Optimal timing of joint replacement using mathematical programming and stochastic programming models.

The optimal timing for performing radical medical procedures as joint (e.g., hip) replacement must be seriously considered. In this paper we show that under deterministic assumptions the optimal timing for joint replacement is a solution of a mathematical programming problem, and under stochastic as...

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Publicado en:Health Care Management Science Vol. 14; no. 4; pp. 361 - 370
Autores principales: Keren B, Pliskin JS, Keren, Baruch, Pliskin, Joseph S
Formato: research Journal Article
Publicado: Springer Nature Dec2011
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Optimal timing of joint replacement using mathematical programming and stochastic programming models.
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          Keren B
          Pliskin JS
          Keren, Baruch
          Pliskin, Joseph S
        affil: Department of Industrial Engineering and Management, SCE-Shamoon College of Engineering, Bialik/Basel Sts., Beer Sheva 84100, Israel
      sug:
        subj:
          Arthroplasty, Replacement
          Decision Support Techniques
          Decision Trees
          Patient Selection
          Aged
          Aged, 80 and Over
          Middle Age
          Quality-Adjusted Life Years
          Reoperation
          Statistics
          Time Factors
          Aged: 65+ years
          Aged, 80 & over
          Middle Aged: 45-64 years
      ab: The optimal timing for performing radical medical procedures as joint (e.g., hip) replacement must be seriously considered. In this paper we show that under deterministic assumptions the optimal timing for joint replacement is a solution of a mathematical programming problem, and under stochastic assumptions the optimal timing can be formulated as a stochastic programming problem. We formulate deterministic and stochastic models that can serve as decision support tools. The results show that the benefit from joint replacement surgery is heavily dependent on timing. Moreover, for a special case where the patient's remaining life is normally distributed along with a normally distributed survival of the new joint, the expected benefit function from surgery is completely solved. This enables practitioners to draw the expected benefit graph, to find the optimal timing, to evaluate the benefit for each patient, to set priorities among patients and to decide if joint replacement should be performed and when.
      pubtype: Academic Journal
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        research
        Journal Article
      ougenre: Article
    language: English
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