Intra- and post-pandemic impact of the COVID-19 outbreak on Stanford Health Care.

Stanford Health Care, which provides about 7% of overall healthcare to approximately 9 million people in the San Francisco Bay Area, has undergone significant changes due to the opening of a second hospital in late 2019 and, more importantly, the COVID-19 pandemic. We examine the impact of these events on anatomic pathology (AP) cases, aiming to enhance operational efficiency in response to evolving healthcare demands. We extracted historical census, admission, lab tests, operation, and AP data since 2015. An approximately 45% increase in the volume of laboratory tests (P < 0.0001) and a 17% increase in AP cases (P < 0.0001) occurred post-pandemic. These increases were associated with progressively increasing (P < 0.0001) hospital census. Census increase stemmed from higher admission through the emergency department (ED), and longer lengths of stay mostly for transfer patients, likely due to the greater capability of the new ED and changes in regional and local practice patterns post-pandemic. Higher census led to overcapacity, which has an inverted U relationship that peaked at 103% capacity for AP cases and 114% capacity for laboratory tests. Overcapacity led to a lower capability to perform clinical activities, particularly those related to surgical procedures. We conclude by suggesting parameters for optimal operations in the post-pandemic era.

Rapid Deployment of Whole Slide Imaging for Primary Diagnosis in Surgical Pathology at Stanford Medicine: Responding to Challenges of the COVID-19 Pandemic.

CONTEXT.­: Stanford Pathology began stepwise subspecialty implementation of whole slide imaging (WSI) in 2018 soon after the first US Food and Drug Administration approval. In 2020, during the COVID-19 pandemic, the Centers for Medicare & Medicaid Services waived the requirement for pathologists to perform diagnostic tests in Clinical Laboratory Improvement Amendments (CLIA)-licensed facilities. This encouraged rapid implementation of WSI across all surgical pathology subspecialties. OBJECTIVE.­: To present our experience with validation and implementation of WSI at a large academic medical center encompassing a caseload of more than 50 000 cases per year. DESIGN.­: Validation was performed independently for 3 subspecialty services with a diagnostic concordance threshold above 95%. Analysis of user experience, staffing, infrastructure, and information technology was performed after department-wide expansion. RESULTS.­: Diagnostic concordance was achieved in 96% of neuropathology cases, 100% of gynecologic pathology cases, and 98% of immunohistochemistry cases. After full implementation, 8 high-capacity scanners were operational, with whole slide images generated on greater than 2000 slides per weekday, accounting for approximately 80% of histologic slides at Stanford Medicine. Multiple modifications in workflow and information technology were needed to improve performance. Within months of full implementation, most attending pathologists and trainees had adopted WSI for primary diagnosis. CONCLUSIONS.­: WSI across all surgical subspecialities is achievable at scale at an academic medical center; however, adoption required flexibility to adjust workflows and develop tailored solutions. WSI at scale supported the health and safety of medical staff while facilitating high-quality patient care and education during COVID-19 restrictions.

Implementation of Epic Beaker Clinical Pathology at Stanford University Medical Center.

OBJECTIVES: To provide an account of implementation of the Epic Beaker 2014 clinical pathology module at Stanford University Medical Center and highlight strengths and weaknesses of the system. METHODS: Based on a formal selection process, Stanford selected Epic Beaker to replace Sunquest as the clinical laboratory information system (LIS). The rationale included integration between the LIS and already installed Epic electronic medical record (EMR), reduction in the number of systems and interfaces, and positive patient identification (PPID). The build was significantly customized and included a first of its kind Epic-to-Epic interface. This was due to the clinical laboratory serving two hospitals (pediatric and adult) with independent instances of Epic. RESULTS: Test turnaround times showed improvement from historical baselines, mostly because of the implementation of PPID. PPID also resulted in significant reduction in mislabeled specimens. CONCLUSIONS: Epic 2014 Beaker clinical pathology is a viable LIS with adequate functionality for a large academic center. Strengths include PPID and integration with the EMR. Integration provides laboratory users with ready access to the patient's relevant clinical history to assist releasing of results and gives physician and nurse providers sophisticated add-on ordering and specimen collection workflows. Areas that could use further development include specimen aliquoting, quality control reporting, and maintenance tools.