Background Referring patients to specialty care is an inefficient and error-prone process. Gaps in the referral process lead to delays in patients’ access to care, negative patient experience, worse health outcomes, and increased operational costs. While implementation of standards-based electronic referral options can alleviate some of these inefficiencies, many referrals to tertiary and quaternary care centers continue to be sent via fax. Objective We describe the design process and architecture for a software application that has been developed and deployed to optimize the referrals intake process by automating the processing and digitization of incoming specialty referral faxes, extracting key data elements and integrating them into the electronic health record (EHR), and organizing referrals. Methods A human-centered design approach was used to identify and describe the inefficiencies in the external referral process at our large, urban tertiary care center. Referrals Automation, an application to convert referral faxes to digital referrals in the EHR, was conceptualized based on key stakeholder interviews and time and motion studies. This application was designed using Substitutable Medical Applications and Reusable Technologies (SMART) and Fast Healthcare Interoperability Resource (FHIR) platforms to allow for adaptability into other healthcare organizations. Results Referrals Automation software was developed as a healthcare information technology solution to streamline the fax to referral process. The application was implemented into several specialty clinics. Metrics were built-in to the applications to evaluate and guide the further iteration of these features. Conclusions Referrals Automation will enhance the referrals process by further streamlining and organizing the patient referral process.

INTRODUCTION AND OBJECTIVE: Referring patients to specialty care is an inefficient and error prone process. Gaps in the referral process lead to longer patient wait times, increased patient anxiety, worse health outcomes, and rising healthcare costs. We developed and implemented referral automation software to improve the efficiency of the referrals process using a combination of novel and off-the-shelf technologies.METHODS: Referrals Automation is an application designed by the Center for Digital Health Innovation at UCSF that automates several manual steps in referral processing. The application automates the receipt and digitization of faxed referrals, parses data elements and creates structured data in the electronic health record (EHR). Referrals are organized into a single window for final human review. The program was first deployed at our institution in July 2018 and expanded to the Urology practice in July 2019. The pre-intervention group data were obtained before April 2019 and the post-intervention group data were obtained from July to October 2019. Data were extracted from the cloud-based Referrals Automation software and from the EHR.RESULTS: Overall, there were 12,630 referrals processed in the pre-launch period (start to end) and 1,505 in the post-launch period. After implementation, patients were called sooner (3.9 days vs. 11.1 days, p< 0.01), appointments were scheduled sooner (6.3 days vs. 12.3 days, p< 0.01), and patients saw the urologist sooner (25.0 days vs. 36.6 days, p< 0.01). After implementing the Referrals Automation application, we observed a 2-5% improvement on our ability to meet the milestones set forth by the organization across all referral process steps.CONCLUSIONS: Automated referral processing software can improve the efficiency of the specialist referral process, leading to quicker appointment scheduling, earlier appointment dates, and improved access to urologic care.