دورية أكاديمية

BPM Support for Patient-Centred Clinical Pathways in Chronic Diseases

التفاصيل البيبلوغرافية
العنوان: BPM Support for Patient-Centred Clinical Pathways in Chronic Diseases
المؤلفون: Marek Szelągowski, Justyna Berniak-Woźny, Cezary Lipiński
المصدر: Sensors, Vol 21, Iss 21, p 7383 (2021)
بيانات النشر: MDPI AG, 2021.
سنة النشر: 2021
المجموعة: LCC:Chemical technology
مصطلحات موضوعية: business process management (BPM), telemedicine, Chronic Obstructive Pulmonary Disease (COPD), clinical pathways (CPs), diagnostic and therapeutic processes, Chemical technology, TP1-1185
الوصف: Epidemiological trends over the past decade show a significant worldwide increase in the burden of chronic diseases. At the same time, the human resources of health care are becoming increasingly scarce and expensive. One of the management concepts that can help in solving this problem is business process management (BPM). The results of research conducted in the healthcare sector thus far prove that BPM is an effective tool for optimizing clinical processes, as it allows for the ongoing automatic tracking of key health parameters of an individual patient without the need to involve medical personnel. The aim of this article is to present and evaluate the redesign of diagnostic and therapeutic processes enabling the patient-centric organization of therapy thanks to the use of new telemedicine techniques and elements of hyperautomation. By using an illustrative case study of one of the most common chronic diseases, Chronic Obstructive Pulmonary Disease (COPD), we discuss the use of clinical pathways (CPs) prepared on the basis of the current version of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) as a communication tool between healthcare professionals, the patient and his or her caregivers, as well as the method of identifying and verifying new knowledge generated on an ongoing basis in diagnostic and therapeutic processes. We also show how conducting comprehensive, patient-focused primary health care relieves the health care system, and at the same time, thanks to the use of patient engagement and elements of artificial intelligence (predictive analyses), reduces the significant clinical risk of therapy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1424-8220
Relation: https://www.mdpi.com/1424-8220/21/21/7383; https://doaj.org/toc/1424-8220
DOI: 10.3390/s21217383
URL الوصول: https://doaj.org/article/a48ec71209cd463f9b80e707a4ed89f4
رقم الأكسشن: edsdoj.48ec71209cd463f9b80e707a4ed89f4
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:14248220
DOI:10.3390/s21217383