Process mining for healthcare: Characteristics and challenges

[EN] 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.This work is partially supported by ANID FONDECYT 1220202, Direccion de Investigacion de la Vicerrectoria de Investigacion de la Pontificia Universidad Catolica de Chile-PUENTE [Grant No. 026/2021] ; and Agencia Nacional de Investigacion y Desarrollo [Grant Nos. ANID-PFCHA/Doctorado Nacional/2019-21190116, ANID-PFCHA/Doctorado Nacional/2020-21201411] . With regard to the co-author Hilda Klasky, this manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE) . The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan)Munoz Gama, J.; Martin, N.; Fernández Llatas, C.; Johnson, OA.; Sepúlveda, M.; Helm, E.; Galvez-Yanjari, V.... (2022). Process mining for healthcare: Characteristics and challenges. Journal of Biomedical Informatics. 127:1-15. https://doi.org/10.1016/j.jbi.2022.10399411512

The Sequence of Steps: A Key Concept Missing in Surgical Training—A Systematic Review and Recommendations to Include It

Background: Surgical procedures have an inherent feature, which is the sequence of steps. Moreover, studies have shown variability in surgeons’ performances, which is valuable to expose residents to different ways to perform a procedure. However, it is unclear how to include the sequence of steps in training programs. Methods: We conducted a systematic review, including studies reporting explicit teaching of a standard sequence of steps, where assessment considered adherence to a standard sequence, and where faculty or students at any level participated. We searched for articles on PubMed, EMBASE, CINAHL, Web of Science, and Google Scholar databases. Results: We selected nine articles that met the inclusion criteria. The main strategy to teach the sequence was to use videos to demonstrate the procedure. The simulation was the main strategy to assess the learning of the sequence of steps. Non-standardized scoring protocols and written tests with variable validity evidence were the instruments used to assess the learning, and were focused on adherence to a standard sequence and the omission of steps. Conclusions: Teaching and learning assessment of a standard sequence of steps is scarcely reported in procedural skills training literature. More research is needed to evaluate whether the new strategies to teach and assess the order of steps work. We recommend the use of Surgical Process Models and Surgical Data Science to incorporate the sequence of steps when teaching and assessing procedural skills

Process Mining for Healthcare: Characteristics and Challenges

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

Process Mining for Healthcare: Characteristics and Challenges

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

Process mining for healthcare: Characteristics and challenges

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.11Ysciescopu