Characterization of the flow of patients in a hospital from complex networks

Miranda, M. A.; Salvatierra, Stella M.; Rodríguez, Isabelle; Alvarez, Manuel; Rodríguez, Victoria María Sueiro

doi:10.1007/s10729-018-9466-2

Cited by 10 publications

(4 citation statements)

References 40 publications

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“…A number of more recent papers follow Garg et al [84] in using metrics of resource usage Statistical analysis of associations within a symptom-diagnosis-treatment model [109]; and between derived pathways and treatments using probabilistic topic models [21] Ibanez-Sanchez et al [110] Fernandez-Llatas et al [111] Statistical analysis of admission times for different groups of patient pathways, extended to show significant effect of departmental reorganisation Vogt et al [112] Outcome analysis including odds of hospitalisation for a very large and disparate set of pathways Findlay et al [113] Extensive analysis of varied care pathways and outcomes populating a pre-defined pathway model Yu et al [114] "Care Pathway Workbench", facilitating guideline and statistical outcome analysis of patient pathways Hierarchical clustering [116] and social network modelling [117][118][119]. Filtering from the departmental perspective allows insights on strategic departments and seasonal variation [118], while associations are found between biomarkers, patterns of collaboration, and outcomes in [119] Table 20 Examples of publications considering pathways from a physical position perspective or cost as enhancing information [11,86,87,95,140,141]; combined with the continuing interest in simulations modelled from derived care pathways described in the "Optimisation and simulation" section, this comprehensive use of data in resource planning and service redesign should find increasing application in health systems under continual pressure to maximise efficiency. In the broader context, clinical pathway redesign is increasingly data-facilitated if not always data-driven; a good example is the recent well publicised report of Connell et al [142], where DeepMind (a subsidiary of Alphabet Inc.) essentially generated a portable implementation of a real-time updated electronic care record to facilitate a streamlined Acute Kidney Injury care pathway.…”

Section: Discussionmentioning

confidence: 99%

Clinical and operational insights from data-driven care pathway mapping: a systematic review

Manktelow¹,

Iftikhar²,

Bucholc

et al. 2022

BMC Med Inform Decis Mak

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Background Accumulated electronic data from a wide variety of clinical settings has been processed using a range of informatics methods to determine the sequence of care activities experienced by patients. The “as is” or “de facto” care pathways derived can be analysed together with other data to yield clinical and operational information. It seems likely that the needs of both health systems and patients will lead to increasing application of such analyses. A comprehensive review of the literature is presented, with a focus on the study context, types of analysis undertaken, and the utility of the information gained. Methods A systematic review was conducted of literature abstracting sequential patient care activities (“de facto” care pathways) from care records. Broad coverage was achieved by initial screening of a Scopus search term, followed by screening of citations (forward snowball) and references (backwards snowball). Previous reviews of related topics were also considered. Studies were initially classified according to the perspective captured in the derived pathways. Concept matrices were then derived, classifying studies according to additional data used and subsequent analysis undertaken, with regard for the clinical domain examined and the knowledge gleaned. Results 254 publications were identified. The majority (n = 217) of these studies derived care pathways from data of an administrative/clinical type. 80% (n = 173) applied further analytical techniques, while 60% (n = 131) combined care pathways with enhancing data to gain insight into care processes. Discussion Classification of the objectives, analyses and complementary data used in data-driven care pathway mapping illustrates areas of greater and lesser focus in the literature. The increasing tendency for these methods to find practical application in service redesign is explored across the variety of contexts and research questions identified. A limitation of our approach is that the topic is broad, limiting discussion of methodological issues. Conclusion This review indicates that methods utilising data-driven determination of de facto patient care pathways can provide empirical information relevant to healthcare planning, management, and practice. It is clear that despite the number of publications found the topic reviewed is still in its infancy.

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Section: Discussionmentioning

confidence: 99%

Clinical and operational insights from data-driven care pathway mapping: a systematic review

Manktelow¹,

Iftikhar²,

Bucholc

et al. 2022

BMC Med Inform Decis Mak

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“…The main applications of process mining in healthcare to date as identified by Rojas et al . [ 25 ] have been to effectively manage the flow of hospital patients [ 26 , 27 ], reveal the order of clinical activities [ 27 , 28 ], identify bottlenecks [ 29 , 30 ], identify outliers when compared against a theoretical workflow model [ 31 ], and examine the relationship between resources [ 32 , 33 ]. A recent review by Halawa et al .…”

Section: Introductionmentioning

confidence: 99%

Process mining to discover patterns in patient outcomes in a Psychological Therapies Service

Potts¹,

Bond

Jordan³

et al. 2023

Health Care Manag Sci

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In the mental health sector, Psychological Therapies face numerous challenges including ambiguities over the client and service factors that are linked to unfavourable outcomes. Better understanding of these factors can contribute to effective and efficient use of resources within the Service. In this study, process mining was applied to data from the Northern Health and Social Care Trust Psychological Therapies Service (NHSCT PTS). The aim was to explore how psychological distress severity pre-therapy and attendance factors relate to outcomes and how clinicians can use that information to improve the service. Data included therapy episodes (N = 2,933) from the NHSCT PTS for adults with a range of mental health difficulties. Data were analysed using Define-Measure-Analyse model with process mining. Results found that around 11% of clients had pre-therapy psychological distress scores below the clinical cut-off and thus these individuals were unlikely to significantly improve. Clients with fewer cancelled or missed appointments were more likely to significantly improve post-therapy. Pre-therapy psychological distress scores could be a useful factor to consider at assessment for estimating therapy duration, as those with higher scores typically require more sessions. This study concludes that process mining is useful in health services such as NHSCT PTS to provide information to inform caseload planning, service management and resource allocation, with the potential to improve client’s health outcomes.

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“…proposed to use graph theory to implement and evaluate layout options for hospital layout problems, and proposed a building information modeling (BIM) algorithm to obtain the optimal layout [9] . In 2020, MA Miranda et al studied the efficiency of hospital operation and management from the dynamics of patient flow based on complex network theory, which can well evaluate the efficiency of hospital services and improve process performance [10] . However, the above two documents are only based on the complex network theory to study the various departments within the hospital, and solve the related problems of the layout of the various departments within the hospital.…”

Section: Introductionmentioning

confidence: 99%

Research on the construction of the referral networks of city hospitals and invulnerability in response to major public health emergency

Rong

2022

ITM Web Conf.

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In face of major public health emergencies, how to ensure the orderly and stable operation of city hospitals? Based on the theory and method of complex network, in this paper, we put forward the construction method of city hospital referral networks, analyze the static characteristics of the constructed network, discuss the invulnerability of networks with four attacking modes, and propose two ways (or integrated) to optimize the invulnerability of networks, which are: (i) Identifying and protecting key hospitals that can increase network invulnerability, (ii) Adding hospitals to the network. Taking hospitals of Wuhan as an example and using the proposed construction method for networks, in this paper, a directed-referral network I with 219 major hospitals in Wuhan is constructed. On the basis of network I, 16 mobile cabin hospitals, Huoshenshan hospital and Leishenshan hospital have been added, the referral-hospital network II of Wuhan is achieved. Compared with network I, network II has better referral ability and invulnerability.

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Characterization of the flow of patients in a hospital from complex networks

Cited by 10 publications

References 40 publications

Clinical and operational insights from data-driven care pathway mapping: a systematic review

Clinical and operational insights from data-driven care pathway mapping: a systematic review

Process mining to discover patterns in patient outcomes in a Psychological Therapies Service

Research on the construction of the referral networks of city hospitals and invulnerability in response to major public health emergency

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