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Indonesian College Students Create App for Kidney Failure Patients

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Patients with Chronic Kidney Failure who use the Continuous Ambulatory Peritoneal Dialysis (CAPD) method often have problems with self-monitoring which can lead to complications. To overcome this problem, students of the Institut Teknologi Sepuluh Nopember (ITS) created the SahabatCAPD  (CAPD’S friends) application with machine learning technology, to help patients detect early risk of complications and improve patient self-monitoring.

The Indonesian government has determined a solution for equitable treatment of end-stage patients, namely through Peritoneal Dialysis therapy, especially the CAPD method. The CAPD method is an alternative because patients can have a 90% better quality of life than other therapeutic methods.

Research in 2016 and 2020 showed the patient neglect rate was 74%. In addition, the patient admitted that it was difficult to recognise the symptoms of complications that resulted in delays in treatment. Patients also do not follow up fluid replacement data, so medical personnel find it difficult to diagnose complications early. Therefore the students propose the research title called Mobile Virtual Assistant Early Detection of Complication Risk of Continuous Ambulatory Peritoneal Dialysis in People with Chronic Kidney Failure Based on Machine Learning, which we also refer to as SahabatCAPD.

The SahabatCAPD app has three main functionality concepts. First, a logbook as a substitute for a dialysis logbook for patients is more effective and systematic in providing follow-up data to medical personnel. Second, a chatbot as a virtual assistant system when patients need education about CAPD. Third, is the machine learning-based complication early detection model.

The app allows patients to connect with medical personnel, so that follow-up fluid replacement data will be easier to monitor. This is intended to make it easier for medical personnel to prevent complications as early as possible. At first, the patient had to bring a notebook to the hospital, now monitoring can be reviewed directly from afar.

In terms of the accuracy of the suitability of the image processing solution for indications and complications, the model has an accuracy of 94.7%. In addition, the app has also been tested on five patients according to the System Usability Scale (SUS) standard and got a score of 80. During the seven days of using the application, patients routinely update fluid replacement data smoothly.

The team also tested the application based on one of the existing medical standards, namely the laboratory test of the Leukocyte Cells Count Value. The comparison between the diagnosis of application results and lab tests has a good match. This app has the potential for copyright and development, which is integrated with the hospital website as a form of the real-time monitoring system.

In the future, the team hopes that the app can be a solution to the problems experienced by patients and medical personnel. They also hope that the potential for developing applications through the website as a real-time monitoring system can be realised soon.

OpenGov Asia reported, for its second phase, the Indonesian government is collaborating with local tech companies to accelerate the process. The country’s health ministry announced a new partnership with an online health-tech platform and a ride-hailing unicorn. The health-tech service provider assists with the registration, scheduling of appointments, and setup of the drive-through centres. While the ride-hailing company supports the transport of those unable or unwilling to use their vehicles. Users can register online to access apps related to the service.

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