Abstract
Abstract Introduction Lower Urinary Symptom (LUTS) are very common among adult men, but they rarely seek medical help, and these issues are not prioritized in healthcare, leading to long wait times to visit a doctor. The potential of AI as an aid has received considerable attention, and a number of apps have started being used in the interaction between patients and healthcare providers. For women with urinary incontinence, there is now an AI applications (APP) reported to give good results. However, for men, there is no available app. Our hypothesis in this study is that AI algorithms applied to self-generated data can provide recommendations that men can follow during the often long wait for a doctor’s visit. We believe that the APP can be used as a complement to a medical examination and thus serve as decision support for healthcare providers in primary care. Objective The purpose of our project is to investigate whether it is possible to partially replace a visit to the health center for men with LUTS by the help of digital medical history and AI-generated individualized recommendations. Furthermore, the collected data can serve as decision support for healthcare providers in outpatient care. Methods Our project is divided into four phases: Phase 1: A retrospective database was established based on data collected during routine doctor’s visits. From this, an algorithm is developed using AI. Phase 2: A prospective database is established with data on patients managed in primary care. The aim is to validate the previously developed algorithm. When patients visit a doctor, they are asked if they want to participate in a study where their information is anonymized and used in the database. Phase 3: The goal is to investigate whether the mobile application can be useful during a doctor’s visit. Phase 4: The value of the app will be evaluated in a randomized study. Results Phase 1: An app with questions that mimic a standardized medical interview has been developed. Phase 2: 150 men over 50 years old with urinary problems will be recommended to fill out the IPSS (symptom questionnaire), a fluid diary and perform urine flow measurements at home. We now have results from the first evaluable 50 patients. It seems relatively few receive treatment at the first visit. Less than half received the same treatment recommendation at the first visit that the AI algorithm would have suggested. Phase 3 and Phase 4: on going. Conclusions As far as we know, this study will be the first to evaluate the possibilities of improving the health of adult men using digital medical history and AI-based advice. In addition to better quality of life, it can also lead to reduced strain on healthcare by saving medical visits and improving the management of such visits through pre-answered questionnaires. Disclosure No.
Published Version
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