Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center.

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.

A risk-based framework for biomedical data sharing.

The problem of biomedical data sharing is a form of gambling; on one hand it incurs the risk of privacy violations and on the other it stands to profit from knowledge discovery. In general, the risk of granting data access to a user depends heavily upon the data requested, the purpose for the access, the user requesting the data (user motives) and the security of the user's environment. While traditional manual biomedical data sharing processes (based on institutional review boards) are lengthy and demanding, the automated ones (known as honest broker systems) disregard the individualities of different requests and offer "one-size-fits-all" solutions to all data requestors. In this manuscript, we propose a conceptual risk-aware data sharing system; the system brings the concept of risk, from all contextual information surrounding a data request, into the data disclosure decision module. The decision module, in turn, imposes mitigation measures to counter the calculated risk.

Methods to Improve Sustainability of a Large Academic Biorepository.

This article discusses the evolution of the University of Pittsburgh (UPitt) Health Sciences Tissue Bank (HSTB) operation and how it has successfully positioned itself, manages to sustain its value, and remains viable in today's research landscape. We describe the various components of our biobanking operation, which are valued by our researchers, thus leading to sustainability for our biorepository. Operating within the infrastructure of a large academic university, we have access to the most cutting-edge database resources for collecting, tracking, and annotating thousands of specimens. We are constantly improving upon our ability to provide real-time longitudinal follow-up data for our collections, thus providing researchers with valuable, highly annotated research specimens. We believe the combination of all that is described within this article helps to create a biobank that will remain sustainable well into the future.

Delayed Access to Involuntary Mental Health Examinations.

Delayed access to involuntary mental health examination for people who receive care in emergency departments (EDs) was examined, and factors that influenced delayed access were explored. A retrospective review of records for the 12 months prior to data collection was conducted to address the study questions. The health services utilization model served as the conceptual framework for this study. Societal, system, and individual factors were considered in examining access to involuntary emergency mental health examination by adult ED patients. Records of 170 people who sought care in EDs and who required involuntary mental health examinations at two hospitals in Florida served as the sources for study data. The mean duration of delay was 14.9 h. The determinants that were significantly associated with longer delays were being male, increased age, and intoxication. The findings can inform the allocation of resources to increase opportunities for positive long-term outcomes following involuntary care.

The biorepository portal toolkit: an honest brokered, modular service oriented software tool set for biospecimen-driven translational research.

BACKGROUND: High throughput molecular sequencing and increased biospecimen variety have introduced significant informatics challenges for research biorepository infrastructures. We applied a modular system integration approach to develop an operational biorepository management system. This method enables aggregation of the clinical, specimen and genomic data collected for biorepository resources. METHODS: We introduce an electronic Honest Broker (eHB) and Biorepository Portal (BRP) open source project that, in tandem, allow for data integration while protecting patient privacy. This modular approach allows data and specimens to be associated with a biorepository subject at any time point asynchronously. This lowers the bar to develop new research projects based on scientific merit without institutional review for a proposal. RESULTS: By facilitating the automated de-identification of specimen and associated clinical and genomic data we create a future proofed specimen set that can withstand new workflows and be connected to new associated information over time. Thus facilitating collaborative advanced genomic and tissue research. CONCLUSIONS: As of Janurary of 2016 there are 23 unique protocols/patient cohorts being managed in the Biorepository Portal (BRP). There are over 4000 unique subject records in the electronic honest broker (eHB), over 30,000 specimens accessioned and 8 institutions participating in various biobanking activities using this tool kit. We specifically set out to build rich annotation of biospecimens with longitudinal clinical data; BRP/REDCap integration for multi-institutional repositories; EMR integration; further annotated specimens with genomic data specific to a domain; build application hooks for experiments at the specimen level integrated with analytic software; while protecting privacy per the Office of Civil Rights (OCR) and HIPAA.

Establishing the role of honest broker: bridging the gap between protecting personal health data and clinical research efficiency.

Background. The objective of this study is to propose the four conditions for the roles of honest brokers through a review of literature published by ten institutions that are successfully utilizing honest brokers. Furthermore, the study aims to examine whether the Asan Medical Center's (AMC) honest brokers satisfy the four conditions, and examine the need to enhance their roles. Methods. We analyzed the roles, tasks, and types of honest brokers at 10 organizations by reviewing the literature. We also established a Task Force (TF) in our institution for setting the roles and processes of the honest broker system and the honest brokers. The findings of the literature search were compared with the existing systems at AMC-which introduced the honest broker system for the first time in Korea. Results. Only one organization employed an honest broker for validating anonymized clinical data and monitoring the anonymity verifications of the honest broker system. Six organizations complied with HIPAA privacy regulations, while four organizations did not disclose compliance. By comparing functions with those of the AMC, the following four main characteristics of honest brokers were determined: (1) de-identification of clinical data; (2) independence; (3) checking that the data are used only for purposes approved by the IRB; and (4) provision of de-identified data to researchers. These roles were then compared with those of honest brokers at the AMC. Discussion. First, guidelines that regulate the definitions, purposes, roles, and requirements for honest brokers are needed, since there are no currently existing regulations. Second, Korean clinical research institutions and national regulatory departments need to reach a consensus on a Korean version of Limited Data Sets (LDS), since there are no lists that describe the use of personal identification information. Lastly, satisfaction surveys on honest brokers by researchers are necessary to improve the quality of honest brokers.

Using patient lists to add value to integrated data repositories.

Patient lists are project-specific sets of patients that can be queried in integrated data repositories (IDR's). By allowing a set of patients to be an addition to the qualifying conditions of a query, returned results will refer to, and only to, that set of patients. We report a variety of use cases for such lists, including: restricting retrospective chart review to a defined set of patients; following a set of patients for practice management purposes; distributing "honest-brokered" (deidentified) data; adding phenotypes to biosamples; and enhancing the content of study or registry data. Among the capabilities needed to implement patient lists in an IDR are: capture of patient identifiers from a query and feedback of these into the IDR; the existence of a permanent internal identifier in the IDR that is mappable to external identifiers; the ability to add queryable attributes to the IDR; the ability to merge data from multiple queries; and suitable control over user access and de-identification of results. We implemented patient lists in a custom IDR of our own design. We reviewed capabilities of other published IDRs for focusing on sets of patients. The widely used i2b2 IDR platform has various ways to address patient sets, and it could be modified to add the low-overhead version of patient lists that we describe.