| 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. |
- Fico, Giuseppe, et al.
(författare)
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What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project
- 2019
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Ingår i: BMC Medical Informatics and Decision Making. - : Springer Science and Business Media LLC. - 1472-6947. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Background: To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models. Methods: The holistic and evidence-based CEHRES Roadmap, used to create eHealth solutions through participatory development approach, persuasive design techniques and business modelling, was adopted in the MOSAIC project to define the sequence of multidisciplinary methods organized in three phases, user needs, implementation and evaluation. The research was qualitative, the total number of participants was ninety, about five-seventeen involved in each round of experiment. Results: Prediction models for the onset of T2D are built on clinical studies, while for T2D care are derived from healthcare registries. Accordingly, two set of DSSs were defined: the first, T2D Screening, introduces a novel routine; in the second case, T2D Care, DSSs can support managers at population level, and daily practitioners at individual level. In the user needs phase, T2D Screening and solution T2D Care at population level share similar priorities, as both deal with risk-stratification. End-users of T2D Screening and solution T2D Care at individual level prioritize easiness of use and satisfaction, while managers prefer the tools to be available every time and everywhere. In the implementation phase, three Use Cases were defined for T2D Screening, adapting the tool to different settings and granularity of information. Two Use Cases were defined around solutions T2D Care at population and T2D Care at individual, to be used in primary or secondary care. Suitable filtering options were equipped with "attractive" visual analytics to focus the attention of end-users on specific parameters and events. In the evaluation phase, good levels of user experience versus bad level of usability suggest that end-users of T2D Screening perceived the potential, but they are worried about complexity. Usability and user experience were above acceptable thresholds for T2D Care at population and T2D Care at individual. Conclusions: By using a holistic approach, we have been able to understand user needs, behaviours and interactions and give new insights in the definition of effective Decision Support Systems to deal with the complexity of T2D care.
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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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| 4. |
- Seoane, Fernando, 1976-, et al.
(författare)
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Value-driven digital transformation in health and medical care
- 2021
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Ingår i: Interactive Process Mining in Healthcare. - Cham : Springer Nature. - 9783030539924 - 9783030539931 ; , s. 13-26
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Bokkapitel (refereegranskat)abstract
- Medical care has been patient centred from the origin and has evolved closely along the evolution of patient needs from the patient as individual to the patient as population, pursuing to provide the medical care of the highest quality standard, and including a public health approach. The holistic unification of patient individual health and patient population approaches through health and patient outcomes was predicted in “Measuring Health Outcomes” (Cairns, J. British Medical Journal;313:6) back in 1996. Advancements of information technologies deploying new data-driven services enabled the rising and supports development of novel multidimensional and holistic approaches to health care as: Value-based Health Care (VBHC) and the Quadruple Aim of healthcare. Considering value in VBHC as achieving the best outcomes from the perspective of the patient versus executing the care process needed to achieve these outcomes in the most optimal way. It is of paramount importance to identify and understand the processes to be improved; that will help us in order to be able to improve the outcomes. Digital health tools enable deployment of information services and data analysis technologies like the process mining one, which is precisely adequate for discovery, analysis and optimizing of the operational models underlying the actual care processes.Despite that the undergoing transformational change is pulled by global needs and driven by information technologies, data availability and data science, the journey ahead for digital health transformation is full of all sort of barriers: regulatory, clinical adoption, medical trust, and patient acceptance, requiring a holistic approach.
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