An Updated “Call Database” to Support Lab Consultation and Quality Improvement Projects

Abstract

Abstract Clinical laboratories may have “on-call” residents and fellows, a practice that assists the laboratory in providing quality support to clinicians and provides valuable clinical experience to trainees. A Call Database may be used as a tool to facilitate call handoffs, as an educational resource and knowledge base for trainees, and as a call logging and review tool as required by the Accreditation Council for Graduate Medical Education (ACGME). The Call Database at our institution currently contains over 51,000 entries and is used by all clinical pathology residents and fellows while “on call.” Prior versions of our Call Database (first developed in 2004 and updated in 2014) were self-hosted applications with limited feature sets that were difficult to support; moreover, they provided few guarantees around electronic protected health information (ePHI), a topic of increasing concern as HIPAA compliance among clinical laboratories is increasingly audited. A review of the current application also identified that it has limited usefulness in supporting faculty review of calls, does not easily allow structured data entry for quality improvement projects, and lacks features commonly seen in modern web applications (eg, rich text editing and file attachments). Here we describe the latest update to our existing Call Database addressing these feature limitations. In addition, we discuss our approach to using a modern cloud-based infrastructure design that address prior shortcomings in data security, user management, and ease of development. The updated Call Database is a single-page web application, compatible with a wide range of local and cloud environments. We updated the user interface with features such as auto-saving of entries, rich text entry, file attachments, and topic tagging. Several new features facilitate the faculty review process: (1) a dedicated “review mode” for rapid viewing and commenting of relevant calls, (2) automated weekly emails by topic sent to faculty, and (3) a user “mention” feature so that trainees can solicit the opinion of faculty in the text of a call or comment itself. Finally, we provide support for customizing the structured data fields of call entries, which enables support of quality improvement and monitoring projects via the call database (eg, a customized entry for monitoring use of specific send-out tests, massive transfusion reactions, etc.). Our application delivers a modern, performant, and easy to use call database for use by trainees and faculty alike. We utilize the Amazon Cloud (AWS) to host the application and have developed a specific set of compliance and risk review documents to address HIPAA compliance. Future work will incorporate user feedback and will focus on supporting the implementation of our application at other sites or clinical pathology residency programs.