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Remote digital pathology allows healthcare systems to maintain pathology operations during public health emergencies. Existing Clinical Laboratory Improvement Amendments regulations require pathologists to electronically verify patient reports from a certified facility. During the 2019 pandemic of COVID-19 disease, caused by the SAR-CoV-2 virus, this requirement potentially exposes pathologists, their colleagues, and household members to the risk of becoming infected. Relaxation of government enforcement of this regulation allows pathologists to review and report pathology specimens from a remote, non-CLIA certified facility. The availability of digital pathology systems can facilitate remote microscopic diagnosis, although formal comprehensive (case-based) validation of remote digital diagnosis has not been reported. All glass slides representing routine clinical signout workload in surgical pathology subspecialties at Memorial Sloan Kettering Cancer Center were scanned on an Aperio GT450 at ×40 equivalent resolution (0.26 µm/pixel). Twelve pathologists from nine surgical pathology subspecialties remotely reviewed and reported complete pathology cases using a digital pathology system from a non-CLIA certified facility through a secure connection. Whole slide images were integrated to and launched within the laboratory information system to a custom vendor-agnostic, whole slide image viewer. Remote signouts utilized consumer-grade computers and monitors (monitor size, 13.3-42 in.; resolution, 1280 × 800-3840 × 2160 pixels) connecting to an institution clinical workstation via secure virtual private network. Pathologists subsequently reviewed all corresponding glass slides using a light microscope within the CLIA-certified department. Intraobserver concordance metrics included reporting elements of top-line diagnosis, margin status, lymphovascular and/or perineural invasion, pathology stage, and ancillary testing. The median whole slide image file size was 1.3 GB; scan time/slide averaged 90 s; and scanned tissue area averaged 612 mm 2. Signout sessions included a total of 108 cases, comprised of 254 individual parts and 1196 slides. Major diagnostic equivalency was 100% between digital and glass slide diagnoses; and overall concordance was 98.8% (251/254). This study reports validation of primary diagnostic review and reporting of complete pathology cases from a remote site during a public health emergency. Our experience shows high (100%) intraobserver digital to glass slide major diagnostic concordance when reporting from a remote site. This randomized, prospective study successfully validated remote use of a digital pathology system including operational feasibility supporting remote review and reporting of pathology specimens, and evaluation of remote access performance and usability for remote signout.

Context.-Digital pathology (DP) implementations vary in scale, based on aims of intended operation. Few laboratories have completed a full-scale DP implementation, which may be due to high overhead costs that disrupt the traditional pathology workflow. Neither standardized criteria nor benchmark data have yet been published showing practical return on investment after implementing a DP platform.Objective.-To provide benchmark data and practical metrics to support operational efficiency and cost savings in a large academic center.Design.-Metrics reviewed include archived pathology asset retrieval; ancillary test request for recurrent/metastatic disease; cost analysis and turnaround time (TAT); and DP experience survey.Results.-Glass slide requests from the department slide archive and an off-site surgery center showed a 93% and 97% decrease, respectively. Ancillary immunohistochemical orders, compared in 2014 (52%)-before whole slide images (WSIs) were available in the laboratory information system-and 2017 (21%) showed $114 000/y in anticipated savings. Comprehensive comparative cost analysis showed a 5-year $1.3 million savings. Surgical resection cases with prior WSIs showed a 1-day decrease in TAT. A DP experience survey showed 80% of respondents agreed WSIs improved their clinical sign-out experience.Conclusions.-Implementing a DP operation showed a noteworthy increase in efficiency and operational utility. Digital pathology deployments and operations may be gauged by the following metrics: number of glass slide requests as WSIs become available, decrease in confirmatory testing for patients with metastatic/recurrent disease, long-term decrease in off-site pathology asset costs, and faster TAT. Other departments may use our benchmark data and metrics to enhance patient care and demonstrate return on investment to justify adoption of DP.

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Objective Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes. Materials and Methods We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent. Results The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence–driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases. Conclusions We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.