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Boodaghian Asl, A., Raghothama, J., Darwich, A. S. & Meijer, S. (2024). A hybrid modeling approach to simulate complex systems and classify behaviors. NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, 13(1), Article ID 9.
Open this publication in new window or tab >>A hybrid modeling approach to simulate complex systems and classify behaviors
2024 (English)In: NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, ISSN 2192-6662, Vol. 13, no 1, article id 9Article in journal (Refereed) Published
Abstract [en]

Many important systems, both natural and artificial, are complex in nature, and models and simulations are one of the main instruments to study them. In this paper, we present an approach where a complex social system is represented at a high level of abstraction as a network, thereby addressing several challenges such as quantification, intervention, adaptation and validation. The network represents the factors that influence the mental health and wellbeing in children and young people. In this article, we present an approach that links a system dynamics simulation to simulate the network and ranking algorithms to measure the vertices' behaviors. The network is enhanced by adding edge strengths in the form of correlations between vertices (established through literature). Such an approach allows us to exploit the network structure to qualify and quantify the vertices of the network, to overlay different processes over the network topology, to add and remove new vertices, and therefore interact dynamically. This in turn allows for the qualification of vertices' importance and network resilience. System dynamics simulation allows for policy analysis, where different scenarios are analyzed by stimulating a set of vertices and the effect over the network is observed. This approach allows for an abstract, flexible, yet comprehensive way of analyzing a complex social network at any scale.

Place, publisher, year, edition, pages
Springer Nature, 2024
Keywords
Simulation and modeling, Ranking algorithm, Complex systems, Mental wellbeing
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-345028 (URN)10.1007/s13721-024-00446-5 (DOI)001186407300001 ()2-s2.0-85188097928 (Scopus ID)
Note

QC 20240408

Available from: 2024-04-08 Created: 2024-04-08 Last updated: 2024-04-08Bibliographically approved
Marzano, L., Darwich, A. S., Raghothama, J., Sven, L., Falk, N., Bodeby, P. & Meijer, S. (2024). Diagnosing an overcrowded emergency department from its Electronic Health Records. Scientific Reports, 14(1), Article ID 9955.
Open this publication in new window or tab >>Diagnosing an overcrowded emergency department from its Electronic Health Records
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2024 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 14, no 1, article id 9955Article in journal (Refereed) Published
Abstract [en]

Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand its dynamics. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitute a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.

Place, publisher, year, edition, pages
Nature Research, 2024
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:kth:diva-346372 (URN)10.1038/s41598-024-60888-9 (DOI)38688997 (PubMedID)2-s2.0-85191754138 (Scopus ID)
Note

QC 20240515

Available from: 2024-05-14 Created: 2024-05-14 Last updated: 2024-05-15Bibliographically approved
Hellstrand, M., Kornevs, M., Raghothama, J. & Meijer, S. (2024). Tensions between real-world practices and the digitalization paradigm for data-driven services in eldercare: observations from an ethnographic study in Sweden. BMC Geriatrics, 24(1), Article ID 98.
Open this publication in new window or tab >>Tensions between real-world practices and the digitalization paradigm for data-driven services in eldercare: observations from an ethnographic study in Sweden
2024 (English)In: BMC Geriatrics, E-ISSN 1471-2318, Vol. 24, no 1, article id 98Article in journal (Refereed) Published
Abstract [en]

Background: The implementation of a data-driven approach within the health care system happens in a rapid pace; including in the eldercare sector. Within Swedish eldercare, data-driven health approach is not yet widely implemented. In the specific context of long-term care for older adults, quality of care is as much determined by how social care is being performed as it is by what kind medical care that is provided. In particular, relational aspects have been proven to have a crucial influence on the experience of quality of care for the actors involved. Drawing on ethnographic material collected at a Swedish nursing home, this paper explores in what way the relational aspects of care could potentially become affected by the increased use of a data-driven health approach. Methods: An ethnographic approach was adopted in order to investigate the daily care work at a long-term care facility as it unfolded. Fieldwork was conducted at a somatic ward in a Swedish long-term care facility over 4 months (86 h in total), utilizing the methods of participant observation, informal interviews and document analysis. The material was analyzed iteratively throughout the entire research process adopting thematic analysis. Results: Viewing our ethnographic material through an observational lense problematising the policy discourse around data-driven health approach, two propositions were developed. First, we propose that relational knowledge risk becoming less influential in shaping everyday care, when moving to a data-driven health approach. Second, we propose that quality of care risk becoming more directed on quality of medical care at the expense of quality of life. Conclusion: While the implementation of data-driven health approach within long-term care for older adults is not yet widespread, the general development within health care points towards a situation in which this will become reality. Our study highlights the importance of taking the relational aspects of care into consideration, both during the planning and implementation phase of this process. By doing this, the introduction of a data-driven health approach could serve to heighten the quality of care in a way which supports both quality of medical care and quality of life.

