1Massachusetts Institute of Technology (M.I.T.), Cambridge, MA 02139, USA. rclacson@mit.edu
This study aimed to understand how home hemodialysis patients communicate with dialysis clinics. By recording and analyzing patient calls, researchers found that scheduling concerns were a major issue. To address this, they developed an automated system called SCHEDULER, which allows patients to schedule appointments over the phone. The system was built using a tool called SPEECHBUILDER from MIT. The study describes the system's design, architecture, and a preliminary evaluation. The findings suggest that automated systems may help reduce the workload on clinic staff by handling routine scheduling calls.
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Area of Science:
Background:
Prior research has shown that patient communication is a key factor in healthcare delivery. It was already known that home hemodialysis patients frequently contact clinics for various reasons. No prior work had resolved the specific frequency of scheduling-related calls. That uncertainty drove the need to analyze real patient interactions. This gap motivated the collection of recorded calls over three months. The goal was to identify common patient concerns. Scheduling concerns emerged as a primary issue. This finding suggested a need for improved systems to manage patient requests.
Purpose Of The Study:
The aim was to investigate how scheduling concerns affect patient communication in home hemodialysis. The specific problem was the high frequency of scheduling-related calls to clinics. These calls place a burden on clinic staff. The motivation was to reduce the time demands on personnel. Automated systems may offer a solution by handling routine requests. This study sought to design a system to address scheduling concerns. The focus was on developing a mixed-initiative spoken dialogue system. The system was intended to allow patients to schedule appointments over the phone.
The most frequent reason was scheduling concerns, as identified from recorded calls over a three-month period.
The SCHEDULER, a mixed-initiative spoken dialogue system, was designed to allow patients to schedule appointments over the telephone.
SPEECHBUILDER was used because it automates the configuration of human language technology servers, enabling the creation of conversational systems.
A mixed-initiative system allows both the user and the system to take initiative in the conversation, enhancing interaction flexibility.
Main Methods:
The study involved recording actual calls made by home hemodialysis patients to a dialysis clinic. The recordings were analyzed to identify frequent patient concerns. Scheduling concerns were found to be a primary issue. A mixed-initiative spoken dialogue system was developed to address this. The system was named SCHEDULER and designed for telephone use. The system was implemented using SPEECHBUILDER, a tool from MIT. SPEECHBUILDER automates the configuration of human language technology servers. The system architecture, design considerations, and preliminary evaluation were described.
Main Results:
The most frequent reason for patient calls was scheduling concerns. An automated system was developed to handle these calls. The system was implemented using SPEECHBUILDER from MIT. The system allows patients to schedule appointments over the telephone. A mixed-initiative dialogue approach was used in the design. The system architecture was described in detail. General design considerations were outlined. A preliminary evaluation of the system was conducted.
Conclusions:
The authors propose that automated systems may reduce the burden on clinic staff by handling scheduling calls. The system described may provide a solution to frequent scheduling concerns. The use of SPEECHBUILDER enabled the development of a conversational system. The system allows patients to schedule appointments via telephone. The mixed-initiative approach was used to enhance user interaction. The preliminary evaluation suggests potential for system improvement. The study suggests that automated systems may improve patient communication. The findings may inform future system design in dialysis clinics.
The preliminary evaluation described the system architecture and design considerations but did not provide final performance metrics.
The system may reduce the time demands on clinic staff by handling scheduling calls automatically.