Applying clustering and AHP methods for evaluating suspect healthcare claims

Hillerman, Tiago P.; Souza, João Carlos; Reis, Ana Carla Bittencourt; Carvalho, Rommel N.

doi:10.1016/j.jocs.2017.02.007

Cited by 61 publications

(37 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Dong and Cooper 24 develop a supply chain risk assessment framework based on AHP and names the framework as 'orders-of-magnitude AHP' (OM-AHP). Hillerman et al 25 present a model for the analysis of suspicious claims data from healthcare providers with the use of different clustering algorithms, while AHP is applied as a MADM method for prioritizing the identified suspect entities for subsequent auditing. The work by Taylan et al 26 is focused on applying the 'FAHP + FTOPSIS' method as to assess the risks of and select a suitable one among the construction projects.…”

Section: Methods: a Literature Studymentioning

confidence: 99%

Modelling the decision of paper shredder selection using analytic hierarchy process and graph theory and matrix approach

Zhuang

Chiang

et al. 2017

Advances in Mechanical Engineering

View full text Add to dashboard Cite

There are so many paper shredder products available in the market, and the decision to select a 'right shredder' usually involves a number of criteria. For organizations, complexity arises when the procurement function is to purchase a massive amount of shredders of the same type. This study initiated the idea to use the analytic hierarchy process with graph theory and matrix approach for solving the problem. The proposed model determines the best shredder from a pool of alternatives, given the buyer-side decision-maker's preference settings. With the expert questionnaire polled and the heterogeneous real data collected, the model is applied to a reduced data set. The size of the decision problem is defined as 8 alternatives are filtered among 26, while the 7 justification attributes considered are fully kept for not losing the experimental meaning. The result shows the effectiveness and applicability of the approach to manage the encountered decision scientifically. As this also implies that not only buyers but also the manufacturers can use this model to analyse 'something', it is confident to conduct more future studies. The R script which implements the dynamic programming concept to calculate the assessed index scores for graph theory and matrix approach is perhaps another contribution of this study.

show abstract

Section: Methods: a Literature Studymentioning

confidence: 99%

Modelling the decision of paper shredder selection using analytic hierarchy process and graph theory and matrix approach

Zhuang

Chiang

et al. 2017

Advances in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…The literature is abundant with its applications, and this is still true in this decade. For space reason, the following recent articles which involve a variety of applications (but not limited to these) are cited [59][60][61][62][63][64][65][66][67]. As can be seen, the popularity of AHP is mainly based on its effectiveness in solving real decision problems; so many hybrid models also involve the use of AHP [68][69][70][71].…”

Section: The Ahp Methods Suggested For Phase Iii's Main Knowledge Discmentioning

confidence: 99%

A Knowledge Discovery Education Framework Targeting the Effective Budget Use and Opinion Explorations in Designing Specific High Cost Product

Chi

Zhuang

Fu³

et al. 2018

Sustainability

View full text Add to dashboard Cite

Abstract:For an R&D institution to design a specific high investment cost product, the budget is usually 'large but limited'. To allocate such budget on the directions with key potential benefits (e.g., core technologies) requires, at first and at least, a priority over the involved design criteria, as to discover the relevant decision knowledge for a suitable budgeting plan. Such a problem becomes crucial when the designed product is relevant to the security and military sustainability of a nation, e.g., a next generation fighter. This study presents a science education framework that helps to obtain such knowledge and close the opinion gaps. It involves several main tutorial phases to construct and confirm the set of design criteria, to establish a decision hierarchy, to assess the preferential structures of the decision makers (DMs) (individually or on a group basis), and to perform some decision analyses that are designed to identify the homogeneity and heterogeneity of the opinions in the decision group. The entire framework has been applied in a training course hold in a large R&D institution, while after learning the staff successfully applied these knowledge discovery processes (for planning the budget for the fighter design works and for closing the opinion gaps present). With the staffs' practical exercises, several empirical findings except for the budgeting priority (e.g., the discrimination between 'more important criteria' against the less important ones) are also interesting. For some examples (but not limited to these), it is found that the results from using two measures (statistical correlation vs. geometrical cosine similarity) to identify the opinion gaps are almost identical. It is found that DMs' considerations under various constructs are sometimes consistent, but often hard to be consistent. It is also found that the two methods (degree of divergence (DoD) vs. number of observed subgroups (NSgs)) that are used to understand the opinions' diversity under the constructs are different. The proposed education framework meets the recent trend of data-driven decision-making, and the teaching materials are also some updates to science education.

show abstract

“…Especially in the case of unsupervised methods, the requirement of another level of investigation and domain expertise to determine the legitimacy of the claims is not formalised. A recent relevant method is the Analytical Hierchary Process based method of Hillerman et al () which can be used to rank the providers and determine outliers. This can help prioritise the leads that are retrieved from the unsupervised method.…”

Section: Directions For Future Researchmentioning

confidence: 99%

Statistical Medical Fraud Assessment: Exposition to an Emerging Field

Ekin

Ieva

Ruggeri

et al. 2018

Int Statistical Rev

View full text Add to dashboard Cite

Health care expenditures constitute a significant portion of governmental budgets. The percentage of fraud, waste and abuse within that spending has increased over years. This paper introduces the emerging area of statistical medical fraud assessment, which becomes crucial to handle the increasing size and complexity of the medical programmes. An overview of fraud types and detection is followed by the description of medical claims data. The utilisation of sampling, overpayment estimation and data mining methods in medical fraud assessment are presented. Recent unsupervised methods are illustrated with real world data. Finally, the paper introduces potential future research areas such as integrated decision making approaches and Bayesian methods and concludes with an overall discussion. The main goal of this exposition is to increase awareness about this important area among a broader audience of statisticians.

show abstract

Applying clustering and AHP methods for evaluating suspect healthcare claims

Cited by 61 publications

References 22 publications

Modelling the decision of paper shredder selection using analytic hierarchy process and graph theory and matrix approach

Modelling the decision of paper shredder selection using analytic hierarchy process and graph theory and matrix approach

A Knowledge Discovery Education Framework Targeting the Effective Budget Use and Opinion Explorations in Designing Specific High Cost Product

Statistical Medical Fraud Assessment: Exposition to an Emerging Field

Contact Info

Product

Resources

About