videos
Related Concept Videos
01:30Methods of Documentation VII: EMR
832
Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
832
01:17Classification of Illness
7.5K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
7.5K
01:30Health Information Technology and Healthcare Information System
831
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
831
01:29Issues And Trends In Healthcare Delivery System
5.6K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.6K
01:10Documentation of Nursing Diagnosis
1.2K
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.2K