Place, publisher, year, edition, pages
Springer Nature, 2024
Keywords
Data driven health, Ethnography, Long term care, Quality of care, Relational care
National Category
Nursing Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:kth:diva-342826 (URN)10.1186/s12877-024-04693-z (DOI)2-s2.0-85182986445 (Scopus ID)
Note

QC 20240201

Available from: 2024-01-31 Created: 2024-01-31 Last updated: 2024-02-01Bibliographically approved
Marzano, L., Dan, A., Tendler, S., Darwich, A. S., Raghothama, J., De Petris, L., . . . Meijer, S. (2023). A Comparative Analysis between Real-World Data and Clinical Trials to Evaluate Differences in Outcomes for SCLC Patients. Journal of Thoracic Oncology, 18(11), S697-S697
Open this publication in new window or tab >>A Comparative Analysis between Real-World Data and Clinical Trials to Evaluate Differences in Outcomes for SCLC Patients
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2023 (English)In: Journal of Thoracic Oncology, ISSN 1556-0864, E-ISSN 1556-1380, Vol. 18, no 11, p. S697-S697Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
ELSEVIER SCIENCE INC, 2023
Keywords
small cell lung cancer, real-world evidence, platinum doublet chemotherapy
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:kth:diva-342734 (URN)001098831602137 ()
Note

QC 20240216

Available from: 2024-02-16 Created: 2024-02-16 Last updated: 2024-02-16Bibliographically approved
Marzano, L., Meijer, S., Dan, A., Tendler, S., De Petris, L., Lewensohn, R., . . . Darwich, A. S. (2023). Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis. Paper presented at The 33rd Medical Informatics Europe Conference, MIE2023, Gothenburg, Sweden. May 22-25, 2023.. Studies in Health Technology and Informatics, 302, 18-22
Open this publication in new window or tab >>Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis
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2023 (English)In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 302, p. 18-22Article in journal (Refereed) Published
Abstract [en]

Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinical oncological data with the purpose of studying survival outcomes and chemotherapy treatment decision in a real-world cohort of small cell lung cancer patients treated at Karolinska University Hospital (Stockholm, Sweden). The results highlighted the potential role of process mining in oncology to study prognosis and survival outcomes with longitudinal models directly extracted from clinical data derived from healthcare.

Place, publisher, year, edition, pages
IOS Press, 2023
Keywords
oncology, Process mining, Real-world Data, small cell lung cancer, treatment decision
National Category
Cancer and Oncology
Research subject
Applied and Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-329927 (URN)10.3233/SHTI230056 (DOI)001071432900004 ()37203601 (PubMedID)2-s2.0-85159759671 (Scopus ID)
Conference
The 33rd Medical Informatics Europe Conference, MIE2023, Gothenburg, Sweden. May 22-25, 2023.
Note

QC 20230628

Available from: 2023-06-26 Created: 2023-06-26 Last updated: 2023-11-07Bibliographically approved
Darwich, A. S., Bostroem, A.-M., Guidetti, S., Raghothama, J. & Meijer, S. (2023). Investigating the Connections Between Delivery of Care, Reablement, Workload, and Organizational Factors in Home Care Services: Mixed Methods Study. JMIR Human Factors, 10, Article ID e42283.
Open this publication in new window or tab >>Investigating the Connections Between Delivery of Care, Reablement, Workload, and Organizational Factors in Home Care Services: Mixed Methods Study
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2023 (English)In: JMIR Human Factors, E-ISSN 2292-9495, Vol. 10, article id e42283Article in journal (Refereed) Published
Abstract [en]

