An application of process mining for queueing system in health service

Yampaka, Tongjai; Chongstitvatana, Prabhas

doi:10.1109/jcsse.2016.7748865

Cited by 9 publications

(3 citation statements)

References 5 publications

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“…Yampaka et al [97] Transitions between states in a data-derived process model modelled as queues, allowing the effects of changes to staffing or patient numbers to be determined Halonen et al [98] Comprehensive full life-cycle multi-method approach to data-driven service reconfiguration. Cycles of redesign and optimisation of resource allocation in a queueing network model informed experimental pilot studies to assess realistic working practices Senderovich et al [99] Fork/join queueing network derived from administrative logs and schedules and Real Time Location Service (RTLS) data of an outpatient service allows simulation of different central pharmacy service policies.…”

Section: References Notable Formentioning

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: References Notable Formentioning

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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“…() described a robust approach and algorithm to queuing in the outpatient setting using a systems engineering approach to wait time, facility resource utilisation, workflow and spatial constraints. Yampaka & Chongstitvatana () similarly reported a ‘process mining’ approach that included the separate throughput projections for each member of the care team (e.g. nurse, pharmacist, doctor) across various activities (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Improved outpatient haemodialysis adequacy using queued schedules

Nappo

Ross

2019

Journal of Renal Care

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SUMMARY Background Although technical advances help achieve haemodialysis adequacy, we hypothesise remediable non‐therapy factors exacerbate patient dissatisfaction, non‐adherence to treatment time and failure to meet dialysis goals. Scheduling inefficiencies lead to the total time in the unit far greater than actual treatment time, impacting facility efficiency and patient frustration. Objectives We used queuing theorem principles to optimise schedules by incorporating timing and workflow for every dialysis process step to design a new schedule, rather than the whole‐shift blocks at baseline. Design The goals were to: (1) craft schedules that maximised efficiency and economics from a facility perspective, and (2) minimise total time in the dialysis unit from a patient viewpoint. As dialysis units are held to a national standard of urea clearance, reduction ratios (URRs) were measured for the 3 months before and after the new scheduling was implemented. Results Dialysis staff and process parameters were measured to craft queued schedules of staggered small groups of patients instead of baseline blocks of 2 large shifts, 24 each. A total of 65 patients changed to groups of 8, with entry‐to‐exit at 290 minutes for four hours treatments. The URRs improved from 72.8 ± 6.9 to 75.2 ± 5.4% (p < 0.001). Before implementation, only 89% of subjects reached the URR facility compliance target of 65%, and afterwards 97% (p < 0.001). Conclusion Queuing theorem principles can be successfully adopted to optimise haemodialysis scheduling. The resultant staggered timing increases facility efficiency, minimises the long wait time dissatisfier, and is associated with improved URRs with more patients reaching target clearance thresholds.

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“…Case Study [33], [17], [23] Banks [7], [24], [39], [44], [19], [12] Healthcare Processes [29], [30], [11] Manufacturing Processes…”

Section: Frameworkmentioning

confidence: 99%

A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

Milani

Maggi

2018

Business Information Systems

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Process mining has gained traction over the past decade and an impressive body of research has resulted in the introduction of a variety of process mining approaches measuring process performance. Having this set of techniques available, organizations might find it difficult to identify which approach is best suited considering context, performance indicator, and data availability. In light of this challenge, this paper aims at introducing a framework for categorizing and selecting performance analysis approaches based on existing research. We start from a systematic literature review for identifying the existing works discussing how to measure process performance based on information retrieved from event logs. Then, the proposed framework is built starting from the information retrieved from these studies taking into consideration different aspects of performance analysis. accessibility to open source tools has never been easier, in particular for data driven analysis of business processes. Therefore, in a digital era, businesses cannot hope to survive with manually driven methods. The process analysis must also be digitally transformed by tapping into data-driven analysis methods.One group of techniques for data driven performance analysis uses event logs of processes to assess performance. Indeed, nowadays, business processes are often supported by IT systems that log their execution. For instance, an order-to-invoice process might include activities such as register, validate, approve, fill order and send invoice. Each order has a unique id and every activity is recorded in the event log with information about the time when it was executed (timestamp) and other additional data such as the resource (person or device) that executed the activity. As such, the process is inherently captured in the log. With process mining techniques [2], the performance of such processes can be assessed and analyzed in great detail based on event logs.The body of research and tools within the field of process mining has grown significantly during this decade. However, the availability of tools and approaches developed for specific aspects of process performance does not make it easier for businesses to employ them. In fact, it poses a challenge. There is no way for businesses to easily get an overview of what performance indicators can be measured, what input data is required for such analysis, or what industry specific implementations are available. In light of this context, we propose a framework for the selection of log-based performance analysis techniques. We do so by conducting a systematic literature review to identify the body of existing work. We analyze the results and focus on identifying existing process performance indicators, required input data, and approaches available. Based on the results, we build a framework for the selection of suitable performance analysis approaches.The structure of this paper is as follows. Section 2 summarizes the research protocol for the systematic survey. In Section 3, the research que...

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An application of process mining for queueing system in health service

Cited by 9 publications

References 5 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

Improved outpatient haemodialysis adequacy using queued schedules

A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

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