유지투석 환자를 위한 인공지능 기반 약물처방 알고리즘 개발
Developing an AI-powered Medication Prescription Algorithm for Maintenance Dialysis Patients
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초록
고령화의 진전에 따라 만성신장질환자는 전 세계 인구의 10명중 1명꼴로 계속 증가하고 있다. 우리나라도 전세계 6위의 만성신부전 환자 보유국으로 투석 환자의 증가에 따른 의료 대응체계 선진화가 필요한 시점이다. 그러나, 우리나라의 인구당 의사 수가 경제협력개발기구(OECD) 최하위 수준이고, 투석 전문의가 부족한 상황이라 담당의사는 야근과 격무에 시달리고 있어서 번아웃이 우려된다. 특히, 혈액투석실에서 가장 중요한 진료는 투석환자의 월검사 및 약물 처방인데 KDIGO guideline, K- DOQI guideline 등을 참고하여 수행하고 있지만, 현재까지 합의된 가이드라인 자체가 부족할 뿐 아니라 약처방 및 검사 해석은 담당 주치의마다 다를 수 있고 각 처방의의 선호도나 지식, 신념에 따라처방이 행해지고 있는 실정이다. 본 연구에서는 과거에 처방된 약 18만건의 데이터를 활용하여 인공지능(AI)모델을 개발하고 적용 가능성을 검증하였다. 개발된 AI기반 약물처방 모델은 분류모델의 성능지표 4가지 모두 0.99이상의 성능을 보였으며, 특히 의사의 주관에 따른 처방 편차를 제거함으로써표준화된 약처방 알고리즘으로 활용할 수 있고 약처방에 소요되는 시간 역시 기존의 10%이하로 단축시켜 의사의 번아웃을 예방하는데 많은 기여를 할 것으로 예상된다.
Abstract
As the global population ages, the incidence of chronic kidney disease (CKD) is escalating, now affecting one in 10 people worldwide. South Korea is no exception, ranking sixth globally in the number of CKD patients. This necessitates a revamping of its medical response system to accommodate the growing number of dialysis patients. However, Korea faces a challenge with its doctor-population ratio, which is the lowest among the OECD countries, coupled with a scarcity of dialysis specialists. As a result, physicians are enduring excessive overtime and workload, raising significant concerns about burnout. Specifically, the critical treatment in hemodialysis centers involves monthly examinations and medication prescriptions for dialysis patients, typically guided by the KDIGO and K-DOQI guidelines. However, practices may vary among attending physicians, with prescriptions influenced by individual preferences, knowledge, and beliefs. In this study, we developed an artificial intelligence model using data from approximately 180,000 past prescriptions and assessed its applicability. The AI-based drug prescription model demonstrated exceptional performance, with scores of 0.99 or higher across all four performance indicators of the classification model. This innovation is anticipated to significantly mitigate physician burnout by reducing it by less than 10%, thereby making a substantial contribution to the healthcare system.
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