Background: Home care is facing increasing demand due to an aging population. Several challenges have been identified in the provision of home care, such as the need for support and tailoring support to individual needs. Goal-oriented interventions, such as reablement, may provide a solution to some of these challenges. The reablement approach targets adaptation to disease and relearning of everyday life skills and has been found to improve health-related quality of life while reducing service use.Objective: The objective of this study is to characterize home care system variables (elements) and their relationships (connections) relevant to home care staff workload, home care user needs and satisfaction, and the reablement approach. This is to examine the effects of improvement and interventions, such as the person-centered reablement approach, on the delivery of home care services, workload, work-related stress, home care user experience, and other organizational factors. The main focus was on Swedish home care and tax-funded universal welfare systems.Methods: The study used a mixed methods approach where a causal loop diagram was developed grounded in participatory methods with academic health care science research experts in nursing, occupational therapy, aging, and the reablement approach. The approach was supplemented with theoretical models and the scientific literature. The developed model was verified by the same group of experts and empirical evidence. Finally, the model was analyzed qualitatively and through simulation methods.Results: The final causal loop diagram included elements and connections across the categories: stress, home care staff, home care user, organization, social support network of the home care user, and societal level. The model was able to qualitatively describe observed intervention outcomes from the literature. The analysis suggested elements to target for improvement and the potential impact of relevant studied interventions. For example, the elements "workload" and "distress" were important determinants of home care staff health, provision, and quality of care.Conclusions: The developed model may be of value for informing hypothesis formulation, study design, and discourse within the context of improvement in home care. Further work will include a broader group of stakeholders to reduce the risk of bias. Translation into a quantitative model will be explored.

Place, publisher, year, edition, pages
JMIR Publications Inc., 2023
National Category
Nursing
Identifiers
urn:nbn:se:kth:diva-333252 (URN)10.2196/42283 (DOI)001025960000001 ()37389904 (PubMedID)
Note

QC 20230731

Available from: 2023-07-31 Created: 2023-07-31 Last updated: 2023-07-31Bibliographically approved
Abourraja, M. N., Marzano, L., Raghothama, J., Boodaghian Asl, A., Darwich, A. S., Meijer, S., . . . Falk, N. (2022). A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics. In: Proceedings of the 2022 Winter Simulation Conference: . Paper presented at Winter Simulation Conference, WSC 2022, Singapore, December 11-14, 2022. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics
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2022 (English)In: Proceedings of the 2022 Winter Simulation Conference, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper, Published paper (Refereed)
Abstract [en]

Demands for health care are becoming overwhelming for healthcare systems around the world regarding theavailability of resources, particularly, in emergency departments (EDs) that are continuously open and mustserve immediately any patient who comes in. Efficient management of EDs and their resources is requiredmore than ever. This could be achieved either by optimizing resource utilization or by the improvement ofhospital layout. This paper investigates, through data-driven simulation alternative designs of workflowsand layouts to operate the ED of the Uppsala University Hospital in Sweden. Results are analyzed tounderstand the requirements across the hospital for reduced waiting times in the ED. The main observationrevealed that introducing a new ward dedicated to patients having complex diagnoses with a capacity ofless than 20 beds leads to lower waiting times. Furthermore, the use of data-mining was of great help inreducing the efforts of building the simulation model.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:kth:diva-330232 (URN)10.1109/wsc57314.2022.10015465 (DOI)000991872900062 ()2-s2.0-85147456598 (Scopus ID)
Conference
Winter Simulation Conference, WSC 2022, Singapore, December 11-14, 2022
Note

QC 20230628

Available from: 2023-06-28 Created: 2023-06-28 Last updated: 2023-09-01Bibliographically approved
Marzano, L., Darwich, A. S., Tendler, S., Dan, A., Lewensohn, R., De Petris, L., . . . Meijer, S. (2022). A novel analytical framework for risk stratification of real‐world data using machine learning: A small cell lung cancer study. Clinical and Translational Science, 15(10), 2437-2447
Open this publication in new window or tab >>A novel analytical framework for risk stratification of real‐world data using machine learning: A small cell lung cancer study
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2022 (English)In: Clinical and Translational Science, ISSN 1752-8054, E-ISSN 1752-8062, Vol. 15, no 10, p. 2437-2447Article in journal (Refereed) Published
Abstract [en]

In recent studies, small cell lung cancer (SCLC) treatment guidelines based on Veterans’ Administration Lung Study Group limited/extensive disease staging and resulted in broad and inseparable prognostic subgroups. Evidence suggests that the eight versions of tumor, node, and metastasis (TNM) staging can play an important role to address this issue. The aim of the present study was to improve the detection of prognostic subgroups from a real-word data (RWD) cohort of patients and analyze their patterns using a development pipeline with thoracic oncologists and machine learning methods. The method detected subgroups of patients informing unsupervised learning (partition around medoids) including the impact of covariates on prognosis (Cox regression and random survival forest). An analysis was carried out using patients with SCLC (n = 636) with stage IIIA–IVB according to TNM classification. The analysis yielded k = 7 compacted and well-separated clusters of patients. Performance status (Eastern Cooperative Oncology Group-Performance Status), lactate dehydrogenase, spreading of metastasis, cancer stage, and CRP were the baselines that characterized the subgroups. The selected clustering method outperformed standard clustering techniques, which were not capable of detecting meaningful subgroups. From the analysis of cluster treatment decisions, we showed the potential of future RWD applications to understand disease, develop individualized therapies, and improve healthcare decision making.

