| 1. |
- Fernandez-Llatas, Carlos, et al.
(författare)
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Empowering ergonomy in workplaces by individual behavior modeling using interactive process mining paradigm
- 2018
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Ingår i: Intelligent Environments 2018. - Amsterdam : IOS Press. - 9781614998730 - 9781614998747 ; , s. 346-354
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Bokkapitel (refereegranskat)abstract
- Work-related disorders account for a significant part of total healthcareexpenditure. Traditionally muscle-skeletal disorders were predominant as source ofwork absenteeism but in last years work activity-related disorders have increasedremarkably. Too little activity at work, sedentarism, or too much work activity leadsto stress. The individualized behavioural analysis of patients could support ergon-omy experts in the optimization of workplaces in a Healthier way. Process MiningTechnologies can offer a human understandable view of what is actually occurringin workplaces in an individualized way. In this paper, we present a proof of con-cept of how Process Mining technologies can be used for discovering the workerflow in order to support the ergonomy experts in the selection of more accurateinterventions for improving occupational health.
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| 2. |
- Ferrando, Carlos, et al.
(författare)
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Effects of oxygen on post-surgical infections during an individualised perioperative open-lung ventilatory strategy : a randomised controlled trial
- 2020
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Ingår i: British Journal of Anaesthesia. - : ELSEVIER SCI LTD. - 0007-0912 .- 1471-6771. ; 124:1, s. 110-120
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Tidskriftsartikel (refereegranskat)abstract
- Background: We aimed to examine whether using a high fraction of inspired oxygen (FIO2) in the context of an individualised intra- and postoperative open-lung ventilation approach could decrease surgical site infection (SSI) in patients scheduled for abdominal surgery. Methods: We performed a multicentre, randomised controlled clinical trial in a network of 21 university hospitals from June 6, 2017 to July 19, 2018. Patients undergoing abdominal surgery were randomly assigned to receive a high (0.80) or conventional (0.3) FIO2 during the intraoperative period and during the first 3 postoperative hours. All patients were mechanically ventilated with an open-lung strategy, which included recruitment manoeuvres and individualised positive end-expiratory pressure for the best respiratory-system compliance, and individualised continuous postoperative airway pressure for adequate peripheral oxyhaemoglobin saturation. The primary outcome was the prevalence of SSI within the first 7 postoperative days. The secondary outcomes were composites of systemic complications, length of intensive care and hospital stay, and 6-month mortality. Results: We enrolled 740 subjects: 371 in the high FIO2 group and 369 in the low FIO2 group. Data from 717 subjects were available for final analysis. The rate of SSI during the first postoperative week did not differ between high (8.9%) and low (9.4%) FIO2 groups (relative risk [RR]: 0.94; 95% confidence interval [CI]: 0.59-1.50; P=0.90]). Secondary outcomes, such as atelectasis (7.7% vs 9.8%; RR: 0.77; 95% CI: 0.48-1.25; P=0.38) and myocardial ischaemia (0.6% [n=2] vs 0% [n=0]; P=0.47) did not differ between groups. Conclusions: An oxygenation strategy using high FIO2 compared with conventional FIO2 did not reduce postoperative SSIs in abdominal surgery. No differences in secondary outcomes or adverse events were found.
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| 3. |
- Munoz-Gama, Jorge, et al.
(författare)
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Process mining for healthcare : Characteristics and challenges
- 2022
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Ingår i: Journal of Biomedical Informatics. - : Elsevier BV. - 1532-0464 .- 1532-0480. ; 127
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Tidskriftsartikel (refereegranskat)abstract
- Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.
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