Authors (including presenting author) :
LAN D, CHAN EYL, YIP KL
Affiliation :
Podiatry Department, Hong Kong East Cluster
Keyword 1: :
Multidisciplinary Communication
Keyword 2: :
Automated Letter Generation
Introduction :
Efficient communication among multidisciplinary teams is crucial for optimal patient management. Existing handwritten referrals may have disadvantages; time consuming or incomplete notes can lead to critical information being missed. Misunderstandings among healthcare providers may occur and this can potentially impact patient outcomes. In view of this, our department implemented a digital referral letter generator to streamline correspondence while prioritizing patient privacy. We carefully addressed concerns about potential violations of patient data privacy to ensure all communications remain confidential and secure.
Objectives :
Our primary aim was to enhance communication efficiency without compromising patient data confidentiality. This solution addresses the diverse needs of our patient population while leveraging readily available digital tools, requiring no additional resources. By focusing on patient privacy, we sought to ensure compliance with healthcare data protection standards.
Methodology :
We developed an intuitive digital form that captures essential information, including patient medical history, major complaints, assessment findings, and treatment summaries. Customization is vital, as departmental templates can be too general and may not adequately address the specific needs of our diverse patient population. Users need to enter only the patient’s surname and select applicable statements, intentionally avoiding personal sensitive identifiers like full names, ID numbers, HN numbers. The data is securely recorded and transformed into a professional referral letter using automation tools. The finalized letter is emailed to clinicians for minor edits, ensuring patient identity is discreetly and only revealed on gum label affixed later.
Result & Outcome :
Drafting a referral letter previously took 12-20 minutes, especially for new podiatrists. With our system, this time has been cut down to just 3-5 minutes, significantly increasing efficiency in our busy outpatient clinic. Feedback from podiatrists has been overwhelmingly positive; they report a smoother workflow, reduced stress, and greater satisfaction in patient care. By accommodating diverse patient needs through tailored statements, we ensure all patients receive appropriate care while reinforcing our commitment to privacy and inclusivity. As AI functionalities for writing referral letters are currently unavailable to podiatrists in our CMS, our digital solution serves as an innovative, resource-efficient alternative. This project demonstrates that it is possible to enhance communication while maintaining rigorous privacy standards. We hope to inspire other clinics to adopt similar strategies for improving efficiency and ensuring data protection, ultimately leading to better healthcare outcomes.