Place, publisher, year, edition, pages
Wiley, 2022
Keywords
C reactive protein; carboplatin; cisplatin; etoposide; irinotecan; lactate dehydrogenase; platinum complex
National Category
Medical and Health Sciences Cancer and Oncology
Identifiers
urn:nbn:se:kth:diva-321440 (URN)10.1111/cts.13371 (DOI)000832654100001 ()35856401 (PubMedID)2-s2.0-85135121261 (Scopus ID)
Funder
Swedish Cancer Society, CAN2021/1469 Pj01Swedish Cancer Society, CAN 2018/597KTH Royal Institute of Technology
Note

QC 20221115

Available from: 2022-11-14 Created: 2022-11-14 Last updated: 2022-11-16Bibliographically approved
Raghothama, J., Baalsrud Hauge, J. & Meijer, S. (2022). Curating Player Experience Through Simulations in City Games. Urban Planning, 7(2), 253-263
Open this publication in new window or tab >>Curating Player Experience Through Simulations in City Games
2022 (English)In: Urban Planning, E-ISSN 2183-7635, Vol. 7, no 2, p. 253-263Article in journal (Refereed) Published
Abstract [en]

The use of games as a method for planning and designing cities is often associated with visualisation, from simplistic to immersive environments. They can also include complex and sophisticated models which provide an evidence base. The use of such technology as artefacts, aids, or mechanics curates the player experience in different and very often subtle ways, influencing how we engage with (simulated) urban phenomena, and, therefore, how the games can be used. In this article, we aim to explore how different aspects of technology use in city games influence the player experience and game outcomes. The article describes two games built upon the same city gaming framework, played with professionals in Rome and Haifa, respectively. Using a mixed-method, action research approach, the article examines how the high-tech, free form single-player games elicit the mental models of players (traffic controllers and planners in both cases). Questionnaires and the players' reflections on the gameplay, models used, and outcomes have been transcribed and analysed. Observations and results point to several dimensions that are critical to the outcomes of digital city games. Agency, exploration, openness, complexity, and learning are aspects that are strongly influenced by technology and models, and in turn, determine the outcomes of the game. City games that balance these aspects unlock player expertise to better understand the game dynamics and enable their imagination to better negotiate and resolve conflicts in design and planning.

Place, publisher, year, edition, pages
Cogitatio, 2022
Keywords
city-gaming, experience, Haifa, modelling, Rome, simulation
National Category
Human Geography Information Systems, Social aspects
Identifiers
urn:nbn:se:kth:diva-315676 (URN)10.17645/up.v7i2.5031 (DOI)000820979800005 ()2-s2.0-85134037995 (Scopus ID)
Note

QC 20220715

Available from: 2022-07-15 Created: 2022-07-15 Last updated: 2023-04-11Bibliographically approved
Meijer, S., Olejniczak, K. & Raghothama, J. (2022). Public Policy and Engineering Systems Synergy. In: Maier, A., Oehmen, J., Vermaas, P.E. (Ed.), Handbook of Engineering Systems Design: (pp. 987-1010). Springer Nature
Open this publication in new window or tab >>Public Policy and Engineering Systems Synergy
2022 (English)In: Handbook of Engineering Systems Design / [ed] Maier, A., Oehmen, J., Vermaas, P.E., Springer Nature , 2022, p. 987-1010Chapter in book (Other academic)
Abstract [en]

Engineering systems cannot be seen separate from the context they work in. Increasing complexity of society makes that larger systems no longer just concern technical aspects but include social and even societal aspects. Particularly, the societal aspects can be subject to public policy as a part of engineering systems design. This chapter provides a discussion of the nature of public policy and the role it plays in engineering systems, as well as the role that engineering systems methods play for public policy design. The mutual relationship is positioned in a historic overview, where particularly the role of participatory methods has grown over time to capture human complex thinking in a world dominated by mathematic modelling approaches. It positions engineering systems to encompass public policy as an integral part of design, so that the traditional divide between engineering and societal contexts can be bridged.

Place, publisher, year, edition, pages
Springer Nature, 2022
Keywords
Behaviour, Engineering systems, Games, Government, Modelling, Policy design, Public policy
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:kth:diva-333071 (URN)10.1007/978-3-030-81159-4_30 (DOI)2-s2.0-85153665198 (Scopus ID)
Note

Part of ISBN 9783030811594 9783030811587

QC 20230725

Available from: 2023-07-25 Created: 2023-07-25 Last updated: 2023-07-25Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3416-4535

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