Healthcare pathway discovery and probabilistic machine learning

Kempa-Liehr, Andreas W.; Lin, Christina Yin-Chieh; Britten, Randall; Armstrong, Delwyn; Wallace, Jonathan; Mordaunt, Dylan; O'Sullivan, Michael J.

doi:10.1016/j.ijmedinf.2020.104087

Cited by 34 publications

(35 citation statements)

References 17 publications

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“…control-flow discovery). For instance, Kempa-Liehr et al [20] use process mining to visualize the prevailing pathways for patients suffering from appendicitis to clinicians. Similarly, Kim et al [52] retrieve the control-flow of the outpatient care process from an event log to gain insights in frequent process paths.…”

Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

“…An important stream of discovery research relates to [12]. Within a clinical context, controlflow discovery unearths latent knowledge by making the actual order of clinical activities in the process explicit and visual [2,19,20]. To obtain a control-flow model from an event log, a multitude of discovery algorithms have been developed, of which an overview is provided in De Weerdt et al [21] and Augusto et al [22].…”

Section: Introduction To Process Mining In Healthcarementioning

confidence: 99%

“…Moreover, the enhanced process model provides a basis to support predictions within a clinical context, e.g. related to the length of stay [42] or the patient recovery time [20].…”

Section: Introduction To Process Mining In Healthcarementioning

confidence: 99%

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Recommendations for enhancing the usability and understandability of process mining in healthcare

Martin

Weerdt

Fernández-Llatas

et al. 2020

Artificial Intelligence in Medicine

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Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process analysis is required, which can be based on real-life process execution data captured by health information systems. Process mining is a research field that focuses on the development of techniques to extract process-related insights from process execution data, providing valuable and previously unknown information to instigate evidence-based process improvement in healthcare. However, despite the potential of process mining, its uptake in healthcare organizations outside case studies in a research context is rather limited. This observation was the starting point for an international brainstorm seminar. Based on the seminar's outcomes and with the ambition to stimulate a more widespread use of process mining in healthcare, this paper formulates recommendations to enhance the usability and understandability of process mining in healthcare. These recommendations are mainly targeted towards process mining researchers and the community to consider when developing a new research agenda for process mining in healthcare. Moreover, a limited number of recommendations are directed towards healthcare organizations and health information systems vendors, when shaping an environment to enable the continuous use of process mining.

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Section: Applications Of Process Mining In Healthcarementioning

confidence: 99%

Section: Introduction To Process Mining In Healthcarementioning

confidence: 99%

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Recommendations for enhancing the usability and understandability of process mining in healthcare

Martin

Weerdt

Fernández-Llatas

et al. 2020

Artificial Intelligence in Medicine

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show abstract

“…Im Folgenden sollen ausgewählte Bereiche dargestellt werden, in denen eine Verbesserung der sektorenübergreifenden Versorgungssteuerung erreicht werden könnte. Vor allem im internationalen Krankenhausumfeld werden datengetriebene Versorgungspfade bereits eingesetzt (Kempa-Liehr et al 2020). Obwohl viele Studien eine Verbesserung der Behandlungsergebnisse nach der Implementierung von IT-gestützten Versorgungspfaden berichten, werden eindeutige Schlüsse noch durch methodische Schwächen erschwert (Neame et al 2019 (Emanuel et al 2016).…”

Section: Versorgungssteuerungunclassified

Sektorenübergreifende Versorgungssteuerung

Messerle

Schreyögg

2021

Krankenhaus-Report 2021

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Zusammenfassung Zusammenfassung Seit Jahrzehnten versucht die Gesundheitspolitik, die Auswirkungen der sektoralen Trennung im Gesundheitswesen abzumildern. Im Ergebnis stehen heterogene Versorgungsoptionen anstelle eines übergreifenden ordnungspolitischen Konzepts. Der von verschiedenen Seiten festgestellte Reformbedarf im Rahmen der Corona-Pandemie sollte nun zum Anlass genommen werden, größere Schritte zu gehen. Ausgehend vom Status quo der Versorgung erscheinen insbesondere drei Handlungsbereiche wichtig: eine sektorenübergreifende, morbiditäts- und leistungsorientierte Versorgungsplanung, ein einheitliches sektorengleiches Vergütungssystem und mehr Freiräume für ein aktives Versorgungsmanagement, um an den lokalen Kontext angepasste Versorgungsmodelle zu ermöglichen.

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“…Com esse acompanhamento bem definido, pode-se avaliar a sequência completa de procedimentos e realizar uma comparação com o modelo recomendado pelo SUS, por exemplo. Tal análise de conformidadeé importante, pois diversos trabalhos têm indicado que há alta variabilidade de trajetórias reais de cuidados naárea de saúde [Kempa-Liehr et al 2020, Lismont et al 2016, Baker et al 2017. Além disso, essas análises permitem criar subsídios para futuras avaliações e proporcionam ferramentas para melhorar a gestão e alocação dos recursos disponíveis [Pollack et al 2013].…”

Section: Introductionunclassified

Análise dos Atendimentos de Gestantes na Rede de Atenção Básica de Saúde no Município de São Paulo

Silva¹,

Santos²,

Rosa³

et al. 2020

Anais Principais Do Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS 2020)

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Neste artigo, são analisadas as trajetórias de atendimento de pacientes na rede de atenção básica de saúde no município de São Paulo. Avaliar como é a trajetória dos pacientes do SUS, seja entre os atendimentos, seja entre as unidades de atendimento, e uma atividade importante para o entendimento é aprimoramento do sistema. Assim, neste artigo, foca-se num contexto de alta relevância social representado pela avaliação da trajetória de gestantes atendidas pelo SUS no município de São Paulo durante os anos de 2014 e 2015. São analisadas as trajetórias dessas gestantes em seus atendimentos e entre as unidades do sistema de saúde. Acredita-se que as análises apresentadas possam auxiliar em um melhor entendimento do sistema e subsidiar decisões para o aprimoramento do sistema de saúde atual.

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Healthcare pathway discovery and probabilistic machine learning

Cited by 34 publications

References 17 publications

Recommendations for enhancing the usability and understandability of process mining in healthcare

Recommendations for enhancing the usability and understandability of process mining in healthcare

Sektorenübergreifende Versorgungssteuerung

Análise dos Atendimentos de Gestantes na Rede de Atenção Básica de Saúde no Município de São Paulo

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