Applying clustering and AHP methods for evaluating suspect healthcare claims
This paper seeks to present a model for the analysis of suspicious claims data from healthcare providers with the use of different clustering algorithms, and the application of the AHP multicriteria method for prioritizing the identified suspect entities for subsequent auditing. We begin with a brief overview of related works that have covered the application of the aforementioned techniques for investigating suspicious entities in the context of internal auditing and healthcare. After presenting the steps for the construction of our own model, we discuss our results. We determine that the application of clustering algorithms to our initial variables resulted in the automatic detection of almost all entities initially classified as suspect. Our AHP model then provided us with rational criteria for effectively and objectively ranking these entities for further investigation
The analytic hierarchy process in medical and health care decision making: A literature review
This paper presents a literature review of the application of the analytic hierarchy process (AHP) to important problems in medical and health care decision making. The literature is classified by year of publication, health care category, journal, method of analyzing alternatives, participants, and application type. Very few articles were published prior to 1988 and the level of activity has increased to about three articles per year since 1997. The 50 articles reviewed were classified in seven categories: diagnosis, patient participation, therapy/treatment, organ transplantation, project and technology evaluation and selection, human resource planning, and health care evaluation and policy. The largest number of articles was found in the project and technology evaluation and selection category (14) with substantial activity in patient participation (9), therapy/treatment (8), and health care evaluation and policy (8). The AHP appears to be a promising support tool for shared decision making between patient and doctor, evaluation and selection of therapies and treatments, and the evaluation of health care technologies and policies. We expect that AHP research will continue to be an important component of health care and medical research.
Competitive benchmarking of health care quality using the analytic hierarchy process: an example from Korean cancer Clinics
Faced with mounting competitive pressures and continued health care reforms, a growing number of health care providers have begun to realize that their future success rests on the ability to undertake a continuous improvement of health care quality. The process of continuous improvement of health care quality is facilitated by health care providers developing reliable quality measures through competitive benchmarking. In an effort to develop a meaningful set of guidelines for competitive benchmarking, and determine comparative measures of health care quality of medical clinics, this paper proposes an analytic hierarchy process (AHP) that can help medical clinics formulate viable service improvement strategies in the increasingly competitive health care industry. This paper also illustrates the usefulness of the proposed health care quality measures using the case of prominent Korean cancer clinics.
Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting
The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context.
Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems
Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture.