Episodes of Care: Theoretical Frameworks Versus Current Operational Realities

Rosen, Amy K.; Mayer‐Oakes, Allison

doi:10.1016/s1070-3241(16)30431-x

Cited by 23 publications

(12 citation statements)

References 24 publications

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“…We used comprehensive Finnish register data in the reconstruction of the care episodes that crossed the boundaries of service providers. The idea of care episode approach is not new [36], but the lack of adequate data has made it difficult to utilize it in practice [37]. Fortunately, the Finnish register system with common personal identity codes in all registers and good data quality [38] made the reconstruction of inpatient care episodes for the total population of hip fracture patients in Finland feasible [22].…”

Section: Discussionmentioning

confidence: 99%

Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach

Riihimäki¹,

Sund

Vehtari³

2009

Health Care Manag Sci

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Effective utilisation of limited resources is a challenge for health care providers. Accurate and relevant information extracted from the length of stay distributions is useful for management purposes. Patient care episodes can be reconstructed from the comprehensive health registers, and in this paper we develop a Bayesian approach to analyse the length of care episode after a fractured hip. We model the large scale data with a flexible nonparametric multilayer perceptron network and with a parametric Weibull mixture model. To assess the performances of the models, we estimate expected utilities using predictive density as a utility measure. Since the model parameters cannot be directly compared, we focus on observables, and estimate the relevances of patient explanatory variables in predicting the length of stay. To demonstrate how the use of the nonparametric flexible model is advantageous for this complex health care data, we also study joint effects of variables in predictions, and visualise nonlinearities and interactions found in the data.

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Section: Discussionmentioning

confidence: 99%

Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach

Riihimäki¹,

Sund

Vehtari³

2009

Health Care Manag Sci

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“…27,29,30 This software is described in detail elsewhere. 31,32 Patients were selected for study inclusion if they had 12 Literature Search. The economic burden of MS is considerable due to the interventions, diagnostics, and monitoring required for MS as well as to the loss in patient productivity and employment.…”

Section: Software and Methods For Aggregating And Organizingmentioning

confidence: 99%

Perspectives for Managed Care Organizations on the Burden of Multiple Sclerosis and the Cost-Benefits of Disease-Modifying Therapies

Owens¹,

Olvey

Skrepnek

et al. 2013

JMCP

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“…The transition edge weights, the weights applied to the MST are the difference of unity and the original edge probability, given as ( d i , d j , f cohesion , g, ∆t)). (14) Once the MST is computed, the episode cohesion measure µ for the candidate episode e of type ξ is computed according to…”

Section: ) Cohesion Episode Measurementioning

confidence: 99%

“…However, manual methods for generating episodes are not scalable, given the difficulties of constructing a comprehensive rule set to fully characterize all the variances and subtleties characteristic of episodes. Rosen et al proposed using clusters to group encounter types into gross categories, such as basic primary care, cancer care, and chronic care [14].…”

Section: Introductionmentioning

confidence: 99%

Context-Sensitive Correlation of Implicitly Related Data: An Episode Creation Methodology

Son

Taira

Kangarloo

et al. 2008

IEEE Trans. Inform. Technol. Biomed.

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Abstract-Episode creation is the task of classifying medical events and related clinical data to high-level concepts, such as diseases. Challenges in episode creation result in part because of data, in the patient record, only implicitly being associated with their respective episodes. Furthermore, traditional approaches have been limited to using feature-poor claims records to generate episodes. The accurate correlation of data to their episodes is valuable in health outcomes research to discern resource utilization with respect to medical conditions. This paper describes a combinatorial optimization approach for constructing episodes, which supports the incorporation of heterogeneous data types. Aspects of this approach include an episode model for characterizing the generation of data elements as a result of a process, a methodology for identifying the relationships between implicit processes and the data elements generated by the processes, a measure for evaluating candidate episode configurations, and an energy-minimization methodology for addressing episode creation. An implementation of this work, called Episode Creation Version 2 (EC2), has been applied on patient records with various episode types, which present with knee pain. EC2 demonstrated data element classification precision and recall scores of 78% and 82%, respectively. Significant improvements in precision and recall were observed over a traditional healthcare services approach.

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Episodes of Care: Theoretical Frameworks Versus Current Operational Realities

Cited by 23 publications

References 24 publications

Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach

Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach

Perspectives for Managed Care Organizations on the Burden of Multiple Sclerosis and the Cost-Benefits of Disease-Modifying Therapies

Context-Sensitive Correlation of Implicitly Related Data: An Episode Creation Methodology

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