Skip to main content

Table 1 The performance of the demographics-based filter (baseline) and the EHR-based ES algorithms

From: Increasing the efficiency of trial-patient matching: automated clinical trial eligibility Pre-screening for pediatric oncology patients

Trial-centered Patient Cohort Identification
Algorithm Evaluation Metrics
WL 95% CI P[%] Sp[%] PV*      
Demographics-based Filter 163 149-179 1.9 24.3 8.30E-21      
DX/ICD-9 50 35-64 6.20 78.1 5.27E-4      
NOTE 28 16-41 10.7 87.9 7.75E-2      
DX/ICD-9+NOTE 24 14-35 12.6 89.9 N/A      
Patient-centered Trial Recommendation
Algorithm Evaluation Metrics
Sub-population case (127 patients) Full-population case (215 patients)
WL 95% CI P[%] Sp[%] PV* WL 95% CI P[%] Sp[%] PV*
Demographics-based Filter 42 40-43 3.2 25.5 1.7E-143 42 40-43 1.9 24.3 1.5E-39
DX/ICD-9 8 6-10 16.8 87.8 2.36E-7 22 19-25 3.6 60.7 3.85E-7
NOTE 4 3-5 33.1 95.0 2.54E-2 20 17-23 3.9 64.9 2.54E-2
DX/ICD-9+NOTE 3 3-4 35.7 95.5 N/A 19 17-22 4.0 65.5 N/A
  1. DX/ICD9 indicates ES algorithm using only structured diagnoses and ICD-9 codes; NOTE, ES algorithm using only clinical notes; DX/ICD-9+NOTE, ES algorithm using both structured data and clinical notes.
  2. WL indicates workload; CI, confidence interval; P, precision and Sp, specificity, PV, p-value.
  3. *P-values were calculated by comparing the workload between DX/ICD-9+NOTE with the other algorithms.
  4. N/A indicates that the performances between the two algorithms are identical and no p-value is returned.