Validation of the Dermatologic Complexity Score for Dermatologic Triage

<b>Background/Objectives:</b> Demand for dermatologic services exceeds specialist capacity, with average wait times of 26-50 days in the United States. Current triage methods rely on subjective judgment or disease-specific indices that do not generalize across diagnoses or translate to operational decisions. We developed and validated the Dermatologic Complexity Score (DCS), a standardized instrument to guide case prioritization across dermatology care settings and evaluate DCS as a workload-reduction filter, enabling safe delegation of approximately half of routine teledermatology cases (DCS ≤ 40) away from specialist review. <b>Methods:</b> We conducted a prospective validation study of the DCS using 100 consecutive teledermatology cases spanning 30 common conditions. The DCS decomposes complexity into five domains (Diagnostic, Treatment, Risk, Patient Complexity, Monitoring) summed to a 0-100 total with prespecified bands: ≤40 (low) (41-70), (moderate) (71-89), (high), ≥90 (extreme). Five board-certified dermatologists and an automated module independently scored all cases. Two primary care physicians completed all ≤40 cases to assess feasibility. Primary outcomes were interrater reliability using ICC (2,1) and agreement with automation. Secondary outcomes included time-to-decision, referral rates, and primary care feasibility. <b>Results:</b> Mean patient age was 46.2 years; 47% of cases scored ≤40, 33% scored 41-70, 18% scored 71-89, and 2% scored ≥90. Interrater reliability was excellent (ICC (1,2)) = 0.979; 95% CI 0.974-0.983), with near-perfect agreement between automated and mean dermatologist scores (r = 0.998). Time-to-decision increased monotonically across DCS bands from 2.11 min (≤40) to 5 (90) min (≥90) (p = 1.36 × 10<sup>-14</sup>). Referral rates were 0% for ≤40, 3% for 41-70, 27.8% for 71-89, and 100% for ≥90 cases. DCS strongly predicted referral decisions (AUC = 0.919). Primary care physicians successfully managed all ≤40 cases but required 6-8 additional minutes per case compared to dermatologists. <b>Conclusions:</b> The DCS demonstrates excellent reliability and strong construct validity, mapping systematically to clinically relevant outcomes, including decision time and referral patterns. The instrument enables standardized, reproducible triage decisions that can optimize resource allocation across teledermatology, clinic, procedural, and inpatient settings. Implementation could improve access to dermatologic care by supporting appropriate delegation of low-complexity cases to primary care while ensuring timely specialist evaluation for high-complexity conditions.

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Journal
Diagnostics
Published
2025-10-31
DOI
https://doi.org/10.3390/diagnostics15212765
Primary Topic
Cutaneous Melanoma Detection and Management
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article
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article

Validation of the Dermatologic Complexity Score for Dermatologic Triage

Neil Jairath, Joshua Mijares, John F. Quinn, Melissa Laughter et al.
Diagnostics
Cutaneous Melanoma Detection and Management
article

Validation of the Dermatologic Complexity Score for Dermatologic Triage

Neil Jairath, Joshua Mijares, John F. Quinn, Melissa Laughter, Sultan H. Qiblawi, George M. Jeha, Katie Beier, Vartan Pahalyants, Vignesh Ramachandran, Andjela Nemcevic, Kanika Garg, Swetha Maddipuddi
article en

Abstract

<b>Background/Objectives:</b> Demand for dermatologic services exceeds specialist capacity, with average wait times of 26-50 days in the United States. Current triage methods rely on subjective judgment or disease-specific indices that do not generalize across diagnoses or translate to operational decisions. We developed and validated the Dermatologic Complexity Score (DCS), a standardized instrument to guide case prioritization across dermatology care settings and evaluate DCS as a workload-reduction filter, enabling safe delegation of approximately half of routine teledermatology cases (DCS ≤ 40) away from specialist review. <b>Methods:</b> We conducted a prospective validation study of the DCS using 100 consecutive teledermatology cases spanning 30 common conditions. The DCS decomposes complexity into five domains (Diagnostic, Treatment, Risk, Patient Complexity, Monitoring) summed to a 0-100 total with prespecified bands: ≤40 (low) (41-70), (moderate) (71-89), (high), ≥90 (extreme). Five board-certified dermatologists and an automated module independently scored all cases. Two primary care physicians completed all ≤40 cases to assess feasibility. Primary outcomes were interrater reliability using ICC (2,1) and agreement with automation. Secondary outcomes included time-to-decision, referral rates, and primary care feasibility. <b>Results:</b> Mean patient age was 46.2 years; 47% of cases scored ≤40, 33% scored 41-70, 18% scored 71-89, and 2% scored ≥90. Interrater reliability was excellent (ICC (1,2)) = 0.979; 95% CI 0.974-0.983), with near-perfect agreement between automated and mean dermatologist scores (r = 0.998). Time-to-decision increased monotonically across DCS bands from 2.11 min (≤40) to 5 (90) min (≥90) (p = 1.36 × 10<sup>-14</sup>). Referral rates were 0% for ≤40, 3% for 41-70, 27.8% for 71-89, and 100% for ≥90 cases. DCS strongly predicted referral decisions (AUC = 0.919). Primary care physicians successfully managed all ≤40 cases but required 6-8 additional minutes per case compared to dermatologists. <b>Conclusions:</b> The DCS demonstrates excellent reliability and strong construct validity, mapping systematically to clinically relevant outcomes, including decision time and referral patterns. The instrument enables standardized, reproducible triage decisions that can optimize resource allocation across teledermatology, clinic, procedural, and inpatient settings. Implementation could improve access to dermatologic care by supporting appropriate delegation of low-complexity cases to primary care while ensuring timely specialist evaluation for high-complexity conditions.

DiagnosticsVol. 15(21)
Philadelphia College of Osteopathic Medicine (US), Mount Sinai Hospital (US), Mount Sinai Medical Center (US), Mount Sinai Hospital (US), St. Mary Mercy Livonia (US), Epiphany Biosciences (United States) (US), Laser and Skin Surgery Center of New York (US), Indiana University – Purdue University Indianapolis (US), New York University (US), University of Toledo (US), Icahn School of Medicine at Mount Sinai (US)
Openalex Percentile: Top 57%
Cutaneous Melanoma Detection and Management
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