Association of Second-Opinion Strategies in the Histopathologic Diagnosis of Cutaneous Melanocytic Lesions With Diagnostic Accuracy and Population-Level Costs.

IMPORTANCE: Diagnostic variation among pathologists interpreting cutaneous melanocytic lesions could lead to suboptimal care. OBJECTIVE: To estimate the potential association of second-opinion strategies in the histopathologic diagnosis of cutaneous melanocytic lesions with diagnostic accuracy and 1-year population-level costs in the US. DESIGN, SETTING, AND PARTICIPANTS: Decision analysis with 1-year time horizon including melanocytic lesion diagnoses available from US pathologists participating in the Melanoma Pathology Study (M-Path) and from the study panel of reference pathologists who classified cases using the MPATH-Dx classification tool. M-Path data collection occurred from July 2013 through March 2015; analyses for the present study were performed between April 2015 and January 2021. EXPOSURES: Various second-opinion strategies for interpretation of melanocytic cutaneous lesions. MAIN OUTCOMES AND MEASURES: Estimated accuracy of pathologists' diagnoses, defined as concordance with the reference panel diagnoses, and 1-year postbiopsy medical costs under various second-opinion strategies. Expected percentage of concordant diagnoses, including percentages of overinterpretation and underinterpretation, and 1-year costs of medical care per 100 000 in the US population. RESULTS: Decision-analytic model parameters were based on diagnostic interpretations for 240 cases by 187 pathologists compared with reference panel diagnoses. Without second opinions, 83.2% of diagnoses in the US were estimated to be accurate-ie, concordant with the reference diagnosis; with overinterpretation (8.0%) or underinterpretation (8.8%), and 16 850 misclassified diagnoses per 100 000 biopsies. Accuracy increased under all second-opinion strategies. Accuracy (87.4% concordance with 3.6% overinterpretation and 9.1% underinterpretation) and cost (an increase of more than $10 million per 100 000 biopsies per year) were highest when second opinions were universal (eg, performed on all biopsies), relative to no second opinions. A selective second-opinion strategy based on pathologists' desire or institutional requirements for a second opinion was most accurate (86.5% concordance; 4.4% overinterpretation; 9.1% underinterpretation) and would reduce costs by more than $1.9 million per 100 000 skin biopsies relative to no second opinions. Improvements in diagnostic accuracy with all second-opinion strategies were associated with reductions in overinterpretation but not underinterpretation. CONCLUSIONS AND RELEVANCE: In this decision-analytic model, selective second-opinion strategies for interpretation of melanocytic skin lesions showed the potential to improve diagnostic accuracy and decrease costs relative to no second opinions or universal second opinions.

Leveraging Linkage of Cohort Studies With Administrative Claims Data to Identify Individuals With Cancer.

BACKGROUND: In an effort to overcome quality and cost constraints inherent in population-based research, diverse data sources are increasingly being combined. In this paper, we describe the performance of a Medicare claims-based incident cancer identification algorithm in comparison with observational cohort data from the Nurses' Health Study (NHS). METHODS: NHS-Medicare linked participants' claims data were analyzed using 4 versions of a cancer identification algorithm across 3 cancer sites (breast, colorectal, and lung). The algorithms evaluated included an update of the original Setoguchi algorithm, and 3 other versions that differed in the data used for prevalent cancer exclusions. RESULTS: The algorithm that yielded the highest positive predictive value (PPV) (0.52-0.82) and κ statistic (0.62-0.87) in identifying incident cancer cases utilized both Medicare claims and observational cohort data (NHS) to remove prevalent cases. The algorithm that only used NHS data to inform the removal of prevalent cancer cases performed nearly equivalently in statistical performance (PPV, 0.50-0.79; κ, 0.61-0.85), whereas the version that used only claims to inform the removal of prevalent cancer cases performed substantially worse (PPV, 0.42-0.60; κ, 0.54-0.70), in comparison with the dual data source-informed algorithm. CONCLUSIONS: Our findings suggest claims-based algorithms identify incident cancer with variable reliability when measured against an observational cohort study reference standard. Self-reported baseline information available in cohort studies is more effective in removing prevalent cancer cases than are claims data algorithms. Use of claims-based algorithms should be tailored to the research question at hand and the nature of available observational cohort data.

The 5 T's: Applying Cognitive Science to Improve Prehospital Medical Education.

Although research on effective teaching methods exists, the application of this information in prehospital medical education is limited. Applying lessons from the realms of cognitive psychology and neuroscience, prehospital educators can enhance their ability to teach. One such concept is the theory of cognitive load. Understanding this theory can reduce the mental strain placed on learners and allow educators to best accomplish long-term learning success, defined as "far transfer" of material to novel contexts. Thus, we propose 5 concise strategies gleaned from cognitive science literature: Tell a story, Time, Technical elements, Think novelly, and Testing and recall (referred to as the "5 T's"). Each strategy is grounded in research and applicable to medical education. Increased educator awareness and use of these strategies garners the potential to transform prehospital medical education.

Variation in Screening Abnormality Rates and Follow-Up of Breast, Cervical and Colorectal Cancer Screening within the PROSPR Consortium.

BACKGROUND: Primary care providers and health systems have prominent roles in guiding effective cancer screening. OBJECTIVE: To characterize variation in screening abnormality rates and timely initial follow-up for common cancer screening tests. DESIGN: Population-based cohort undergoing screening in 2011, 2012, or 2013 at seven research centers comprising the National Cancer Institute-sponsored Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium. PARTICIPANTS: Adults undergoing mammography with or without digital breast tomosynthesis (n = 97,683 ages 40-75 years), fecal occult blood or fecal immunochemical tests (n = 759,553 ages 50-75 years), or Papanicolaou with or without human papillomavirus tests (n = 167,330 ages 21-65 years). INTERVENTION: Breast, colorectal, or cervical cancer screening. MAIN MEASURES: Abnormality rates per 1000 screens; percentage with timely initial follow-up (within 90 days, except 9-month window for BI-RADS 3). Primary care clinic-level variation in percentage with screening abnormality and percentage with timely initial follow-up. KEY RESULTS: There were 10,248/97,683 (104.9 per 1000) abnormal breast cancer screens, 35,847/759,553 (47.2 per 1000) FOBT/FIT-positive colorectal cancer screens, and 13,266/167,330 (79.3 per 1000) abnormal cervical cancer screens. The percentage with timely follow-up was 93.2 to 96.7 % for breast centers, 46.8 to 68.7  % for colorectal centers, and 46.6 % for the cervical cancer screening center (low-grade squamous intraepithelial lesions or higher). The primary care clinic variation (25th to 75th percentile) was smaller for the percentage with an abnormal screen (breast, 8.5-10.3 %; colorectal, 3.0-4.8 %; cervical, 6.3-9.9 %) than for the percentage with follow-up within 90 days (breast, 90.2-95.8 %; colorectal, 43.4-52.0 %; cervical, 29.6-61.4 %). CONCLUSIONS: Variation in both the rate of screening abnormalities and their initial follow-up was evident across organ sites and primary care clinics. This highlights an opportunity for improving the delivery of cancer screening through focused study of patient, provider, clinic, and health system characteristics associated with timely follow-up of screening abnormalities.