Using Natural Language Processing to Improve Discrete Data Capture From Interpretive Cervical Biopsy Diagnoses at a Large Health Care Organization.

CONTEXT.­: The terminology used by pathologists to describe and grade dysplasia and premalignant changes of the cervical epithelium has evolved over time. Unfortunately, coexistence of different classification systems combined with nonstandardized interpretive text has created multiple layers of interpretive ambiguity. OBJECTIVE.­: To use natural language processing (NLP) to automate and expedite translation of interpretive text to a single most severe, and thus actionable, cervical intraepithelial neoplasia (CIN) diagnosis. DESIGN.­: We developed and applied NLP algorithms to 35 847 unstructured cervical pathology reports and assessed NLP performance in identifying the most severe diagnosis, compared to expert manual review. NLP performance was determined by calculating precision, recall, and F score. RESULTS.­: The NLP algorithms yielded a precision of 0.957, a recall of 0.925, and an F score of 0.94. Additionally, we estimated that the time to evaluate each monthly biopsy file was significantly reduced, from 30 hours to 0.5 hours. CONCLUSIONS.­: A set of validated NLP algorithms applied to pathology reports can rapidly and efficiently assign a discrete, actionable diagnosis using CIN classification to assist with clinical management of cervical pathology and disease. Moreover, discrete diagnostic data encoded as CIN terminology can enhance the efficiency of clinical research.

Serum Fibrosis Marker Panels FIB-4 Index and Aspartate Aminotransferase (AST)-to-Platelet Ratio Index (APRI) Are Equivalent to AST Alone at Predicting Liver Fibrosis in a Cohort of 1731 Patients Infected with Hepatitis C Virus.

BACKGROUND: Efficient tools are needed to stage liver disease before treatment of patients infected with hepatitis C virus (HCV). Compared to biopsy, several studies demonstrated favorable performance of noninvasive multianalyte serum fibrosis marker panels [fibrosis-4 (FIB-4) index] and aspartate aminotransferase (AST)-to-platelet ratio index (APRI), but suggested cutoffs vary widely. Our objective was to evaluate FIB-4 index and APRI and their component tests for staging fibrosis in our HCV-infected population and to determine practical cutoffs to help triage an influx of patients requiring treatment. METHODS: Transient elastography (TE) results from 1731 HCV-infected patients were mapped to an F0-F4 equivalent scale. Each patient's APRI and FIB-4 index were calculated. Areas under the receiver operator curve (AUROCs) and false-positive and false-negative rates were calculated to retrospectively compare the performance of the indices and their component tests. RESULTS: The highest AUROCs for distinguishing severe (F3-F4) from mild-to-moderate (F0-F2) fibrosis had overlapping 95% CIs: APRI (0.77; 0.74-0.79), FIB-4 index (0.76; 0.73-0.78), and AST (0.74; 0.72-0.77). Cutoffs had false-negative rates of 2.7%-2.8% and false-positive rates of 6.4%-7.4% for all 3 markers. CONCLUSIONS: AST was as effective as FIB-4 index and APRI at predicting fibrosis. Published cutoffs for APRI and FIB-4 index would have been inappropriate in our population, with false-negative rates as high as 11%. For our purposes, no serum fibrosis marker was sufficiently sensitive to rule-out significant fibrosis, but cutoffs developed for AST, FIB-4 index, and APRI all had specificities of 79.2%-80.3% for ruling-in severe fibrosis and could be used to triage 1/3 of our population for treatment without waiting for TE or liver biopsy.

Factors influencing women's acceptance of prenatal screening tests.

OBJECTIVE: To determine the factors influencing a woman's acceptance of the expanded alpha-fetoprotein (AFP) test. METHODS: A population-based case-control study. All women (age < 35) who declined the expanded AFP test were identified as eligible cases. Controls were randomly selected from all women (age < 35) who accepted the test. RESULTS: We interviewed 199 cases and 229 controls before 30 weeks of gestation. While 47% of cases reported opposition to abortion as one of their reasons for declining the test (Group A), the remaining 53% of cases had a variety of other reasons for declining (Group B). After controlling for potential confounders, factors significantly associated with declining the test included: skepticism of the usefulness of the test results (odds ratio (OR) = 33.0), influence from family members (OR = 11.4), low educational level (OR = 7.1), willingness to keep a malformed fetus (OR = 6.2), failure to use providers as useful sources of information (OR = 5.0), and misunderstanding of the purpose of the test (OR = 2.0). Polytomous logistic regression revealed that Groups A and B had different determining factors as well as common factors. CONCLUSION: While many influential factors for participating in prenatal screening remain unmodifiable, some of them may be addressed to improve women's acceptance of prenatal screening tests.