Can a care pathway help streamline the care process for patients with chronic fatigue syndrome?

Verhelst, D; Nachtergaele, M; Hindryckx, C; Vandevyvere, K.; Seghers, S.; Smessaert, K; Vanderschueren, Steven

doi:10.1258/jicp.2011.011024

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…Only 4 of them have been published. [26][27][28][29] Other knowledge-sharing network are, for example European Pathway Association (www.ep-a.org) or the Japanese Society for Clinical Pathways (www.jscp.…”

Section: F I G U R E 3 Type Of Indicators Based On Clinical Pathway Compass Domainsmentioning

confidence: 99%

Overview on the target population and methods used in care pathway projects: A narrative review

et al. 2021

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In general, there is evidence of poor efficiency and effectiveness of care processes in all countries, including high-income countries, as (i) one in 10 patients is adversely affected during treatment, (ii) healthcare-associated infections can be expected in seven in 100 hospitalised patients and (iii) there is still a considerable proportion of patients who do not receive appropriate evidence-based care because of unwarranted variation. 1 This implies that the quality of care patients receive is organised in a suboptimal way. [2][3][4] Adherence to guidelines can improve the organisation of care and consequently quality of care. To improve adherence to guidelines, five strategies are necessary: (i) a checklist with interventions linked in time and space in the clinical guideline, (ii) identify barriers for using clinical guidelines and share successful implementation strategies, (iii) integrate guidelines for conditions that

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Section: F I G U R E 3 Type Of Indicators Based On Clinical Pathway Compass Domainsmentioning

confidence: 99%

Overview on the target population and methods used in care pathway projects: A narrative review

et al. 2021

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“…As a result, the crisp direct-relation matrix Z k is derived: (10) Sub-step 1.4: Combining all direct-relation matrices Z 1 , Z 2 , ..., Z K into an aggregate matrix using an averaging process as follows:…”

Section: The Fuzzy Matrixmentioning

confidence: 99%

“…On the contrary, it can be a risky proposition with potential for large investments but little or even an adverse effect upon outcomes. A number of studies have shown that a large percentage of CP implementation projects have been unsuccessful [6,[9][10][11][12][13][14]34]. There are many factors to guarantee or even exaggerate the effectiveness of CPs.…”

Section: Introductionmentioning

confidence: 99%

A Method to Evaluate Critical Factors for Successful Implementation of Clinical Pathways

Dong

Huang

2015

Appl Clin Inform

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Incorporating comorbidities into latent treatment pattern mining for clinical pathways

Huang

Dong

et al. 2016

Journal of Biomedical Informatics

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In healthcare organizational settings, the design of a clinical pathway (CP) is challenging since patients following a particular pathway may have not only one single first-diagnosis but also several typical comorbidities, and thus it requires different disciplines involved to put together their partial knowledge about the overall pathway. Although many data mining techniques have been proposed to discover latent treatment information for CP analysis and reconstruction from a large volume of clinical data, they are specific to extract nontrivial information about the therapy and treatment of the first-diagnosis. The influence of comorbidities on adopting essential treatments is crucial for a pathway but has seldom been explored. This study proposes to extract latent treatment patterns that characterize essential treatments for both first-diagnosis and typical comorbidities from the execution data of a pathway. In particular, we propose a generative statistical model to extract underlying treatment patterns, unveil the latent associations between diagnosis labels (including both first-diagnosis and comorbidities) and treatments, and compute the contribution of comorbidities in these patterns. The proposed model extends latent Dirichlet allocation with an additional layer for diagnosis modeling. It first generates a set of latent treatment patterns from diagnosis labels, followed by sampling treatments from each pattern. We verify the effectiveness of the proposed model on a real clinical dataset containing 12,120 patient traces, which pertain to the unstable angina CP. Three treatment patterns are discovered from data, indicating latent correlations between comorbidities and treatments in the pathway. In addition, a possible medical application in terms of treatment recommendation is provided to illustrate the potential of the proposed model. Experimental results indicate that our approach can discover not only meaningful latent treatment patterns exhibiting comorbidity focus, but also implicit changes of treatments of first-diagnosis due to the incorporation of typical comorbidities potentially.

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Can a care pathway help streamline the care process for patients with chronic fatigue syndrome?

Cited by 4 publications

References 11 publications

Overview on the target population and methods used in care pathway projects: A narrative review

Overview on the target population and methods used in care pathway projects: A narrative review

A Method to Evaluate Critical Factors for Successful Implementation of Clinical Pathways

Incorporating comorbidities into latent treatment pattern mining for clinical pathways

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