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Obstructive sleep apnoea: Improving healthcare services by combining process modelling and population analysis
- Source :
- International journal of medical informatics 127 (2019): 43–51. doi:10.1016/j.ijmedinf.2019.04.013, info:cnr-pdr/source/autori:Leo C.G; Mincarone P.; Bodini A.; Sedile R.; Guarino R.; Tumolo M.R.; Malorgio R.; Quitadamo M.; Sabato E.; Viegi G.; Insalaco G.; Sabina S./titolo:Obstructive sleep apnoea: Improving healthcare services by combining process modelling and population analysis/doi:10.1016%2Fj.ijmedinf.2019.04.013/rivista:International journal of medical informatics/anno:2019/pagina_da:43/pagina_a:51/intervallo_pagine:43–51/volume:127
- Publication Year :
- 2019
- Publisher :
- Elsevier Science Ireland, Shannon , Paesi Bassi, 2019.
-
Abstract
- Context Disease management broke through in the early 1990s to counterbalance hyper-specialization with a more comprehensive approach. Its role became immediately relevant in chronic conditions and, consequently, in Obstructive Sleep Apnoea (OSA). This is a common chronic condition for which is important to organise services at the local level, taking into account organisational factors and the characteristics of the assisted population. Objectives The aim of this work is to propose and apply, coherently with a disease management approach, a combination of healthcare process modelling and population analysis as a way to identify critical issues and explore shared solutions. Methods A multidisciplinary working group was created with scholars who are skilled in process analysis, statistics and medicine. Through semi-structured interviews and on-site meetings, healthcare processes were represented with a standard graphical language: Unified Modeling Language™. Population analysis was based on statistical analysis performed on a 5-year retrospective cohort assisted by a Community Pulmonary Service. Results A shared graphic presentation of the current healthcare process and the results of the statistical analyses constituted the knowledge base to identify critical issues and recommend corresponding solutions, which include: a) refine the local patient database with additional details on comorbidities and risk factors; b) support a greater involvement of “gate-keepers” in the screening phase; c) provide practical tools for the definition of strategies to increment the adherence to therapy; d) include recommendations for physical exercise and interdisciplinary cooperation; and e) define process indicators for measuring the quality of the screening and therapeutic phases. Conclusion The concomitant analyses of formalised processes and critical risk factors represent a useful approach for systematically identifying areas of improvement in healthcare processes and allow us to discuss solutions. Moreover, the specific adoption of UML® for graphical modelling and representation of patient care processes allows us to formalise them by adopting a standard language that can be taken as the basis for implementing web services to support the execution of the modelled processes.
- Subjects :
- Adult
Male
Process modeling
Process management
020205 medical informatics
Computer science
Process (engineering)
Population
Health Informatics
Context (language use)
02 engineering and technology
Comorbidity
03 medical and health sciences
0302 clinical medicine
Multidisciplinary approach
Risk Factors
Health care
Disease management
0202 electrical engineering, electronic engineering, information engineering
Humans
Mass Screening
Process modelling
030212 general & internal medicine
Disease management (health)
education
Healthcare process assessment
Aged
Retrospective Studies
education.field_of_study
Sleep Apnea, Obstructive
business.industry
Obstructive
Sleep apnea
Middle Aged
Knowledge base
Predictive model
Chronic Disease
Female
business
Delivery of Health Care
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- International journal of medical informatics 127 (2019): 43–51. doi:10.1016/j.ijmedinf.2019.04.013, info:cnr-pdr/source/autori:Leo C.G; Mincarone P.; Bodini A.; Sedile R.; Guarino R.; Tumolo M.R.; Malorgio R.; Quitadamo M.; Sabato E.; Viegi G.; Insalaco G.; Sabina S./titolo:Obstructive sleep apnoea: Improving healthcare services by combining process modelling and population analysis/doi:10.1016%2Fj.ijmedinf.2019.04.013/rivista:International journal of medical informatics/anno:2019/pagina_da:43/pagina_a:51/intervallo_pagine:43–51/volume:127
- Accession number :
- edsair.doi.dedup.....4b27499df30cc086d5e9057deb39bf78