Your browser doesn't support javascript.
BPM Support for Patient-Centred Clinical Pathways in Chronic Diseases.
Szelagowski, Marek; Berniak-Wozny, Justyna; Lipinski, Cezary.
  • Szelagowski M; Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland.
  • Berniak-Wozny J; Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland.
  • Lipinski C; Center for Innovation and Technology Transfer, Medical University of Lodz, 90-149 Lódz, Poland.
Sensors (Basel) ; 21(21)2021 Nov 06.
Article in English | MEDLINE | ID: covidwho-1512568
ABSTRACT
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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Telemedicine / Pulmonary Disease, Chronic Obstructive Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Female / Humans / Male Language: English Year: 2021 Document Type: Article Affiliation country: S21217383

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Telemedicine / Pulmonary Disease, Chronic Obstructive Type of study: Diagnostic study / Experimental Studies / Prognostic study Limits: Female / Humans / Male Language: English Year: 2021 Document Type: Article Affiliation country: S21217383